Development of indices for agricultural drought monitoring using a spatially distributed hydrologic model

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Title: Development of indices for agricultural drought monitoring using a spatially distributed hydrologic model
Author: Narasimhan, Balaji
Abstract: Farming communities in the United States and around the world lose billions of dollars every year due to drought . Drought Indices such as the Palmer Drought Severity Index (PDSI ) and Standardized Precipitation Index (SPI ) are widely used by the government agencies to assess and respond to drought . These drought indices are currently monitored at a large spatial resolution (several thousand km2 ) . Further , these drought indices are primarily based on precipitation deficits and are thus good indicators for monitoring large scale meteorological drought . However , agricultural drought depends on soil moisture and evapotranspiration deficits . Hence , two drought indices , the Evapotranspiration Deficit Index (ETDI ) and Soil Moisture Deficit Index (SMDI ) , were developed in this study based on evapotranspiration and soil moisture deficits , respectively . A Geographical Information System (GIS ) based approach was used to simulate the hydrology using soil and land use properties at a much finer spatial resolution (16km2 ) than the existing drought indices . The Soil and Water Assessment Tool (SWAT ) was used to simulate the long -term hydrology of six watersheds located in various climatic zones of Texas . The simulated soil water was well -correlated with the Normalized Difference Vegetation Index NDVI (r ~ 0 .6 ) for agriculture and pasture land use types , indicating that the model performed well in simulating the soil water . Using historical weather data from 1901 -2002 , long -term weekly normal soil moisture and evapotranspiration were estimated . This long -term weekly normal soil moisture and evapotranspiration data was used to calculate ETDI and SMDI at a spatial resolution of 4km ? ? 4km . Analysis of the data showed that ETDI and SMDI compared well with wheat and sorghum yields (r > 0 .75 ) suggesting that they are good indicators of agricultural drought . Rainfall is a highly variable input both spatially and temporally . Hence , the use of NEXRAD rainfall data was studied for simulating soil moisture and drought . Analysis of the data showed that raingages often miss small rainfall events that introduce considerable spatial variability among soil moisture simulated using raingage and NEXRAD rainfall data , especially during drought conditions . The study showed that the use of NEXRAD data could improve drought monitoring at a much better spatial resolution .
URI: http : / /hdl .handle .net /1969 .1 /2727
Date: 2005-11-01

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Development of indices for agricultural drought monitoring using a spatially distributed hydrologic model. Available electronically from http : / /hdl .handle .net /1969 .1 /2727 .

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