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Assessing the vulnerability of small-scale water resources using high spatial resolution remote sensing Al-Khalifa, Sammy
Abstract
Water stress due to physical scarcity and poor water quality impacts billions of people worldwide. Internationally, an important goal of the United Nations’ Sustainable Development Goals (SDGs) is the improvement of ambient water quality by tracking the proportion of inland water bodies with acceptable water quality. Thus, there is a global, pressing need for fast, reliable, and accessible ways to monitor the water quality in small inland water bodies. In this research, I evaluate the utility of high spatial resolution remote sensing for monitoring water quality constituents (Chlorophyll-a and turbidity) in small reservoirs (0.01 km²) in southwestern Kenya. First, I used a novel combination of remote sensing indices and landscape features to build statistically robust empirical models of water quality parameters that were measured in situ. I then used these models to extrapolate water quality in 60 reservoirs over 43 consecutive months (2019-July 2022) across a land-use gradient. These results were then used to examine patterns in water quality across space and time. Finally, I used high spatial resolution imagery to quantify the areal change (or drying out) of reservoirs throughout a single dry season. Overall, Sentinel-2 satellite imagery produced better models of Chl-a (R² = 0.66) when compared to PlanetScope imagery which produced more accurate maps of turbidity (R² = 0.72). Furthermore, introducing landscape features such as land cover, maximum reservoir size, and proximity to roads improved the statistical power of models by as much as 9%. Turbidity was marginally significantly different in reservoirs across the land-use gradient, with the transition zone having the most turbid reservoirs. From 2019 to 2022, Chl-a and turbidity have been steadily improving in 46% and 40% of reservoirs, respectively. Notably, Chl-a concentrations have been improving more rapidly in the cropland zone. Additionally, nearly half of reservoirs lost over 50% of their surface area during the 2021 dry season, a period of exceptionally intense drought; whereas a quarter of all reservoirs dried out completely. This research has the potential to help support monitoring and planning within the water resources sector by prioritizing the use of climate resilient infrastructure such as water pans.
Item Metadata
Title |
Assessing the vulnerability of small-scale water resources using high spatial resolution remote sensing
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Creator | |
Supervisor | |
Publisher |
University of British Columbia
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Date Issued |
2023
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Description |
Water stress due to physical scarcity and poor water quality impacts billions of people worldwide. Internationally, an important goal of the United Nations’ Sustainable Development Goals (SDGs) is the improvement of ambient water quality by tracking the proportion of inland water bodies with acceptable water quality. Thus, there is a global, pressing need for fast, reliable, and accessible ways to monitor the water quality in small inland water bodies. In this research, I evaluate the utility of high spatial resolution remote sensing for monitoring water quality constituents (Chlorophyll-a and turbidity) in small reservoirs (0.01 km²) in southwestern Kenya.
First, I used a novel combination of remote sensing indices and landscape features to build statistically robust empirical models of water quality parameters that were measured in situ. I then used these models to extrapolate water quality in 60 reservoirs over 43 consecutive months (2019-July 2022) across a land-use gradient. These results were then used to examine patterns in water quality across space and time. Finally, I used high spatial resolution imagery to quantify the areal change (or drying out) of reservoirs throughout a single dry season.
Overall, Sentinel-2 satellite imagery produced better models of Chl-a (R² = 0.66) when compared to PlanetScope imagery which produced more accurate maps of turbidity (R² = 0.72). Furthermore, introducing landscape features such as land cover, maximum reservoir size, and proximity to roads improved the statistical power of models by as much as 9%. Turbidity was marginally significantly different in reservoirs across the land-use gradient, with the transition zone having the most turbid reservoirs. From 2019 to 2022, Chl-a and turbidity have been steadily improving in 46% and 40% of reservoirs, respectively. Notably, Chl-a concentrations have been improving more rapidly in the cropland zone. Additionally, nearly half of reservoirs lost over 50% of their surface area during the 2021 dry season, a period of exceptionally intense drought; whereas a quarter of all reservoirs dried out completely. This research has the potential to help support monitoring and planning within the water resources sector by prioritizing the use of climate resilient infrastructure such as water pans.
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Genre | |
Type | |
Language |
eng
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Date Available |
2023-01-20
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0423220
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2023-05
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International