WOFOST Model Based on Soil Moisture Driven and Its Adaptability

doi:10.3969/j.issn.1000-6362.2015.03.003

Abstract

Abstract: The crop growth model of WOFOST is used to simulate crop growth by estimation of soil relative humidity based on daily precipitation. It is difficult to set different scenarios of soil drought levels by changing daily precipitation, because of the randomness of daily precipitation. This weakness imposed restrictions on the simulation of crop growth under different water stress, and also had bad effects on the accuracy of the simulation. In the current study, a revised WOFOST crop growth model directly based on soil relative humidity was developed. The Compaq Visual Fortran 6.5 was applied as the development platform, and the source code of WOFOST model was modified by Fortran language, which replacing the driving file of daily precipitation with soil relative humidity. The revised WOFOST crop growth model was used to simulate corn growth under the stages of seedling emergence- jointing and tasseling-mature in the conditions of water stress. The results were compared with that under natural precipitation in Xiajin agricultural meteorological station in the Shandong Province in 2013. The results showed that the accuracy of model obviously improved by using the revised model in the output results of the fresh leaf dry weight, fresh stem dry weight, vegetative organs dry weight, total weight of the ground material and leaf area index. Furthermore, the corn growth under different soil drought levels was simulated by setting different water stress scenarios due to the stability of soil moisture. The revised WOFOST model is useful to evaluate the impact of different drought levels on corn growth, and to determine the indexes of corn growth and development.

Key words: Soil moisture driving force, Precipitation driving force, WOFOST model, Driver file modification

WANG Rui，LI Ya fei，ZHANG Li juan，WANG Jian lin，WANG Zhi wei. WOFOST Model Based on Soil Moisture Driven and Its Adaptability[J]. Chinese Journal of Agrometeorology, 2015, 36(03): 263-271.

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