monitoring and modeling agricultural drought for …...famine early warning systems network ·...
TRANSCRIPT
U.S. Department of the InteriorU.S. Geological Survey
AGU Fall Meeting
December 14, 2009 – San Francisco
Monitoring and modeling agricultural drought for famine early warning
James VerdinChris Funk, Michael Budde, Ronald Lietzow, Gabriel Senay, Ronald Smith, Diego Pedreros 1
James Rowland, Guleid Artan 2
Greg Husak, Joel Michaelsen, Alkhalil Adoum, Gideon Galu, Tamuka Magadzire, Mario Rodriguez 3
1. U.S. Geological Survey, EROS Center, Sioux Falls, South Dakota 2. ARTS, USGS EROS, Sioux Falls, South Dakota3. University of California, Santa Barbara
AGU Fall Meeting
December 14, 2009 – San Francisco
Famine Early Warning Systems Network
An activity of the Office of Food for Peace at USAID, which directly supports its goal:
“to ensure that appropriate… emergency food aid is provided to the right people in the right places at the right time and in the right way”
FEWS NET is a food securitydecision support system
with embedded climate services
AGU Fall Meeting
December 14, 2009 – San Francisco
Famine Early Warning Systems Network· FEWS NET identifies the times and places
that aid is need by the most food insecure populations of the developing world
· The activity has been continuous since 1985· The Office of Food for Peace distributed
$2.8 B in aid in 2008
AGU Fall Meeting
December 14, 2009 – San Francisco
U.S. Agency for International Development
FEWS NET Implementing Partners
Prime contractor (Chemonics International)
U.S. Geological Survey + UCSB Geography
National Oceanic and Atmospheric Administration
National Aeronautics and Space Administration
USDA Foreign Agricultural Service
AGU Fall Meeting
December 14, 2009 – San Francisco
Famine Early Warning Systems Network
· Livelihood systems are based on subsistence agriculture and/or pastoralism, and are highly climate-sensitive
· Conventional climate station networks are sparse and/or late reporting
· Satellite remote sensing and atmospheric models fill the gap, and provide the basis for early detection of agricultural drought
AGU Fall Meeting
December 14, 2009 – San Francisco
Famine Early Warning Systems Network
· Rainfall, vegetation, snow pack, ET are monitored for rangelands, rain fed crops, and irrigated crops
· A convergence of evidence approach is used
· As new satellite sensors and models have become available, there has been continuous improvement in remote monitoring of agricultural drought
AGU Fall Meeting
December 14, 2009 – San Francisco
Time Series Vegetation Index Imageryfrom NASAsince 1985
AGU Fall Meeting
December 14, 2009 – San Francisco
NDVI time series for growing seasons 1999/00 (good) 2000/01 (about average)2001/02 (poor) and the historical mean
Seasonal Vegetation Index by Crop Zone
AGU Fall Meeting
December 14, 2009 – San Francisco
Time Series Rainfall Grids
· Use of NOAA satellite RFE since mid-1990s
· A blend of TIR, MW, and station observations
· Used to force crop water balance models
AGU Fall Meeting
December 14, 2009 – San Francisco
WRSI = f (ppt, pet, WHC, Crop Type, SOS, EOS, LGP)
RFE(NOAA)
calculated fromNOAA GDASat EROS
FAO soils mapof the world Kc (FAO)
Water Requirement Satisfaction Index
AGU Fall Meeting
December 14, 2009 – San Francisco
Mapping Agricultural Drought
WRSI Soil Water Index
AGU Fall Meeting
December 14, 2009 – San Francisco
Thank you!
MODIS Snow Covered Area
AGU Fall Meeting
December 14, 2009 – San Francisco
Modeling Snow Water Equivalent
AGU Fall Meeting
December 14, 2009 – San Francisco
Thank you!
Basin Seasonal Snow Water Volume
AGU Fall Meeting
December 14, 2009 – San Francisco
Energy Balance Estimates of Crop ET
AGU Fall Meeting
December 14, 2009 – San Francisco
MODIS NDVI
AGU Fall Meeting
December 14, 2009 – San Francisco
Production estimation - Zimbabwe
AGU Fall Meeting
December 14, 2009 – San Francisco
2003
2008
Afghanistan Drought Impact on 2008 HarvestMaximum NDVI 2003 vs. 2008 for rain fed and irrigated crops
AGU Fall Meeting
December 14, 2009 – San Francisco
FEWS NET Remote Monitoring· FEWS NET has evolved a diverse suite of
monitoring products in an incremental, piecemeal fashion· Favorable for a robust convergence of evidence· Unfavorable if the independent methods produce
physically incompatible explanations of observed conditions
· Food crisis of 2008 has prompted expansion of remote monitoring
· New technology presents the opportunity for improved use of available data -> LDAS
AGU Fall Meeting
December 14, 2009 – San Francisco
Timor LesteA
B
New FEWS NET Operational Priority Countries
Red – Current countries
Yellow – Weather/agricultural outcomes AND availability/access monitoring
Green – Weather/agricultural outcomes
C
Current monitoring domains: A, B, C
Remote Monitoring System - Expanded Coverage
P
N
S
E
AG GEO DATA
1. Admin Units
2. Rangelands
3. Principal crops
• Growing areas
• Crop calendars
• Rain fed?
• Irrigated?
4. Snow pack
• Catchments
• Rivers
• Growing areas
Geoserver Database
Decision Support Interface
Interactive Analysis
Tool
Early Warning Explorer
Topography,Soils
Land Cover, Vegetation Properties
Meteorological Forecasts,
Analyses, and/or Observations
Snow Soil MoistureTemperature
Land Surface Models(CLM, Noah, VIC, etc)
Data Assimilation Modules
Soil Moisture &
Temperature
EvaporationSensible Heat
Flux
Runoff
SnowpackProperties
Inputs OutputsPhysics Applications
A LIS Instance for FEWS NET
Weather
Climate
Water Resources
Agriculture
Drought
Natural Hazards
AGU Fall Meeting
December 14, 2009 – San Francisco
Soil Moisture Active and Passive (SMAP)
Mission
• Soil Moisture on Earth Grid at 10 km with 24 hr latency• Surface and Root Zone Soil Moisture on Earth Grid at 10 km with 7 day latency• Launch scheduled in 2013-2014 time frame
AGU Fall Meeting
December 14, 2009 – San Francisco
Thank you