1 presented by bryce contor university of idaho idaho water resources research institute spokane...
TRANSCRIPT
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Presented byPresented byBryce ContorBryce Contor
University of Idaho University of Idaho Idaho Water Resources Research Idaho Water Resources Research
InstituteInstitute
Spokane Valley - Rathdrum Prairie Aquifer Study
Human Water Use in the SVRP Human Water Use in the SVRP AquiferAquifer
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Outline of Talk
• Water-use Overview
• Data Sources
• Estimated Components
• Interesting Observations
• Uncertainty
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I: Water-use Overview
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MODFLOW Well Term:Human Pumping & Returns
• Domestic, Commercial, Municipal and Industrial (DCMI)
• Agricultural
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Human Extraction in the Larger Water-budget Context
Human Use and Other Water-budget Components
-1200
-1000
-800
-600
-400
-200
0
200
400
600
800
Pre
cip.
Rec
h.
Trib
utar
y V
alle
ys
Lake
s
Fro
m S
pok
R
Net
Hum
an U
se
To
Spo
k R
To
Litt
le S
pok
To
Long
Lak
e
Cha
nge
Sto
rage
Ave
rag
e C
FS
All figures are AQUIFER CENTRIC (Negative = Water Out)
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Spatial Distribution: Cell-by-Cell
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Spatial Distribution: Smoothed
8-300
-250
-200
-150
-100
-50
0
50
100
DCMIPump
DCMIPerc
AgPump
Ag Perc
Ave
rag
e C
FS
Ag Perc
Ag Pump
Perc, Estimate
Perc, Records
Rural Estimate
Purveyor Records
Self Industrial
Human Use By Component
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Time Series
Time Series, Net Human Extraction - SVRP
-300
-250
-200
-150
-100
-50
0
1990 1995 2000 2005
Ann
ual A
vg C
FS
Net DCMI Net Ag Total Net Extraction
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• USGS Water-use Data Program (Molly Maupin)
• SVRP Model Data Archive (GIS Data from Counties, Cities and States)
• National Ag Statistics Service crop reports (USDA)
• University of Idaho Evapotranspiration Tables
II. Data Sources
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• Personal contacts (cities, Spokane County, Panhandle Health District, Jacklin Seed, irrigation districts)
• Aerial photos (USDA)• NLCD impermeable-cover data (USGS
Seamless Data Server)• Idaho water-rights data (IDWR)
• CH2M Hill & Golder Reports
• PRISM precipitation data (Oregon State U)
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III. Estimated Components
• DCMI uses in small towns & rural homes
• Agricultural irrigation outside reporting purveyor service areas
• Partitioning of pumping data to indoor & outdoor use & percolation
• Partitioning of outdoor use to ag & landscape irrigation (for reporting only)
• Idaho self-supplied industrial use
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III. Estimated Components – Example 1
Gross Pumping from Data
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Pum
ping
Rat
e
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Gross Pumping from Data
Indoor Use
Outdoor Use
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Pum
ping
Rat
e
Winter baseline(avg of winter months)
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Gross Pumping from Data
Indoor Use
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Pum
ping
Rat
e
Winter baseline(avg of winter months) Typical pattern for
purveyors with no ag-irrigation component
Landscape Irr
Ag Irr
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III. Estimated Components – Example 2
However, there are too many cells to count rural homes in each one.
In rural areas where there are no pumping data,we estimate water use based on number of homes.
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We developed an equation based on statistical sampling, by counting homes in aerial photos & comparing with remote-sensing impermeable cover data. Using the equation we canestimate rural homes in non-sampled cells.
Homes/mi2 = 13.6 + 8,744 (impermeable fraction)2
sample map of impermeable fraction
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III. Estimated Components – Example 3
City Polygon Experiment -1992 Image 1:4000
300 0 300 600 Feet
Spatial distributionof percolationdepends onactual waterdeliveryareas.
We used aerial photos to map changes overtime.
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City Polygon Experiment -circa 1998 Image 1:4000
300 0 300 600 Feet
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City Polygon Experiment -2004 Image 1:4000
300 0 300 600 Feet
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IV. Interesting Observations
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Trends in Purveyor Pumping
-250
-200
-150
-100
-50
0
1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
aver
age
cfs
Pump AgIrr LndScpIrr Indoor
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Seasonality
Typical Seasonal Pumping Patterns - Two Years
-500
-400
-300
-200
-100
0
100
200
0 6 12 18 24
cfs
Rec Purv
No Rec DCMI
Ag Pump
PurvIrrPerc
NoRecordsLndscpPerc
AgIrrPerc
PurveyorSpticPerc
NoRecordsSpticPerc
SelfIndust
No time lagwas applied
topercolation
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V. Estimated Uncertainty in Well Term
80%
85%
90%
95%
100%
105%
110%
115%
120%
0.8 0.9 1 1.1 1.2
+/- 1 std dev+/- 17 cfs
+/- 2 std dev+/- 34 cfs
This is theuncertaintydue to ourmeasurement/estimation methods
