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DIVISION S-1—SOIL PHYSICS

Calibration of a Two-Dimensional Root Water Uptake Model

J. A. Vrugt^a, J. W. Hopmans^*,b and J. imunek^c

^a Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, The Netherlands, Nieuwe Prinsengracht 130, Amsterdam, 1018 VZ
^b Hydrology Program, Dept. Land, Air and Water Resources (LAWR), University of California, Davis, CA 95616, USA
^c USDA Salinity Laboratory, University of California, Riverside, CA 95207, USA

* Corresponding author (jwhopmans{at}ucdavis.edu)

Although solutions of multidimensional transient water flow can be obtained by numerical modeling, their application may be limited in part as root water uptake is generally considered to be one-dimensional only. The objective of this study was to develop and test a two-dimensional root water uptake model, which can be incorporated into numerical multidimensional flow models. The two-dimensional uptake model is based on the model by Raats, but is extended with a radial component. Subsequently, the root water uptake model was incorporated into a two-dimensional flow model, and root water uptake parameters were optimized, minimizing the residuals between measured and simulated water content data. Water content was measured around a sprinkler-irrigated almond tree (Prunus laurocerasus M.J.Roem) for a 16-d period at 25 locations, following irrigation. To calibrate the flow and root water uptake model, a genetic algorithm (GA) was used to find the approximate global minimum of the optimized parameter space. The final fitting parameters were determined using the Simplex algorithm (SA). With the optimized root water uptake parameters, simulated and measured water contents during the 16-d period were in excellent agreement, with R² values generally ranging between 0.94 and 0.99 and a root mean squared error (RMSE) of 0.015 m³ m^-3. The developed root water uptake model is extremely flexible and allows spatial variations of water uptake as influenced by nonuniform (drip irrigation) and uniform water application patterns.

Abbreviations: CIMIS, California Irrigation Management Information System • CV, coefficient of variation • GA, genetic algorithm • RMSE, root mean squared error • SA, simplex algorithm

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