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Impacts of partial-retention harvesting with no buffer on the thermal regime of a headwater stream and… Guenther, Steven Martin 2007

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IMPACTS OF PARTIAL-RETENTION HARVESTING WITH NO BUFFER ON THE THERMAL REGIME OF A HEADWATER STREAM AND ITS RIPARIAN ZONE  by Steven Martin Guenther B.Sc. (Hon's) University of Toronto 2004  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE  in  The Faculty of Graduate Studies  (Geography)  UNIVERSITY OF BRITISH COLUMBIA April 2007 © Steven Martin Guenther 2007  ABSTRACT  The temperatures o f stream water and the stream bed influence biogeochemical processes and the growth and distribution o f fish and macro-invertebrate species in streams. While numerous studies have examined the effects o f various harvesting practices on stream temperature, none has estimated the effects on bed temperature, or conducted heat budget analysis before and after harvest to assess the mechanisms that control the magnitude o f post-harvest stream heating. In this study, we analyzed data from a paired-catchment experiment involving both control and treatment streams and pre- and post-harvest monitoring. The partial retention harvesting resulted in removal o f 50% o f the basal area along 300 m o f the channel in the treatment catchment. Stream temperature, bed temperature, riparian microclimate and stream hydrology were monitored in the treatment stream both before and after harvest. Daily maximum stream temperatures increased by up to over 7 °C during summer. Effects on winter temperatures were relatively small. Summer bed temperatures increased by as much as 6 °C, with greatest warming in areas o f down-welling flow into the stream bed. Heat budgets were estimated for two reaches o f a headwater stream before and after partial retention harvesting. Heat budget components responded in variable ways to the logging treatment depending on the reach, date, and weather. Incoming solar radiation was the largest input o f energy into the stream following harvesting, while latent heat, hyporheic heat, groundwater heat, and bed heat exchanges tended to reduce the amount o f daytime stream heating after harvest. These results w i l l assist in understanding and predicting the spatial and temporal variability in stream temperature response to forest harvesting.  ii  TABLE OF CONTENTS ABSTRACT  ii  T A B L E OF CONTENTS  iv  LIST OF T A B L E S  .'  '.  vi  LIST OF FIGURES  vii  ACKNOWLEDGEMENTS  ;  1 INTRODUCTION  x  1  1.1  SIGNIFICANCE OF S T R E A M TEMPERATURES A N D THE IMPACTS. OF F O R E S T R Y P R A C T I C E S 1.2 A P P R O A C H E S T O Q U A N T I F Y I N G S T R E A M T E M P E R A T U R E REPONSE OF FOREST H A R V E S T I N G 1.3 F A C T O R S C O N T R O L L I N G S T R E A M T E M P E R A T U R E R E S P O N S E TO FOREST PRACTICES 1.4 B E D T E M P E R A T U R E R E S P O N S E T O L O G G I N G A N D T H E I M P A C T S ON THE BENTHIC ENVIRONMENT 1.5 R E S E A R C H Q U E S T I O N S A N D T H E S I S O R G A N I Z A T I O N  2 METHODS STUDY AREA 2.1.1 Physiography and Climate 2.1.2 Study Streams 2.1.3 Logging Treatment 2.2 F I E L D M E A S U R E M E N T S 2.2.1 Stream temperature 2.2.2 Bed temperature 2.2.3 Discharge 2.2.4 Hydraulic gradients ; 2.2.4.1 Piezometers and installation 2.2.4.2 Measurement 2.2.4.3 Calculations and errors 2.2.5 Hydraulic conductivity 2.2.5.-1 Method 2.2.5.2 Error Assessment 2.2.6 Meteorological measurements 2.2.7 Solar radiation 2.2.8 Canopy photo graphy 2.2.9 Stream geometry measurements 2.2.10 Evaporation 2.2.10.1 Evaporation calculation and error 2.3. D A T A A N A L Y S I S 2.3.1 Treatment effect calculations 2.3.1.1 Stream temperature 2.3.1.2 B e d temperature 2.3.2 Principal component analysis ( P C A ) 2.3.3 Cross correlation analysis 2.3.4 Hyporheic exchange estimation  1 2 3 5 6  .. 8  2.1  :  8 8 8 9 9 9 10 10 11 11 11 12 12 12 13 13 13 14 14 14 15 15 15 16 17 17 18 18 iii  2.3.5 2.3.6  Stream geometry calculations Heat budget calculations 2.3.6.1 . Net Radiation 2.3.6.2 Latent heat 2.3.6.3 Sensible heat 2.3.6.4 B e d heat conduction 2.3.6.5 Heat transfer associated with hyporheic exchange  19 19 20 21 21 21 22  2.3.6.6  22  Groundwater heat  3 HYDRO-CLIMATIC CONDITIONS DURING THE STUDY PERIOD 3.1 3.2  STUDY PERIOD H Y D R O C L I M A T E POST-LOGGING C H A N G E S IN T H E R I P A R I A N Z O N E 3.2.1 Canopy cover 3.2.2 W i n d speed 3.2.3 A i r temperature 3.2.4 Humidity 3.2.4 Evaporation 3.2.5 Overview o f changes in riparian microclimate  4 STREAM TEMPERATURE RESPONSE TO A DISPERSED RETENTION LOGGING TREATMENT 4.1 4.2 4.3  4.4 4.5  INTRODUCTION STREAM TEMPERATURE PATTERNS R E S U L T S OF P A I R E D - C A T C H M E N T A N A L Y S I S 4.3.1 Pre-harvest regressions 4.3.2 Logging effects on daily maximum temperatures 4.3.3 Logging effects on daily mean temperatures 4.3.4 Logging effects on daily minimum temperatures METEOROLOGICAL AND HYDROLOGICAL CONTROLS ON TREATMENT EFFECT DISCUSSION 4.5.1 Stream temperature response to logging 4.5.2 Relative effects o f meteorology and streamflow 4.5.3 Efficacy o f dispersed retention logging for mitigating stream warming 4.5.4 Biological and ecological implications  5 HYDROLOGY AND THERMAL REGIME OF THE STREAM BED 5.1 5.2  5.3  INTRODUCTION L O W R E A C H RESULTS 5.2.1 Discharge and lateral inflow 5.2.2 Hydraulic gradients and conductivity 5.2.3 Seep temperatures and bed temperature patterns at step-pool sequences 5.2.4 Paired-catchment analysis o f bed temperature response to logging 5.2.5 Principal component analysis 5.2.6 Cross correlation analysis MID R E A C H RESULTS 5.3.1 Discharge and lateral inflow 5.3.2 Hydraulic gradients and conductivity '. 5.3.3 B e d temperature patterns in relation to vertical water flux  25 25 25 25 26 26 26 27 27  33 33 33 34 34 35 35 36 36 36 36 37 38 39  47 47 47 47 48 49 49 50 51 52 52 52 53 iv  5.3.4 Paired-catchment analysis o f bed temperature response to logging 5.3.5 Principal component analysis 5.3.6 Cross-correlation analysis DISCUSSION 5.4.1 Hydrologic characteristics 5.4.2 Thermal characteristics 5.4.3 Biological implications  53 54 55 55 55 57 59  EFFECTS OF FOREST HARVESTING ON STREAM HEAT BUDGETS: AN EXPERIMENTAL APPROACH  73  6.1 6.2 6.3 6.4 6.5 6.6  73 73 74 74 76 77  5.4  6  7  INTRODUCTION O V E R V I E W OF PERIODS USED FOR H E A T B U D G E T A N A L Y S I S SOLAR RADIATION MODELLING HEAT BUDGET RESULTS FORTHE LOW R E A C H HEAT B U D G E T RESULTS FOR THE MID R E A C H DISCUSSION '.  '.  CONCLUSIONS 7.1  87  S U M M A R Y OF M A I N FINDINGS : ... 7.1.1 Stream temperature response to a dispersed retention logging treatment 7.1.2 Hydrology and thermal regime o f the stream bed 7.1.3 Heat budget analysis before and after logging 7.2 R E C O M M E N D A T I O N S F O R F U T U R E W O R K ;  87 87 88 :.. 88 89  REFERENCES  91  APPENDECIES  97  APPENDIX APPENDIX APPENDIX APPENDIX APPENDIX APPENDIX  A B C D E F  97 98 99 100 101 102  v  LIST OF TABLES Table 3.1  Climate data (total precipitation and air temperature) at M K R F Headquarters and discharge and stream temperature from East Creek and Griffith Creek for July and August.  28  Results o f the generalized least squares regression analysis for Griffith Creek at four sites located 0 to 300 m upstream o f the lower edge o f the cut block, and for two unlogged control streams (East Creek and Spring Creek)  41  Results o f generalized least squares regression analysis o f daily maximum treatment effect as a function o f the logarithm o f mean daily discharge and daily maximum air temperature  41  Griffith Creek L o w Reach discharge values in Ls" . U B and L B are the reach upper and lower boundary, respectively, and S2 and S3 are locations of step-pool sequences  61  Table 5.2  Hydraulic conductivities measured at Griffith Creek L o w Reach  61  Table 5.3  M e a n differences between observed and predicted temperatures for the preand post-logging periods, for one down-welling ( D W ) and one upwelling/neutral ( U W / N ) site in the low reach  62  Table 5.4  Measured streamfiow at Griffith Creek M i d Reach (Ls" ). U B and L B are the reach upper and lower boundaries, respectively. Location o f L 5 is shown on Figure 4.8  62  Table 5.5  Hydraulic conductivities measured at Griffith Creek M i d Reach  63  Table 5.6  Mean differences between observed and predicted temperatures for the preand post-logging periods, for one down-welling ( D W ) and one upwelling/neutral ( U W / N ) site in the mid reach  63  R M S E o f heat budget reach-average temperature change rates for two water column depths in Griffith L o w Reach  80  R M S E o f heat budget reach-average temperature change rates for two water column depths in Griffith M i d Reach  80  Table 4.1  Table 4.2  Table 5.1  Table 6.1 Table 6.2  1  1  LIST OF FIGURES Figure 2.1  Maps o f M a l c o l m Knapp Research Forest and Griffith Creek  23  Figure 2.2  Diagram o f Plexiglas evaporation pan  24  Figure 3.1  Weather and streamflow from October 2002 to October 2006  28  Figure 3.2  Pre- (left) and post-logging (right) hemispheric photographs from the same location o f Griffith Creek L o w Reach taken in 2004 and 2005, respectively ;  29  Pre- (left) and post-logging (right) hemispheric photographs from the same location o f Griffith Creek M i d Reach taken in 2004 and 2005, respectively  29  Picture o f Griffith Creek catchment in summer 2005, following 50% removal o f basal area  30  Pre- and post-logging relations between daily mean wind speed at the Griffith Creek riparian station and a control meteorological site  30  Pre- and post-logging relations between daily maximum and minimum air temperature for Griffith Creek and a control meteorological site  31  Pre- and post-logging relations between relative humidity and vapour pressure at Griffith Creek and a control meteorological site  31  Relations between calculated and measured evaporation from Griffith Creek  32  Observed 10 minute interval stream temperatures for the control stream (Mike Creek) and Griffith Creek from 16 July 2002 to 24 September 2006  42  Deviations between observed and predicted daily maximum, mean, and ' minimum temperatures for two unlogged control streams  42  Deviations between observed and predicted daily maximum temperature at four locations along Griffith Creek  43  Exceedance probability curves for four locations in Griffith Creek o f daily maximum treatment effect temperatures for both post-logging years Winter (December - January), Spring (May - June), and Summer (July August) periods  43  Predicted and observed daily maximum stream temperatures for the Griffith Creek 0 m logger from January 2005 to October 2006  44  Deviations between observed and predicted daily mean temperature at four locations along Griffith Creek  44  Exceedance probability curves for four locations in Griffith Creek o f daily mean treatment effect temperatures for both post-logging years Winter (December - January), Spring (May - June), and Summer (July - August) periods  45  Figure 3.3  Figure 3.4 Figure 3.5 Figure 3.6 Figure 3.7 Figure 3.8 Figure 4.1 Figure 4.2 Figure 4.3 Figure 4.4  Figure 4.5 Figure 4.6 Figure 4.7  vii  Figure 4.8 Figure 4.9  Figure 4.10  Figure 5.1 Figure 5.2  Figure 5.3 Figure 5.4 Figure 5.5 Figure 5.6  Figure 5.7  Figure 5.8 Figure 5.9  Figure 5.10 Figure 5.11 Figure 5.12 Figure 5.13  Deviations between observed and predicted daily minimum temperature at four locations along Griffith Creek  45  Exceedance probability curves for four locations in Griffith Creek o f daily minimum treatment effect temperatures for both post-logging years Winter (December - January), Spring (May - June), and Summer (July - August) periods  46  Scatterplots o f daily maximum treatment effect for Griffith Creek 0 m temperature logger versus daily maximum air temperature and the logarithm o f daily mean discharge for Spring ( M a y and June) and Summer (July and August) periods o f 2005 and 2006  46  M a p o f Griffith Creek L o w Reach, showing locations o f thermocouple nests, groundwater seep location, and piezometer locations in brackets  64  B e d temperatures o f SI and S3 down-welling ( D W ) and upwelling/neutral ( U W / N ) sites at 10 cm depth i n the L o w Reach, with stream and 50 cm depth groundwater seep temperatures for two warm days in pre- and post- logging summers  64  Means o f mean seasonal bed temperatures grouped by hydrologic setting . and depth for pre- and post-logging summers  65  Difference between observed and predicted daily maximum stream and bed temperatures in the low reach  66  Time series o f principal component scores from P C A o f L o w Reach bed temperatures for pre- (left) and post-logging (right) periods  67  Ordination o f first and second principal components for pre-logging (left) and post-logging (right) bed temperature data by depth and hydrologic setting (top) and location in the stream (bottom)  67  L o w Reach cross correlation coefficients o f bed temperature versus stream and seep temperatures plotted against bed temperature depth for two consecutive clear (top) and cloudy (bottom) sky days in the pre- (left) and post-logging (right) period  68  M a p o f Griffith Creek M i d Reach, showing locations o f thermocouple nests, groundwater seep location, and piezometer number locations  68  B e d temperatures at 10 cm depth in the M i d Reach, with stream and 50 cm depth groundwater seep temperatures for two warm days in pre- and postlogging summers  69  Difference between observed and predicted daily maximum stream and bed temperatures in the mid reach.  .70  Time series o f principal component scores from P C A o f M i d Reach bed temperatures for pre- and post-logging periods  71  Ordination o f first and second principal components for pre-logging and post-logging bed temperature data by depth and location i n the stream  71  M i d Reach cross correlation coefficients o f bed temperature versus stream and seep temperatures plotted against bed temperature depth for two consecutive clear and cloudy sky days in the pre- and post-logging period  72 viii  Figure 6.1 Figure 6.2 Figure 6.3 Figure 6.4  Figure 6.5  Figure 6.6  Figure 6.7  Figure 6.8  Figure 6.9  Figure 6.10  Figure 6.11  Figure 6.12  A i r and stream temperatures and streamflow for July and August 2004. The shaded portion indicates the periods for the Heat Budgets  80  A i r and stream temperatures and streamflow for July and August 2005. The shaded portion indicates the periods for the Heat Budgets  81  Modelled and observed solar radiation for pre- and post-logging conditions above Griffith Creek  81  Energy, fluxes and reach-average observed and modelled temperature change rates for two water column depths for July 5 and 6, 2004, in Griffith L o w Reach  82  Energy fluxes and reach-average observed and modelled temperature change rates for two water column depths for August 15 and 16, 2004 in Griffith L o w Reach  .82  Energy fluxes and reach-average observed and modelled temperature change rates for two water column depths for July 3 and 4, 2005 in Griffith L o w Reach  83  Energy fluxes and reach-average observed and modelled temperature change rates for two water column depths for August 10 and 11, 2005 in Griffith L o w Reach  ..83  Energy fluxes and reach-average observed and modelled temperature change rates for two water column depths for July 5 and 6, 2004 in Griffith M i d Reach  84  Energy fluxes and reach-average observed and modelled temperature change rates for two water column depths for August 15 and 16, 2004 in Griffith M i d Reach  84  Energy fluxes and reach-average observed and modelled temperature change rates for two water column depths for July 3 and 4, 2005 in Griffith M i d Reach '.  85  Energy fluxes and reach-average observed and modelled temperature change rates for two water column depths for August 10 and 11, 2005 in Griffith M i d Reach ,  85  Reach-average observed and modelled temperature change rates for August 10 and 11, 2005 in Griffith L o w Reach  86  ACKNOWLEDGEMENTS This research was made possible with the support o f many people. M a n y thanks go to my supervisor D a n Moore, whose guidance, expertise, open door policy, and level o f excellence through this project have given me a bench mark to aspire to. Additional thanks go to Markus Weiler for his helpful comments on drafts of this thesis. This research was made possible only with the extensive help i n the field by Takashi G o m i , Francis W u , Jackie Ngai, Jenn Todd, Elisa Scordo, Ian Redden, Dani Ramos, Matt Bauer, Pamela O, and Ritter. I have to specifically thank Takashi G o m i whose work in setting up the research sites gave me the opportunity to work on this extensive data set. Special thanks go to my wife Pam who was an unending source o f support through the duration o f this degree.  CHAPTER ONE  INTRODUCTION 1.1  SIGNIFICANCE OF S T R E A M T E M P E R A T U R E S A N D T H E I M P A C T S OF FORESTRY PRACTICES Stream temperature plays a critical role in stream ecology. It influences dissolved oxygen  concentrations, rates o f biochemical and biological processes, and can control species distributions for both invertebrates and fish [Beschta et al, 1987; Vannote and Sweeney, 1980]. Stream temperature is particularly important in relation to cold-water species such as salmonids. Increases in stream temperature reduce the survival o f salmonid ova [Crisp,  1988] and can  interfere with the survival and abundance of salmonid food sources, such as macro-invertebrates [Crisp,  1990; Vannote and Sweeney, 1980]. In addition to temperature o f surface water in a  channel, the amount o f water exchange in the substrate o f the stream channels and its temperature is vital to the survival and spawning success o f most salmonid species andCaissie,  2003; Curry andDevito,  1996; White et al,  [Alexander  1987].  It has been recognised for decades that many forestry practices, such as streamside clearcutting, can cause increases in stream temperature over the summer months [Johnson and Jones, 2000; Levno and Rothacher,  1967; Titcomb,  1926]. Documented increases in summer maximum  temperature have ranged up to 13 °C [Moore et al, 2005b]. This influence has generated significant concern about the potential negative influences o f forest harvesting on stream ecology, respiration rates as well as nutrient dynamics and transport into downstream systems [Allen, 1995; Findlay,  1995]. In British Columbia and throughout the Pacific Northwest, a  particular concern is the impact that logging-related stream temperature increases have on salmonid populations [Beschta et al, 1987; Curry et al, 2002]. The conventional approach to minimising the impact o f forestry practices on stream temperatures is the retention o f linear buffer strips along the stream [Brown, 2006; Macdonald  1970; Gomi et al,  et al, 2003]. However, linear buffer strips are highly susceptible to  windthrow, which can render them ineffective. Alternatives to linear buffers are variable retention logging practices, which may have similar benefits to stream temperature with a reduced susceptibility to blowdown or windthrow. A s o f the late 1990's partial retention logging approaches have been implemented in British Columbia [Beese et al, 2003]. Variable retention  1  logging practices involve leaving standing trees as patches or as single trees, and w i l l hereafter be called patch retention and dispersed retention, respectively. Similar to linear buffers, variable retention logging has the potential to mitigate seasonal increases o f headwater stream temperatures but may be less susceptible to the effects o f wind. Partial retention logging approaches can also reduce the opportunity costs for timber companies by not restricting access to portions o f the basin, as can occur with continuous linear buffers. While the use o f linear buffer strips to minimize logging-related stream heating has received significant attention in the literature [Bourque and Pomeroy, et al, 2006; Macdonald  2001; Brown,  1970; Gomi  et al, 2003], only one study appears to have tested the ability o f a  partial retention technique to protect stream temperature, and that was on only one stream [Macdonald,  2003]. Therefore further research is warranted to investigate whether partial  retention logging approaches are able to minimize seasonal stream temperatures.  1.2  APPROACHES TO QUANTIFYING S T R E A M T E M P E R A T U R E REPONSE TO FOREST HARVESTING Two empirical approaches have been used to quantify the effects o f stream temperature  response to forest practices: (1) spatial comparisons with no pre-harvest data, and (2) studies involving pre- and post-harvest monitoring. The spatial comparison approach involves monitoring temperatures for streams with different amounts o f forest harvesting within their catchments, and uses a space-for-time substitution to infer the effects o f harvesting [Burton and Likens,  1973; Mellina  et al, 2002; Storey and Cowley,  1997; Zwieniecki,  1999]. A major  drawback to this approach is that inherent differences in temperature regimes among the study catchments can confound the identification o f treatment effects. Studies involving pre- and post-harvest monitoring are most efficient when some method is employed to control for climatic variations between the pre- and post-harvest years [Loftis et al, 2001]. Some studies have used air temperature data as a covariate [Curry et al, 2002; Holtby,  1982]. However, there is often significant scatter in the relation between stream  temperature and air temperature, reducing the statistical power o f the approach. A more powerful approach is the use o f control streams, which remain untreated through the study period. Although some studies have used A N O V A to analyse the post-harvest response for the treatment streams [Feller,  1981; Johnson  and Jones, 2000; Macdonald  et al, 2003], many studies used a  paired-catchment analysis, which involves fitting a regression between each treatment stream and a control stream using the pre-treatment data; this regression is then used in the post-harvest 2  period to predict what temperatures would have been had the treatment not been applied 1981; Gomi et al, 2006; Harris,  1977; Johnson  and Jones, 2000; Macdonaldet  [Feller,  al, 2003; Moore  et al, 2005c]. The differences between the observed post-harvest temperatures and those predicted using the pre-harvest regression constitute estimates o f the change associated with the logging treatment. Harris [1977] followed the standard approach o f analysing stream temperature metrics computed at an annual time step to avoid potential problems with autocorrelation. A n important limitation to our ability to assess the biological significance o f stream temperature changes is that most studies examined metrics, such as summer maximum temperature, that may not be biologically significant, especially in cases where temperatures do not approach or exceed thresholds for mortality. Sullivan et al [2000] and Nelitz et al. [2006] argued that the use o f a bio-energetic approach may provide a sounder basis for assessing risks to organisms, and that metrics such as the maximum weekly average temperature ( M W A T ) may be an appropriate metric. Furthermore, there is some suggestion that temperatures between autumn and spring may be important in relation to growth and development o f stream organisms [Holtby, 1988; Leggett  and Carscadden,  1978].  Moore et al [2005c] and G o m i et al. [2006] pioneered the use o f time series regression to allow the analysis o f daily time series while explicitly accounting for autocorrelation in the residuals. This approach allows forestry-related stream temperature changes to be estimated on a daily basis, providing more information on the seasonal and interannual variations in temperature response. For example, G o m i et al. [2006] found that maximum treatment effects occurred in late spring/early summer, rather than in late summer, when annual temperature maxima normally occur. The use o f daily time series also allows calculation o f metrics such as M W A T and the effect o f forest harvesting on them. While the approaches described above allow the effects o f forest harvesting on stream temperature to be estimated, they do not provide any information on what processes were responsible. This topic is addressed in the next section.  1.3  FACTORS CONTROLLING S T R E A M T E M P E R A T U R E RESPONSE TO FOREST PRACTICES Stream temperatures reflect the influences o f a variety o f energy fluxes, which can be  classed as being atmospheric or terrestrial. Atmospheric energy exchanges include solar radiation, longwave radiation, sensible heat, and latent heat. Terrestrial fluxes include bed heat conduction, heat from groundwater discharge, and hyporheic heat exchanges. Heat budgets have 3  been used to understand stream temperature dynamics in a variety o f settings; however most o f these studies were not conducted in the context o f forest harvesting [Evans et al, 1998; Webb and Zhang, 1997]. The earliest heat budget study focused on forest harvesting was conducted by Brown [1969]; since then, only Story et al. [2003], Johnson [2004] and Moore et al. [2005c] appear to have estimated heat budgets for forestry-influenced streams. Sensible and latent heat exchanges can be determined using empirical wind functions employing measurements o f air temperature, humidity and wind speed [Brown, al, 1998; Johnson,  2004; Moore et al, 2005c; Webb and Zhang,  1969; Evans et  1997]. This approach may  result in significant errors since wind in an incised stream channel or under intact forest can often be near or below stall speeds for typical anemometers [Story et al, 2003]. In such cases, some data logger systems record the stall speed, even though the true wind speed was lower, resulting in over-estimates o f the sensible and latent heat exchanges. Even with this bias, studies in. clear cuts found sensible and latent heat exchanges were small and even one order o f magnitude lower than incident solar radiation [Brown,  1969; Johnson,  2004; Moore et al, 2005c].  The determination o f incoming solar radiation in forested environments and their complicated shade regimes is a significant challenge. Webb and Zhang [1997] used a light meter to determine the fraction o f incoming light between a site that is covered by tree canopy and one that is not. However, the estimation o f shading cannot be represented by a constant fraction o f open-site solar radiation because it varies with the sun's movement and changes in cloud cover. Several modelling studies have used geometric calculations o f shade based on tree height, terrain angles, and stream width [e.g., Rutherford  et al, 1997; Sridhar  et al, 2004]. However, these  approaches are difficult to apply to dispersed retention harvesting, which should result in more complex patterns o f sky blockage. Moore et al. (2005c) addressed this problem using hemispheric photographs o f the canopy to model the transmission o f both direct and diffuse radiation based on the spatial distribution o f canopy gap fraction. These analyses were used in conjunction with measurements o f direct and diffuse radiation made in a clear cut to model the direct and diffuse radiation reaching the stream surface. This approach also accounts for bank shading and any other obstruction that shades the stream channel by blocking the transmission o f solar radiation. Hydrologic and bed processes can influence the thermal regime o f streams. Hyporheic exchange appears to influence stream temperature patterns in both space and time and Caissie,  2003; Johnson,  [Alexander  2004] though only three studies appear to have estimated the  associated heat exchange [Cozzetto et al, 2006; Moore et al, 2005c; Story et al, 2003]. Story et 4  al. (2003) found that hyporheic exchange was quantitatively an important process in driving downstream cooling under forest cover below a cut block. Moore et al. (2005c) showed that hyporheic exchange appeared to play a secondary, though still important, role within a clear cut, acting to suppress daytime heating. However, estimates o f hyporheic exchange flows, and their associated heat exchanges, is subject to considerable uncertainty [Kasahara  and Wondzell, 2003;  Moore et al., 2005c; Story et al., 2003]. Bed heat conduction tends to suppress daytime heating and nocturnal cooling  [Brown,  1969; Moore et al.., 2005c]. Previous studies suggest that bed heat conduction in a clearcut has the potential to be between 10 and 25% o f the net radiation o f a stream for step-pool units [Moore et al, 2005c] and [Brown,  1969] bedrock channel substrates, respectively. Bed heat  conduction depends on the thermal properties o f the stream bed and also on the vertical temperature gradients within the bed, which in turn depend on the influence o f groundwater discharge [Silliman  and Booth,  1993; Story et al, 2003]. Therefore, the magnitude o f bed heat  conduction should depend on the local hydrologic context o f the stream reach or channel unit. Groundwater is typically cooler than stream water i n summer/daytime and warmer in winter/night-time [Bogan et al, 2003; Webb and Zhang, 1997]. Groundwater discharge thus acts to reduce diurnal and seasonal temperature fluctuations. There is mixed evidence about the role of groundwater on stream temperature response to forest harvesting. Where streams have warm sources, such as lakes or wetlands, groundwater discharge can result in downstream cooling, even as a stream flows through a clear cut [Medina  et al, 2002]. However, there is also a  widespread belief that shallow groundwater warms in logged basins due to reduced transpiration and increased solar radiation at the soil surface, and that the associated advection o f heat by discharge into a stream can contribute to post-logging stream warming [Bourque 2001; Brosofske  1.4  et al,  1997; Hartman  and Scrivener,  1990; Hewlett  and Fortson,  and  Pomeroy,  1982].  BED T E M P E R A T U R E RESPONSE TO LOGGING A N D THE IMPACTS O N THE BENTHIC ENVIRONMENT While the impacts o f logging on stream temperatures are clear, the impacts on the benthic  environment are still not understood. Only two studies have examined benthic temperatures in a forestry context, and neither used a before/after approach to quantify the increases in the postlogging period [Ringler  and Hall,  1975; Curry et al, 2002].  Water exchange between the channel and the stream bed, called hyporheic exchange, is argued to be as vital a component as the temperature o f the stream to the survival and abundance 5  o f most salmonid species [Alexander  and Caissie,  2003; Curry and Devito,  1996; White et  al,  1987]. Hyporheic exchange is largely controlled by the geomorphic features o f the stream channel, such as riffle-pool and step-pool sequences which help force water into the substrate at the top o f a riffle or step feature and allow water to remerge in a pool [Brunke and Gonser, 1997; Findlay,  1995; Harvey  andBencala,  1993; Hill et al,  1998; Kasahara  and Wondzell,  2003].  Water in the hyporheic'zone is a mixture of stream and groundwater, and the hyporheic water temperature is determined to a large extent by the amounts o f each o f the two components and their respective temperatures [Alexander Silliman  and Booth,  and Caissie,  2003; Hendricks  and White, 1991;  1993; White et al, 1987]. Further research has observed that areas o f  upwelling hyporheic flow have water temperatures related to groundwater and downwelling flow is similar to that o f surface water temperatures [Bilby, 1984; Malard  et al, 2001; Moore  et al.,  2005c]. Based on this existing knowledge, a reasonable hypothesis is that the response o f benthic temperatures to forest harvesting should depend on the local hydrologic environment, in particular whether upwelling or downwelling flow occurs.  1.5  R E S E A R C H QUESTIONS A N D THESIS O R G A N I Z A T I O N The literature review above has identified a number o f gaps in our understanding o f  stream temperature response to forest harvesting, and these form the context for the current study. The specific research questions are provided below.  (1) standing  To what extent can a dispersed timber in the basin protect  treatment effects vary in relation and inter-annual  (2)  changes  Which energy processes  characterised relative  a headwater  to short-term  changes  vary with patterns  complex shade environment  logging  stream from weather  temperature  conditions,  changes?  How do  and the effects of  of the stream bed after logging,  of hyporheic  exchange  seasonal  associated  with partial-retention  atmospheric  and do the  and groundwater  control the changes, in summer stream  using fish-eye canopy photography?  to the better-studied  treatment that removes 50% of the  variations?  What are the temperature  temperature  (3)  climatic  retention  harvesting  How important  discharge?  temperatures? be  Can the  adequately  are the terrestrial  processes  processes?  6  This study addressed these questions at Griffith Creek, a headwater stream located in the Malcolm Knapp Research Forest. The study is part o f a broader, interdisciplinary experiment on the ecological effects o f alternative riparian management strategies [Kiffney et al, 2003]. The study is unique in that it combines a traditional paired-catchment approach, with data collection before and after harvest and the inclusion o f a control stream, with a process-focused heat budget study. It employs the time-series regression approach for developing pre-harvest regressions, to maximize the information available in the daily time series data. The remainder o f the thesis is organized as follows. Chapter T w o describes the study site, field monitoring program and methods o f data analysis. Chapter Three provides an overview o f the hydroclimatic context o f the study period, with a specific focus on microclimatic conditions over Griffith Creek both before and after harvest. Chapter Four applies the paired catchment approach to quantify stream temperature response and address question (1). Chapters Five and Six respectively address questions (2) and (3). Chapter Seven summarizes the main conclusions from the three components o f the study and identifies topics for further research.  7  CHAPTER TWO  METHODS 2.1  STUDY AREA  The study was conducted in the University of British Columbia M a l c o l m Knapp Research Forest. It is one component o f a broader experiment on the effects o f alternative riparian management strategies on stream and riparian ecology. While the broader experiment currently involves 13 streams subjected to a range o f treatments (plus 3 control streams), this study focused on one treatment stream, Griffith Creek. This section provides background to the study area and describes the characteristics o f the catchments and streams included in the study.  2.1.1  Physiography and Climate The University o f British Columbia M a l c o l m Knapp Research Forest ( M K R F ) is located  approximately 60 k m east o f Vancouver in the Lower Mainland o f British Columbia, Canada. This area has a maritime climate exhibiting relatively dry summers and wet mild winters. Mean annual precipitation varies between 2000 and 2500 m m over the study catchments, with the fall and spring periods (between October and April) receiving approximately 70% o f the total annual precipitation. Precipitation falling as snow only accounts for approximately 15% o f the annual precipitation amounts due to the low elevation and relatively warm maritime climate. Soils i n the forest consist o f highly permeable shallow podzols formed in glacial till of approximately 1 m in depth. The soil is underlain by relatively impermeable compacted basal till or granitic bedrock [Hutchinson  and Moore,  2000]. The forest prior to logging consisted of  mature second growth trees approximately 30 to 40 m tall, with a canopy cover greater than 90%. Tree species are dominated by three types, western hemlock (Tsuga heterophylla), red cedar (Thuja picata),  and Douglas fir (Pseudo-tsuga  menziesii),  western  from most to least abundant,  respectively.  2.1.2  Study Streams The treatment stream, Griffith Creek, is a first order stream with a basin area o f 10 ha.  Three streams remained untreated throughout the study to serve as experimental controls (East, M i k e , and Spring Creeks); these have similar basin areas, with the largest being 20 ha (see 8  Figure 2.1 for locations o f streams). A l l streams produce surface flow throughout their length for most o f the year and exhibited southerly aspects. A 300 m study reach was designated in Griffith Creek. The 0 m location is the lowest point o f the 300 m study reach, and is equipped with a V notch weir. The 300 m location is the furthest upstream location to produce surface flow in the driest portion o f the year. The elevation o f Griffith Creek from weir to headwaters ranges from 365 to 405 m above sea level. The headwater portion o f Griffith Creek is characterized by steep channel gradients o f approximately 20% in an incised channel, which decreases in steepness in the downstream direction to less than 7% slope. Bed materials change in composition from large cobbles in the headwaters to sand downstream and increasing amounts o f organic matter i n lower 150 m o f the primary study reach. Two study reaches were designated in Griffith Creek for detailed study o f the hydrology and thermal regime. The " L o w " Reach was located at approximately the 100 m location o f Griffith's primary study reach and was 20 m in length. The " M i d " Reach was 30 m in length and was located at approximately the 180 m location o f the Griffith Creek primary study reach (Figure 2.1). Both reaches were instrumented with piezometers and thermocouple nests (see relevant sections for details); in addition, the L o w Reach was equipped with a meteorological . station directly above the stream.  2.1.3  Logging Treatment The logging treatment that was applied to Griffith Creek's catchment involved dispersed  retention o f single spaced trees within the basin including the riparian zone, with 50% o f the basal area being removed from within the cut block. Smaller stems were removed, leaving the larger stems for harvest at a later date. Logging started in September, 2004, and was completed by the end o f November, 2004. The forest remained intact for the top 80 m o f Griffith Creek because logging was not feasible in the upper portion o f the basin (Figure 2.1). Timber was removed using skidders on the east side o f Griffith Creek, and by high-lead cable yarding on the west side, due to the steeper slopes.  2.2  FIELD M E A S U R E M E N T S  2.2.1  Stream temperature Stream temperature in M K R F was recorded with Onset 3 2 K StowAway TidbiT  temperature probes which are accurate to ±0.2°C. Each stream involved in this study at M K R F  9  was equipped with one temperature probe at the lower boundary o f the cut block, and for the control streams at an equivalent downstream distance (~ 300 metres downstream from its headwater). Griffith Creek was also equipped with three additional data loggers at approximately 100 m intervals upstream o f the lower boundary. A l l temperature loggers were placed in pools o f the streams to ensure data loggers were submerged in water year round and equipped with solar shields, made o f perforated 5 c m diameter white P V C pipe, to ensure only water temperature was measured. Data collection began 2 years prior to timber harvesting to ensure enough data was collected to fit the pre-logging regressions in the paired-catchment design.  2.2.2  B e d temperature Bed temperature data were collected at the L o w and M i d Reaches o f Griffith Creek.  Measurements were made using copper-constantan thermocouples with measurement precisions of ±0.2°C and were recorded using Campbell Scientific 2 I X data loggers and multiplexers. Temperatures were scanned every 10 s and averaged every 10 minutes. Thermocouples were installed in the bed using wooden stakes to which the thermocouples were attached, referred to as thermocouple nests, which were driven into the stream bed. Nests were installed so that depths o f thermocouples were either 1, 5, 10, 15, and 30 cm or 1, 5, 10, and 20 cm below the stream bed. B e d temperature data collection started in fall 2003 at the M i d Reach, while the L o w Reach was instrumented i n February, 2004. Both sites recorded bed temperatures until 11 September 2004, when data loggers were removed for timber harvesting, and data loggers were reinstalled on 23 M a r c h 2005. Thermocouple nests were not moved between the pre- and posttreatment periods.  2.2.3  Discharge Discharge was measured at the lower and upper boundaries o f the study reaches and  occasionally at additional locations within the reaches throughout the summer o f 2005. The method employed was a constant rate N a C l dilution gauging method outlined i n Moore [2005a]. A W T W electrical conductivity ( E C ) and temperature probe was used to measure the E C of the stream water before the injection began (ECb ) and when the E C reached a plateau value (EC ). g  SS  Discharge (_>) was calculated as: [2.2.3.1]  Q = -, ^ k(EC -EC ) s  hg  10  where q is the injection rate o f the salt solution, and k is the slope o f the linear relation between relative concentration ( R C ) and E C . The coefficient k was derived by adding 10 m l of the injection solution to 1 L o f stream water, creating a secondary solution. This secondary solution was then added in 10 m l increments to a 1 L volume o f stream water; E C was measured after each addition o f secondary solution. RC then can be calculated as [2.2.3.2]  RC = ^  C  " ^  y  where, Ey is the cumulative amount of secondary solution added, and V is the volume o f stream 0  water (L), RC  is the relative concentration of the secondary solution and can be calculated as  sec  [2.2.3.3]  sec  RC =—?— sec y  ^  +  x  where X and V are the volume (L) o f injection solution and stream water used to make the 0  secondary solution, respectively. Rating curves using a power-law relation were fitted between the measured discharges and the stream stage at the time o f measurement; stream stage was measured continuously at a stilling well installed at the 0 m location o f Griffith Creek. Under suitable conditions (i.e., complete tracer mixing within the dilution reach), discharge measurements based on constantrate salt injection can be accurate within ± 5 % of the calculated value [Moore, 2005a].  2.2.4 2.2.4.1  Hydraulic gradients Piezometers and installation Hydraulic gradients within the stream bed were measured using two types o f  piezometers: 6 m m internal diameter plexiglas piezometers (0.60 m in length), and 12 mm internal diameter aluminium drive point piezometers (0.65 m in length). Both types had a 0.05 m perforated section at the bottom o f the pipe. Aluminum piezometers were driven into the stream bed to the desired depth while plexiglas piezometers were installed using a steel drive rod with a steel sheath around it. The drive rod and sheath were driven into the stream bed to the desired depth, the drive rod was withdrawn, and the piezometer was dropped into the sheath. Once the piezometer was in place, the sheath was also removed from the stream bed.  2.2.4.2  Measurement Hydraulic head levels were measured using an electronic beeper to determine the height  of the water inside the piezometers. Stream water height along the piezometer was also 11  measured. These measurements were made on a weekly basis throughout the summers o f 2004 and 2005. Accuracy is approximately ± 5 m m for each hydraulic head measurement.  2.2.4.3  Calculations and errors Hydraulic gradients (HG) were calculated using equation [2.2.4.1]: [2.2.4.1]  HG = — L  where Ah is the difference in hydraulic head between two points, and L is the distance between head measurements, equal to the depth o f the piezometer screen within the bed. Piezometers were installed to depths o f at least 20 cm. The depth of the piezometer screen was calculated by subtracting the length o f tube protruding above the bed from the distance from the top of the piezometer tube to the mid-point o f the screen. The piezometer depth is accurate to approximately ± 5 mm. Relative errors in calculated hydraulic gradients were calculated as: [2.2.4.2] •  SHOJiK-h,) HG  SL  {h -h,)  L  2  where SHG is the error in hydraulic gradient, 6(h2 - hi) is the error in the hydraulic head difference (10 mm), SL is the error in the piezometer depth (5 mm), and hi and h.2 are the SL hydraulic head measurements. The highest error in the term — is 0.025 (for a depth of 20 cm, L  which was among the shallowest depths for piezometers). Thus, the largest relative error in the calculated hydraulic gradients is [2.2.4.3] 8HG ^ = — - — + HG- 0.025 = 0.05 + HG • 0.025 m  m a x  dl  dh  Therefore, the errors for hydraulic gradients of 0.05 and 0.5 are 0.05 and 0.06, respectively. Considering the magnitudes o f possible errors in hydraulic gradients, all values o f hydraulic gradient less than 0.05 in magnitude are considered neutral.  2.2.5 2.2.5.1  Hydraulic conductivity Method Hydraulic conductivity ( K ) was measured 6 times throughout the summer o f 2005 in 6  Plexiglas piezometers located in the stream in both the L o w and M i d reaches to capture a range of flow conditions throughout the summer. A version o f the two point falling head test outlined 12  by Baxter et. al. [2003] was used due to the high K o f the stream substrate, which meant that water levels fell too quickly to make multiple measurements. The piezometer was filled to overflowing by pouring water into the top to create a positive head gradient, then the time taken for the head to fall to the stream water level was recorded. The initial head was thus the top of the piezometer tube, and the second point was the stream water level.  2.2.5.2  Error Assessment  Errors for K were assessed using an approximate 68% confidence interval (CI) around the geometric mean for each piezometer. These were calculated as: [2.2.5.1]  c  /  =  1 0  m«»n(iogA:)±.T.  where s is the standard error and calculated using equation [2.2.5.2] e  [2.2.5.2]  s  ^ ^ o g K ) •\Jn  where sd is the standard deviation o f the logarithm (base 10) o f the K values, and n is the number of observations.  2.2.6  Meteorological measurements Measurements o f wind speed, air temperature, and relative humidity were made at two  locations in M K R F starting i n the summer o f 2003. A meteorological site was established directly over the water o f Griffith Creek within the L o w Reach. The second meteorological site was located approximately 1 k m away in a clear cut area that was logged i n 2002, called control met site (see figure 2.1 for location o f Griffith .Creek and control met site). A t both sites measurements were made using a M e t One Anemometer (wind speed), and a Campbell Scientific CS-500 temperature and humidity probe, that were recorded with a Campbell Scientific C R 1 0 X data logger every minute and averaged every 10 minutes.  2.2.7  Solar radiation Solar radiation was measured at the control met site starting in the summer of 2003. Two  K i p p and Zonen C M - 6 B pyranometers were scanned every second and averaged every 10 minutes. One o f the pyranometers measured total incoming shortwave radiation while the other measured only diffuse radiation with the use o f a shadowband that was adjusted every few days throughout the summer months. Five additional C M - 3 pyranometers were installed directly above Griffith Creek to calibrate and assess errors of solar radiation modelling. A t each location 13  where a pyranometer was installed in Griffith Creek, a hemispherical photograph was taken o f the forest canopy that was shading the pyranometer (see additional details in next section).  2.2.8  Canopy photography A l o n g the study reaches o f Griffith Creek, hemispheric images o f the forest canopy  above the stream were taken every 3 m once each in the summers o f 2004 and 2005. A l l hemispheric canopy images were oriented to north using a compass and levelled with a fish eye level to ensure the images took a picture o f the canopy directly above the stream. These images were analyzed using Gap Light Analyzer software [Frazer et al, 1999], to determine the gap fraction distribution, which was used for modelling incident solar radiation at the stream. Hemispheric canopy images were taken using a digital camera using auto focus and automated light settings to optimize the image quality. These settings resulted in varying hues o f blues and white for gaps, which was problematic when setting the colour thresholds in G L A to determine gaps i n the canopy. Best results were obtained when hemispheric images were preprocessed using Photoshop to render all sky fields to the colour white. This procedure allowed for more precise gap fraction analysis because the sky was analyzed uniformly as a gap, compared to the hues o f blue and white, which behaved differently with varying threshold levels. Thresholds needed to be significantly higher (less gap) than visual interpretation would suggest to achieve modelled below-canopy radiation values that matched measured data.  2.2.9  Stream geometry measurements Measurements o f stream geometry were conducted for both o f the study reaches in the  summers o f 2004 and 2005. A longitudinal reference line was set up along the study reaches o f Griffith Creek. A t 1 m intervals perpendicular to the reference line, stream cross sections were measured. Cross sections were established by measuring depths where the channel cross section changed shape and the distance from the stream bank.  2.2.10 Evaporation To verify the evaporation rates calculated using the Penman equation (Equation 2.3.6.4) described below, four Plexiglas evaporation pans were installed in the stream water of Griffith Creek. The evaporation pans were transparent to minimize heating o f the water in the pans (see Figure 2.2 for diagram o f evaporation pan). The pans were connected to a Mariotte reservoir,  14  which maintained a constant water level within the pan. Evaporation from the pan resulted water being drawn from the reservoir. The four evaporation pans were located along approximately 100 m o f the stream, between the L o w and M i d Reach. During each visit in the field, when no precipitation was occurring, evaporation pans were measured in the morning and once or twice throughout that day, approximately every 4 hr, to determine the evaporation rates. Temperature o f the water in the evaporation pan and the stream water surrounding it were also measured to calculate vapour pressure accurately.  2.2.10.1  Evaporation calculation and error  Evaporation (E) was calculated using equation [2.2.10.1] [2.2.10.1]  E =  (Ah-a)/(A-At)  where Ah is the change in height o f the reservoir, a the internal area o f the reservoir less the area of the air tube (254 m m ) , A is the area of the pan (1.8-10 m m ) and At is the change in time 2  4  2  (s). The error then can be calculated as [2.2.10.2]  SE E  L =  m  Ah  j r  8  1  a  The measurement error o f h can be assumed to be 1 mm, which then makes 5h = 2 mm, and an average value for Ah was 5 m m over a 4 hr period. Error o f the reservoir area can be calculated using equation [2.2.10.3] [2.2.10.3]  5a = 2nr • 5r + 2nr • 5r 2  2  x  x  where ri is the external radius o f the air tube and  the internal radius o f the reservoir. The  measurement error o f the radii are 0.05 m m for each measurement, which then makes 5a = 4 m m . Since an average measurement period was 4 hr, then an estimate o f the error can be 2  assumed to be approximately 6.0 10" m m h" . 4  2.3  DATA ANALYSIS  2.3.1  Treatment effect calculations  1  Treatment effect is defined as the change in a system's response, in this case stream temperature, which is caused by a specific treatment such as partial retention logging. The analysis involved fitting a regression relation using pre-harvest temperature data from a treatment stream as the predictor variable and temperature data from a control stream as the  15  response variable. After harvest, the pre-harvest regression was used to predict what the temperature in the treatment stream should have been had logging not occurred. The difference between the observed and predicted temperatures is an estimate o f the treatment effect. One challenge in fitting the pre-harvest regressions is that the residuals are temporally autocorrelated, i.e. the residual on a given day is correlated to the residual o f the preceding day or possibly days. Temporal autocorrelation violates the assumption o f independence required by ordinary least squares regression. Therefore, Generalized Least Squares ( G L S ) regression analysis was employed using the statistical package S-Plus. Generalized Least Squares regression does not require that the residuals be independent. The fitted model was: [2.3.1.1]  y  = B + B  t  n  + B s'm(2nf IT) + 6  lXl  2  cos(2njIT)+s,  3  where y, and x, are the temperatures o f the treatment and control stream respectively, B , /?/, B , 0  2  and /J3 are regression coefficients, j is the Julian calendar day, and T is the number o f days per year (365.25). The terms  sin(2^'/r) and cos(2^7'/r) were added to the model as sinusoidal  seasonal trends to help account for any seasonality in the residuals [Moore,  2005c; Watson,  2001]. The error term i n the model (e ) was modelled as an autoregressive process to the order t  using equation 2.3.1.2. [2.3.1.2]  e, =p s,_ + x  p e,_  x  2  2  +  +  p s,_ +u k  k  t  where p is the autocorrelation between error terms at a time lag o f " / " days, £,., is the error term t  "/" days before day  u, is a random disturbance that is assumed to have a Gaussian  distribution, and k is determined by analyzing the number o f days which are significantly autocorrelated to the stream temperature that is being calculated using Equation 2.3.1.1. Treatment effect (T ) can then be calculated as: e  [2.3.1.3]  T =y,-y, e  where y, and y are the measured and predicted temperatures o f the treatment stream on day /. t  2.3.1.1  Stream temperature Temperature data were summarised from 10 min intervals to daily minimum, maximum,  and mean temperatures for all temperature loggers. Treatment effects for stream temperatures were calculated for all four temperature loggers in Griffith Creek. Regressions were fitted using each o f the three control streams (Mike, Spring and East Creeks). The fitted regression with the lowest standard error o f the residuals (Mike Creek) was then used for calculating the treatment effect. T o assess the stability o f the pre-harvest regression, regressions were also fitted for 16  temperatures in the other two control streams (East Creek and Spring Creek) using M i k e Creek temperature as a predictor variable. These "control-control" regressions were fitted using data from the pre-harvest period, then applied for the post-harvest period. Under the null hypothesis of no treatment effect (true in the case o f a control-control regression), the distribution of residuals for the post-harvest period should not differ statistically from those for the pre-harvest period.  2.3.1.2  B e d temperature To assess the effect o f the logging on the bed temperatures, the same regression analysis  was applied to bed temperatures collected in Griffith Creek. N o bed temperatures were recorded in a control stream; therefore, the control stream temperature o f M i k e Creek was used as the independent variable. B e d temperatures were also summarized from 10 m i n intervals to daily minimum, maximum, and mean variables prior to regression analysis.  2.3.2  Principal component analysis. ( P C A ) Although P C A does not appear to have been applied previously to stream bed  temperatures, it is widely used in meteorology, climatology and hydrology to reduce the size o f data sets and to find underlying patterns [Bao et al, 2002; Jolliffe, Termonia,  1990; Mantua  et al, 1997;  2001]. It is particularly useful for exploring data sets comprising time series measured  at multiple locations, which is the structure o f the bed temperature data set. P C A has also been used in studies o f flora and fauna species in streams in relation to different hydrological and geomorphological factors [Bornette  andAmoros,  1991; Brittain  et al, 2001; Shieh and  Yang,  2000]. Bed temperature data were collected at 10 minute intervals at multiple depths and locations in the stream bed at both the L o w and M i d Reaches o f Griffith Creek. Given the differences in hydrological processes between the two reaches, P C A was applied separately to the two reaches, using the statistical package S-Plus. The P C A involved the correlation matrix, not the covariance matrix. Eigenvalues o f near or greater than 1 were considered significant, and P C scores for the significant P C ' s were plotted against time to determine the structure o f variance represented by each P C .  17  2.3.3  Cross correlation analysis Cross correlation analysis was conducted on bed temperatures to determine their relations  with stream and groundwater temperatures in both reaches in the pre- and post-logging periods. Bed, stream, and groundwater temperatures were assembled for two-day periods for each study reach under both clear and cloudy skies for both the pre- and post-logging periods. Each bed temperature measurement was cross-correlated to groundwater and stream temperatures, respectively, using the statistical package R [Ihaka and Genrfeman,  1996]. The maximum  correlation coefficients for each cross correlation were recorded, along with the lag associated with the maximum cross-correlation.  2.3.4  Hyporheic exchange estimation Hyporheic exchange rates were estimated from physical measurements made in the field.  The assumption was made that hyporheic exchange is direct from step to pool and no water travels further than the immediate downstream pool. If this is assumed then Fh can be defined yp  as: [2.3.4.1]  .  F =A qJL _ hyp  mr  s  p  where ^4,„/is the infiltration area o f the step (m ), q is the rate o f infiltation ( m s" ) and L . is the 2  3  1  z  s p  distance between step and pool (m). The infiltration area and the length between step and pool were estimated from piezometer measurements in the field, while q was calculated using one o f z  two methods. The first uses Darcy's L a w : [2.3.4.2]  q =K -Ah/Az 2  sal  where q is the flux rate o f water infiltrating the bed (m s" ), K 1  z  sat  is the saturated hydraulic  conductivity in step-pool sections o f the streams, and Ah/ Az is the vertical hydraulic gradient in the infiltration area o f the step. This method is complicated by two factors. First is the assumption that the medium through which the water is moving should be homogenous, which cannot necessarily be assumed. Secondly, the measurement o f hydraulic conductivity in this environment is difficult due to the relatively high conductivity values and the uncertainties involved i n using a two point method. Therefore, a second method can be used, as described by equation 2.3.4.3, which does not require these two assumptions to hold. [2.3.4.3]  q =<h> z  where ^ is the effective porosity o f the material and v is the vertical velocity o f the water infiltrating the stream bed. The effective porosity values were assumed to be 0.30, which is 18  typical for sands and gravels [Freeze and Cherry,  1979]. Velocities o f down-welling locations  identified using hydraulic head measurements were calculated using the lag between the 1 and either the 5 or 10 cm thermocouples located in these steps. Therefore, velocities were calculated using equation 2.3.4.4. [2.3.4.4]  v = (Az)/r  max  where Az is the difference i n depth (m) between the thermocouples, and r  m a x  is the time lag  between the two thermocouple maximum daily temperatures.  2.3.5  Stream geometry calculations Reach-average width and depth were calculated from the stream geometry measurements  for use in the heat budget calculations. Firstly, the average depth for each cross section {d.) was calculated [2.3.5.1]  ^ =  i;[(w _ - )'.rf . ]+[( _ - ).(rf -rf )-0.5] /  1  W/  /  I  W/  1  W/  /  M  where w, and d, are the distance from a stream bank and the corresponding depth in metres, respectively. Reach average width (w) was calculated as: [2.3.5.2]  w=  -Yw  i  where n is the number o f cross-sections measured, and w are the individual width j  measurements (m). Average depth o f the study reach was calculated using Equation 2.3.5.3: [2.3.5.3]  d =  -Lfi^) nw M  where d is the reach average depth (m).  2.3.6  Heat budget calculations To quantify the relative contribution o f the processes within the stream that are  contributing to the changes in stream temperature a heat budget approach was applied to the two study reaches o f Griffith Creek in both the pre- and post-logging period. Two-day periods in July and August consisting o f at least one day o f cloudless sky and little discharge variability were used for the analysis. The heat budget that was used is a combination heat budget and water balance model from Moore et al.  [2005c]. 19  p.3.6.1]  A<r  >  =  F  „  At  where the term ^  <  ^  >  At  (  T  - r j Q*+Q. + Q +Q (  „  h  w Ld,  +Q  c  gw  + Q  hyp  pc d,  s  p  is the change in the spatial mean water temperature (°C) over time, Fd  S  is the downstream discharge (m s"), T  and T  U S  D S  are the stream temperatures at the upstream and  downstream boundaries o f the reach (°C), w is the mean water surface width (m), and L and d, s  are the length and average depth o f the study reach (m). Q* is the net radiation ( W m" ), Q the 2  e  latent heat exchange ( W m ' ) , Q is the sensible heat flux from air to water ( W m" ), Q is the bed 2  2  h  heat conduction ( W m" ),  c  the energy exchange from ground water inflow ( W m" ), Qh  is the  yp  energy exchanged from hyporheic exchange ( W m" ), p is the water density (kg m" ), and c the 2  3  p  specific heat o f the water (J kg" K " ) . Each component o f the heat budget w i l l be explained in 1  1  detail below.  2.3.6.1  Net radiation Net radiation (Q*) is one o f the more complicated processes to quantify in forested  environments. Since the banks o f the stream and the trees shade the stream channel at different times o f the day, the most appropriate method to accurately determine the actual amount o f radiation that is reaching the stream channel is to use a model. The model o f net radiation can be expressed i n two components shortwave and longwave radiation. The shortwave (K*) component can be expressed as: [2.3.6.2]  = (l-«XAs,  tf*  where a is the albedo, D and S are the direct and diffuse components o f incident solar radiation t  t  at time (/), respectively ( W m" ), g, is the canopy gap fraction at the sun's position at time (/). Longwave radition (L*) was expressed as: [2.3.6.3]  L* = \f e v  a  + (l - + 2 7 3 . 1 6 )  4  -S CT{T W  W  +273.16)  4  where s , &/, s are the emissivities o f the atmosphere, foliage, and water, a is the Stefana  w  Boltzmann constant (5.67 10" W m" K " ) , and T and T represent the temperature o f the air and 8  2  4  a  w  water (°C), respectively. Emissivity values o f 0.95 were used for both foliage and water, atmospheric emissivity was calculated using the Idso [1981] equation. The sky view factor is represented by f , and is calculated using: v  , 2, 'A  [2.3.6.4]  / » = - { 71  0 0  \g*{6,a )cos6-s\n9-d0-da s  s  20  where g*(9,a ) is the gap fraction as a function o f zenith and azimuth angles, and 6 and a are s  s  the zenith and azimuth angles respectively. Net radiation was then calculated as:  [2.3.6.5]  Q* =  K*+L*  Solar radiation was modeled using 5° increments o f both zenith and azimuth angles. Modeled radiation values were then compared to measured values over Griffith Creek in both the pre- and post-logging periods to calibrate the hemispheric images defining the amount o f radiation penetrating the canopy.  2.3.6.2  Latent heat The latent heat exchange, Qe, is expressed using a Penman equation from Webb and  Zhang [1997]: [2.3.6.6]  Q =285.9(0.132 + 0 . 1 4 3 ^ - e ) e  w  where u is the wind speed (m s" ), and e and e refer to the vapour pressures (kPa) of the air 1  a  a  w  and water, respectively. Saturation vapour pressure (e ) was calculated as a function o f air or sat  water temperature (T) as follows:  [2.3.6.7]  e  sm  = 0.6108. i o  75 7 7 ( 7 + 2 3 7 3 )  The vapour pressure at the water surface was assumed to equal e , while the actual vapour sat  pressure o f the air (e ) was calculated using equation 2.3.6.8:. a  [2.3.6.8]  e =(—)e a  sal  where RH is the relative humidity measured at the riparian meteorological site in Griffith Creek the stream.  2.3.6.3  Sensible heat The sensible heat flux from the air to the water, Qh, is computed as:  [2.3.6.9]  Q =Wa-T )l{e -eM h  w  a  where y is the psychometric constant o f 0.622 kPa°C"', using an average value o f atmospheric pressure o f 98.0 kPa, and T and T are the temperatures (°C) o f the air and water respectively. a  w  The terms e , e , and Q are the same as described above. a  2.3.6.4  w  e  B e d heat conduction Bed heat conduction, Q , was calculated using Fourier's law as: c  21  [2.3.6.10]  Q =K (T„-T )/(0.04m) e  e  w  where K is the thermal conductivity ( W m" °C~), and Tb and T are bed temperatures at depths c  w  of 0.05 and 0.01 m , respectively (°C). The thermal conductivity was assumed to equal 2.6 W m"  1  K " , based on estimates provided by Lapham [1989] using a porosity value o f 0.30, which is 1  typical for sands and gravels [Freeze and Cherry,  2.3.6.5  1979].  Heat transfer associated with hyporheic exchange Energy exchange with the hyporheic zone can be expressed as:  P p hyp( hyp-<T >) C  [2.3.6.11] where Fh  yp  Q  =  hyp  F  T  is the hyporheic exchange (m s" m"), Th is the temperature o f the hyporheic zone yp  in °C, and <T> is the spatial mean water temperature (°C). Hyporheic exchange was determined using physically derived hyporheic exchange values described above. Hyporheic temperatures Thyp were measured using thermocouples at 0.01 m depths located in up-welling zones o f the stream.  2.3.6.6  Groundwater heat Groundwater contribution (Q^ ) to the heat budget can be expressed as: v  [2.3.6.12]  _>  where the terms T^ and T  =  v  us  nc F p  I T  *"  M  -  T  ^  )  are temperatures o f the groundwater and the upstream boundary o f  the sub-reach (°C). These temperatures were acquired by identifying seepage zones and 3  measuring these water temperatures. F  pv  1 1  is the groundwater inflow rate (m s" m") and is  computed as the difference in discharge between the upstream (F ) and downstream (Fd ) us  discharges  (mV ), measured 1  S  using constant-rate salt dilution. The groundwater inflow rate is  then calculated as: [2.3.6.13]  F  gw  =  ~/"  Fds  x  22  Figure 2.1 Map of Malcolm Knapp Research Forest (left) showing the location of study streams and control meteological site, and map of Griffith Creek (right) showing temperature loggers, meteorological site, study reaches, and gauging station.  23  Reservoir —  24  CHAPTER THREE  HYDRO-CLIMATIC CONDITIONS DURING THE STUDY PERIOD 3.1  STUDY PERIOD H Y D R O C L I M A T E = A i r temperatures were similar among the summers from 2002 to 2006 (Figure 3.1), with r  the pre- and post-logging periods showing similar ranges o f minimum, mean, and maximum temperature (Table 3.1). Summer precipitation varied by almost a factor o f five among years, with the driest and wettest summers occurring during the pre-logging period. Stream discharge for Griffith Creek and an un-logged control stream, East Creek, varied similarly over the study period (Figure 3.1). Discharge at East Creek was approximately an order of magnitude greater than at Griffith Creek, consistent with the difference i n drainage area. Summer mean discharge at East Creek generally varied in concert with summer total precipitation, with the exception of 2004, which had the highest precipitation but lower streamflow than in 2005 (Table 3.1). However, 2004 had the highest summer mean air temperatures, likely resulting in greater evapotranspiration. M a x i m u m stream temperature at East Creek generally followed mean air temperature, with the coolest conditions in 2002 and the warmest in 2004. Overall, the post-logging period was climatologically within the range o f variability observed during the pre-logging summers, so that the pre-harvest regression relations should be valid during the post-harvest period. Based on East Creek temperatures, it appears that 2004 had the most extreme conditions for stream heating, so that the post-logging stream temperature changes may not be as extreme as could have occurred under drier conditions. 3.2  P O S T - L O G G I N G C H A N G E S IN T H E R I P A R I A N Z O N E  3.2.1  Canopy cover Following the 50% partial retention logging treatment, canopy closure decreased by  13.0% and 14.5% for the L o w and M i d Reaches, respectively, resulting in canopy closures of 81.5% for both reaches. Paired pre- and post-harvest hemispherical canopy photographs from the same locations over Griffith Creek show that the predominant reduction in shade occurred at low zenith angles, so that increases in solar radiation reaching the stream would mainly occur near noon o f each day (Figures 3.2 and 3.3). Figure 3.4 shows the relatively open canopy in the 25  post-logging period within the Griffith Creek basin, with large amounts o f sunlight reaching the ground. 3.2.2  W i n d speed Mean July-August wind speeds at the control site were about 1.6 m s" in the pre-harvest 1  period, compared to 1.1 m s" in the post-harvest period. Prior to harvest, wind speeds in the 1  riparian zone were often near the stall speed o f 0.447 m s" and showed little correlation with 1  wind speeds at the open site (r = < 0.01) (Figure 3.5). After harvest, riparian wind speeds increased and showed greater correlation with wind speeds in the open (r = 0.65). 2  3.2.3  A i r temperature Scatterplots o f July and August daily minimum temperatures between the Griffith Creek  riparian meteorological station and the control station show no clear difference between the preand post-harvest periods, and the regression lines indicate close to a 1:1 relation between the two sites (Figure 3.6). The regression fits became stronger after logging, with r increasing from 0.77 2  in the pre-logging period to 0.88 in the post-logging period. The scatterplots and regression lines for daily maximum air temperature show that there were no logging-related increases in the riparian zone o f Griffith Creek when temperatures at the control station were near 15 °C, but increases exceeded 2 °C when control temperatures were greater than 25 °C (Figure 3.6). Regression fits strengthened from the pre-logging to the postlogging period, with r increasing from 0.90 to 0.97. The post-logging regression line was 2  roughly parallel to the 1:1 line, with Griffith Creek riparian temperatures being approximately 2 °C lower than the control site temperatures. The Griffith Creek riparian site is approximately 200 m higher in elevation than the control site, which accounts for an approximate 1.3 °C difference using a typical environmental lapse rate o f 0.65 °C/100 m elevations; The remaining difference between the sites could reflect the effects of shading and possibly some influence o f the stream.  3.2.4  Humidity Relative humidity and vapour pressure were approximately 10% and 1.5 kPa lower after  harvesting, respectively (Figure 3.7). The regression lines for both relative humidity and vapour 1  2  pressure had r values o f 0.86 for the pre-logging period. For the post-logging period, r remained 0.86 for vapour pressure but increased to 0.96 for relative humidity. These reductions in the humidity o f the riparian microclimate are likely related to the increases in wind speed 26  causing increased ventilation in the riparian zone, and thus a greater coupling with broader airmass characteristics and a decrease in the local influence o f the stream.  3.2.4. Evaporation Both measured and calculated evaporation from Griffith Creek increased significantly in the post-logging period (Figure 3.8). The pre-logging period was characterized by low to no evaporation, with 17 calculated and 5 measured values (out o f a total o f 30) indicating no evaporation or condensation occurring on the stream. In the post-logging period, evaporation rates increased dramatically with no condensation occurring and maximum rates o f 9.6 10" and 3  9.5 10" mm/hr for calculated and measured values, respectively. The substantial scatter in the relation between measured and calculated evaporation is likely due, in part, to spatial variability in the conditions driving evaporation at each pan, which may have differed from those measured at the riparian meteorological station. Thus, the data used in the Penman calculations may not have been representative o f conditions at the pans, which were located i n pools along a 100-m reach. In addition to the scatter is a tendency for the Penman equation to overestimate evaporation. One possible source o f this bias is the fact that the riparian wind speeds were frequently below the anemometer's stall speed, and the default value of 0.447 m s" would have overestimated wind speed and, thus, calculated evaporation. Another 1  possible source o f bias is the lack o f correction for atmospheric stability, which would have occurred given that daytime summer air temperatures were generally greater than stream temperature. Overall, however, the Penman evaporation was i n the right order o f magnitude.  3.2.5. Overview o f changes i n riparian microclimate The effect o f logging appears to have increased ventilation o f the riparian zone, thus coupling it more strongly to the regional climate and disconnecting it from the local influence o f the stream. Increased ventilation is clearly evident in the increased wind speed in the postharvest period, and is also evidenced by the stronger relations between riparian and control climatic elements for the post-logging period. The end result o f harvesting was increased solar radiation, daily maximum air temperature and wind speed, with decreased humidity, both relative and absolute. The effects o f these changes in riparian microclimate on stream temperature w i l l be the focus o f Chapter 6.  27  Table 3.1 Climate data (total precipitation and air temperature) at MKRF Headquarters and discharge and stream temperature from East Creek and Griffith Creek for July and August. Year  r\ 1 d VanaDlc  \ / o *~ 1 O  2002  2003  2004  2005  2006  32.0  32.5  35.0  31.0 ;  35.5  17.7  18.7  19.5  18.1  18.2  Air T (°C)  7.0  8.0  9.0  9.0  8.5  Days > 30 (°C)  6  5  2  3  4.  Precipitation (mm)  57.4  26.8  194.7  159.4  44.2  Q  Griffith (Ls" )  NA  NA  0.72  1.15  0.21  East (Ls' )  6.34  3.29  7.91  11.03  4.01  13.9  15.2  15.5  14.2  15.0  AirT Air T  max  (°C)  m e a n  ( C)  min  1  m e a n  Q  1  m e a n  EastT  max  (°C)  40  01-Jan-03  01-Jan-04  01-Jan-05  01-Jan-06  Figure 3.1 Weather and streamflow from October 2002 to October 2006. From top to bottom: daily maximum and minimum air temperature, Griffith Creek discharge, daily total precipitation. The shaded portion indicates the period of logging.  28  *3  Figure 3.2 Pre- (left) and post-logging (right) hemispheric photographs from the same location o f Griffith Creek L o w Reach taken in 2004 and 2005, respectively.  Figure 3.3 Pre- (left) and post-logging (right) hemispheric photographs from the same location o f Griffith Creek M i d Reach taken i n 2004 and 2005, respectively.  29  Figure 3.4 Griffith C r e e k catchment in s u m m e r 2005, f o l l o w i n g 50% r e m o v a l o f basal area.  • oe •»  o  Pre-logging Pre-logging Post-logging  o  0  o o o  0.7  o  c  E.  I  <5  0 6  ^  li 0 5  •'to'**  > e  CP  °  0  o  o  .*  o o  0  %  O  04 00  08  1 2  1.6  Control (m s' ) 1  Figure 3.5 P r e - and p o s t - l o g g i n g relations between daily mean w i n d speed at the Griffith C r e e k riparian station and a control meteorological site less than 1 k m away, for the months o f July and A u g u s t . D a t a span the years 2003 to 2006, with the later two years b e i n g post-logging data from Griffith C r e e k . Regression lines for the pre- and postharvest periods are s h o w n .  30  6  8  10  12  14  16  18  20  22  10  15  20  25  30  35  40  Control (°C) Control (°C) Figure 3.6 Pre- and post-logging relations between daily maximum and minimum air temperature for Griffith Creek and a control meteorological site less than 1 km away, for the months of July and August. Data span the years 2003 to 2006, with the later two years being post-logging datafromGriffith Creek. Regression lines for the pre- and postharvest periods are shown.  40  1 30  V  ,  ,  ,  ,  ,  ,  1  40  50  60  70  80  90  100  110  8-K^ 8  ,  ,  ,  '-,  ,  ,  1  10  12  14  16  18  20  22  Control (%) Control (kPa) Figure 3.7 Pre- and post-logging relations between relative humidity and vapour pressure at Griffith Creek and a control meteorological site less than 1 km away, for the months of July and August. Data span the years 2003 to 2006, with the later two years being post-logging data from Griffith Creek. Regression lines for the pre- and postharvest periods are shown.  31  -0.004  0.000  0.004 0.008 Penman (mm/hr)  0.012  Figure 3.8 Relations between calculated and measured evaporation from Griffith Creek. Filled and open symbols are for pre- and post-logging periods, respectively. Evaporation was measured and calculated in the summers of 2004 and 2005. The solid line represents the 1:1 line with dashed lines as the 0.0 mm/hr evaporation rates for visual reference. Error bars represent the maximum possible measurement error for the evaporimeters.  32  CHAPTER FOUR  STREAM TEMPERATURE RESPONSE TO A DISPERSED RETENTION LOGGING TREATMENT 4.1.  INTRODUCTION It has been recognised for decades that traditional forestry practices, such as clear-cutting,  cause increases in stream temperature over the summer months as a result o f decreased shade and increased solar radiation reaching the water surface. [Johnson and Jones, 2000; Levno and Rothacher,  1967; Titcomb,  1926]. Linear buffer strips are the traditional method for mitigating  stream temperature increases; however, they are highly susceptible to windthrow, which can render them ineffective. Alternatives to linear buffers are partial retention logging approaches which have been implemented since the late 1990's in British Columbia [Beese et al, 2003]. However, only one study by Macdonald et al. [2003] has been conducted to date on the effects o f partial retention logging on the stream environment. In this study the effects o f a dispersed retention logging treatment on stream temperature w i l l be assessed using a paired-catchment pre/post-logging analysis. The effectiveness o f this logging treatment w i l l be assessed by calculating the treatment effect in the post-logging period. Additionally, the contribution o f air temperature and discharge on treatment effect w i l l be assessed using regression analysis for the spring and summer seasons o f the two post-logging years.  4.2  STREAM TEMPERATURE PATTERNS Throughout the pre-logging period, stream temperatures for Griffith Creek and the  unlogged control stream (Mike Creek) varied similarly (Figure 4.1). The control stream was slightly warmer with mean and maximum pre-logging temperatures o f 9.1 °C and 17.2 °C, compared to Griffith Creek, which showed mean and maximum temperatures o f 8.9 °C and .16.7 °C. During the post-logging period, Griffith Creek exhibited a distinctly different temperature signature in the summer months compared to the un-logged control. Diurnal variations increased dramatically with fluctuations o f up to 5 °C compared to the control stream, which showed fluctuations o f approximately 1.5 °C for the same period in the summer o f 2006. The postlogging mean and maximum temperatures also changed, with mean temperatures o f 8.5 °C and 33  .9.0 °C and maximum temperatures o f 16.8 °C and 20.5 °C for the control and Griffith Creek, respectively. M i n i m u m temperatures did not change between logging periods with temperatures ranging close to 0.0 °C for both streams.  4.3  RESULTS OF P A I R E D - C A T C H M E N T A N A L Y S I S  4.3.1  Pre-harvest regressions  .  Generalised least-squares ( G L S ) regressions were fitted for the pre-harvest period, using M i k e Creek as the control, for temperatures measured at sites along Griffith Creek. Regressions were also fitted for two other control streams (East and Spring Creeks), also using M i k e Creek as the predictor. The paired-catchment analysis for stream temperature found significant residual autocorrelation for all three temperature metrics. Daily maximum temperatures required residual autocorrelation for lags o f 1 day for all four locations in Griffith Creek and the two un-logged control streams. Mean daily temperature required 2 days o f residual autocorrelation for Griffith Creek and 3 days for East and Spring Creeks. For minimum daily temperature, two locations had significant lag-1 autocorrelation, three had significant lag-2 autocorrelation and East Creek had significant lag-5 autocorrelation (Table 4.1). Degrees o f freedom for the pre-logging regression were between 760 and 796, and standard errors o f the residuals ranged from 0.27 to 0.49 °C. To assess the stability o f the pre-harvest regressions, relations were fitted for two unlogged control streams (East Creek and Spring Creek) using the control for Griffith Creek, M i k e Creek, as the predictor. Relations were fitted using data from the pre-harvest period, then applied in the post-harvest period. If the pre-harvest regressions are stable, the deviations for the postharvest period for East and Spring Creeks should be similar to those for the pre-harvest period. A s shown in Figure 4.2, most o f the deviations for the post-harvest period lie within two standard errors o f the residual. The minor deviations outside the predicted range are most noticeable for daily maximum temperatures and are reasonably absent in the daily minimum temperatures. Spring Creek generally showed more deviation outside the prediction range than did East Creek. Overall, the paired-catchment analysis should be capable o f identifying treatment effects that exceed 1 °C. Further evidence for stability o f the pre-harvest regressions for Griffith Creek is the pattern o f deviations from 0 m (bottom end of cut block) to 300 m (80 m upstream of cut block). The deviations for the 300 m logger, which should exhibit no change due to logging, are similar between the pre- and post-harvest periods, as expected (Figures 4.3 to 4.5).  34  4.3.2  Logging effects on daily maximum temperatures Treatment effects in the post-logging summers varied with location (Figure 4.3). While  the 300 m location, located above the cut block, showed little to no response, all three downstream locations showed significant increases in both o f the post-logging summers. Increases were higher in 2006 compared to 2005, with increases o f almost 7 °C at the 200 m location in the 2006 summer compared to 5 °C in 2005. The 100 and 0 m locations did not show increases as high as the 200 m location, but overall showed a greater number o f days that temperature increased by at least 5 °C (Figure 4.4). Treatment effect tended to increase with downstream distance for spring and summer periods. However, in summer the logger at 200 m (the most upstream logger within the cutblock) recorded the greatest treatment effect and the 100 m logger showed greater probability to exceed 3.5 °C than the other loggers. Winter treatment effects did not appear significant and no longitudinal pattern was present. Almost all winter treatment effects were within the two times the standard error o f the residual bounds. Time series o f observed and predicted maximum temperatures at the 0 m logger are shown in Figure 4.5. There is little apparent logging effect from late autumn through winter, with notable warming beginning in early spring and extending to late summer/early autumn. The largest treatment effects occurred in spring and not during the period o f seasonal peak temperatures. Figure 4.5 shows that, while predicted temperatures without logging would have been expected to exceed 15 °C only during one warming event each year, that value was exceeded several times each year after logging. In fact, in 2006, maximum temperatures exceeded 20 °C during two warming events  4.3.3  Logging effects on daily mean temperatures The paired-catchment analysis for mean daily temperatures revealed similar responses to  those for daily maximum temperatures, though smaller in magnitude (Figure 4.6, Figure 4.7). A t the 300 m location, increases in mean daily temperature were only noticeable in the summer o f 2006. The three downstream locations showed post-logging temperature increases in the summer of 2005, and even greater increases in 2006. The greatest increases i n daily mean temperatures occurred at the 200 m and 0 m locations. The summer and spring months showed similar responses for the two lower loggers but not for the 200 m logger, which increased in treatment effect in the summer compared to the spring. During winter, the mean responses tended to be negative, suggesting increased cooling after harvest. However, the mean responses were small and possibly not statistically significant. 35  4.3.4  Logging effects on daily minimum temperatures In contrast to daily maximum and mean temperatures, only small deviations occurred in  the summers following logging, with maximum increases o f 2.2 °C (Figure 4.8). Post-logging changes in minimum winter temperatures tended to be negative, possibly reflecting increased heat loss v i a longwave radiation, though the changes were small and did not vary with downstream distance, suggesting that they may not be statistically significant (Figure 4.9). In the summer period the greatest increases in daily minimum temperature occurred at the 200 m location; however, the 0 and 100 m locations showed greater warming than the 200 m location in both spring and summer periods.  4.4  METEOROLOGICAL A N D HYDROLOGICAL CONTROLS O N TREATMENT EFFECT To explore the relative effects o f meteorological conditions and streamflow on the  magnitude o f post-logging temperature changes, the treatment effect for daily maximum temperature at the Griffith Creek 0 m location was analyzed using G L S regression analysis. Treatment effect was regressed against daily maximum air temperature and the logarithm o f daily mean discharge for the spring and summer months, respectively, o f both post-logging years. Significant autocorrelation o f the residuals from the generalized least squares regression was 1 day for both seasons. Scatterplots for both seasons showed that the relationships were stronger for the spring season compared to the summer period for both air temperature and the logarithm of discharge (Figure 4.10). Treatment effect was negatively correlated with discharge and positively correlated with daily maximum air temperature for both seasons (Table 4.2). The regression coefficients for air temperature were greater in the spring season than in the summer. This indicates that a change in treatment effect (°C) that would be associated with a 1 °C change in daily maximum air temperature would be 0.24 °C in spring and 0.16 °C in summer. Discharge regression coefficients indicate that a doubling or halving o f discharge would change the treatment effect by 0.26 °C in the spring and 0.14 °C in the summer seasons.  4.5  DISCUSSION  4.5.1  Stream temperature response to logging The paired catchment analysis showed similar results, standard errors o f the residuals, and  significant orders o f residual autocorrelation to those reported by Moore et al. [2005c] and Gomi 36  et al: [2006] for other sites in M a l c o l m Knapp Research Forest. Daily maximum and mean temperatures increased notably during spring and summer at the three temperature loggers located within the cutblock. Spring and summer means o f the post-logging deviations from the regression analysis showed that even though increases in temperature were similar for the three locations in the cutblock, the 0 m and 100 m loggers responded with more seasonal warming than . the 200 m location. The 300 m temperature logger, located above the cutblock with the forest canopy still intact, did not respond significantly using any o f the temperature variables in the post-logging summers. Comparison o f the four temperature loggers suggests that downstream distance was only a significant control on the mean seasonal response, reflecting the overall heat accumulation o f the stream, and not on maximum temperature changes. Temperatures generally increased substantially between the 300 m and 200 m locations and then showed only minor variation in the remaining downstream direction. This spatial pattern o f warming is consistent with studies at A Creek in M a l c o l m Knapp Research Forest, where daily maximum temperatures increased dramatically over the first 50-100 m downstream o f the cut block edge, then alternately warmed and cooled over distances o f 10's o f metres [Moore et al, 2005c]. The variations in the temperature responses, especially for seasonal maximum changes, are likely a result o f local controls on stream temperature, such as lateral inflow or hyporheic discharge. To ensure that temperature loggers remained submerged during summer low flows they were placed i n pools. Pools have been found to be locations o f mixing o f stream water with water from the hyporheic zone [Bilby, 1984; Moore et al, 2005c; Story et al, 2003], which is typically cooler than stream water during the daytime in summer. Temperature variation within pools o f the Griffith L o w Reach exceeded 2 °C on occasion, similar to the results o f Moore et al. [2005c], who reported variations o f water temperature in pools up to 3 °C. The effect o f discharging hyporheic water may contribute to the slight variations in response between the three downstream temperature loggers, particularly during the low flows experienced in 2006.  4.5.2  Relative effects o f meteorology and streamflow Treatment effect was positively related to daily maximum air temperature and showed a  negative relation to the logarithm o f discharge, similar to findings for another site in the M a l c o l m Knapp Research Forest (Moore  et al., 2005b). Treatment effects were more sensitive to changes  in air temperature and discharge in spring than in summer. This seasonal contrast is likely a result of the energetic feedbacks associated with the higher temperatures in summer: as stream 37  temperature increases, heat losses by outgoing longwave radiation and evaporation increasingly tend to offset heat gains by solar radiation [Mohseni et al, 1998]. A contributing factor to decreased sensitivity in summer is heat storage in the stream bed. O n cooler days in the summer, heat could be conducted from the bed to the stream, suppressing stream cooling. The larger value of the lag-one autocorrelation coefficient in the summer compared to spring supports the suggestion that day-to-day carryover o f heat via storage in the bed tends to suppress stream temperature responsiveness.  4.5.3  Efficacy o f dispersed retention logging for mitigating stream warming Research on clearcut logging has shown that in most cases maximum temperature  responses vary from less than 4 °C to as high as 13 °C [Feller,  1981; Gomi et al, 2006;  Harris,  1977; Johnson and Jones, 2000; Moore et al., 2005c]. To mitigate these stream temperature increases, linear buffers have been used, with effective mitigation depending on the buffer width and type. G o m i et al. [2006] showed in the southern coast region o f B C that a 10 m buffer allowed increases in daily maximum temperature of up to 4.4 °C, while Macdonald et al. [2003] found that buffer widths o f 20 m with merchantable timber removed from the buffer strip allowed daily maximum temperature increases up to 3 °C in central B C . Full-retention 30 m buffers were shown in two studies to be effective, with maximum summer temperatures increasing by only 2.2 °C or less [Gomi et al., 2006; Harris,  1977].  The results presented here suggest that dispersed retention o f 50% throughout the cut block is not effective at mitigating stream temperature increases i n the post-logging summers. Increases o f at least 5.5 °C are similar to the increases reported following clearcut logging, such as at A Creek in M a l c o l m Knapp Research Forest, where daily maximum temperatures increased by up to 5 °C [Gomi et al, 2006]. The increases at the 200 m temperature logger, which is located approximately 20 m below the cut block boundary, show that even a decrease in the canopy closure created by a 50% dispersed retention causes significant temperature increases in a short downstream distance. It is difficult to assess the effectiveness o f the 50% partial retention harvesting relative to. studies employing other treatments, as the inherent sensitivities o f a stream to warming w i l l vary among sites, particularly due to differences in stream depth, stream-groundwater interactions and bank shading. For example, while the 50% removal o f basal area produced marked warming, it is possible that much greater warming might have occurred with clearcut logging. One approach to  38  comparing the 50% partial retention harvesting to alternative strategies is v i a heat budget modelling, using different shading scenarios to represent effects o f different treatments. This approach w i l l be employed in Chapter 6.  4.5.4  Biological and ecological implications Even though forest harvesting can produce marked warming, potentially lethal  temperatures for salmonids are rarely reached, especially for the time periods that are required to harm fish [Beschta et al, 1987; Curry et al, 2002]. However, Curry et al. [2002] suggested that forestry practices which change stream temperatures may have detrimental effects on the spawning success o f some species. The primary concerns for non-fish-bearing headwater streams such as Griffith Creek are not on the fishes themselves but on the food sources for fish such as macroinvertebrates, which may affect fish downstream o f the logged catchment. Increases i n stream temperature are generally accepted to affect the distribution and abundance o f macroinvertebrates in the benthic zone o f streams [Vannote and Sweeney, 1980; Ward and Stanford, 1992]. However, the relation between changes in thermal regime and invertebrate response is complex, and cannot be represented using simple thresholds for mortality or morbidity. For example, diurnal fluctuations of 10 °C (i.e., ± 5 °C around the mean) decreased the mean temperature required to cause lethal results on mayfly Deleatidium  autumnale  to 22 °C from 24 °C [Cox and Rutherford,  1999].  Research conducted on changes in macroinvertebrate communities after logging has shown that effects are either not detectable on longer time scales or are short lived, persisting on the order o f < 5 years [Herlihy  et al, 2005; Hutchens et al, 2004]. This time scale is roughly consistent with  the time required for thermal recovery associated with regrowth o f riparian vegetation following logging, which occurred or was at least underway within 5 to 10 years after harvest in many studies [Moore et al, 2005b]. Griffith Creek showed increased daily fluctuations o f up to 5 °C and maximum temperatures o f 20.5 °C i n the post-logging period. Based on the results presented by C o x and Rutherford [1999], mortality o f mayfly would not be expected to occur in Griffith Creek. However, it is unclear whether the results o f Cox and Rutherford [1999], based on studies in N e w Zealand, are applicable at Griffith Creek, especially to species other than mayflies. Furthermore, the temperature changes could affect growth and/or development rates and thus the timing of emergence and/or condition o f invertebrates at emergence, both o f which could have broader ecological impacts. 39  Overall, the effects o f logging on macroinvertibrate communities has not been adequately addressed in the literature. Some o f the questions that need to be understood are: What is the impact o f logging on the benthic thermal environment? H o w does hydrologic interaction contribute to the change in the benthic environment? D o spatial patterns develop in the distribution o f macroinvertebrate communities in relation to hyporheic exchange zones? These questions w i l l be addressed in Chapter 5.  40  Table 4.1 Results o f the generalized least squares regression analysis for Griffith Creek at four sites located 0 to 300 m upstream o f the lower edge o f the cut block, and for two unlogged control streams (East Creek and Spring Creek). A l l regressions use M i k e Creek as the control. s is the residual standard error for the pre-logging regression, d.f. is the pre-logging degrees o f freedom, and k is the order o f the residual autocorrelation. e  Daily Maximum  Daily M e a n  Location  Daily Minimum Se  Se  Se  (°C)  d.f.  k  (°C)  d.f.  k  (°C)  d.f.  k  Om  0.36  796  1  0.29  796  2  0.33  796  2  100 m  0.30  784  1  0.27  784  2  0.32  780  1  200 m  0.29  785  1  0.28  785  2  0.34  785  2  300 m  0.36  760  1 '  0.32  760  2  0.37  760  1  East  0.32  788  1  0.33  789  3  0.49  789  5  Spring  0.39  791  1  0.39  791  3  0.44  791  2  '  Table 4.2 Results o f generalized least squares regression analysis o f daily m a x i m u m treatment effect ( T E ) as a function o f the logarithm o f mean daily discharge (log Q ) and daily m a x i m u m air temperature ( T ) . The fitted model is T E = b + b , log Q + b T + e. W m a x  a m a x  w m a x  Season  0  2  a m a x  bo  bx  (p value)  (p value)  (p value)  -1.874  -0.856  0.242  (<.001)  (0.047)  (<.001)  -1.405  -0.470  0.162  (0.006)  (0.211)  (<.001)  Spring  Summer  b  2  N  R ad) . 2  A  P\  0.73  0.83  115  0.57  0.47  1.05  124  0.79  41  01-Jan-04  01-Jan-03  01-Jan-06  01-Jan-05  Figure 4.1 Observed 10 minute interval stream temperatures for the control stream (Mike Creek) and Griffith Creek from 16 July 2002 to 24 September 2006. Shaded area indicates the logging period (September - November 2004).  Spring Creek  East Creek Maximum  er  2  °— 2 <J> O T3  Mean  a>  2 g -2 O 2  Minimum  -2 01-Jan-03  01-Jan-04  01-Jan-05  01-Jan-06  01-Jan-03  01-Jan-04  01-Jan-05  01-Jan-06  Figure 4.2 Deviations between observed and predicted daily maximum, mean, and minimum temperatures for two unlogged control streams using temperatures at Mike Creek (a third control stream) as the predictor variable. For the post-harvest period, the deviation is an estimate of the effect of harvesting. Shaded area indicates the logging period (September - November 2004). Horizontal dashed lines indicate 2 times the standard error of residualsfromthe prelogging regression.  42  8  01-Jun-02  01-Jun-03  01-Jun-04  01-Jun-05  01-Jun-06  Figure 4.3 Deviations between observed and predicted daily maximum temperature at four locations along Griffith Creek. Distances are measured from the downstream end of the cut block. The 300 m logger is 80 m upstream of the cutblock. For the post-harvest period, the deviation is an estimate of the effect of harvesting. Shaded area indicates the logging period (September - November 2004). Horizontal dashed lines indicate 2 times the standard error of residualsfromthe pre-logging regression.  10  30  50  70  90  10  30.  50  70  90  10  30  50  70  90  Exceedance Probability (%) Figure 4.4 Exceedance probability curves for four locations in Griffith Creek for treatment effects for daily maximum temperatures for both post-logging years Winter (December - January), Spring (May - June), and Summer (July - August) periods. Horizontal dashed lines indicate 2 times the standard error of residuals from the pre-logging regression.  43  4 2  300  m  200  m  100  m  0  o_ 2  o 0 OJ  T3  £  OJ oo .Q  o  1  01-Jun-02  01-Jun-03  01-Jun-04  1  1  01-Jun-05  01-Jun-06  Figure 4.6 Deviations between observed and predicted daily mean temperature at four locations along Griffith Creek. Distances are measured from the downstream end of the cut block. The 300 m logger is upstream of the cutblock. For the post-harvest period, the deviation is an estimate of the effect of harvesting. Shaded area indicates the logging period (September - November 2004). Horizontal dashed lines indicate 2 times the standard error of residuals from the pre-logging regression.  44  Winter  o  o-o  0 O TJ 0) i_ -i—*  Q_ i  •7  T3 OJ CO  o  f/f  1/  10  —  30  0m 100 m 200 m 50  70  90  Exceedance Probability (%) Figure 4.7 Exceedance probability curves for four locations in Griffith Creek for treatment effects for daily mean temperatures for both post-logging years Winter (December - January), Spring (May - June), and Summer (July August) periods. Horizontal dashed lines indicate 2 times the standard error of residuals from the pre-logging regression.  O o  "O CD -4-»  o Q. i  "O CD  £  CD CO  o  01-Jun-03  01-Jun-04  01-Jun-05  01-Jun-06  Figure 4.8 Deviations between observed and predicted daily minimum temperature at four locations along Griffith Creek. Distances are measured from the downstream end of the cut block. The 300 m logger is upstream of the cutblock. For the post-harvest period, the deviation is an estimate of the effect of harvesting. Shaded area indicates the logging period (September - November 2004). Horizontal dashed lines indicate 2 times the standard error of residualsfromthe pre-logging regression. 45  Exceedance Probability (%) Figure 4.9 Exceedance probability curves for four locations in Griffith Creek for treatment effects for daily minimum temperatures for both post-logging years Winter (December - January), Spring (May - June), and Summer (July August) periods. Horizontal dashed lines indicate 2 times the standard error of residuals from the pre-logging regression.  Spring  . . 1  .  1  •«  ys-Summer  •  • , •» : s* • • •  • «•••••» - ,•1 » 10  15  20  . \  . •  •  • •  25  30  Daily Maximum Air Temperature (°C)  35  -1.0  -0.5  0.0  0.5  1.0  1.5  Logarithm of daily mean Discharge (Ls ) 1  Figure 4.10 Scatterplots of daily maximum treatment effect for Griffith Creek 0 m temperature logger versus daily maximum air temperature and the logarithm of daily mean discharge for Spring (May and June) and Summer (July and August) periods of 2005 and 2006.  46  CHAPTER FIVE  HYDROLOGY AND THERMAL REGIME OF THE STREAM BED 5.1  INTRODUCTION Although many studies have addressed the temperature response o f stream water after  logging [e.g., Gomi et al, 2006; Johnson  and Jones, 2000; Levno and Rothacher,  1926] and temperature patterns o f water in the,hyporheic zone [e.g., Bilby,  1967;  1984; Malard  Titcomb,  et al,  2001; Moore et al, 2005c], there is a significant gap in the literature relating to responses o f bed temperature after forestry practices. Only two studies have addressed the impact o f logging on the benthic environment and neither used a before-after approach to quantify the increases in the post-logging period [Ringler  and Hall, 1975; Curry et al, 2002].  This chapter addresses these knowledge gaps by documenting the changes in bed temperature patterns i n a headwater stream before and after harvest. Data for both hyporheic flow directions and long term bed temperature profiles w i l l be used to assess i f hyporheic-exchangeinduced bed temperature patterns are present in forested headwater streams and how they are affected by logging.  5.2  LOW R E A C H RESULTS  5.2.1  Discharge and lateral inflow Measured discharge varied from 10.0 to 0.17 L s" throughout the summer o f 2005 (Table 1  5.1). The reach generally gained flow, with changes o f -5.9% to 15.3% between the upper and lower boundaries. The apparent losses could have been caused by measurement error, which is likely on the order o f + 5% for each measurement, or up to + 16% error for the difference. There does not appear to be any systematic relation between lateral inflow and stream discharge. O n four occasions, additional discharge measurements were conducted to assess the locations o f lateral inflow in the reach. In all but one measurement no discharge was gained above the S2 location and greater than 50% o f the lateral inflow entered below S3 (see Figure 5.1 for locations).  47  5.2.2  Hydraulic gradients and conductivity Locations o f hyporheic exchange flow into and out o f the stream bed were inferred using  hydraulic gradients between piezometers and the stream surface. The L o w Reach is characterized by 3 step-pool sections which resulted in the identification o f 3 distinct down-welling and upwelling zones (Figure 5.1). Down-welling ( D W ) zones were easier to define based on the hydraulic gradients and represented a larger proportion o f the stream channel, while up-welling zones were smaller i n comparison. Step units within the study reaches, all o f which were located above woody debris, exhibited generally large negative hydraulic gradients (flow into the stream bed), as high as -0.74 at a depth o f 25 cm below the stream bed (Appendix A and B). Up-welling sites were found in pools below steps in only a small zone directly downstream o f the woody debris. These areas exhibited lower magnitudes o f hydraulic gradients compared to their downwelling counterparts, ranging between 0 and 0.23. Since up-welling zones were relatively weak and the measurement uncertainty was ± 0.05, all up-welling sites and these with gradients of magnitudes equal to or less than 0.05 were considered as up-welling or neutral ( U W / N ) zones. Spearman correlations calculated between hydraulic gradients and discharge exhibited more positive correlations than negative in both study period summers (Appendix A and B ) . Critical values o f the Spearman correlations for the pre- and post-logging periods were 0.738 for n = 8 and 0.490 for n = 17, respectively. This indicates that two relationships in 2004 and 3 in 2005 were statistically significant, which is greater than amount expected from an alpha value o f 0.05 under the null hypothesis (i.e. 1 significant correlation). Therefore, the pattern between hydraulic gradient and discharge is positive but not strong. Furthermore, between the pre- and post-logging periods there were no noticeable changes between hydraulic gradients in piezometers, except for P3 and P6, which changed from weak D W to U W / N . Piezometer P6 still showed D W flows in the post-logging summer; however, the values were within the measurement error and therefore considered U W / N . After completion o f logging piezometer P3 was replaced and the change in direction o f hydraulic gradient may be attributed to not being able to replace it in the exact location and depth as the preceding year. Hydraulic conductivity values from the post-harvest summer showed no systematic difference between U W / N and D W locations (Table 5.2). Values ranged between 1.110  -3  and  1.7-10" m s" , with the geometric means of each piezometer ranging between 4.0-10" and 6.7-10"' 7  1  4  ms" . 1  48  5.2.3  Seep temperatures and bed temperature patterns at step-pool sequences Seep temperatures measured at 50 cm depth showed diurnal changes o f less than 0.2 °C  and were lower than stream and bed temperatures for the two warm sunny days shown in the prelogging summer (Figure 5.2). B e d temperatures at 10 cm depth at D W zones were approximately 1.0 - 1.5 °C higher than the bed temperatures o f the U W / N zone (Figure 5.2). Stream temperature had a similar diurnal pattern to the D W sites but was approximately 1 °C warmer than the upwelling neutral sites and 0.5 °C cooler than the D W sites. Daily maximum temperatures were reached by stream water earliest followed by D W zones and U W / N zones, respectively. Stream water temperature was measured 1 m downstream of S I D which likely resulted in U W water mixing with stream water and causing the lower temperature compared to the D W bed temperatures. In the post-logging summer, seep temperatures showed similar patterns to the pre-logging summer with temperatures ranging between 13 and 14 °C. Differences in bed temperatures between D W and U W / N zones were greater following logging, with D W zones being up to 2 °C warmer than U W / N zones. Stream temperatures were higher than D W bed temperatures in the post-logging summer, opposite to the pattern in the pre-logging summer. Stream temperature reached its daily maximum earliest in the day followed by D W and U W / N sites. Overall maximum temperatures increased in the post harvest summer, and diurnal temperature variations of both stream and bed temperatures increased compared to the pre-harvest summer. Mean summer bed temperatures (measured 13 July to 12 September, 2004, and 10 July to 9 September, 2005) varied with depth and hydrologic setting (i.e., D W vs U W / N ) (Figure 5.3). Temperature differences between hydrologic settings at a given depth were about 0.5 °C for all depths except for the 1 c m depth in the post-logging year, when differences between the hydrologic settings were 0.2 °C. Between the pre- and post-logging summers, temperatures increased by approximately 0.2 °C i n both hydrologic settings. The largest increase occurred at the U W / N sites at 1 c m depth, which increased by 0.4 °C i n the post-logging summer.  5.2.4  Paired-catchment analysis o f bed temperature response to logging Residuals from the pre-harvest regression for daily maximum temperatures exhibited the  most persistent autocorrelation, with significant autocorrelation for lags o f 3 or 2 days, while daily minimum and mean temperatures involved 1 - 2 days o f lag (Table 5.3). Based on the difference between observed and predicted temperatures for the post-harvest period, daily maximum stream temperatures in the study reach increased by up to 5.5 °C (Figure 5.4). Daily 49  maximum bed temperatures showed varied responses to the logging treatment depending on their position in the stream. A t U W / N sites, bed temperatures increased up to 2 °C at 20 cm depth and up to 3 °C at the 1 c m depth. Areas o f the stream bed which exhibited D W flows showed bed temperature responses more closely related to that o f the stream temperature. However, the number o f days that D W sites reached these increases was fewer compared to those o f the stream. Increases were highest near the surface, with increases at the 1 cm depth reaching 6 °C, while the 15 cm bed temperature depth responded with increases o f slightly greater than 3 °C. Table 5.3 summarizes the mean values o f the pre- and post-logging treatment effects calculated from the regression analysis using daily maximum, mean, and minimum temperatures. For maximum daily temperatures, post-logging temperature increases were largest near the surface and decreased with depth. Areas exhibiting D W flows showed larger increases when compared to their equivalent depths in the U W / N zones. Daily mean temperatures showed the same pattern o f increases as daily maximum temperatures, only with smaller increases at equivalent depths and hydrologic setting. Small post-logging increases were found for daily minimum temperatures, with small (and likely insignificant) temperature decreases in the 10 and 20 cm thermocouple depths o f the U W / N site.  5.2.5  Principal component analysis Principal component (PC) analysis was applied to bed temperatures at the L o w Reach  from 13 July to 12 September, 2004, and 10 July to 9 September, 2005, and resulted in sample sizes o f 8830 and 7138 i n the pre- and post-logging summers, respectively. The first two P C ' s accounted for 95.7 and 3.5% o f the total variance i n the pre-logging summer and 83.3 and 11.6% in the post-logging summer. Eigenvalues o f the first two P C ' s were 5.1 and 1.0 in the pre-logging period and 4.7 and 1.8 i n the post-logging summer, respectively. Since the first two P C scores accounted for at least 95% o f the variance in the data sets and eigenvalues were less than 1.0 past the second P C , no other P C ' s were considered in the analysis. Time series o f the P C scores (Figure 5.5) show that the first P C in each year accounted for the variation o f the seasonal temperature pattern and included some portion o f the diurnal pattern, while the second P C explained variation in the diurnal cycle among locations. Ordination o f the first two P C loadings revealed similar patterns in both years (Figure 5.6). Loadings on P C 2 separated the shallow D W sites (most negative P C 2) from the deeper U W / N sites, and the deepest D W site (most positive P C 2). The loadings on P C 1 were inversely related to the absolute value o f the P C 2 loading. The ordination could be interpreted as .  5  0  representing a gradient o f temperature patterns reflecting surface influence (negative P C 2) to those reflecting a dominant subsurface signature (positive P C 2). This hypothesis is explored further in the next section. Ordination based on site does not show a systematic longitudinal thermal pattern with the second principal component, in contrast to that found for depth and hydrologic setting.  5.2.6  Cross correlation analysis Cross correlation analysis was conducted on bed temperatures for two consecutive clear  and cloudy sky days in the pre-and post-logging periods (Appendix C ) . Stream temperature and seep temperatures were used as independent variables representing surface-dominated and subsurface temperature signals, respectively. The time step was 10 minutes. Cross-correlations with stream temperature decreased with depth and those with seep temperature increased with depth (Figure 5.7). This was true i n both the pre- and post-logging periods and under both clear and cloudy conditions. The lag associated with maximum cross-correlation showed an inverse relation with the correlation coefficient and decreased with increasing correlation (Appendix C ) . In the pre-logging period under clear sky conditions, cross-correlations with stream temperature decreased less rapidly with depth at D W sites (S1U, S 2 U , and S3U) compared to their U W / N counterparts ( S I D , and S3D). For example, cross-correlations at 15 to 20 cm depth remained near or above 0.8 at D W sites, but dropped below 0.5 for U W / N sites. The opposite pattern held for cross-correlations with seep temperature for clear days. During cloudy conditions, cross-correlations with both stream and seep temperatures were relatively high at all depths, exceeding 0.77. There was no clear distinction between U W / N and D W sites under cloudy sky conditions. The post-logging period showed broadly similar patterns to those for the pre-logging period although with less variation with depth and among sites. Under clear skies, crosscorrelations with stream temperature were similar to those in the pre-logging period, while, crosscorrelations with seep temperatures generally increased relative to pre-harvest conditions for depth less than 20 cm. Under cloudy conditions, cross-correlations showed more variation in the post-logging period compared to the pre-logging period. Cross-correlations with both seep and stream temperatures did not differ greatly between clear and cloudy conditions in the postlogging period, with the exception o f reduced variation and slightly higher correlations i n the cloudy-day correlations with seep temperature. Hydrologic setting was not as significant a control  51  on correlations compared to the pre-logging period, with only the clear-sky correlations using stream temperature showing deviations for U W / N sites.  5.3  MID R E A C H RESULTS  5.3.1  Discharge and lateral inflow The M i d Reach is characterized by a more complicated geomorphic pattern compared to  the L o w Reach, with no clearly identifiable step-pool sections. Measured discharge ranged from 0.15 to 8.99 L-s" (Table 5.4). Calculated lateral inflow was always positive and ranged from 1% 1  to 54% o f the downstream discharge. Estimated errors were on the order o f ± 11% for the percent groundwater contribution. The percentage of flow associated with lateral inflow to the reach tended to be higher at lower flows. The additional discharge measurements at the mid-reach L 5 location showed that, in almost all cases except for the 24 October measurement, more than half o f the lateral inflow was acquired above the L 5 location (see Figure 5.8).  5.3.2  Hydraulic gradients and conductivity Hydraulic gradients throughout the reach exhibited no clear pattern with channel  morphology, particularly step-pool units (Figure 5.8). This reach exhibited fewer strong D W zones and a greater proportion o f U W / N zones compared to the L o w Reach (Appendix D and E ) . Four piezometers changed direction o f hydraulic gradient between the pre- and post-logging periods (1, 4, 9, and 10), all o f which were replaced after logging. The change in direction of hydraulic gradient may be attributed to not being able to replace them i n the exact location and depth as the preceding year. Hydraulic gradients at 25 cm depth ranged from -0.65 ( D W flow) to 0.13 ( U W / N ) . However, the majority of the piezometers showed l o w hydraulic gradients throughout the study period, relative to those at the L o w Reach. Hydraulic gradients at M i d Reach showed generally more positive Spearman correlations with discharge in both study periods (Appendix D and E ) . M i d Reach Spearman correlations showed similar numbers o f significant relationships to the L o w Reach. In the post-logging summer, 5 piezometers exhibited Spearman correlations above the critical value o f 0.490, but none in the pre-logging period exceeded the critical value o f 0.738 based on the number o f observations. This result suggests that hydraulic gradient was positively but weakly related to discharge for the post-logging summer.  52  Hydraulic conductivity values generally ranged from about 10" to 10" m-s"' (Table 5.5). 6  4  There were no noticeable patterns in hydraulic conductivity relating to discharge or hydrologic setting throughout the summer o f 2005.  5.3.3  B e d temperature patterns in relation to vertical water flux In the pre-logging summer, bed temperatures at 10 cm depth were greater than the seep  temperature and lower than stream temperature on warm summer days (Figure 5.8). B e d temperatures exhibited diurnal fluctuations o f about 0.5 ° C , similar to that for seep temperature but less than the 2 °C fluctuation exhibited by stream temperature. The U W / N location showed the lowest 10-cm bed temperatures, while the L 2 D W site had the highest 10-cm bed temperatures. Stream temperature was measured upstream o f L I and therefore was not affected by the lateral inflow, which may explain the lag i n the timing o f maximum temperatures between the stream and the bed. In the post-logging summer, seep and stream temperatures remained the lowest and highest, respectively. However, bed temperatures at the L I and L 2 locations were similar to stream temperature during the coolest portion of the diurnal cycle. The diurnal variation in all the measured bed temperatures increased dramatically in the post-harvest summer and showed fluctuations o f 1 - 2 °C. Location L 3 , an U W / N site, remained the coolest o f the thermocouple locations. Location L 4 , a down-welling site that had essentially the same diurnal variability as the other sites in the pre-logging summer, became notably more responsive to diurnal heating, rising and peaking in concert with stream temperature.  5.3.4  Paired-catchment analysis o f bed temperature response to logging For the pre-harvest regressions, the order of significant residual autocorrelation was either  3 or 1 with daily minimum temperatures only requiring 1 day, and with mean and maximum requiring mostly 3 days o f lag. Degrees o f freedom ranged from 201 to 355 for the regressions , (Table 5.6). Harvesting appeared to increase daily maximum bed temperatures by no more than 2 °C despite increases in stream temperature o f up to 5 °C (Figure 5.10). A s shown in Table 5.6, there were only small increases in the post-logging summer for daily maximum temperatures, with little difference between depth and hydrologic setting. Daily mean temperature showed an almost uniform temperature increase o f between 0.3 to 0.4 °C in the D W zone. In the up-welling zone, increases in mean temperature ranged from 0.51 °C at 5 cm to 0.19 °C at 30 cm. For daily 53  minimum temperatures, there appeared to be no treatment effect at the down-welling site but a variable response at the up-welling site, with a slight warming at 5 cm and slight cooling at deeper levels.  5.3.5  Principal component analysis Principal component analysis was conducted on bed temperature data from 5  thermocouple locations from 2 July to 24 August, 2004, and 1 July to 11 September, 2005. In the pre- and post-logging periods there were 7625 and 10319 observations for each period respectively. Time series o f principal component scores show that the first P C i n each summer represented the variation o f the seasonal temperature changes as well as some proportion o f the diurnal cycle, incorporating 94.6% i n the pre- and 92.3% o f the variation in the post-logging summers (Figure 5.11). The second P C represented the remainder o f the diurnal variation, accounting for 5.2% in the pre-logging period and 5.8% in the post-logging summer! Eigenvalues in the pre- and post-logging period were (4.4, 0.9) and (4.4, 1.1) for the first two P C ' s , respectively. The ordination o f the first and second P C loadings shows different patterns in the pre- and post-logging summers (Figure 5.12). In the pre-logging period, there was no clear pattern associated with depth (Figure 5.12, top left panel). However, there appeared to be some pattern associated with site. For each site, the points tended to fall along a set o f lines with positive slope (Figure 5.12, bottom left panel). The deeper locations tend to be in the lower left and shallower points in the upper right. Points for sites L I , L 4 and L 5 fall along one line, while points for site L 2 fall along a separate line, shifted down. The points for site L 3 fall along a third, even lower line, and are closely clustered in the lower right corner o f the graph. For the post-logging summer, the ordination reveals a strong relation between the P C 2 loading and depth (Figure 5.12, top right panel). Deeper thermocouples were associated with positive loadings for P C 2, and shallower thermocouples with negative loadings for P C 2. The contrast between up-welling and down-welling had a more subtle effect than for the L o w Reach. For example, comparing points for L 4 (down-welling) and L 5 (up-welling) for the same depth reveals that Location L 5 showed higher loadings in the second P C when compared to the respective depth o f L 4 , indicating that the U W / N zone plotted higher along the second P C loading axis than its D W counterpart.  54  5.3.6  Cross-correlation analysis Cross-correlation analyses were conducted on two consecutive clear and cloudy sky days  in the pre-and post-logging periods. Stream temperature and seep temperatures were used as independent variables and the time step was 10 minutes (Appendix F). A s for the L o w Reach, cross-correlations with stream temperature were high at the surface and decreased with depth. The reverse pattern held for cross-correlations with seep temperature (Figure 5.13). The lag associated with the maximum cross-correlation showed an inverse relation with correlation coefficient and decreased with increasing correlation (Appendix F). In the pre-logging period the most noticeable pattern was the high cross-correlations with seep temperature for locations below 10 cm depth. This pattern was present regardless o f location or sky condition, especially in the U W / N locations L3 to L 5 . Cross-correlations with stream temperature were generally weaker than for the L o w Reach, but varied with location and sky condition. Under clear skies, cross-correlations with stream temperature were high for L 2 at 5 cm, but decreased rapidly with depth, while locations L 3 to L 5 had weak cross-correlations at all levels, including 5 cm. Under cloudy skies L 2 showed high correlations at the surface and higher correlations compared to the clear sky conditions at depth. Thermocouple locations L 3 to L 5 showed a reduced range o f correlation coefficients compared to the clear sky condition, from 0.50 to 0.66. The contrast between up-welling and down-welling sites, as reflected in the contrast between L 4 ( D W ) and L 5 ( U W / N ) , was weaker than that observed at the L o w Reach. For the post-logging summer, cross-correlations with stream temperature generally increased for clear sky conditions at all depths, compared to pre-logging conditions, while crosscorrelations with seep temperature decreased. Patterns at L 2 were no longer distinct from those at the other sites. The contrast between L 4 and L 5 was similar to that for the pre-harvest period.  5.4  DISCUSSION  5.4.1  Hydrologic characteristics The two reaches were hydrologically distinct in terms o f the magnitude o f lateral inflow  within the reach and the role o f step-pool structures in creating zones o f down-welling and upwelling flow. The M i d Reach received a greater proportion o f its downstream discharge from lateral inflow compared to the L o w Reach, which appeared to lose flow on three measurement dates. These losing periods followed extended periods o f low precipitation, except for the measurement on 9 September, 2005, which was conducted after a 6.5 m m event on the preceding day. The M i d Reach on that day showed significant gains and derived 40% o f its downstream 55  flows from lateral inflow. The slopes bounding the M i d Reach appeared to respond relatively rapidly to precipitation events under dry antecedent conditions, i n contrast to the slopes bounding the L o w Reach, which showed little or no response. Hydraulic gradients were variable throughout each reach, with the L o w Reach exhibiting more D W zones while the M i d Reach contained more piezometers reading positive or slightly fluctuating hydraulic gradients. Vertical hydraulic gradients in D W zones were greater and thus could be measured more accurately compared to the U W / N areas in either reach. There was little variation throughout each year or between logging periods in terms o f the direction and magnitude o f gradients. Hydraulic gradients showed very weak positive relationships to discharge for both reaches; however, not enough piezometers showed this trend to definitively accept that there is a correlation between discharge and hydraulic gradients. In general, U W / N zones were found in pools with low elevations below log or rock jams, especially in the L o w Reach where these were the only locations U W / N zones were found. In the M i d Reach, U W / N zones were confined to pools only upstream o f the groundwater seep; below the seep, U W / N zones were more common and not as confined to low-lying channel morphologies. These results contrast with recent research on hyporheic exchange in mountain channels in the Oregon Cascades, where up-welling zones were generally not observed even in non-losing reaches where they should be present [Anderson  et al, 2005; Gooseff et al, 2005;  Wondzell, 2005]. The measurable U W zones in Griffith Creek may be a result o f the relatively consistent lateral inflow that was measured in the two study reaches, causing positive hydraulic gradients from groundwater inflow. This is especially true o f the M i d Reach, which generally showed more U W zones than the L o w Reach and exhibited larger contributions from lateral inflow throughout the study period. This relation between the presence/absence of lateral inflow and the occurrence o f up-welling flow is also supported by the contrast between the portion o f M i d Reach upstream o f the seep from the portion below. The relatively consistent gradients that were measured may be an artefact o f the depth o f the hyporheic zone and the depth at which hydraulic gradients were measured in piezometers in Griffith Creek. If the piezometers were too deep, they might be characterizing the flow system linking the hillslopes to the channel rather than a true hyporheic flow system. Consequently, the observed up-welling zones might actually be related to lateral inflow rather than discharging hyporheic water. This suggestion is supported by results from the cross-correlation o f the L o w Reach, which shows the strong disconnection o f the 20 cm depth bed temperature from the  56  stream temperature and the strong correlation with seep temperature compared to the D W zones and the other bed temperature depth correlations.  5.4.2  Thermal characteristics In the L o w Reach, bed temperatures were strongly controlled by their hydrologic setting.  Temperatures at U W / N sites were lower than at D W sites at equivalent depths during summer. This temperature difference between areas o f subsurface exchange is consistent with much research over the past two decades [Alexander al, 2002; Malcolm  and Caissie,  2003; Constantz  et al, 2002; Moore et al, 2005c; Silliman  and Booth,  et al, 1998; Curry et  1993; White et  al,  1987]. In the M i d Reach, this effect o f vertical water flux on bed temperature was weaker, likely due to the complicated hydrologic pattern and the fact that distinctive zones o f up-welling and down-welling were not as apparent. The weaker contrast between up-welling and down-welling sites at M i d Reach could also reflect the greater influence o f the lateral inflow, as suggested by the relatively strong cross-correlations between bed and seep temperatures in the pre-harvest summer. The degree to which bed temperatures responded to logging was strongly dependent on the hydrologic setting. In the L o w Reach, the maximum post-logging increases in bed temperatures at D W zones were similar to, though smaller than, the maximum changes in stream temperature. Post-logging increases in bed temperatures also occurred at U W / N sites, though they were smaller than those at D W zones. Bed temperature increases were greatest near the surface and decreased with depth. In the M i d Reach, there were smaller increases in post-logging summer bed temperatures for both hydrologic settings. In part, the smaller post-harvest increases could reflect the smaller change in stream temperature that occurred at M i d Reach (e.g., compare the top graphs in Figure 5.10 and Figure 5.4), although it might also reflect the stronger influence of lateral inflow on bed temperatures. A t the L o w Reach, the mean increase in bed temperature was greatest for the daily maximum temperature; at the M i d Reach, the mean increase was greatest for daily mean temperature. For both reaches, mean post-logging temperature increases generally decreased with depth, except for the mean change i n mean daily temperature at M i d Reach. The results for L o w Reach indicate that the stream bed w i l l likely not warm uniformly following logging, but the magnitude of change w i l l be controlled by the direction o f flow into or out o f the bed and the thermal signature o f the source water. The results for M i d Reach, particularly the tendency to a more uniform increase in temperature with depth, suggest that 57  vertical heat transport, via conduction and advection, was not the only process causing temperature increases, and that horizontal heat advection via lateral inflow may have played a role. Effects o f hydrologic setting on the bed temperature patterns were also detectable using P C A . Ordination o f the loadings for the L o w Reach bed temperatures showed that the combined effects o f hydrologic setting and depth were expressed by the second principal component for both the pre- and post-logging periods. The second P C accounted for more variance in the postlogging period (11.6% vs 3.5%), possibly reflecting the fact that the effect o f logging was more strongly expressed at D W sites and at shallow depths, effectively strengthening the pre-harvest pattern o f bed temperature contrasts. Ordination did not show as clear a picture for the M i d Reach. In the pre-logging period, the horizontal location appeared to account for more of the structure in the ordination plot than the depth. In the post-logging period, the ordination dominantly represented the effect of depth via the second P C , similarly to the pre-logging plots. However, the proportion o f variance accounted for by the second P C did not increase after logging at M i d Reach, as it did at L o w Reach. Therefore, it appears that, after logging, the effect o f depth displaced the effect o f horizontal location as a second-order influence on temperature variability. One interpretation o f these results is that vertical heat transport in the bed was relatively small in the pre-logging period and the thermal signature o f the groundwater seep had a larger influence on the bed temperature patterns. However, with removal o f the canopy in the post-logging period, increased solar radiation influenced the bed temperatures through heat conduction associated with the increased insolation at the surface o f the bed. This would explain the pattern with depth being established in the post-logging period. The points in Figures 5.6 and 5.12 exhibit a horseshoe pattern. This pattern is common when conducting P C A and is debated by authors to its meaning. Detrended correspondence analysis ( D C A ) can be used to correct the shape [Chang and Gauch,  1986]. However, it is not  clear i f D C A w i l l rectify the distortion in the analysis and may even add to it [Kenkel and  Orloci,  1986]. A critique even suggests that the shape is simply an artifact o f the data that are used i n the analysis and does not affect the results [Wartenberg  et al, 1987]. Due to these differing opinions  it is believed that the results from the P C A are not distorted. The fact that the ordination patterns can be interpreted i n relation to plausible changes in heat transport processes following harvest supports their validity.  58  Cross-correlation analyses were consistent with the results o f P C A . The L o w Reach showed especially consistent results, with the easily identifiable U W / N and D W zones showing higher correlations with seep and stream temperatures, respectively. However, where the crosscorrelation results assisted interpretation was in the M i d Reach with its complicated thermal patterns. In the pre-logging period, the high correlations with seep temperature for the L 3 , L 4 , and L 5 thermocouple locations, which are downstream of the seep, and the different patterns at the L I and L 2 locations, are broadly consistent with the effect o f horizontal location that is present i n the pre-harvest ordination. The C C A are also consistent with the contrasting changes in mean daily temperature for L 4 ( D W ) and L 5 ( U W / N ) . Cross-correlations with seep temperature exceeded 0.5 at all depths at L 5 , while at L 4 they dropped below 0.5 i n the top 10 cm, consistent with the stronger influence o f vertical heat transport from the surface v i a down-welling flow at that site. A n example o f the potential role that U W / N zones have on stream temperature is illustrated in the pre-logging portion o f Figure 5.2. This figure shows that stream temperature was lower than bed temperatures i n the D W zone but higher than those i n the U W / N zone. Water temperature data loggers were placed in pools throughout the stream to ensure that they would be submerged during summer l o w flow periods. This particular water temperature probe was located approximately 1 m downstream o f the S I D bed temperature site, therefore being in a location where it was receiving a mixture o f stream surface water and water that discharged from the bed, giving it an intermediate temperature signature. The S3 site showed similar temperature contrasts between D W and U W / N sites, suggesting that this pattern o f stream water mixing below steps may be a common phenomenon, consistent with previous studies [Bilby, 1984; Moore et al, 2005c; Story et al., 2003]. This pattern was not present in the post-logging period, likely as a result o f the increased solar radiation warming the water mixture before it reached the water temperature probe.  5.4.3  Biological implications Griffith Creek is non-fish bearing; however, these results are consistent with other  research that local U W zones and groundwater discharge provide cooler water temperature locations and can be areas o f refuge for fish in extreme summer warm periods [Power et al., 1999]. The lower magnitude o f post-logging warming in the U W / N zone also suggests that U W zones may retain their cool water properties and may be able to provide areas o f thermal refuge in fish-bearing reaches. However, the post-harvest data from the L o w Reach suggested that stream 59  water did heat shortly, after emerging from the bed, and thus that the area or volume o f cool-water zones in a stream may be reduced. These findings also have implications for the distribution and abundance o f benthic communities, which are strongly influenced by their thermal environment [Vannote and Sweeney, 1980]. Research conducted on stream invertebrates showed that daily temperature fluctuations o f 10 °C decreased the mean temperature required to cause lethal results in mayfly Deleatidium autumnale by up to 2 °C [Cox and Rutherford, 1999]. This may be o f concern when considering the increased amplitude o f daily bed temperatures in the post-logging period and the greater proportion o f the stream bed that exhibited D W flows compared to U W flows i n the L o w Reach. Although Griffith Creek did not approach these increased mortality ranges it should be noted that benthic communities may be reduced in abundance because U W / N zones, which may be required for optimal growth and fecundity o f invertebrates in post-logging conditions, may not be as abundant as the less favourable D W zones in the post-logging period.  60  Table 5.1 Griffith Creek Low Reach discharge values in Ls"'. UB and LB are the reach upper and lower boundary, respectively, and S2 and S3 are locations of step-pool sequences. 30/5/ 2005  24/6/ 2005  22/7/ 2005  25/7/ 2005  2/8/ 2005  5/8/ 2005  5/9/ 2005  17/9/ 2005  8/10/ 2005  29/10/ 2005  UB  0.83.  2.50  1.03  0.82  0.24  0.31  0.18  0.30  9.54  3.08  S2  0.85  0.24  9.54  3.08  S3  0.9  0.26  9.69  3.11  LB  0.98  10.01  3.15  S2-UB  0.02  0.00  0.00  0.00  S3 -S2  0.05  0.02  0.15  0.03  LB-S3  0.08  0.02  0.32  0.04  LB - UB  0.15  -0.02  -0.04  0.01  0.04  0.00  -0.01  0.01  0.47  0.07  Lateral Inflow Percent  15.3  -0.8  -4.0  1.2  14.3  0.0  -5.9  3.2  4.7  2.2  2.48  0.99  0.83  0.28  0.31  0.17  0.31  Table 5.2 Hydraulic conductivities measured at Griffith Creek Low Reach. CI indicates approximate 68% confidence intervals. • Hydraulic Conductivity (m s") 1  Piezometer  Lower CI  Geometric Mean  Upper CI 1.4E-04  2 (UW/N)  NA  NA  2.4E-05  3.5E-05  2.3E-05  5.9E-05  4.2E-05  1.3E-05  4.2E-05  3 (UW/N)  NA  . NA  1.6E-04  6.8E-04  1.0E-04  8.6E-04  4.0E-04  9.3E-05  4.0E-04  1.7E-03  6.7E-06  2.2E-04  4(DW)  1.7E-07  NA  9.0E-06  1.7E-05  1.2E-05  1.6E-05  6.7E-06  2.0E-07  1.4E-04  2.4E-04  1.6E-04  1.1E-04  1.6E-04  • 2.4E-04  6 (UW/N)  1.7E-04  1.9E-04  9.0E-05  1.7E-04  8 (UW/N)  2.0E-04  7.5E-04  1.1E-04  ' 4.0E-04  1.6E-04  1.2E-04  2.5E-04  9.9E-05  2.5E-04  6.1E-04  12 (DW)  7.4E-05  6.5E-05  8.1E-05  7.4E-05  6.4E-05  5.5E-05  6.7E-05  5.5E-05  6.7E-05  8.2E-05  Sample Date  2/8/ 2005  5/8/ 2005  15/8/ 2005  5/9/ 2005  3/10/ 2005  8/10/ 2005  29/10/ 2005  61  Table 5.3 Mean differences between observed and predicted temperatures for the pre- and post-logging periods, for one down-welling (DW) and one up-welling/neutral (UW/N) site in the low reach. s of residuals is the standard error of the pre-logging regression, d.f. is the pre-logging degrees of freedom, and k is the order of the residual autocorrelation. e  Temperature Variable  Period  DW 1 cm  DW 5 cm  DW 10 cm  DW 15 cm  UW/N 1 cm  UW/N. 5 cm  UW/N 10 cm  UW/N 20 cm  Daily Maximum  Pre-logging  0.09  0.09  0.04  0.06  0.00  0.01  0.03  0.14  Post-logging  1.20  1.03  0.99  0.76  1.08  0.81  0.62  . 0.42  s of residuals  0.60  0.58  0.45  0.48  0.44  0.48  0.53  0.79  d.f.  143  143  143  143  143  143  143  143  K  3  3  2  2  2  3  3  3  Pre-logging  0.01  -0.02  -0.02  0.00  0.02  0.02  0.04  0.08  Post-logging  0.75  0.62  0.47  0.36  0.56  0.45  0.33  0^26  s of residuals  0.48  0.48  0.51  0.55  0.51  0.53  0.57  0.61  d.f.  143  143  143  139  143  143  143  143  K  2  2  2  2  2  2  2  1  Pre-logging  -0.01  0.00  0.01  0.02  0.00  0.00  0.01  0.07  Post-logging  0.35  0.29  0.11  0.02  0.25  0.12  -0.01  -0.08  s of residuals  0.48  0.48  0.51  0.55  0.51  0.53  0.57  0.61  d.f.  143  143  143  143  143  143  143  143  K  2  2  2  2  2  2  2  1  e  Daily Mean  e  Daily Minimum  e  Table 5.4 Measured streamflow at Griffith Creek Mid Reach (Ls"'). UB and LB are the reach upper and lower boundaries, respectively. Location of L5 is shown on Figure 4.8. 6/6/ 2005  24/6/ 2005  18/7/ 2005  22/7/ 2005  25/7/ 2005  5/8/ 2005  5/9/ 2005  17/9/ 2005  8/10/ 2005  24/10/ 2005  29/10/ 2005  UB  1.43  2.06  0.95  0.86  0.57  0.12  0.09  0.14  8.31  5.65  2.48  L5  1.95  8.78  5.85  2.73  LB  2.17  8.99  6.02  2.82  L5 - UB  0.52  0.20  0.47  0.20  0.25  LB-L5  0.22  0.08  0.21  0.17  0.09  LB-UB  0.74  0.02  0.28  0.08  0.08  0.14  0.06  0.10  0.68  0.37  0.34  Lateral Inflow Percent  34.1  1.0  22.8  8.5  12.3  53.8  40.0  41.7  7.6  6.2  12.1  1.15 2.08  1.23  0.94  0.65  0.26  0.15  0.24  62  Table 5.5 Hydraulic conductivities measured at Griffith Creek Mid Reach. CI indicates approximate 68% confidence intervals. Hydraulic Conductivity (m s  Piezometer  Lower CI  Geometric Mean  Upper CI  2 (UW/N)  2.5E-05  1.3E-05  1.5E-04  1.2E-04  9.0E-05  5.8E-05  1.1E-05  5.8E-05  3.1E-04  6 (UW/N)  NA  2.4E-05  8.8E-05  7.4E-06  4.3E-06  1.2E-05  7.0E-07  1.2E-05  2.2E-04  8 (UW/N)  NA  9.2E-06  2.3E-05  1.0E-05  1.0E-05  1.1E-05  4.8E-06  1.1E-05  2.7E-05  9 (UW/N).  NA  1.6E-05  4.4E-05  4.7E-05  5.8E-05  3.8E-05  1.4E-05  3.8E-05  1.0E-04  10 (DW)  NA  3.3E-05  1.3E-05  1.1E-05  1.0E-05  1.4E-05  4.9E-06  1.4E-05  4.0E-05  11 (UW/N)  4.3E-06  NA  6.4E-05  7.5E-05  8.2E-05  4.3E-05  3.4E-06  4.3E-05  5.5E-04  12 (DW)  NA  6.3E-05  1.8E-04  6.2E-05  9.0E-05  8.9E-05  3.2E-05  9.0E-05  2.5E-04  4.9E-06  4.0E-05  3.2E-04  13 (DW)  NA  NA  2.8E-05  1.6E-04  2.4E-05  4.0E-05  Sample Date  5/08/ 2005  15/08/ 2005  5/09/ 2005  3/10/ 2005  8/10/ 2005  29/10/ 2005  Table 5.6 Mean differences between observed and predicted temperatures for the pre- and post-logging periods, for one down-welling (DW) and one up-welling/neutral (UW/N) site in the mid reach. s of residuals is the standard error of the pre-logging regression, d.f. is the pre-logging degrees of freedom, and k is the order of the residual autocorrelation e  Temperature Variable  Period  DW 5 cm  DW 10 cm  DW 15 cm  DW 30 cm  UW/N 5 cm  UW/N 10 cm  UW/N 15 cm  UW/N 30 cm  Daily Maximum  Pre-logging  0.08  0.08  0.07  0.04  0.02  0.05  0.07  0.05  Post-logging  0.15  0.17  0.20  0.18  0.33  0.03  0.09  0.14  s of residuals  0.81  0.74  0.67  0.52  0.58  0.65  0.59  0.51  d.f.  355  355  336  344  201  324  355  355  K  3  3  3  3  1  3  3  1  Pre-logging  0.09  0.08  0.07  0.04  0.04  0.05  0.07  0.08  Post-logging  0.37  0.34  0.36  0.34  0.51  0.22  0.27  0.19  s of residuals  0.84  0.78  0.71  0.57  0.59  0.69  0.60  0.62  d.f.  355  355  336  344  201  324  355  355  K  3  3  3  3  1  3  3  3  Pre-logging  0.08  0.07  0.06  0.04  0.04  0.07  0.08  0.08  Post-logging  0.02  0.02  -0.01  -0.02  0.15  -0.17  -0.12  -0.04  s of residuals  0.8.6  0.77  0.70  0.66  0.66  0.73  0.65  0.61  d.f.  355  355  336  344  201  324  355  355  K  1  1  1  1  1  1  1  1  e  Daily Mean  e  Daily Minimum  e  63  Figure 5.1 Map of Griffith Creek Low Reach, showing locations of thermocouple nests (S1U, SID, S2U, S3U, S3D), groundwater seep location, and piezometer locations (numbers in brackets). Bold numbers indicate study period average hydraulic gradients (negative values indicating flow into the stream bed). Stream flows according to arrow.  Pre-logging  10cmDW 10 cm UW/N  20  Post-logging  19 H 18  /X"*" ,  17 _..  /  • .  .  16 15  GW 50 cm J  ,  - --  14 "  "  "  ~  13  1  15-Aug-04  "  16-Aug-04  08-Aug-05  09-Aug-05  Figure 5.2 Bed temperatures of SI and S3 down-welling (DW) and up-welling/neutral (UW/N) sites at 10 cm depth in the Low Reach, with stream and 50 cm depth groundwater seep temperatures for two warm days in pre- (left) and post-logging (right) summers.  64  14.7  Pre-logging  1  4  Post-logging  14^5  14.5 O  14.7  14.3  3  14.1  ¥ 14.1 \ j» 13.9 E 13.7  \  \ \  \ ^ \ ^\  \ \  \  13.3 DW  \  \ s  13.5  13.9 •  \ \  1 cm 5 cm 10 cm 15 cm DW20 UW/N  13.7 13.5  •  UW/N  13.3 DW  UW/N  Figure 5.3 Means of mean seasonal bed temperatures grouped by hydrologic setting and depth for 3 down-welling and 2 up-welling sites in the pre- and post-logging summers (13/7/2004 - 12/9/2004 and 10/7/2005 - 9/9/2005).  65  01-Jun-04  01-Oct-04  01-Feb-05  01-Jun-05  O1-Oct-05  Figure 5.4 Difference between observed and predicted daily maximum stream and bed temperatures in the low reach. Bed temperatures are shown for one down- (DW) and one up-welling/neutral (UW/N) location. Vertical lines indicate logging period (Sep 04 - Nov 04). Horizontal dashed lines indicate 2 times the s of residuals from the prelogging regression. Bed temperature data are missing from 22 April to 8 June 2004 due to a malfunction of the data logging system, and no data were recorded between 11 September 2004 and 23 March 2005. e  66  01-Sep-05  01-Aug-05  01-Sep-04  01-Aug-04  Figure 5.5 T i m e series o f principal component scores from P C A o f L o w Reach bed temperatures for pre- (left) and post-logging (right) periods. Scores are plotted for the first two principal components.  • T_  0.4 0.3 0.2  A  •  0.1  O  0.0  • •  CM  O  A  Q.  -0.1  V  -0.2  0  T  1 cmDW 1 cm UW/N 5 cm DW 5 cm UW/N 10cmDW 10 cm UW/N 15cmDW 20 cm UW/N 30 cm DW  0.4 • 0.3 •  oo  0.2 •  0.0 -0.1 A  -0.4 0.4  0.2 0.1 CM  o  o.o  QL  -0.1  • o • •  •  -0.4  O Post-logging (depth)  A.  0.3 G  S1U DW S1D UW/N S3U DW S3D UW/N S2U DW  o  0.2  • ft  0.1  6  • o  0.0  •  -0.1  *  -0.2  -0.2  -0.3  -0.3 -0.4  -0.3  0.4  • o  0.3  Q  -0.2  Pre-logging (depth)  -0.3  • 1 o • A J •  0.1 •  Pre-logging (site) 0.180  0.185  0.190 PC 1  0.195  -0.4 0.200 0.12  3  O  Post-logging (site)  • 0.14  0.16  0.18  0.20  0.22  PC 1  Figure 5.6 Ordination o f first and second principal components for pre-logging (left) and post-logging (right) bed temperature data by depth (top) and site (bottom). D W and U P / N indicates down-welling and up-welling/neutral sites respectively.  67  -5 -10 -  £ r~  Q. 0  Q  -15 -20 -25 -30 0.0  Pre-logging Clear Sky  Post-logging Clear Sky  Pre-logging Cloudy Sky  Post-logging Cloudy Sky  -O—•— —A— -V-0- • -  S1U (DW) Stream S3U (DW) Stream S1D (UW/N) Stream S2U (DW) Stream S3D (UW/N) Stream S1U (DW) Seep  -m—A— - • - • -  S3U S1D S2U S3D  —I— 0.2  (DW) Seep (UW/N) Seep (DW) Seep (UW/N) Seep I  0.4  0.6  Correlation Coefficient  Correlation Coefficient  Figure 5.7 L o w R e a c h cross correlation coefficients o f bed temperature versus stream a n d seep temperatures plotted against b e d temperature depth for t w o consecutive clear (top) a n d c l o u d y (bottom) s k y days i n the pre- (left) a n d post-logging (right) p e r i o d .  Figure 5.8 M a p o f Griffith C r e e k M i d R e a c h , s h o w i n g locations o f t h e r m o c o u p l e nests ( L 1 - L 5 ) , groundwater seep location, a n d piezometer locations (numbers i n brackets). B o l d numbers indicate study p e r i o d average h y d r a u l i c gradients (negative values indicating flow into the stream bed). Stream flows a c c o r d i n g to arrow.  68  10-Aug-04  11-Aug-04  14-Aug-05  15-Aug-05  Figure 5.9 B e d temperatures at 10 cm depth in the mid reach, with stream and 50 c m depth groundwater seep temperatures for two warm days in pre- (left) and post-logging (right) summers.  69  6 4  Stream Temperature  2 0 4 2 0 4  L5 5 cm UW/N  2 0 _  4  o°  2  L4 10 cm DW  T3 OJ O T3 0 i _  0_ I  CD CD CO  L4 15 cm DW  O L5 15 cm UW/N  L4 30 cm DW  L5 30 cm UW/N  1  01-Aug-03  01-Feb-04  01-Aug-04  i 01-Feb-05  01-Aug-05  Figure 5.10 Difference between observed and predicted daily maximum stream and bed temperatures in the mid reach. Bed temperatures are shown for one down- (DW) and one up-welling/neutral (UW/N) location. Vertical lines indicate logging period (Sep 04 - Nov 04). Horizontal dashed lines indicate 2 times the s of residuals from the prelogging regression. Bed temperature data are missing from 22 April to 8 June 2004 due to a malfunction of the data logging system, and no data were recorded between 11 September 2004 and 23 March 2005. e  70  01-Sep-05  01-Aug-05  01-Jul-05  O1-Aug-04  01-Jul-04  Figure 5.11 Time series o f principal component scores from P C A o f M i d Reach bed temperatures for pre- (left) and post-logging (right) periods. Scores are plotted for the first two principal components.  0.6  T  0.5 -  o  0.4 -  A  •  0.3 •  V  O +  0.2 • CM  o 0-  0.1 -  V  -0.2 -0.3 •  A  0  o+ A  0.1  Q  +  V  +  I  0.5 0.4 -  A  0.3 •  V  0.2 •  +  -0.4  •  •  + V A  0.2  •  0+  •  0.1 0.0  +  E  -0.1  -0.2  +  V  +  V  A  -0.2  •  -0.3  A  °  + +  *  V  -0.4  -0.4 -0.5 • 0.20  Post-logging (depth)  -0.5  0.3  0.0 •  -0.3  CP  0.4  o  L 1 L2 L3 L4 L5  -0.1  ^  -0.3  O  0.1 -  •  -0.2  Pre-logging (depth)  o •  A  So  0.0  +  -0.5 -  o Q.  o  0.3 0.2  -0.4 -  CM  •  -0.1  0.0 -0.1 -  0.6  0.4  •  1 cm 5 cm 10 cm 15 cm 20 cm 30 cm  Post-logging (site) -0.5 0.30 0.195 0.200 0.205 0.210 0.215 0.220 0.225 0.230  Pre-logging (site) 0.22  0.24  0.26  0.28  PC 1  PC 1  Figure 5.12 Ordination o f first and second principal components for pre-logging (left) and post-logging (right) bed temperature data by depth (top) and location in the stream (bottom).  71  Pre-logging Clear Sky  Post-logging Clear Sky  Pre-logging Cloudy Sky  Post-logging Clouy Sky  E o Q.  CD Q  -O-O—A— -V- • -m—A— -V-  L2 (DW) Stream L3 (UW/N) Stream L4 (DW) Stream L5 (UW/N) Stream L2 (DW) Seep L3 (UW/N) Seep L4 (DW) Seep L5 (UW/N) Seep  —I—  0.0  Correlation Coefficient  0.2  0.4  Correlation Coefficient  Figure 5.13 Mid Reach cross correlation coefficients of bed temperature versus stream and seep temperatures plotted against bed temperature depth for two consecutive clear (top) and cloudy (bottom) sky days in the pre- (left) and post-logging (right) period.  72  CHAPTER SIX  EFFECTS OF FOREST HARVESTING ON STREAM HEAT BUDGETS: AN EXPERIMENTAL APPROACH 6.1  INTRODUCTION Stream temperatures reflect the influences o f a variety o f energy fluxes, which can be  classed as being atmospheric or terrestrial. Atmospheric energy exchanges include solar radiation, longwave radiation, sensible heat, and latent heat. Terrestrial fluxes include bed heat conduction, heat from groundwater discharge, and hyporheic heat exchanges. Heat budgets have been used to understand stream temperature dynamics in a variety o f settings; however most o f these studies were not conducted in the context o f forest harvesting [Evans et al, 1998; Webb and Zhang, 1997]. The earliest heat budget study focused on forest harvesting was conducted by Brown [1969]; since then, only Story et al. [2003], Johnson [2004] and Moore et al. [2005b] appear to have estimated heat budgets for forestry-influenced streams. None o f those studies applied heat budgets in both pre- and post-logging conditions at the same site, making the analysis o f which processes are responsible for stream temperature increases more difficult to assess. This chapter w i l l focus on the results o f the application o f a heat budget analysis to two study reaches both before and after a 50% dispersed retention logging treatment along the stream. Analysis w i l l focus on the identification o f the processes which are responsible for creating the thermal regime o f the stream in the post-logging environment. Methods have been described i n detail i n chapter two.  6.2  O V E R V I E W OF PERIODS USED FOR H E A T B U D G E T A N A L Y S I S Heat budgets were calculated for two days in July and August o f both the pre- and post-  logging period. The pre-logging summer was warmer and drier than the post-logging summer (Figure 6.1 and 6.2, and chapter 3). The two-day periods used in the heat budget were similar between pre- and post-logging summers. Daily maximum air temperature was greater in 2004 for both the July and August two-day periods, with daily maximum temperature near 30°C compared to 25°C in the post-logging summer. M i n i m u m air temperatures were similar for both periods, with values ranging between 10 °C and 15 °C. This pattern was reversed for stream temperatures: the post-logging summer was warmer by at least 1 °C compared to the respective 73  period o f the pre-logging summer. Discharge also was greater in the post-logging summer compared to 2004, with values averaging one order o f magnitude greater than the pre-logging summer.  6.3  SOLAR RADIATION MODELLING Solar radiation for the heat budget was modelled using hemispheric canopy images taken  above the stream to map the distribution o f canopy, gaps in relation to the sun's position. Modelled solar radiation was compared to measured data to calibrate the darkness threshold o f the images in both the pre- and post-logging periods. For the pre-logging period, the calibration was based on hourly averages o f solar radiation for three pyranometers located directly over Griffith Creek. For the post-logging period, data were only available for one location over the stream. The calibration periods for both the pre- and post-logging conditions consisted o f generally clear sky conditions. Calibration emphasized clear sky conditions due to the proportions o f these conditions during the summer months when stream heating occurred. Calibration in the pre-logging period was relatively accurate, with only small deviations present between the modelled and below canopy measurements (Figure 6.3). The post-logging calibration was not as accurate, with the modelled radiation exhibiting a lower peak but greater amounts o f radiation in the morning and evening compared to the measured below canopy observations. However, the daily radiation totals were approximately equal between observed and modelled data.  6.4  HEAT BUDGET RESULTS FOR THEL O W R E A C H In the pre-logging period, the primary positive flux was net radiation during the day time,  with sensible and latent heat contributing small quantities irregularly for latent heat (Figure 6.4. and 6.5). B e d heat conduction and hyporheic heat exchange were the dominant day time cooling fluxes, accounting for almost 60% and 40% o f the heat losses in the pre-logging period, respectively. Groundwater discharge contributed consistently small magnitudes near 2 W m" ; these negative fluxes were strongest during daytime and decreased at night. A l l fluxes were relatively small in magnitude, ranging from about 70 to -40 W m~ . The heat fluxes exhibited some contrasts between the July and August periods in the prelogging period. In July, most heat fluxes became negligible at night, with the exception of bed heat conduction, which was a heat source, and latent heat which acted as cooling fluxes. In  74  August, net radiation remained positive at night, while bed heat conduction became a heat sink. Hyporheic exchange also became a nocturnal heat sink in August. The agreement between observed and modelled rates o f temperature change varied. In July, the heat budget predicted almost continuous cooling, in contrast to the observed pattern o f diurnal warming and nocturnal cooling. In August 2004, the modelled temperature changes were in reasonable agreement with observations at night, with both indicating weak cooling. However, the heat budget predicted cooling through the morning in contrast to observed warming, and warming i n the late afternoon, when weak cooling actually occurred. In the post-logging period, energy fluxes were generally greater than in the pre-logging period, ranging from 390 to -50 W m~ i n July and 380 to -110 W m" i n August (Figure 6.6 and 2  2  6.7). Fluxes were lower i n July compared to August, similar to the pre-logging situation. The relative magnitudes o f most o f the energy fluxes were similar to those during the pre-logging period, with net radiation remaining the dominant daytime warming flux and sensible heat adding small amounts. In contrast to the pre-logging period, groundwater discharge assumed a stronger role as a daytime cooling flux. Latent heat changed sign i n the post-logging period, and remained continuously negative and accounted for almost 25% o f the cooling. Hyporheic exchange, bed heat conduction, and groundwater discharge accounted for, on average, 40, 25, and 10% o f the cooling in the two post-logging study periods, respectively. One exception to this pattern occurred i n the evening after a warm day in August, when bed heat conduction and hyporheic heat exchange became positive (Figure 6.7). Consistent with the increased heat inputs after logging, observed rates o f temperature change exceeded 1 °C/hr, i n contrast to maximum pre-logging warming rates o f about 0.3 °C/hr. The observed and modelled rates o f temperature change showed better agreement than for the pre-logging period, particularly.at night. However, the heat budget over-predicted warming in the morning and late afternoon, and over-predicted cooling in the early evening. For the pre-logging period, increasing the stream depth used in the heat budget calculations improved the agreement between predicted and observed temperature change to some degree by dampening the modelled rate o f temperature change, but there were still notable discrepancies. Increasing stream depth for the post-logging period greatly increased the agreement between predicted and observed temperature changes. However, some o f the short term fluctuations were not represented by the heat budget model. This is supported by root mean squared error ( R M S E ) values which showed that model agreement with observed values increased when water column depth was increased, with R M S E values decreasing 0.20 and 0.12 75  for July and August o f the pre-logging period and 0.46 and 0.45 in July and August o f the postlogging period (Table 6.1).  6.5  HEAT BUDGET RESULTS FORTHE MID R E A C H Energy fluxes showed similar patterns i n the M i d Reach as for the L o w Reach in both the  pre- and post-logging periods (Figure 6.8 to 6.11). Inputs o f energy were dominated by net radiation, and i n the pre-logging July period, latent and sensible heat added energy to the stream during day time. Negative fluxes in the pre-logging period were dominated by bed heat conduction, accounting for approximately 50% o f the heat loss, as well as groundwater discharge, hyporheic exchange, and latent heat, accounting for approximately 25, 20 and 5% o f the heat loss, respectively. In the post-logging period, all terms except net radiation were negative fluxes. B e d heat conduction, latent heat, groundwater discharge, and hyporheic exchanges each accounted for approximately 25% o f the day time cooling fluxes in the M i d Reach. In the July example for the pre-logging period, the modelled temperature changes captured the observed diurnal warming and nocturnal cooling, but greatly exaggerated the rates, particularly for nocturnal cooling. In the August example, the modelled temperature changes were strongly biased toward cooling. In the post-logging period, modelled temperature changes dramatically over-predicted day time warming and night time cooling. A s with the L o w Reach, the heat budget generally overestimated daytime heating and underestimated a short period after sunset. Agreement between modelled and observed rates o f temperature change increased for both pre- and post-logging periods by increasing stream depth (Figures 6.8 to 6.11). Calculated R M S E values for the two modelled depths reduced when depth was increased with values decreasing from 0.42 to 2.69 (Table 6.2), Depth had to be increased more i n the M i d Reach than the L o w Reach to achieve agreement with observed data. The improved agreement between modelled and observed rates o f temperature change with increased stream depth suggests that the conceptualization o f hyporheic exchange in the heat budget model may not be appropriate. Figure 6.12 illustrates the rates o f temperature change for the model without the hyporheic heat exchange component. Depth was set to achieve the best fit to daytime heating. This revised model underestimated rates o f cooling in the early evening. Modelled rates o f temperature change were reasonable for the cloudy day. The fit was not as  76  precise i n comparison to that o f Figure 6.7, where hyporheic exchange was included in the heat budget.  6.6  DISCUSSION Modelled rates o f temperature change did not agree well with observed rates in the pre-  logging period. In particular, the heat budget appeared to be biased toward cooling, in contrast to the consistently observed daytime warming. However, all fluxes were small, and thermal differences used to compute heat fluxes were on the order o f ± 0.2 °C, the same as the measurement error. Modelled and observed rates o f temperature change agreed better after logging, at least at the L o w Reach, when stronger thermal contrasts dominated. The heat budget model performed better in the L o w Reach than in the M i d Reach. A major source o f error in the heat budget estimates could be the difficulty in accurately modelling solar radiation in such complex shade environments. For example, the overestimation of dT/dt on overcast days, when all fluxes but net radiation were minor, suggests that net radiation has been overestimated (Figure 6.6, July 2, 2005). Similarly, the overestimation o f dT/dt i n the morning and late afternoon could result from underestimation o f shading at lower sun angles. However, the improved agreement with observed dT/dt when reach average water column depth was increased suggests that our depth estimates are too low. Moore et al. [2005c] observed similar results, with doubling the water column depth creating much better agreement with the observed rate o f temperature change. This result suggests either that the reach-average water column depth was underestimated, or that the volume o f water involved in stream heating and cooling is not only constrained to that o f the water column. W h i l e uncertainty does exist i n the estimated depths, it is not likely to be large enough to account for the depth increases that were required to match modelled and observed rates o f temperature change. These results suggest that our conceptualization o f hyporheic exchange flows may not be accurate, especially since we focused on parameterizing the effects o f vertical exchanges. This parameterization is based on the notion that hyporheic residence times are on the order o f hours, so that the temperature o f discharging hyporheic water is out o f phase with stream temperature. However, this conceptualization does not account for short duration hyporheic exchange through steps and lateral flow paths through point bars and across the stream banks. These exchanges effectively increase the active water volume that is heated and cooled, but without the effects o f a significant temperature difference between downwelling and discharging water. Tracer studies conducted on Griffith Creek's L o w and M i d Reach showed that the transient storage zone 77  represented a mean depth o f approximately 7 cm for both reaches (Gomi, unpublished data). This value is somewhat lower than differences between measured water column depths and those used to achieve a good fit i n the heat budgets, which were 6 c m for the L o w and 13 c m for the M i d Reach. Errors i n solar radiation and water column depth cannot account for all o f the discrepancies between modelled and observed temperature change. For example, the overestimation o f late-afternoon cooling (e.g., Figure 6.7, August 8, 2005) suggests that some of the cooling fluxes have been inaccurately estimated, specifically evaporation and hyporheic exchange. The comparison o f the Penman equation with measured pan evaporation suggests that the calculated evaporation does tend to be too high. Hyporheic exchange is a difficult term to estimate, as it depends on correct estimation o f the hydrologic flux as well as the temperature o f discharging hyporheic water. The spatial resolution o f our temperature measurements in the water column and the stream bed was likely insufficient to represent accurately the temperatures and temperature gradients driving hyporheic heat exchange and bed heat conduction. This was especially true for the M i d Reach, which exhibited a more complex hydrology and thermal regime compared to the L o w Reach (see Chapter 5). Additionally, the relatively heavy concentration o f measurements in the M i d Reach near and in areas that were influenced by the groundwater seep may have influenced the spatial distribution o f bed and hyporheic exchange measurements. Errors i n sensible heat are likely small since the calculated values were negligible, and the evaporation pan measurements indicate that the Penman equation tends to over-estimate turbulent exchange in this environment. (Figure 3.8). The results presented in this study are broadly consistent with previous research on forest streams by Story et al. [2003], Johnson [2004], and Moore et al. [2005c]. Hyporheic heat exchange was reported by Moore et al. [2005c] to be approximately 2 5 % o f the net radiation, lower than in the L o w Reach but o f similar magnitude to that in the M i d Reach. B e d heat conduction was estimated to be approximately 25% o f net radiation in both reaches o f Griffith Creek, which was higher than Moore et al. [2005c], but o f similar magnitudes to those estimated by Brown [1969] for conduction in a bedrock stream. The high rates o f bed heat conduction at Griffith Creek are likely a result o f the relatively large quantities o f lateral inflow and the interaction o f groundwater in the streambed, which creates steep thermal gradients and larger energy fluxes for both bed heat conduction and hyporheic heat exchanges. Latent and sensible heat fluxes were negligible i n the pre-logging period, but they increased to account for 25% and a small proportion o f the cooling in the post-logging periods, respectively. Previous studies have 78  noted that sensible and latent heat exchanges tend to be an order o f magnitude lower than net radiation [Johnson,  2004; Moore et al, 2005], which is in a similar range for both the L o w and  M i d Reach post-logging results. The results o f this study demonstrate that net radiation is the dominant flux driving postlogging warming. Sensible heat flux was negligible before harvesting and became a small cooling flux i n the post-harvest period, indicating that advection o f warm air from the harvested area cannot be invoked as a cause o f stream heating. Similarly, although the temperature o f lateral inflow (shallow groundwater) did increase by about 2 °C after logging, it remained lower than stream temperature during the day time and thus did not contribute to stream warming. It is possible, however, that the warming o f lateral inflow could have influenced daily minimum temperatures, which increased by up to about 2 °C during summer . Latent heat accounted for about 25% o f the calculated cooling fluxes. The remainder was contributed by hyporheic exchange, bed heat conduction and, to a lesser extent in the L o w Reach, groundwater discharge.  79  Table 6.1 R M S E of heat budget reach-average temperature change rates for two water column depths in Griffith Low Reach. Date  Water Column Depth (cm)  RMSE  Water Column Depth (cm)  RMSE  July 2004  4.0  0.45  8.0  0.25  August 2004  1.8  0.31  3.0  0.19  July 2005  8.2  0.65  20.0  0.18  August 2005  4.2  0.73  10.0  0.28  Table 6.2 R M S E of heat budget reach-average temperature change rates for two water column depths in Griffith Mid Reach. Date  Water Column Depth (cm)  RMSE  Water Column Depth (cm)  RMSE  July 2004  2.0  0.74  18.0  0.05  August 2004  2.3  0.53  10.0  0.11  July 2005  7.3  0.72  25.0  0.15  August 2005  2.3  3.04  15.0  0.34  18 A 16 14 H 12 10 1 4 0.1 0.01 01/07/2004  01/08/2004  Figure 6.1 A i r and stream temperatures and streamflow for July and August 2004. From top to bottom: daily maximum and minimum air temperature, Griffith Creek stream temperature and discharge. The shaded portion indicates the periods for the Heat Budgets.  80  01/08/2005  01/07/2005  Figure 6.2 A i r and stream temperatures and streamflow for July and August 2005. From top to bottom: daily maximum and m i n i m u m air temperature, Griffith Creek stream temperature and discharge. The shaded portion indicates the periods for the Heat Budgets.  00:00:00  12:00:00  0:00:00  12:00:00  Figure 6.3 M o d e l l e d and observed solar radiation for pre- and post-logging conditions above Griffith Creek.  81  — - Mod. d = 4.0 cm o Observed Mod. d = 8.0 cm  04/07/2004  06/07/2004  05/07/2004  Figure 6.4 Energyfluxesand reach-average observed and modelled temperature change rates for two water column depths for July 5 and 6, 2004, in Griffith Low Reach.  1  14/08/2004  15/08/2004  T  r  16/08/2004  Figure 6.5 Energyfluxesand reach-average observed and modelled temperature change rates for two water column depths for August 15 and 16, 2004 in Griffith Low Reach.  82  02/07/2005  03/07/2005  04/07/2005  Figure 6.6 Energy fluxes and reach-average observed and modelled temperature change rates for two water column depths for July 3 and 4, 2005 in Griffith Low Reach.  400  — ,  09/08/2005  1  i  i  i  10/08/2005  i  11/08/2005  Figure 6.7 Energy fluxes and reach-average observed and modelled temperature change rates for two water column depths for August 10 and 11, 2005 in Griffith Low Reach.  83  04/07/2004  05/07/2004  06/07/2004  Figure 6.8 Energy fluxes and reach-average observed and modelled temperature change rates for two water column depths for July 5 and 6, 2004 in Griffith Mid Reach.  14/08/2004  15/08/2004  16/08/2004  Figure 6.9 Energy fluxes and reach-average observed and modelled temperature change rates for two water column depths for August 15 and 16, 2004 in Griffith Mid Reach.  84  02/07/2005  03/07/2005  04/07/2005  Figure 6.10 Energy fluxes and reach-average observed and modelled temperature change rates for two water column depths for July 3 and 4, 2005 in Griffith Mid Reach.  Mod. d = 2.3 cm _o_  09/08/2005  10/08/2005  observed Mod. d = 15 cm  11/08/2005  Figure 6.11 Energy fluxes and reach-average observed and modelled temperature change rates for two water column depths for August 10 and 11, 2005 in Griffith Mid Reach.  85  o— Observed - — Mod. d = 15 cm  09/08/2005  10/08/2005  11/08/2005  Figure 6.12 Reach-average observed and modelled temperature change rates for August 10 and 11, 2005 in Griffith Low Reach.  86  CHAPTER SEVEN  CONCLUSIONS 7.1  S U M M A R Y OF M A I N FINDINGS  .  7.1.1  Stream temperature response to a dispersed retention logging treatment Warming was greatest in spring and summer, with no apparent warming in winter. The  largest treatment effects occurred in spring and not during the period o f seasonal peak temperatures, consistent with results from the Oregon Cascades [Johnson and Jones, 2000] and at other sites at M K R F [Gomi et al, 2006]. While seasonal means o f the daily mean and maximum temperatures increased with downstream distance through the cut block, post-logging changes in daily maximum temperature did not consistently increase with downstream distance. The greatest change in daily maximum temperature, 8 °C, occurred 200 m above the lower end o f the cut block, suggesting that daily maximum temperatures can respond to local variations in heat exchanges, and not just the accumulation of heat as water flows through the cut block. The magnitude o f warming was positively correlated to air temperature and negatively related to discharge. Daily minimum temperatures increased slightly in the summer months but showed no decreases in the two post-logging years. Despite the considerable amount o f shade provided by the dispersed retention within the cut block, the magnitude o f warming at Griffith Creek is similar to or greater than that found for a number o f streams subject to clear-cut logging with no riparian buffer, both in M a l c o l m Knapp Research Forest [Gomi et al, 2006] and at other sites in the Pacific Northwest [Moore et al., 2005b]. One explanation is that Griffith Creek has a small catchment (12 ha) and thus low summer flows compared to many o f the streams examined in previous studies. These low flows, combined with Griffith Creek's weakly incised channel and low banks, yield low surface water depths, increasing Griffith Creek's sensitivity to increased energy inputs. Therefore, it is difficult to assess the extent to which the 50% dispersed retention treatment protected Griffith Creek from stream warming through comparisons with other streams, without explicitly accounting for inherent differences i n sensitivities through the use o f a physically based heat budget model.  87  7.1.2  Hydrology and thermal regime o f the stream bed Bed temperature patterns differed between upwelling/neutral and downwelling zones.  Temperatures responded to the logging treatment less dramatically i n U W / N areas compared to D W areas, which showed similar maximum increases to those for stream water. The U W / N zones were better correlated with groundwater temperature patterns, while D W areas showed stronger correlations with surface water temperatures. Lateral inputs had a large influence on the thermal regime of the stream bed and almost overpowered the thermal patterns produced by vertical hyporheic exchange at some locations. Overall this study showed that bed temperature response to the logging treatment was not uniform and depended strongly on the direction o f hyporheic exchange flows. Post-logging bed temperature increases did not appear to be great enough to cause mortality o f benthic invertebrates, based on published temperature thresholds for species found in Griffith Creek. However, the bed temperature changes could influence rates o f growth and/or development and also timing o f emergence. Because the post-logging thermal response varied with the direction o f hyporheic exchange flows, the biological response to such changes should also exhibit distinctive spatial patterns. Such patterns should be considered in future attempts to assess the ecological influence o f post-logging stream warming.  7.1.3  Heat budget analysis before and after logging Net radiation was the dominant input o f energy to the stream in both the pre- and post-  logging periods. Latent and sensible heat was occasionally positive in the pre-logging period, and became negative fluxes in the post-logging summer. Therefore, advection o f warm air from cut blocks does not appear to be a viable mechanism for explaining post-logging stream warming, reinforcing the dominant consensus that increased solar radiation following logging is the main driver o f stream warming. Heat losses were dominated by groundwater, bed heat conduction, and hyporheic heat exchange. These terrestrial fluxes comprised 75% o f the total heat loss from the stream, with evaporation being the main atmospheric heat loss. The large differences between observed and modelled rates o f temperature change in the pre-logging period were likely a result of small thermal gradients, which were near measurement errors for the temperature probes. The post-logging period showed better correspondence between observed and modelled temperature change, although the heat budget exhibited systematic errors, particularly by overestimating daytime warming. The good agreement between modelled and observed rates o f temperature change with increased water column depth suggests 88  that rapid flow o f water through the hyporheic zone increases the active volume o f stream water engaged i n heating and cooling. If this is the case, then the conceptualization o f the thermal influence o f the hyporheic zone used in this study, and by Moore et al. [2005c] should be reassessed.  7.2  RECOMMENDATIONS FOR FUTURE R E A S E A R C H This study revealed significant variability in bed temperatures, which undoubtedly  introduced significant error into the calculated bed heat conduction and the heat exchange associated with hyporheic flows (which used bed temperatures to estimate the temperature o f discharging hyporheic water). Bed temperatures were influenced by vertical advection v i a hyporheic exchange, as well as by advection via lateral inflow. To reduce uncertainties in the terrestrial heat fluxes, further research is required on water fluxes between a stream and its bed and banks, particularly the interactions between hyporheic flow paths and lateral inflow. Given the difficulties o f studying these processes in complex headwater streams, it may be useful to study these processes through the use o f numerical groundwater models and through physical models (e.g., flumes with step-pool structures). Understanding the processes in simplified systems may assist i n designing sampling schemes to better measure the processes in complex streams. While variations i n surface water temperatures were not sampled to the same degree as bed temperatures, there was evidence o f significant heterogeneity. For example, water temperatures in one pool were found to vary by up to 2 °C, and stream warming did not consistently display a systematic downstream pattern. Furthermore, water temperatures differed between areas o f the stream bed influenced by different vertical hyporheic exchange flows. Because most of the energy flux computations involve stream temperature, it is critical to specify it accurately. A more detailed study o f the variability o f surface water temperatures in both time and space would help address some of the errors in the heat budget calculations, especially in a hydrologically complex reach such as the M i d Reach. Given the significance o f solar radiation as the dominant driver o f post-logging warming, it is crucial to be able to estimate accurately how much insolation reaches the stream surface. Further research should focus on validating the use o f canopy photographs for modelling solar radiation under complex canopies, particularly in relation to developing robust guidelines for setting thresholds for distinguishing sky from foliage.  89  This study has helped to answer questions related to how much stream temperatures change after logging and which processes are responsible. However, further research is required to examine how these temperature changes influence biological and ecological processes, and thus answer questions about their broader significance.  90  REFERENCES Alexander, M . D . , Caissie, D . (2003), Variability and comparison o f hyporheic water temperatures and seepage fluxes in a small Atlantic salmon stream, Ground Water, 41, 72-82. A l l e n , J. D . (1995), Stream ecology: Structure and function o f running waters, Chapman & H a l l , N e w York, 388 pp. Anderson, J. K . , Wondzell, S . M . , Gooseff, M . N . , and Haggerty, R. 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(1999), Influences o f streamside cover and stream features on temperature trends i n forested streams of Western Oregon, Western Journal of Applied Forestry, 14, 106-113.  96  APPENDIX A. Hydraulic gradients measured in Griffith Creek Low Reach during 2004. r are Spearman Correlation between discharge and hydraulic gradients, DW and UW/N indicates seasonally down- and upwell ing/neutral hydraulic gradients, respectively. Columns are arranged from left to right in order of decreasing discharge. s  Piezometer  Hydraulic Gradient  r  s  Hydrologic Setting  1  0.03  0.00  0.02  -0.02  0.00  0.02  0.00  -0.03  0.58  UW/N  2  -0.03  0.00  0.00  -0.03  0.00  0.00  0.00  0.00  -0.51  UW/N  3  -0.14  -0.08  0.00  -0.03  -0.03  -0.03  -0.09  -0.09  0.09  DW  4  -0.04  -0.06  -0.06  0.00  -0.08  -0.04  0.00  -0.02  -0.45  DW  5  0.00  0.06  0.00  0.00  0.00  0.03  0.07  0.07  -0.69  UW/N  6  -0.10  -0.09  -0.08  0.00  -0.28  -0.07  -0.15  -0.16  0.34  DW  7  -0.33  -0.37  -0.13  NA  -0.21  NA  -0.39  -0.43  0.55  DW  8  0.00  0.03  0.00  0.00  0.00  0.00  0.00  -0.05  0.62  UW/N  9  0.00  0.04  0.00  0.00  0.00  0.00  0.04  0.02  -0.38  UW/N  10  -0.13  -0.59  -0.59  -0.63  0.00  -0.72  -0.74  -0.74  0.76  DW  11  -0.49  -0.48  -0.47  -0.52  -0.65  -0.53  -0.56  -0.54  0.77  DW  12  -0.28  -0.08  -0.25  -0.26  0.00  -0.39  -0.36  -0.45  0.57  DW  13  -0.18  -0.29  -0.15  -0.16  -0.37  -0.17  -0.12  -0.12  -0.55  DW  Discharge Ls"  0.58  0.15  0.15  0.09  0.07  0.05  0.03  0.03  Sample Date  24/8/ 2004  13/7/ 2004  3/8/ 2004  6/8/ 2004  22/7/ 2004  28/7/ 2004  13/8/ 2004  16/8/ 2004  1  97  APPENDIX B. Hydraulic gradients measured in Griffith Creek Low Reach during 2005. r are Spearman Correlation between discharge and hydraulic gradients, DW and UW/N indicates seasonally down- and up-welling/neutral hydraulic gradients, respectively. Columns are arranged from left to right in order of decreasing discharge. s  Piezometer  Hydrologic s  S e K i n g  1  0.17  0.15  0.15  0.23  0.09  0.15  0.15  0.18  0.14  0.19  0.17  0.17  0.19  0.22  0.20  0.11  0.17  -0.24  UW/N  2  0.00  0.00  0.00  0.00  -0.03  -0.02  -0.02  0.00  -0.02  0.00  0.00  -0.04  0.00  0.00  0.00  -0.04  -0.03  0.33  UW/N  3  0.00  0.00  0.00  0.00  0.04  0.13  -0.05  0.10  -0.02  0.07  -0.04  0.05  -0.03  0.00  -0.02  0.00  -0.05  0.32  UW/N  4  0.02  0.00  0.03  0.02  -0.07  -0.10  -0.08  -0.08  0.03  -0.09  0.00  -0.09  0.07  0.00  0.00  0.10  -0.09  0.07  DW  5  0.02  0.00  0.00  ' 0.00  0.00  -0.02  -0.02  -0.02  0.00  0.00  -0.03  -0.03  0.00  -0.03  0.03  0.00  0.00  0.17  UW/N  -0.04  0.43  UW/N  6  0.00  0.00  -0.02  0.07  0.00  -0.02  -0.02  -0.02  -0.04  -0.02  -0.04  -0.04  -0.03  -0.04  0.00  0.02  7  -0.15  -0.15  -0.14  -0.06  -0.35  -0.35  -0.33  -0.35  -0.30  -0.40  -0.20  -0.36  -0.33  -0.26  -0.29  -0.33  -0.33  0.36  DW  8  0.00  0.02  0.00  0.03  0.02  0.00  0.00  0.00  0.03  0.09  0.00  0.03  0.00  0.00  -0.03  -0.02  0.03  0.15  UW/N  9  0.00  0.00  0.00  0.01  0.00  0.02  0.02  0.00  0.02  0.02  0.00  0.00  0.00  0.00  0.00  0.00  0.04  -0.07  UW/N  10  -0.57  -0.58  -0.49  -0.33  -0.60  -0.58  -0.59  -0.63  -0.63  -0.61  -0.59  -0.58  -0.61  -0.62.  -0.60  -0.60  -0.61  0.59  DW  11  -0.41  -0.43  -0.30  -0.28  -0.45  -0.45  -0.45  -0.50  -0.49  -0.44  -0.47  -0.45  -0.45  -0.45  -0.45  -0.44  -0.44  0.55  DW  12  -0.33  -0.32  -0.41  -0.27  -0.33  -0.35  -0.29  -0.36  -0.37  -0.36  -0.35  -0.34  -0.36  -0.35  -0.35  -0.36  -0.34  0.36  DW  13  -0.28  -0.24  -0.20  -0.26  -0.14  -0.11  -0.11  -0.14  -0.16  -0.12  -0.17  -0.17  -0.16  -0.16  -0.21  -0.12  -0.22  -0.21  DW  14  -0.11  -0.11  -0.10  -0.09  NA  NA .  NA  NA  -0.12  NA  -0.14  NA  -0.14  -0.14  -0.14  -0.15  -0.17  0.89  DW  15  -0.02  -0.11  0.00  0.00  NA  NA  NA  NA  0.00  NA  -0.05  NA  -0.05  -0.05  -0.02  -0.05  -0.02  0.18  DW  Discharge L s Sample Date  oo  r  Hydraulic Gradient  g  g  2  8/10 /2005  5  5  3  3/10 /2005  4  8  4  29/10 /2005  3  6  g 24/10 /2005  2  .76 6/6 /2005  0.83 22/7 /2005  0.72 30/5 /2005  0.55 25/7 /2005  0.52 5/9 /2005  0.36 29/7 /2005  0.33 17/9 /2005  0.28 2/8 /2005  0.28  0.26  2/9 . /2005  10/9 /2005  0.24 26/9 /2005  0.22 5/8 /2005  0.15 15/8 /2005  APPENDIX C. Cross-correlation coefficients and lags in minutes for bed temperatures on two clear and cloudy sky days in the pre- and post-logging period in the Low Reach. CC is the Cross-correlation coefficient. DW and UW mean down- and up-welling flows, respectively. Post-Logging Period  Pre-Logging Period Location and depth (cm)  Seep Temperature  Stream Temperature  Seep Temperature  Stream Temperature  Seep Temperature  Stream Temperature  Seep • Temperature  CC  Lag  CC  Lag  CC  Lag  CC  Lag  CC  Lag  CC  Lag  CC  Lag  CC  Lag  S1U 1 (DW)  0.98  0  0.14  770  0.98  0  0.85  0  0.92  -190  0.45  580  0.84  -20  0.58  520  S1U5(DW)  0.96  -50  0.14  690  0.97  0  0.87  0  0.90  -230  0.47  550  0.77  0  0.57  510  S1U 10 (DW)  0.91  -120  0.23  230  0.95  0  0.90  0  0.86  -280  0.49  480  0.70  0  0.55  510 480  S1U 15 (DW)  MO  Stream Temperature  Cloudy Sky  Clear Sky  Cloudy Sky  Clear Sky  0.83  -180  0.33  190  0.94  0  0.92  0  0.82  -340  0.51  430  0.66  0  0.54  320  0.66  0  0.52  440  S 1 U 3 0 (DW)  0.51  -390  0.76  0  0.88  0  0.95  0  0.67  -500  0.54  S I D 1 (UW)  0.98  0  0.17  750  0.99  0  0.83  0  0.92  -90  0.42  650  0.92  0  0.58  640  S1D5(UW)  0.88  -110  0.31  240  0.98  0  0.88  0  0.87  -120  0.45  610  0.87  -20  0.58  540 510  S I D 10 (UW)  0.75  -170  0.52  140  0.96  0  0.90  0  0.83  -190  0.48  550  0.82  -50  0.58  S I D 20 (UW)  0.44  -320  0.84  50  0.92  0  0.93  0  0.67  -340  0.48  480  0.72  -80  0.55  490  S2U 1 (DW)  0.97  -10  0.14  740  0.99  0  0.80  0  0.92  10  0.42  780  0.97  0  0.50  710  S2U 5 (DW)  0.95  -70  0.16  680  0.98  0  0.85  0  0.89  -20  0.45  700  0.95  0  0.54  640 540  S2U 10 (DW)  0.90  -130  0.24  200  0.95  0  0.90  0  0.85  -170  0.49  590  0.86  -20  0.56  S2U 20 (DW)  0.80  -200  0.43  150  0.92  0  0.93  0  0.79  -250  0.53  490  0.76  -40  0.56  510  S3U 1 (DW)  0.95  90  0.13  890  0.99  0  0.77  0  0.86  80  0.39  870  0.75  60  0.38  860  S3U 5 (DW)  0.99  0  0.15  780  0.99  0  0.81  0  0.96  0  0.40  820  0.98  0  0.51  780  S3U 10 (DW)  0.97  -30  0.16  740  0.99  0  0.84  0  0.94  -70  0.42  720  0.98  0  0.56  640 520  S3U 15 (DW)  0.93  -90  0.21  270  0.97  0  0.87  0  0.87  -180  0.47  570  0.86  -10  0.57  S3U 30 (DW)  0.61  -290  0.68  50  0.92  0  0.94  0  0.63  -460  0.57  330  0.62  -110  0.53  440  S3D 1 (UW)  0.93  -80  0.19  290  0.98  0  0.88  0  0.91  -160  0.47  620  0.88  0  0.57  540  S3D 5 (UW)  0.87  -130  0.31  210  0.96  0  0.90  0  0.86  -230  0.50  550  0.77  0  0.57  510 500 440  S3D 10 (UW)  0.73  -210  0.51  130  0.94  0  0.92  0  0.77  -340  0.48  340  0.70  0  0.55  S3D 20 (UW)  0.49  -350  0.79  20  0.91  0  0.95  0  0.67  -440  0.52  230  0.65  0  0.53  APPENDIX D. Hydraulic gradients measured in Griffith Creek Mid Reach during 2004. r are Spearman Correlation between discharge and hydraulic gradients, DW and UW/N indicates seasonally down- and upwelling/neutral hydraulic gradients, respectively. Columns are arranged from left to right in order of decreasing discharge. s  Piezometer  Hydraulic Gradient  r  s  Hydrologic Setting  1  0.00  -0.10  -0.03  -0.05  -0.03  0.00  -0.03  0.00  -0.25  DW  2  0.01  0.01  0.01  0.01  0.02  -0.01  0.01  0.01  0.11  UW/N  3  0.09  0.05  0.09  0.05  0.09  0.05  0.05  0.05  0.57  UW/N  4  0.09  0.09  0.06  0.03  0.00  0.00  0.03  0.03  0.71  UW/N  5  -0.61  -0.52  -0.53  -0.50  -0.50  -0.46  -0.53  -0.50  -0.52  DW  6  0.00  0.04  0.00  0.01  0.01  0.00  0.00  0.00  0.28  UW/N  7  0.00  0.00  0.00  0.00  0.00  0.06  0.00  0.00  -0.25  UW/N  8  -0.01  0.00  -0.12  -0.02  -0.02  -0.02  -0.02  -0.02  0.35  UW/N  9  -0.05  -0.07  -0.07  -0.07  -0.10  -0.07  -0.07  -0.10  0.63  DW  10  0.02  0.02  0.05  0.02  0.09  0.02  0.00  0.02  0.36  UW/N  11  0.00  0.10  0.00  0.03  0.00  0.00  0.00  0.00  0.34  UW/N  12  NA  NA  NA  NA  NA  NA  NA  NA  NA  NA  13  -0.19  -0.25  -0.22  -0.25  -0.19  -0.25  -0.25  -0.22  0.31  DW  0.41  0.09  0.09  0.05  0.04  0.02  0.01  0.01  24/8 /2004  13/7 /2004  3/8 /2004  6/8 /2004  22/7 /2004  28/7 /2004  13/8 /2004  16/8 /2004  Discharge Ls" Sample Date  1  100  APPENDIX E. Hydraulic gradients measured in Griffith Creek Mid Reach during 2005. r are Spearman Correlation between discharge and hydraulic gradients, D UW/N indicates seasonally down- and up-welling/neutral hydraulic gradients, respectively. Columns are arrangedfromleft to right in order of decreasing discharge.  1  s  Piezometer  Hydraulic Gradient  Is  Hydrologic Setting  1  0.11  0.09  0.04  0.06  0.06  0.02  0.05  0.04  0.02  0.04  0.00  0.05  0.00  0.05  0.00  0.00  0.05  0.57  UW/N  2  0.05  0.11  0.00  0.08  -0.05  0.00  0.03  -0.06  0.03  -0.06  0.00  -0.06  0.03  0.06  0.00  0.13  0.03  0.04  UW/N  3  0.05  0.00  0.06  0.06  0.03  NA  0.00  0.03  0.04  0.00  0.00  0.04  0.04  0.00  0.04  -0.04  -0.04  0.51  UW/N  4  -0.06  -0.08  0.00  0.00  -0.02  NA  -0.03  0.00  0.00  -0.03  -0.06  0.00  -0.03  0.00  0.00  -0.06  -0.06  -0.03  DW  5  0.00  0.02  0.05  0.02  -0.08  NA  -0.04  -0.04  -0.02  -0.09  -0.07  -0.09  -0.05  -0.05  -0.05  -0.11  -0.02  0.60  DW  6  0.00  -0.05  0.02  0.05  -0.02  0.00  0.00  0.09  0.02  0.02  0.05  0.00  0.05  0.02  0.00  0.00  0.02  -0.21  UW/N  7  -0.02  0.00  0.02  0.00  0.00  NA  -0.03  0.00  0.05  0.00  0.05  -0.03  -0.03  0.03  0.00  0.00  0.03  -0.19  UW/N  8  0.00  0.02  0.02  0.00  -0.02  0.00  -0.02  -0.15  0.02  0.00  -0.02  0.00  -0.02  0.04  0.00  -0.02  0.02  0.04  UW/N  9  0.07  0.02  0.02  0.00  " 0.07  0.04  0.05  0.05  0.06  0.05  0.00  0.02  0.03  0.03  0.03  0.02  0.02  0.26  UW/N  10  -0.11  -0.11  -0.12  -0.03  -0.11  -0.16  -0.16  -0.17  -0.06  -0.19  -0.18  -0.17  -0.18  -0.06  -0.16  0.26  -0.24  0.31  DW  11  0.02  0.04  0.04  0.04  0.04  0.02  0.08  0.02  -0.13  0.02  0.02  0.02  0.02  -0.09  0.00  -0.02  0.00  0.71  UW/N  12  -0.22  -0.65  -0.24  -0.12  -0.51  -0.43  -0.51  -0.12  -0.07  -0.37  -0.13  -0.34  -0.04  -0.09  -0.19  -0.32  -0.13  0.71  DW  13  -0.12  -0.13  -0.08  -0.04  -0.13  NA  -0.16  -0:17  -0.15  -0.19  -0.15  -0.19  -0.11  -0.17  -0.20  -0.17  -0.19  0.71  DW  Discharge Ls"'  6.79  5.34  4.59  3.36  2.42  1.13  0.52  0.39  0.36.  0.23  0.22  0.18  0.18  0.17  0.15  0.14  0.09  Sample Date  8/10 /2005  3/10 /2005  29/10 /2005  24/10 /2005  6/6 /2005  18/7 /2005  25/7 /2005  5/9 /2005  29/7 /2005  17/9 /2005  2/8 /2005  2/9 /2005  10/9 /2005  26/9 /2005  5/8 /2005  15/8 /2005  • 30/5 /2005  APPENDIX F. Cross-correlation coefficients and lags in minutes for bed temperatures on two clear and cloudy sky days in the pre- and post-logging period in the Mid Reach. CC is the Cross-correlation coefficient. DW and UW mean down- and up-welling flows, respectively. Post-Logging Period  Pre-Logging Period  Location and Depth (cm)  o  Stream Temperature  Cloudy Sky  Clear Sky  Cloudy Sky  Clear Sky Seep Temperature  Stream Temperature  Seep Temperature  Stream Temperature  Seep Temperature  Stream Temperature  Seep Temperature  CC  Lag  cc  Lag  cc  Lag  cc  Lag  cc  Lag  cc  Lag  cc  Lag  cc  Lag  Ll-5  0.90  -60  0.39  450  0.93  -30  0.73  320  0.96  10  0.45  430  0.99  20  0.60  440  Ll-10  0.24'  -470  0.98  0  0.60  -380  0.97  0  0.70  -190  0.80  100  0.82  -190  0.82  170  L2-5  0.73  -120  0.55  210  0.88  -90  0.79  240  0.87  -80  0.63  220  0.94  -80  0.72  280  L2-10  0.46  -260  0.82  40  NA  NA  NA  NA  0.77  -130  0.76  120  0.86  -160  0.79  180  L2-30  0.24  -690  0.98  0  0.57  -510  0.92  -20  0.41  -510  0.94  0  0.54  -470  0.94  0  L3-1  0.39  -250  0.83  10  0.66  -210  0.88  80  0.93  0  0.46  390  0.98  10  0.58  430  0.64  340  '  L3-5  NA  NA  NA  NA  0.61  -250  0.92  40  0.93  -10  0.58  300  0.97  -20  . L3-10  0.31  -350  0.93  0  0.61  -300  0.96  10  0.82  -30  0.64  220  0.94  -90  0.69  270  L3-20  0.25  -510  0.99  0  0.60  -410  0.99  0  0.66  -220  0.86  0  0.82  -220  0.82  110  L4-1 (DW)  NA  NA  NA  NA  0.63  -80  0.81  210-  0.87  50  0.35  530  0.95  50  0.59  490  L4-5 (DW)  0.69  -120  0.58  210  0.63  -130  0:84  190  0.96  0  0.39  480  0.98  0  0.62  380  L4-10(DW)  0.48  -220  0.79  60  0.55  -230  0.89  60  0.98  -10  0.48  360  0.93  -40  0.69  290  L4-15 (DW)  0.36  -340  0.92  0  0.53  -320  0.96  0  0.89  -90  0.58  280  0.84  -130  0.77  190  L4-30 (DW)  0.25  -560  0.99  0  0.50  -450  0.95  0  0.67  -270  0.90  0  0.65  -310  0.94  0  L5-1 (UW)  0.50  -210  0.75  60  0.63  -190  0.87  120  0.96  0  0.53  310  0.94  -30  0.70  320  0.74  250  L5-5 (UW)  NA  NA  NA  NA  0.56  -250  0.91  40  0.87  -30  0.60  280  0.89  -100  L5-10 (UW)  0.32  -370  0.94  0  NA  NA  NA  NA  0.80  -100  0.69  100  0.83  -140  0.79  180  L5-15(UW)  0.26  -470  0.98  0  0.53  -410  0.98  0  0.69  -190  0.81  0  0.75  -210  0.84  110  L5-30 (UW)  0.25  -670  0.99  0  0.59  500  0.94  -10  0.51  -380  0.99  0  0.61  -370  0.99  0  

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