An analytical method for predicting surface soil moisture from rainfall observations

被引:74
作者
Pan, FF
Peters-Lidard, CD
Sale, MJ
机构
[1] Oak Ridge Natl Lab, Div Environm Sci, Oak Ridge, TN 37831 USA
[2] NASA, Hydrol Sci Branch, Goddard Space Flight Ctr, Greenbelt, MD 20071 USA
关键词
soil moisture; precipitation; Antecedent Precipitation Index (API); loss coefficient;
D O I
10.1029/2003WR002142
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
[1] A simple analytical method for estimating surface soil moisture directly from rainfall data is proposed and studied. Soil moisture dynamics are represented by a linear stochastic partial differential equation [Entekhabi and Rodriguez-Iturbe, 1994]. A diagnostic equation is derived from the soil moisture dynamics equation by eliminating the diffusion term. The derived daily soil moisture function is a time-weighted average of previous cumulative rainfall over a given period (e.g., > 14 days). The advantage of this method is that information on the initial condition of soil moisture, which is often not available at all times and locations, is not needed. The loss coefficient in the diagnostic equation for soil moisture can be estimated from land surface characteristics and soil properties. The method for determining the averaging window size, the loss coefficient, and the infiltration coefficient are described and demonstrated. The soil moisture data observed during three field experiments, i.e., Monsoon' 90, Washita' 92, and SGP' 97, are compared to the calculated soil moisture. The results indicate that the proposed method is robust and has the potential for useful soil moisture predictions.
引用
收藏
页码:SWC31 / SWC315
页数:20
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