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Modelling Soil Water Dynamics from Soil Hydraulic Parameters Estimated by an Alternative Method in a Tropical Experimental Basin.

Authors :
Silva Ursulino, Bruno
Maria Gico Lima Montenegro, Suzana
Paiva Coutinho, Artur
Hugo Rabelo Coelho, Victor
Cezar dos Santos Araújo, Diego
Cláudia Villar Gusmão, Ana
Martins dos Santos Neto, Severino
Lassabatere, Laurent
Angulo-Jaramillo, Rafael
Source :
Water (20734441); May2019, Vol. 11 Issue 5, p1007, 1p
Publication Year :
2019

Abstract

Knowledge about soil moisture dynamics and their relation with rainfall, evapotranspiration, and soil physical properties is fundamental for understanding the hydrological processes in a region. Given the difficulties of measurement and the scarcity of surface soil moisture data in some places such as Northeast Brazil, modelling has become a robust tool to overcome such limitations. This study investigated the dynamics of soil water content in two plots in the Gameleira Experimental River Basin, Northeast Brazil. For this, Time Domain Reflectometry (TDR) probes and Hydrus-1D for modelling one-dimensional flow were used in two stages: with hydraulic parameters estimated with the Beerkan Estimation of Soil Transfer Parameters (BEST) method and optimized by inverse modelling. The results showed that the soil water content in the plots is strongly influenced by rainfall, with the greatest variability in the dry–wet–dry transition periods. The modelling results were considered satisfactory with the data estimated by the BEST method (Root Mean Square Errors, RMSE = 0.023 and 0.022 and coefficients of determination, R<superscript>2</superscript> = 0.72 and 0.81) and after the optimization (RMSE = 0.012 and 0.020 and R<superscript>2</superscript> = 0.83 and 0.72). The performance analysis of the simulations provided strong indications of the efficiency of parameters estimated by BEST to predict the soil moisture variability in the studied river basin without the need for calibration or complex numerical approaches. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20734441
Volume :
11
Issue :
5
Database :
Complementary Index
Journal :
Water (20734441)
Publication Type :
Academic Journal
Accession number :
136752934
Full Text :
https://doi.org/10.3390/w11051007