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Acadia Park/Agronomy Building : water consumption data analysis Lennon, Kathryn Oct 10, 2014

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 UBC Social Ecological Economic Development Studies (SEEDS) Student ReportKathryn LennonAcadia Park/Agronomy Building: Water Consumption Data AnalysisPLAN 597October 10, 201411451680University of British Columbia Disclaimer: “UBC SEEDS provides students with the opportunity to share the findings of their studies, as well as their opinions, conclusions and recommendations with the UBC community. The reader should bear in mind that this is a student project/report and is not an official document of UBC. Furthermore readers should bear in mind that these reports may not reflect the current status of activities at UBC. We urge you to contact the research persons mentioned in a report or the SEEDS Coordinator about the current status of the subject matter of a project/report”.  	   Acadia	  Park/Agronomy	  Building:	  Water	  Consumption	  Data	  Analysis	  	  	  	  	  	  	   PLAN	  597:	  Planning	  for	  Water	  Resource	  Management	  Assignment	  1	  Kathryn	  Lennon	  October	  10,	  2014	  	  	  	  	  	  	   1	  	  1)	  Background	  The	  data	  is	  for	  a	  piece	  of	  the	  Acadia	  Park	  Residences	  located	  on	  Agronomy	  Road,	  however,	  Powerhouse	  staff	  did	  not	  know	  which	  exactly	  which	  building.	  Acadia	  Park	  includes	  one	  bedroom	  high-­‐rise	  apartment	  residences,	  two	  and	  three	  bedroom	  apartments,	  row	  houses,	  and	  one	  to	  four	  bedroom	  townhouses.	  	  Acadia	  Park	  is	  a	  year-­‐round	  student	  family	  residence.	  It	  is	  reserved	  for	  couples	  and	  adults	  with	  one	  or	  more	  dependent	  children	  18	  years	  of	  age	  or	  younger.	  	  	  	  2)	  Data	  Collection	  55	  data	  points	  were	  obtained	  from	  the	  Powerhouse	  for	  the	  Acadia	  Park/Agronomy	  Residence	  (Customer	  #403).	  The	  data	  had	  to	  be	  re-­‐inputted	  into	  columns	  in	  order	  to	  be	  analyzed.The	  data	  is	  quarterly	  data,	  from	  2001-­‐2014,	  consisting	  of	  high/peak	  flows	  and	  low	  flows	  in	  cubic	  meters,	  and	  water	  consumption	  calculated	  in	  cubic	  feet.	  	  The	  data	  is	  for	  March,	  June,	  September	  and	  December	  from	  2001-­‐2005,	  and	  in	  March,	  May,	  September	  and	  December	  from	  2006-­‐2014.	  	  It	  was	  unknown	  which	  year	  renovations	  were	  done	  in.	  What	  was	  known	  was	  that	  most	  renovations	  are	  done	  over	  the	  summer	  months,	  May	  to	  September,	  as	  they	  have	  the	  least	  impact	  on	  residents.	  Acadia	  Park’s	  water	  consumption	  is	  on-­‐going	  as	  it	  is	  a	  year-­‐round	  residence	  setting.	  	  Calculations:	  Values	  for	  water	  consumption	  had	  already	  been	  calculated.	  However,	  when	  I	  carried	  out	  my	  own	  calculations,	  to	  verify,	  using	  the	  formula	  below,	  some	  of	  the	  results	  I	  obtained	  were	  different	  (see	  numbers	  highlighted	  in	  red,	  29088	  vs.	  56574,	  and	  15302	  vs.	  16103).	  	  Thus,	  there	  are	  some	  inaccuracies	  in	  the	  data	  obtained.	  However,	  I	  chose	  to	  use	  the	  consumption	  values	  contained	  in	  the	  original	  excel	  file	  received	  from	  Powerhouse	  staff,	  rather	  than	  my	  own	  calculations.	  	  	  	  	  	  *The	  Conversion	  Rate	  is	  applied	  because	  the	  water	  usage	  for	  the	  buildings	  is	  measured	  in	  cubic	  meters	  while	  the	  charges	  are	  applied	  in	  cubic	  feet.	  (Current	  High	  Flow	  Meter	  Reading-­‐Previous	  High	  Flow	  Meter	  Reading)	  (Current	  Low	  Flow	  Meter	  Reading-­‐Previous	  Low	  Flow	  Meter	  Reading)	  *	  35.314475	  (Conversation	  Rate)	   	  Consumption	   =	   +	   x	  	   2	  	  	  Sample	  Data,	  Showing	  Inaccuracies:	  	  Date	  High	  Flow	  (ft3	  )	   Low	  Flow	  (ft3	  )	   Consumption	  (ft3	  )	  	   Verification	  Calculation	  (ft3	  )	  23-­‐09-­‐2005	   80	   16284	   42519	   42519	  08-­‐12-­‐2005	   80	   17119	   29488	   29488	  21-­‐03-­‐2006	   80	   18058	   33160	   33160	  19-­‐05-­‐2006	   80	   18397	   11972	   11972	  21-­‐09-­‐2006	   881	   19198	   56574	   29088	  13-­‐12-­‐2006	   80	   19654	   16103	   15302	  26-­‐03-­‐2007	   80	   21076	   50217	   50217	  	  	  A	  second	  example	  of	  a	  problem	  area	  is	  that	  the	  high	  flow	  for	  21-­‐09-­‐2006	  was	  recorded	  as	  881,	  but	  it	  should	  be	  close	  to	  80.	  All	  problem	  figures	  have	  been	  highlighted	  in	  red	  (see	  Appendix).	  	  3)	  Data	  Analysis	  	  Summary	  Statistics:	  	   Median	   32560	  Mean	   32633	  Variance*	   11437	  	  	  *Variance	  is	  calculated	  as	  sample	  standard	  deviation.	  	  	  	   3	  	  	  	  The	  data	  distribution	  can	  be	  described	  as	  bell-­‐shaped,	  slightly	  skewed	  right,	  suggesting	  a	  fairly	  normal	  distribution.	  The	  highest	  frequency	  of	  water	  consumption	  is	  for	  30001-­‐40000	  cubic	  feet,	  which	  is	  close	  to	  the	  mean	  of	  32633.	  The	  lowest	  water	  consumption	  is	  for	  50001-­‐60000	  cubic	  feet.	  This	  suggests	  that	  there	  is	  a	  limit	  on	  high	  water	  consumption;	  this	  limit	  could	  be	  the	  price	  paid	  for	  water	  usage.	  It	  could	  also	  indicate	  that	  it	  is	  unusual	  to	  consume	  an	  extremely	  high	  volume	  of	  water.	  	  	  0	  2	  4	  6	  8	  10	  12	  14	  16	  18	  20000	   30000	   40000	   50000	   60000	  Frequecny	  Water	  Consumption	  (Cubic	  Feet)	  Figure	  1:	  Distribution	  for	  Quarterly	  Water	  Consumption,	  from	  2001-­‐2014	  	   4	  	  	  From	  this	  figure,	  there	  is	  seasonal	  variation	  in	  water	  consumption.	  Generally,	  peak	  water	  consumption	  is	  measured	  in	  September.	  This	  accounts	  for	  the	  summer	  months	  of	  June,	  July,	  August.	  The	  lowest	  water	  consumption	  is	  measured	  in	  March	  or	  May,	  which	  accounts	  for	  the	  winter	  months	  of	  December,	  January	  and	  February.	  	  	  The	  limitation	  in	  reading	  this	  pattern	  is	  that	  the	  quarterly	  data	  was	  	  collected	  in	  March,	  June,	  September	  and	  December	  from	  2001-­‐2005,	  and	  in	  March,	  May,	  September	  and	  December	  from	  2006-­‐2014.	  	  Thus,	  while	  June	  is	  considered	  a	  summer	  month,	  May	  is	  not,	  so	  it	  may	  not	  be	  appropriate	  to	  compare	  June	  and	  May.	  What	  is	  missing	  is	  the	  dates	  when	  renovations	  occurred.	  	  	  	  0	  10000	  20000	  30000	  40000	  50000	  60000	  Water	  Consumption	  (cubic	  feet)	  Quarter	  Figure	  2:	  Quarterly	  Water	  Consumption,	  2001-­‐2014	  	  	   5	  	  	  4)	  Findings	  The	  data	  does	  not	  show	  any	  clear	  difference	  or	  patterns	  around	  how	  the	  renovations	  impacted	  water	  consumption.	  Further	  analysis	  that	  looks	  at	  monthly	  data	  could	  help	  look	  at	  more	  fine-­‐grained	  differences	  in	  water	  consumption.	  All	  that	  can	  be	  inferred	  from	  this	  data	  is	  that	  there	  are	  seasonal	  patterns	  in	  water	  usage.	  Since	  the	  dates	  of	  renovations	  were	  unknown,	  pre-­‐renovation	  and	  post-­‐renovation	  water	  consumption	  could	  not	  be	  compared	  	  	  0	  10000	  20000	  30000	  40000	  50000	  60000	  1	   2	   3	   4	  Water	  Consumption	  (cubic	  feet)	  Quarter	  Figure	  3:	  Seasonal	  Water	  Consumption,	  2001-­‐2014,	  Acadia/Agronomy	  Building	  	  2002	  2003	  2004	  2005	  2006	  2007	  2008	  2009	  2010	  2011	  2012	  2013	  2014	  March	   September	   December	  May/June	  	   6	  	  APPENDIX	  	  Date	  High/Peak	  Flows	  (cubic	  meters)	  Low	  (cubic	  meters)	   Consumption	   Verficiation	  Calculation	  20-­‐06-­‐2001	   60	   1543	   1342	   	  21-­‐09-­‐2001	   60	   2260	   25320	   25320	  04-­‐12-­‐2001	   60	   2992	   25850	   25850	  12-­‐03-­‐2002	   60	   3880	   31359	   31359	  24-­‐06-­‐2002	   60	   4920	   36727	   36727	  24-­‐09-­‐2002	   60	   5763	   29770	   29770	  13-­‐12-­‐2002	   60	   6650	   31324	   31324	  20-­‐03-­‐2003	   80	   7071	   15574	   14887	  17-­‐06-­‐2003	   80	   7610	   19035	   19035	  19-­‐09-­‐2003	   80	   8821	   42766	   42766	  11-­‐12-­‐2003	   80	   9741	   32489	   32489	  22-­‐03-­‐2004	   80	   10665	   32631	   32631	  29-­‐06-­‐2004	   80	   11683	   35950	   35950	  14-­‐09-­‐2004	   80	   12677	   35103	   35103	  14-­‐12-­‐2004	   80	   13684	   35562	   35562	  17-­‐03-­‐2005	   80	   14527	   29770	   29770	  21-­‐06-­‐2005	   80	   15080	   19529	   19529	  23-­‐09-­‐2005	   80	   16284	   42519	   42519	  08-­‐12-­‐2005	   80	   17119	   29488	   29488	  21-­‐03-­‐2006	   80	   18058	   33160	   33160	  19-­‐05-­‐2006	   80	   18397	   11972	   11972	  21-­‐09-­‐2006	   881	   19198	   56574	   29088	  13-­‐12-­‐2006	   80	   19654	   16103	   15302	  26-­‐03-­‐2007	   80	   21076	   50217	   50217	  30-­‐05-­‐2007	   80	   21596	   18364	   18364	  13-­‐09-­‐2007	   80	   23137	   54420	   54420	  14-­‐12-­‐2007	   50	   24190	   36127	   37156	  10-­‐03-­‐2008	   10	   25170	   33196	   34568	  	   7	  22-­‐05-­‐2008	   10	   25820	   22954	   22954	  15-­‐09-­‐2008	   10	   27045	   43260	   43260	  19-­‐12-­‐2008	   10	   28475	   50500	   50500	  17-­‐03-­‐2009	   10	   29265	   27898	   27898	  21-­‐05-­‐2009	   10	   30055	   27898	   27898	  17-­‐09-­‐2009	   10	   31390	   47145	   47145	  16-­‐12-­‐2009	   10	   32550	   40965	   40965	  16-­‐03-­‐2010	   10	   33600	   37080	   37080	  19-­‐05-­‐2010	   10	   34405	   28428	   28428	  15-­‐09-­‐2010	   10	   35780	   48557	   48557	  16-­‐12-­‐2010	   10	   36895	   39376	   39376	  16-­‐03-­‐2011	   10	   37805	   32136	   32136	  18-­‐05-­‐2011	   10	   38470	   23484	   23484	  15-­‐09-­‐2011	   10	   39760	   45556	   45556	  19-­‐12-­‐2011	   10	   41025	   44673	   44673	  20-­‐03-­‐2012	   10	   42110	   38316	   38316	  17-­‐05-­‐2012	   16	   42775	   23696	   23490	  13-­‐09-­‐2012	   10	   44030	   44320	   44314	  19-­‐12-­‐2012	   10	   45172	   40329	   40329	  18-­‐03-­‐2013	   0	   410	   14479	   -­‐1580757	  21-­‐05-­‐2013	   0	   1070	   23308	   23308	  19-­‐09-­‐2013	   0	   2320	   44143	   44143	  18-­‐12-­‐2013	   0	   3330	   35668	   35668	  14-­‐03-­‐2014	   0	   4050	   25426	   25426	  21-­‐05-­‐2014	   5	   4620	   20306	   20134	  17-­‐09-­‐2014	   5	   5470	   30017	   30017	  	  	  

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