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Measuring and Modeling the Water Balance in Low-Rainfall Cropping Systems  Public Access Limited Time

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  Transactions of the ASABE. 60(6): 2097-2110. (doi: 10.13031/trans.12581) @2017
Authors:   Anthony M. Whitbread, Munir P. Hoffmann, C. William Davoren, Damian Mowat, Jeffrey A. Baldock
Keywords:   APSIM, Climate risk management, Crop models, Decision support, Soil moisture.

Abstract. In low-rainfall cropping systems, understanding the water balance, and in particular the storage of soil water in the rooting zone for use by crops, is considered critical for devising risk management strategies for grain-based farming. Crop-soil modeling remains a cost-effective option for understanding the interactions between rainfall, soil, and crop growth, from which management options can be derived. The objective of this study was to assess the error in the prediction of soil water content at key decision points in the season against continuous, multi-layer soil water measurements made with frequency domain reflectometry (FDR) probes in long-term experiments in the Mallee region of South Australia and New South Wales. Field estimates of the crop lower limit or drained upper limit were found to be more reliable than laboratory-based estimates, despite the fact that plant-available water capacity (PAWC) did not substantially differ between the methods. Using the Agricultural Production Systems sIMulator (APSIM) to simulate plant-available water over three-year rotations, predicted soil water was within 7 mm (PAWC 64 to 99 mm) of the measured data across all sowing events and rotations. Simulated (n = 46) wheat grain production resulted in a root mean square error (RMSE) of 492 kg ha-1, which is only marginally smaller than that of other field studies that derived soil water limits with less detailed methods. This study shows that using field-derived data of soil water limits and soil-specific settings for parameterization of other properties that determine soil evaporation and water redistribution enables APSIM to be widely applied for managing climate risk in low-rainfall environments.

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