Estimation of Soil Moisture Contents of Paddy Fields in Vavuniya District using Remote Sensing Technology

Abstract

Soil moisture is an important bio-physical parameter that is used as an interface for the land surface and for the atmosphere, particularly in agricultural perspective. Cultivation of paddy is a major livelihood activity associated with seasonal rainfall and the supplementary irrigation in Vavuniya District. This study aimed towards the estimation of soil moisture content using remote sensing technology (SEBAL- Surface Energy Balance Algorithm for Land) for paddy fields in Vavuniya District after the Maha season during the period of March to July 2012 associated with MODIS products and meteorological data from Vavuniya meteorological station. It was clearly identified except in July, estimated soil moisture content at the top layer (0 -1 5 cm) showed both under-estimation and over-estimation. Other estimation of soil moisture correlated perfectly with measured soil moisture content. The obtained root mean square error (RMSE) for each month during the study period lies in the range of 5-10 % except in July (12.58% ). Therefore, this estimation could be used to estimate the soil moisture content up to 15 cm from surface to this region. From the estimation of soil moisture content using SEBAL algorithm, estimated moisture content lies in between 30- 40 % during March & April. Then, there was a sudden drop of moisture content in May (10-20% ) and increased to about 26% in June. Hence, there is a possibility of using residual soil moisture with the supplementary irrigation for the cultivation of crops such as vegetable, chili, oil crops and onion.