One common problem is associated with water balance calculation methods for determining soil moisture for scheduling irrigation: errors in the estimated soil moisture are cumulative and frequent recalibrations are needed. A simple and robust approach to estimation of daily soil moisture using a daily diagnostic soil moisture equation is suggested and studied. The estimated soil moisture is a function of the time-weighted summation of the ratio of historical precipitation rate to soil moisture loss coefficient. To capture the seasonal variation in soil moisture loss coefficient, a sinusoidal wave function of the day of year (DOY) is used to represent the seasonal variation in loss coefficient. A 3-year continuous data set of daily soil moisture and daily precipitation collected at each of four Soil Climate Analysis Network sites—AR2091; in Arkansas, GA2013 in Georgia, NM2107 in New Mexico, and PR2052 in Puerto Rico—is applied to test the proposed method. The land cover/land use of these four sites is agricultural/crop fields, grasslands, or desert. Root mean square errors of the estimated volumetric soil moisture are less than 5% (v/v), and all correlation coefficients, R2, are greater than 0.78. The results indicate that there are three advantages associated with the suggested approach: (1) errors in estimated soil moisture are noncumulative; (2) regular recalibration is not required; and (3) numerical iteration and initial moisture information are not required.
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Feifei Pan (2011) studied this question.
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