Abstract
Soil wetness is an important parameter that provides information about the state of soils, soil moisture, soil wetness, and surface runoff that is useful in flood forecasting. Soil wetness data over large regions are now available through microwave remote sensing. In the present study, we have made efforts to understand the relation between soil wetness index (SWI) and precipitation. We have used Special Sensor Microwave Imager (SSM/I) brightness temperature data to calculate SWI over the Indian subcontinent. The SWI estimate has been tested through (i) the difference in estimated SWI values during the monsoon and non-monsoon periods; and (ii) the correlation between estimated SWI and precipitation, since it is difficult to obtain SWI directly. SWI estimates were found to be relatively higher during the monsoon period as compared with those during the non-monsoon period. A positive linear correlation (R2 > 0.5) was found between SWI estimates and precipitation. During flooding, a sharp increase in SWI was observed, and the SWI values remained high for the duration of the flood. The SWI shows characteristic behavior over different river basins due to changes in the geological terrain, lithology, meteorological conditions, and rainfall.
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