Determination of bare surface soil moisture from combined temporal evolution of land surface temperature and net surface shortwave radiation

Land surface soil moisture (SSM) is an important variable for hydrological, ecological, and meteorological applications. A multi-linear model has recently been proposed to determine the SSM content from the combined diurnal evolution of both land surface temperature (LST) and net surface shortwave radiation (NSSR) with the parameters TN (the LST mid-morning rising rate divided by the NSSR rising rate during the same period) and t(d) (the time of daily maximum temperature). However, in addition to the problem that all the coefficients of the multi-linear model depend on the atmospheric conditions, the model also suffers from the problems of the nonlinearity of TN as a function of the SSM content and the uncertainty of determining the t(d) from the diurnal evolution of the LST. To address these problems, a modified multi-linear model was developed using the logarithm of TN and normalizing t(d) by the mid-morning temperature difference instead of using the TN and t(d). Except for the constant term, the coefficients of all other variables in the modified multi-linear model proved to be independent of the atmospheric conditions. Using the relevant simulation data, results from the modified multi-linear model show that the SSM content can be determined with a root mean square error (RMSE) of 0.030m(3)/m(3), provided that the constant term is known or estimated day to day. The validation of the model was conducted using the field measurements at the Langfang site in 2008 in China. A higher correlation is achieved (coefficient of determination: R-2=0.624, RMSE=0.107m(3)/m(3)) between the measured SSM content and the SSM content estimated using the modified multi-linear model with the coefficients determined from the simulation data. Another experiment is also conducted to estimate the SSM content using the modified model with the constant term calibrated each day by one-spot measurements at the site. The estimation result has a relatively larger error (RMSE=0.125m(3)/m(3)). Additionally, the uncertainty of the determination of the coefficients is analysed using the field measurements, and the results indicate that the SSM content obtained using the modified model accurately characterizes the surface soil moisture condition. Copyright (c) 2012 John Wiley & Sons, Ltd.