1 Presented by Bryce Contor University of Idaho Idaho Water Resources Research Institute Spokane Valley - Rathdrum Prairie Aquifer Study Human Water Use.

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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

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Questions?

[email protected]