Potential of Probabilistic Hydrometeorological Approach for Precipitation-Based Soil Moisture Estimation
Publication: Journal of Hydrologic Engineering
Volume 20, Issue 4
Abstract
In this paper, a hydrometeorological approach to the probabilistic simulation of soil moisture is proposed. The time series of in situ soil moisture and meteorological variables at a monthly scale from different monitoring stations across India are utilized. Preliminary investigation with both precipitation and near-surface air temperature as meteorological variables reveals that the strength of association between soil moisture and precipitation is more significant compared to that between soil moisture and temperature. Precipitation-based probabilistic estimation of soil moisture using the proposed hydrometeorological approach is tested with in situ observed soil moisture data and with soil moisture data of the Climate Change Initiative project, funded by the European Space Agency. The results are found to be promising. In addition, the proposed hydrometeorological approach is able to provide the information on uncertainty associated with the estimation. It is also shown that the parameter of the developed model is linked to the predominant soil textural class. Higher values of the model parameter [dependence parameter () for the selected copula] correspond to clay loam, medium values correspond to loamy sand or loam, and low values correspond to sandy loam to sandy soil. Three stations outside India, which are widely separated across the globe with known soil textural class, are also considered, and the performance of the proposed model is tested by estimation of the model parameter depending on the soil textural class. The results are found to be reasonably good, indicating the spatial transferability of the proposed approach.
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Acknowledgments
We acknowledge the financial support of the Australia India Strategic Research Fund (AISRF) through a bilateral project, DST/INT/AUS/P-27/2009 and by another project supported by Ministry of Earth Sciences (MoES), India. We thank Prof. Alan Robock at Rutgers University in New Brunswick, New Jersey, for providing soil moisture data and related information. We also wish to thank the anonymous reviewers for their thoughtful suggestions and efforts to improve the manuscript.
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Journal of Hydrologic Engineering
Volume 20 • Issue 4 • April 2015
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© 2014 American Society of Civil Engineers.
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Received: Jun 21, 2013
Accepted: May 30, 2014
Published online: Aug 13, 2014
Discussion open until: Jan 13, 2015
Published in print: Apr 1, 2015
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