PENGOLAHAN CITRA DIGITAL

AGRICULTURAL DROUGHT MONITORING AND ASSESMENT

The Famine Early Warning Systems Network (FEWS NET) is a program of the U.S. Agency for International Development (USAID), Office of Food for Peace, that helps target over 1.5 billion dollars of assistance to more than 40 countries each year.  Its history goes back to the mid-1980s, when it had a particular focus on the Sahel, and it continues today with a presence in 17 Sub-Saharan African countries, Haiti, Guatemala, and Afghanistan.  Since its beginning, FEWS NET has been known for its innovative use of geospatial data and satellite remote sensing to help understand what is happening in regions with scarce observations on the ground.  The U.S. Geological Survey, NASA, and NOAA have been developing applications for FEWS NET as long term implementing partners.

In 2011, drought and famine in the Horn of Africa pointed up the vulnerability to climate shocks of people living with poverty, conflict, and weak institutions. This is especially so for herders and subsistence farming livelihoods, which are highly climate-sensitive.  Drought monitoring is as important to famine early warning as tracking market food prices and household nutrition/mortality surveys.  Because station networks in the countries of concern are sparse and often report with significant delay, FEWS NET depends on satellite observations and modeling to fill in the gaps.

Before monitoring crop and rangeland growing conditions, it is necessary to geographically characterize the ways in which households earn income and access food.  FEWS NET does this by producing livelihood zone maps (e.g., http://www.fews.net/docs/Publications/KE_Livelihoods.pdf).  The maps are accompanied by seasonal monitoring calendars, which describe the critical events in the annual cycle of the livelihood systems.  These are essential to understanding the impact of a shock on household income and food access.

Vegetation index imagery is the remote sensing product that has the longest history of use with FEWS NET.  Beginning in the 1980s, NASA provided new images every ten days at a spatial resolution of 8 km to help reveal zones of low plant vigor indicative of drought.  Today, thanks to expedited processing by NASA and USGS, Normalized Difference Vegetation Index (NDVI) images are available every five days at 250 meter resolution, only 12 hours after the last satellite overpass. 

Figure 1 presents an NDVI anomaly image for the Horn of Africa in May, 2011, that clearly illustrates the extent of the devastating failure of rains in the region.

Figure 1.  USGS eMODIS vegetation anomaly image for the Horn of Africa, May 1-10, 2011.

Rainfall is of course a fundamental variable for drought monitoring, and FEWS NET uses Rainfall Estimate (RFE) products from NOAA that blend satellite data with station observations on a 0.1 degree (about 10 km) grid.  These are produced daily by combining cloud top temperature images from geostationary satellites, microwave scattering images from polar orbiting satellites, and rain gauge totals reported to the World Meteorological Organization, where available.  Figure 2 presents an example NOAA RFE image for the African continent.

Figure 2.  Example Rainfall Estimate (RFE) image produced by NOAA for FEWS NET.

In order to better understand the agricultural implications of the RFE, USGS has developed a gridded version of the Water Requirement Satisfaction Index (WRSI), a crop water balance model developed by FAO.  Using grids of potential evapotranspiration computed from output fields of NOAA atmospheric models, along with crop specific coefficients and soil maps, it is possible to compute the extent to which incident rainfall (from RFE) has met the seasonal requirement of staple crops monitored by FEWS NET.  Figure 3 presents an example of output from the WRSI model.

Figure 3.  Example WRSI image for maize in the Horn of Africa in 2009.

A more recent product developed for FEWS NET by USGS uses land surface temperature images, at 1 km resolution, from the NASA MODIS instrument.  These are used in an energy balance calculation to reveal zones of abnormally low crop and rangeland evapotranspiration (ET) due to drought.  Figure 4 presents an example of an ET anomaly (Eta) product.

Figure 4.  Example of an evapotranspiration anomaly image computed from MODIS land

surface temperature data using an energy balance method.  Drought in the Horn of

Africa appears prominently in red tones.

All of these products have their relative strengths and weaknesses.  Fortunately, the underlying geophysical observations behind NDVI, WRSI, and Eta are independent of one another.  This means that they can be used jointly in a convergence of evidence approach to confidently identify zones of drought impact on the landscape.

FEWS NET also uses geospatial climate products that look into the future.  During the 1990s, seasonal forecasts were integrated into preparation of 3-6 month food security outlooks in conjunction with Regional Climate Outlook Forums in Africa.  In the 2000s, the importance of climate change has been recognized through detailed analyses of observed climate trends, diagnostic ocean-atmosphere studies, and interpretations of GCM scenarios.  A series of fact sheets is being produced to present these findings in a way that is helpful to development planners (e.g., http://pubs.usgs.gov/fs/2010/3074/).

The case of the Horn of Africa in 2010-2011 demonstrates how FEWS NET’s understanding of livelihoods and climate (locally and globally) made possible early warning months before the crisis, and enabled pre-positioning of food and supplies in the region (http://www.fews.net/docs/Publications/La_Nina_Brief_East%20Africa_Sept_2... ) In spite of these efforts, conditions overwhelmed the capacity of humanitarian organizations to provide food aid, driving home the lesson that long term disaster reduction lies with political stability, development, and climate change adaptation, rather than emergency response.

In order to support progress in this direction, FEWS NET is applying its experience in drought monitoring to develop loss exceedence curves for crop production shortfall.  Using the RFE record since 2000, a set of 500 seasonal rainfall sequences has been developed statistically to drive the WRSI model.  The 500 WRSI outcomes, in turn can be expressed as yield reductions and shortfall in production on a national scale.  Using these 500 cases of production shortfall, it is possible to build a loss exceedence curve describing the magnitude of agricultural drought impact and associated probability of occurrence.  Figure 5 presents an example of such a curve for national millet harvest production loss in a Sahelian country.  Tools like these will be essential to the implementation of proactive disaster risk reduction programs.  Such programs will be able to greatly reduce human suffering beyond the capabilities of even the best emergency response campaigns.

For more information, please visit

http://www.fews.net

http://earlywarning.usgs.gov/fews

http://www.cpc.ncep.noaa.gov/products/fews/

Figure 5.  Example of a loss exceedence curve for drought impact on the national millet harvest of a Sahelian country.  Work in progress for FEWS NET by H. Jayanthi and G. Husak at the University of California, Santa Barbara.

Sumber:

https://www.agriskmanagementforum.org/content/geospatial-methods-agro-climatic-monitoring-food-security-assessment