Assessing potential of vertical average soil moisture (0-40cm) estimation for drought monitoring using MODIS data: A case study

摘要

Soil moisture is an important parameter in the research of hydrology, agriculture, and meteorology. The present study is designed to evaluate the potential of estimating vertical average soil moisture (0-40cm) using MODIS data. It has been found that the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) are related to surface soil moisture, and a second order polynomial relationship between ground measurement soil moisture and NDVI and LST can be developed. Therefore, six days' NDVI and LST data calculated from Terra Moderate Resolution Imaging Spectroradiometer (MODIS) of Shandong province during October in 2010 to May in 2011 were combined with ground measured volumetric soil moisture in different depth (10cm, 20cm, 40cm, and vertical average (0-40cm)) and different soil type to determine regression relationships. The result shows that significantly relationship exists between the NDVI and LST and soil moisture at 10cm and 20cm depth, slighter lower correlation coefficients are obtained for vertical average soil moisture (0-40cm), and worst correlationships are found for soil moisture at 40 cm depth. In addition, those regression relationships are soil type dependent. This means that it is feasible to estimate vertical average soil moisture (0-40cm) for drought monitoring using MODIS data.