An analytical method for predicting surface soil moisture from rainfall observations
- ORNL
- Georgia Institute of Technology
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.
- Research Organization:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE)
- DOE Contract Number:
- DE-AC05-00OR22725
- OSTI ID:
- 930785
- Journal Information:
- Water Resources Research, Vol. 39, Issue 11; ISSN 0043-1397
- Country of Publication:
- United States
- Language:
- English
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