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Elsevier Masson, Agricultural Water Management, 2(56), p. 113-129

DOI: 10.1016/s0378-3774(02)00009-4

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Simulating the fate of water in a soil-crop system of a semi-arid Mediterranean area with the WAVE 2.1 and the EURO-ACCESS-II models

Journal article published in 2002 by Je E. Fernandez, C. Slawinski ORCID, F. Moreno, Rt T. Walczak, Marnik Vanclooster
This paper is available in a repository.
This paper is available in a repository.

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Abstract

In this paper. we evaluated the WAVE 2.1 and the EURO-ACCESS-II models for predicting crop water consumption, water losses by drainage and volumetric soil water content in a cropped soil under Mediterranean conditions. A detailed dataset was constructed for a furrow-irrigated experimental plot on a homogeneous sandy soil, cropped with maize during the seasons 1992 and 1993. The calibration and the validation results of the models were evaluated by using both simulation graphics and two specific modelling evaluation statistics: the root mean square error (RMSE) and the modelling efficiency. Results showed that both models are able to predict the fate of water in this coarse textured irrigated soil subjected to semi-arid Mediterranean environmental and agronomical conditions. Reasonably good predictions of the seasonal evolution both of the crop evapotranspiration and the water losses by drainage were obtained with both models. Soil moisture was also well predicted by the models when considering total soil moisture storage in the root zone of plants. However, the deviations between the predicted and observed moisture values increased when considering each soil layer separately. Sensitivity analysis showed that the input values of the crop coefficient have a significant influence on predictions made by the WAVE 2.1 model. The value of the hydraulic conductivity close to saturation had a significant influence on the predicted water losses by drainage in the EURO-ACCESS-II model. Our results showed that calibration for the specific environmental conditions of the field sites is required before using any of the two models in a purely prediction model. During this calibration, special attention must be given to the input values of those variables which are most affected by spatio-temporal variability within the field. (C) 2002 Elsevier Science B.V. All rights reserved.