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Evaluating the utility of the Vegetation Condition Index (VCI) for monitoring meteorological drought in Texas
- Quiring, Steven M., Ganesh, Srinivasan
- Agricultural and forest meteorology 2010 v.150 no.3 pp. 330-339
- vegetation, water stress, drought, meteorological data, growing season, precipitation, temporal variation, plant growth, spatial variation, correlation, environmental factors, agroecological zones, land use, vegetation cover, irrigation, soil properties, Texas
- The relationship between the satellite-based Vegetation Condition Index (VCI) and a number of frequently used meteorological drought indices was evaluated using data from all 254 Texas counties during 18 growing-seasons (March to August, 1982-1999). In particular, the response of the VCI was compared to that of the Palmer Drought Severity Index (PDSI), Moisture Anomaly Index (Z-index), Standard Precipitation Index (SPI), percent normal, and deciles. Overall the VCI is most strongly correlated with the 6-month SPI, 9-month SPI and PDSI. This indicates that, at least over Texas, the growing-season VCI responds to prolonged moisture stress and it appears to be less sensitive to short-term precipitation deficiencies. There was also significant spatial variability in the strength of the relationship between the VCI and the meteorological drought indices. Generally, counties in northwestern and southwestern Texas had much higher correlations (R ² >0.6) than counties in eastern Texas and along the Gulf Coast (R ² <0.1). Nearly 75% of these spatial variations can be explained using a series of environmental variables. It appears that the climate region is the most important determinant of the nature of the relationship between the VCI and PDSI. Other important variables include the land use/land cover in each county, the amount of irrigation, and soil properties. These results demonstrate that care must be taken when using the VCI for monitoring drought because it is not highly correlated with station-based meteorological drought indices and it is strongly influenced by spatially varying environmental factors.