Monitoring and modeling agricultural drought for famine early warning

Transcription

1 Monitoring and modeling agricultural drought for famine early warning James Verdin Chris 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 Dakota 3. University of California, Santa Barbara U.S. Department of the Interior U.S. Geological Survey

2 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 security decision support system with embedded climate services

3 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

4 FEWS NET Implementing Partners U.S. Agency for International Development Prime contractor (Chemonics International) U.S. Geological Survey + UCSB Geography National Oceanic and Atmospheric Administration National Aeronautics and Space Administration USDA Foreign December 14, Agricultural 2009 San Francisco Service

5 Famine Early Warning Systems Network Livelihood systems are based on subsistence agriculture and/or pastoralism, and are highly climatesensitive 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

6 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

7 Time Series Vegetation Index Imagery from NASA since 1985

8 Seasonal Vegetation Index by Crop Zone NDVI time series for growing seasons 1999/00 (good) 2000/01 (about average) 2001/02 (poor) and the historical mean

9 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

10 Water Requirement Satisfaction Index WRSI = f (ppt, pet, WHC, Crop Type, SOS, EOS, LGP) RFE (NOAA) calculated from NOAA GDAS at EROS FAO soils map of the world Kc (FAO)

11 Mapping Agricultural Drought WRSI Soil Water Index

12 MODIS Snow Covered Area Thank you!

13 Modeling Snow Water Equivalent

14 Basin Seasonal Snow Water Volume Thank you!

15 Energy Balance Estimates of Crop ET

16 MODIS NDVI

17 Production estimation - Zimbabwe

18 Afghanistan Drought Impact on 2008 Harvest Maximum NDVI 2003 vs for rain fed and irrigated crops

19 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

20 New FEWS NET Operational Priority Countries Remote Monitoring System - Expanded Coverage B C A Timor Leste Red Current countries Current monitoring domains: A, B, C Yellow Weather/agricultural outcomes AND availability/access monitoring Green Weather/agricultural outcomes

21 Geoserver Database P N AG GEO DATA 1. Admin Units S Decision Support Interface Interactive Analysis Tool Early Warning Explorer 2. Rangelands 3. Principal crops Growing areas Crop calendars Rain fed? Irrigated? 4. Snow pack E Catchments Rivers Growing areas

22 Inputs A LIS Instance for FEWS NET Physics Outputs Applications Topography, Soils Land Surface Models (CLM, Noah, VIC, etc) Soil Moisture & Temperature Weather Land Cover, Vegetation Properties Evaporation Sensible Heat Flux Climate Water Resources Meteorological Forecasts, Analyses, and/or Observations Runoff Agriculture Drought Snow Soil Moisture Temperature Data Assimilation Modules Snowpack Properties Natural Hazards

23 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 time frame

24 Thank you