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.