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• W2465433093 abstract "The efficient irrigation systems require key soil parameters, field capacity, and wilting point to estimate the maximum soil water holding capacity. The present study employs the inverse modeling method to determine the soil water contents at field capacity and wilting point through utilization of near-surface satellite soil moisture. The study also compares the field capacity and wilting point as obtained from the soil hydraulic parameters based on Rosetta pedotransfer functions. Efficiency is improved with reduction in root mean square error (RMSE) and mean bias error (MBE) in estimating the soil water retention curve by the optimized method as compared to pedotransfer function. These parameters were then used as input parameters in the HYDRUS-1D model along with integration of tropical rainfall measuring mission rainfall data set and the results of observed and simulated soil water contents were compared. It was found that the optimized parameters were able to simulate the soil water contents with RMSE in the range of 0.03–0.07 and MBE in the range of 0.03–0.23 for all the depths during both calibration and validation. However, with pedotransfer-based parameters the RMSE and MBE were found in the range of 0.11–0.15 and 0.69–1.03, respectively." @default.
• W2465433093 created "2016-07-22" @default.
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• W2465433093 date "2016-01-01" @default.
• W2465433093 modified "2023-10-14" @default.
• W2465433093 title "Integrative Use of Near-Surface Satellite Soil Moisture and Precipitation for Estimation of Improved Irrigation Scheduling Parameters" @default.
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• W2465433093 doi "https://doi.org/10.1016/b978-0-12-803388-3.00014-0" @default.
• W2465433093 hasPublicationYear "2016" @default.
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