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Soil moisture availability has a significant impact on environmental processes of different scales. Errors in initializing soil moisture in numerical weather forecasting models tend to cause errors in short‐term weather and medium range predictions. We study the use of two drought indices: Palmer Drought Severity Index (PDSI) values and Standardized Precipitation Index (SPI) for estimating soil moisture. SPI and PDSI values are compared for three climate divisions: western mountains, central piedmont, and the coastal plain in North Carolina, USA. Results suggest SPI to be more representative of short‐term precipitation and soil moisture variation and hence a better indicator of soil wetness. A regression equation that uses SPI is proposed to estimate soil moisture.
Sims et al. (2002) studied this question.