Satellite and Ground-based Approaches for Monitoring Impacts of AgricultureMonitoring Impacts of Agriculture

on Groundwater Resources

Bridget R. Scanlon, Laurent Longuevergne, Guillaume Favreau*, Claudia Faunt**

Center for Sustainable Water Resources, CSWRhttp://www.beg.utexas.edu/cswr/

Bureau of Economic Geology, Jackson School of Geosciences, University of Texas at AustinUniversity of Texas at Austin

*Universite de Montpelier, France**US Geological Survey, San Diego, California

Water Balance Componentsp

Precipitation: SSM/I TRMMPrecipitation: SSM/I, TRMM Evapotranspiration: MODIS, AVHRR, LandSatS il M i t SSM/I AMSR SMOSSoil Moisture: SSM/I, AMSR, SMOSGroundwater: GRACEStreamflow: Laser/Radar AltimeterVegetation: AVHRR, TM, MODIS

P ET R SP – ET – Roff = S

Can we close the water budget using satellite data?

OutlineOutline

• Background on GRACE dataBackground on GRACE data• Applications

G– Ganges– Niger

S– US High Plains– US California Central Valley

• Global surface water basin product (Google Earth)

MethodsGRACEGravity RecoveryMethods Gravity Recoveryand Climate Expt.

Launched March2002

Total water storage change

GRACE (Change in Total Water Storage, TWS)

TWS= SW + SM + GWSW

SW: surface water; SM soil moistureGW, groundwater

soil moisture

GW, groundwater

groundtwater

Total Water Storage Change (TWSC)

TWS= SW + SM + GWSW

SW: surface water; SM soil moistureGW, groundwater

soil moisture

GW, groundwater

groundt GW = TWS – SW – SMwater

Total Water Storage Change (TWSC)

TWS= SW + SM + GWSW

SW: surface water; SM soil moistureGW, groundwater

soil moisture

GW, groundwater

groundt GW = TWS – SW – SM

GW TWS SM

water

GW = TWS – SM

Total Water Storage Change (TWSC)

TWS= SW + SM + GWSW

SW: surface water; SM soil moistureGW, groundwater

soil moisture

GW, groundwater

groundt GW = TWS – SW – SM

GW TWS SM

water

GW = TWS – SM

SM: estimated from GLDAS: Global Land DataSM: estimated from GLDAS: Global Land Data Assimilation SystemFour land surface models:VIC, CLM, NOAH, and MOSAIC

GRACEGRACE• Analysis centers: CSR, GFZ, JPL, GRGS, DEOSy , , , ,• Time scale: 7 d - monthly• Spatial scale: ≥ 400,000 km2p ,• Data processing: remove atmospheric, oceanic,

and tidal effects (centers), destripe the data, filter th d tthe data

• Correct for bias and leakages• Error analysis: measurement errors processing• Error analysis: measurement errors, processing

errors, model errors• Work with a geodesistWork with a geodesist

Use of GRACE Data in Water Resources

WL Rising

GroundwaterGroundwater

WL Rising

Recharge – Discharge = GW = GRACE – SMg g

Use of GRACE Data in Water Resources

WL Rising

GroundwaterGroundwater

WL Rising

Recharge – Discharge = GW = GRACE – SMg g

Increase in recharge from climate or land use change

Use of GRACE Data in Water Resources

GroundwaterGroundwater

Recharge – Discharge = GW = GRACE – SMRecharge Discharge GW GRACE SM

GW from GRACE ~ irrigation pumpage

Outline

• Background on GRACE dataBackground on GRACE data• Applications

G– Ganges– Niger

S– US High Plains– US California Central Valley

• Global surface water basin product (Google Earth)

Groundwater Depletion in Ganges Basin

Rodell et al., 2009

Groundwater Depletion based on GRACEbased on GRACE

Trend in groundwater storage: 12.5 mm/yr (basin area 1 million km2)~ 100 mm/yr in irrigated area (150,000 km2)

Drilling in Rajasthang j

Jaipur siteRecharge rates under rainfed agriculture: 60 – 90 mm/yrRecharge under irrigated agriculture: 50 – 120 mm/yr

8 – 19% of mean annual precipitation (600 mm/yr)Irrigation of 20 – 40% of cultivated land with 300 mm/yr should be sustainable. Scanlon et al., 2010

(2) Example of Groundwater Storage Increase

Niger

Studied since 1990sI t ti l AMMA j tInternational AMMA project

Favreau et al., 2009

Groundwater Level Rises

80

100

Grouc2.5

3.0

40

60

undwater

change (m

1 0

1.5

2.0

WL

0

20

rlevelm

)

0.0

0.5

1.0

1950 1960 1970 1980 1990 2000

Favreau et al., 2002, GW

Groundwater Level Rises, No Link to Climate

80

100

Grouc2.5

3.0

40

60

undwater

change (m

1 0

1.5

2.0

WL

0

20

rlevelm

)

0.0

0.5

1.0

1950 1960 1970 1980 1990 2000

(mm

/yr)

200

400Mean 563 mm(1905-1999)

reci

pita

tion

(

-200

0

Favreau et al., 2002, GW

1950 1960 1970 1980 1990 2000P

r

-400

Groundwater Level Rises Caused by Cultivation (land use changes)( g )

)

80

100

ange

(m)

2.5

3.0

FallowNatural

Gro

and

area

(%)

40

60

ter l

evel

cha

1 0

1.5

2.0

Cultivated WL

oundwater

change (m

La

0

20

Gro

undw

a

0.0

0.5

1.0

Plateau

r levelm

)

1950 1960 1970 1980 1990 2000

(mm

/yr)

200

400Mean 563 mm(1905-1999)

reci

pita

tion

(

-200

0

Favreau et al., 2002, GW

1950 1960 1970 1980 1990 2000

Pr

-400

GRACE resultsGroundwater results

A 10 000 k ² A 150 000 k ²Area: 10 000 km²Trend: +23 mm/yr

Area: 150 000 km²Trend: +18 mm/yr

GRACE can be used to regionalize trends

GRACE – GLDAS (SM) = GW( )

Increase in GW = 18 mm/yr

(3) US High-Plains Aquifer

450,000 km2 area

Grassland56%

O

Shrubland3%

Rainfed28%

Irrigated12%

Other1%

High Plains Aquifer, US

Water available: 4,000 km3

Water depleted: 330 km3 (8%)

Recharge: 10 – 86 mm/yr

SHP: Recharge increase from 10 to 30 mm/yr after cultivation

Could support irrigation of 10% of cultivated land with 300 mm/yr

McGuire et al., 2009

Groundwater Depletion under Irrigated Agriculture

m)

0

20

to w

ater

(m 20

40

60

1910 1930 1950 1970 1990 2010

Dep

th80

1001910 1930 1950 1970 1990 2010

GRACE Data for High Plainsfor High Plains

Comparison of GRACE Data with Measured SM + GW

r2 = 0.87

r2 = 0 84r = 0.84

r2 = 0.88

(4) California Central Valley

Area: 52,000 km2

Total water stored: 1000 km3

Water depletion: 60 km3

Faunt et al., 2009

Change in Storage with Timeg g

Faunt et al., 2009

GRACE data (CSR, GRGS)GRACE data (CSR, GRGS)NOAH (SM + Snow)

GRACE data (CSR, GRGS)GRACE data (CSR, GRGS)NOAH (SM + SNOW)

Surface water storage26 reservoirs

GRACE data (CSR, GRGS)GRACE data (CSR, GRGS)NOAH (SM + SNOW)

Surface water storage26 reservoirs

GRACE – SM – Snow – SWGRACE SM Snow SW

Groundwater hydrograph

OutlineOutline

• Background on GRACE dataBackground on GRACE data• Applications

G– Ganges– Niger

S– US High Plains– US California

• Global surface water basin product (Google Earth)

Google Earth Product for Surface Water 218 basins TRIP database218 basins, TRIP database

Longuevergne, 2010

Google Earth Basins Product

Download links

Basin explorerLonguevergne et al., 2010

GRACE Total Water Storage Change (GRGS) (mm)Annual Signal (mean: 2003 – 2009)

Amplitude of annual signal ranges from 0 – 250 mm (median 46 mm)( )Median error 10 mm

GRACE Total Water Storage Change (GRGS) (mm/yr)Trend (2003 – 2009)

Trend: 30 to 30 mm/yr; median 2 0 mm/yrTrend: -30 to 30 mm/yr; median 2.0 mm/yr

↑ precipitation (climate), permafrost

↓ ice loss, drought, irrigation

GRGSGRACE

NOAHNOAHLSM

SoilSoilMoisture

SummarySummary

• Useful tool for estimating seasonal, interannual, and secular variations in total water storage changes down to 400,000 km2 spatial resolution and ~ 7 d temporal400,000 km spatial resolution and 7 d temporal resolution

• Seasonal signal dominant: median 46 mm in 218 basinsE ±10• Error: ±10 mm

• Disaggregation of TWS to SW, SM, and GW depends on GLDAS models– Need to improve modeling to include surface water and

groundwater, irrigation• Calculation of trends depends on time period and p p

interannual variability