Monitoring Water Use and Drought at Field to Global Scales, Chris Hain

Monitoring Water
Use and Drought at
Field to Global
Scales
Martha C. Anderson, Feng Gao,
Yun Yang, Liang Sun, Yang Yang
USDA-Agricultural Research Service
Hydrology and Remote Sensing Laboratory
Beltsville, MD
Chris Hain
Earth System Science Interdisciplinary Center,
University of Maryland, NOAA-NESDIS

Landscape scale
TRAD - Landsat, MODIS
Ta - ALEXI
TRAD (φ), fcTRAD (φ), fc
Rsoil
Tc
Tac
Hs
Ts
Ra H = Hc + Hs
Rx
Hc
Ta
ABL
Ta
ALEXI DisALEXI
5 km
30 m
Two-SourceModel
TRAD,i(φi), fc,i
i
Ra,i
Blending height
(ALEXI disaggregation)
Multi-scaleETmodelingsystem
Regional scale
DTRAD - Geostationary
Ta - ABL model
Surface temp:
Air temp:
NENA Stakeholders Workshop – October 2015
TRAD (φ), fcTRAD (φ), fc
Rsoil
Tc
Tac
Hs
Ts
Ra H = Hc + Hs
Rx
Hc
Ta
ABL
Ta
ALEXI DisALEXI
5 km
30 m
Two-SourceModel
TRAD,i(φi), fc,i
i
Ra,i
Blending height
Energy balance:
ET = (RNET - G) - H
Normalization
=
T
E
C02
(Atmosphere-Land Exchange Inverse model)

Polar
(Landsat)
Airborne
(USUaircraft)
Watershed
(60m)
Fieldscale
(30m)
SURFACE TEMPERATURE EVAPOTRANSPIRATION
GEO
(GOESImager)
Regional
(5km)
GEO
(GOESSounder)
Continental
(10km)
Temperature(C)
Polar
(MODIS)
Basin
(1km)
LatentHeat(Wm-2)
GEO
(ISCCP)
Global
(25km)
1 July 2002 – 10:30AM LST
corn
soy
Hourly
Daily
1 LS – 16 day
2 LS – 8 day
DATA FUSION:
daily ET at
field scale

ApplicationsforRemotelySensedET
WATER
MANAGEMENT
DROUGHT
MONITORING
FOOD AND WATER
SECURITY

… Field-Scale Water Management
APPLICATIONS FOR SATELLITE ET

Waterusedynamicsinvineyards
Gallo Vineyards, Central Valley CA
1
2
GRAPEX2013, 14, 15

Landsat 8 - 2013
Waterusedynamicsinvineyards
Gallo Vineyards, Central Valley CA

0
2
4
6
8
10
12
14
16
18
200
2
4
6
8
10
100 120 140 160 180 200 220 240 260 280 300
ET(mm/day)
Day of year
SITE 1:
Pinot Noir – 8 YR (2013)
GRAPEX2013-2014
Rainfall(mm/day)
ALEXI ET (4km)
Observed ET
Landsat retrieval
Landsat-MODIS fusion
Precipitation
4km

0
2
4
6
8
10
12
14
16
18
200
2
4
6
8
10
100 120 140 160 180 200 220 240 260 280 300
ET(mm/day)
Day of year
GRAPEX2013-2014
Rainfall(mm/day)
ALEXI ET (4km)
Observed ET
Landsat retrieval
Precipitation
SITE 2:
Pinot Noir – 5 YR (2013)
4km

Waterusedynamicsinvineyards UAV LST – 0.6 m (August 9, 2014)
7 AM 11 AM Time difference

… Crop stress and yield impacts
MONITORING DROUGHT
InterSucho Summer School – June 2015

SatelliteETDroughtIndicator
Atmosphere-Land Exchange Inverse Model (ALEXI)
(Anderson et al., 1997, 2007)

GOES Evaporative Stress Index JUNE 2002
565000 570000 575000 580000 585000 590000
3490000
3495000
3500000
3505000
3510000
3515000
565000 570000 575000 580000 585000 590000
3490000
3495000
3500000
3505000
3510000
3515000
Drought/CropStress

… Africa/NENA
GLOBAL APPLICATIONS FOR SATELLITE ET

ALEXI (Energy balance) Noah (Water balance)
2009 FEBRUARY
(MJ m-2 d-1)
ALEXI
NOAH
MOD16

0
2
4
6
8
ET(mm/day)
Waterusebyirrigation
0
1
2
3
4
2006 2007 2008 2009 2010 2011 2012 2013 2014
ALEXIET(mm/day)
YEAR
Houborg et al., 4th International Symposium of RAQRS, Valencia, Spain, Sept. 2014
GROUNDWATER
DEPLETION TRENDS
(GRACE, mm/yr)
ALEXI ET – AL JOWF IRRIGATION SITE
MODIS (1km) LANDSAT (30m)
MULTI-SCALE ET MAPPING (mm/day)

YieldestimationinTunisia
YIELD
ESTIMATION
Middle East Water and Livelihoods Initiative (WLI)
Partners: Tunisia (N. Sghaier, CNCT), USAID, ICARDA

YieldestimationinTunisia 2001 2002 2003 2004 2005 2006 2007
2008 2009 2010 2011 2012 2013
ESI
Wheatyield
anomalyESI
Wheatyield
anomaly
ESI: Evaporative Stress Index (ET/PET anomalies)

-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
-16 -12 -8 -4 0 4 8 12 16 20 24 28 32
Correlationcoefficient(r)
Week of year
Harvest BE KE AR JE BA BI MA NA SI ZA
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
-16 -12 -8 -4 0 4 8 12 16 20 24 28 32
Week of year
DTRMM Precip
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
-16 -12 -8 -4 0 4 8 12 16 20 24 28 32
Week of year
DCHIRPS Precip
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
-16 -12 -8 -4 0 4 8 12 16 20 24 28 32
Week of year
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
-16 -12 -8 -4 0 4 8 12 16 20 24 28 32
Week of year
ESI DLAI
Governorates (Northern Tunisia)
INDEX CORRELATIONS WITH ANNUAL WHEAT YIELD ANOMALIES (2002-2013)
Harvest

Loblolly Pine Plantation, NC
Landsat 8 - 2013
Effectofforestmanagement

ALEXI ET
Observed ET
Landsat retrievals
Landsat-only
NC2:
Loblolly Pine (2013)
(Yang et al., 2015)

ALEXI ET
Observed ET
Landsat retrievals
Landsat-only
NC3:
Clearcut Pine (2013)
(Yang et al., 2015)

Waterusevariabilitywithstandage
Pine Plantation Stand Age
(Yang et al., 2015)

JAN-FEB MAR-APR MAY-JUN JUL-AUG SEP-OCT NOV-DEC
ALEXINOAH+IRRIGMOD16LAI
LAI (-)
ET (mm d-1)
NILE DELTA

GEZIRA IRRIGATION SCHEME
ALEXIMOD16LAI
LAI (-)
ET (mm d-1)
NOAH+IRRIG

ALEXIMOD16LAI
LAI (-)
ET (mm d-1)
SUDD WETLAND
NOAH+IRRIG

ALEXIMENADomains
Evapotranspiration 2009
JAN-FEB MAR-APR JUN-JUL AUG-SEP
MJ m-2 day-1
0
5
10
15
20
25
0
1
2
3
4
5
6
7
2007 2007.5 2008 2008.5 2009 2009.5 2010 2010.5 2011 2011.5 2012
DailyFlux(MJm-2day-1)
LeafAreaIndex
LAI Net Radiation Latent HeatNILE DELTA
0
5
10
15
20
25
0
1
2
3
4
5
6
7
2007 2007.5 2008 2008.5 2009 2009.5 2010 2010.5 2011 2011.5 2012
LeafAreaIndex
LAI Net Radiation Latent Heat
GEZIRA
0
5
10
15
20
25
0
1
2
3
4
5
6
7
2007 2007.5 2008 2008.5 2009 2009.5 2010 2010.5 2011 2011.5 2012
LeafAreaIndex
LAI Net Radiation Latent Heat
SUDD

AfricanMonsoonProject
(MJ m-2 d-1)
African Monsoon Multidisciplinary Analysis (CNRM, CESBIO)
BENIN
NIGER
MALI Flux towers
Landsat Science Team, July 2015NENA Stakeholders Workshop – October 2015

MSG (3km)
MSG (3km)
MODIS (1km)
MODIS (1km)L7 (30m)L7 (30m)
L7 (30m)
Bellefoungou Forest
BENIN, AFRICA
ET (mm/d)

Benin, Africa
Landsat 7 - 2009
Forrestandfieldtowersites
Daily ET 324

0
2
4
6
8
10
0 50 100 150 200 250 300 350
ET(mm/day)
Day of year
Nalohou(Fallowfield)
ALEXI ET
Observed ET
Landsat retrievals
Landsat-only

0
2
4
6
8
10
0 50 100 150 200 250 300 350
ET(mm/day)
Day of year
BellefoungouForest
ALEXI ET
Observed ET
Landsat retrievals
Landsat-only

GOES/MODIS/Landsat FUSION
GOES
(ALEXI)
MODIS
(DisALEXI)
LANDSAT
(DisALEXI)
DOY 328 329 330 331 332 333 334 335 336
Landsat 5 Landsat 7
(Gao et al, 2006)
Spatial Temporal Adaptive Reflectance Fusion Model
(STARFM)
Daily Evapotranspiration – Orlando, FL, 2002

EvaluationoffusedETfluxes
SMEX02
Soil Moisture Experiment 2002
Ames, Iowa
Rainfed corn and soybean
BEAREX08
Bushland ET and Remote sensing Experiment 2008
Bushland, Texas
Rainfed and irrigated cotton
MEAD
Ameriflux site (S. Verma)
Mead, NE
Rainfed and irrigated corn and soybean
4 km
SMEX02

ModelperformanceonLandsatdates
SMEX02 BEAREX08 MEAD
1.08 MJ m-2 d-1
8%
MAE:
RE:
1.3 MJ m-2 d-1
10%
1.3 MJ m-2 d-1
11%

Validationusingfluxtowerdata
0
50
100
150
200
250
300
150 160 170 180 190 200 210 220 230 240
CumulativeET(mm)
Day of Year
0
2
4
6
8
10
150 160 170 180 190 200 210 220 230 240
DailyET(mmperday)
Day of Year
Reference ET
Observed ET
Landsat retrievals
Landsat-only
0
2
4
6
8
10
150 165 180 195 210 225 240
DailyET(mmperday)
Day of Year
RAIN
Rainfed soybean – SMEX02 (Iowa)

SMEX02cumulativefluxes
y = 1.0089x - 7.2676
R² = 0.8784
y = 1.2552x - 76.752
R² = 0.8699
175
200
225
250
275
300
175 200 225 250 275 300
Modeledcumulativeflux(mm)
Observed cumulative flux (mm)
Landsat-only
Landsat-MODIS
(7% RE)
(4% RE)

BEAREX08andMEAD BEAREX08 MEAD
Unirrigated cotton
Irrigated cotton
Irrigated corn
Unrrigated corn

Waterusevariabilitywithstandage
(Yang et al., 2015)

Waterusevariabilitywithlanduse
(Yang et al., 2015)

Monitoring Water Use and Drought at Field to Global Scales, Chris Hain

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