Optimising Fruit Cultivars Irrigation Via a Hierarchical Partitioning

C. VAN CAUWENBERGHE, A. BANDONI

Cincinnati COnvention Center, Cincinnati, Ohia, USA

Congreso; AIChE Annual Meeting 2005; 2005

AICHE

The urgent current necessities in modern agriculture has afforded in a growing application of computer science and electronics to this field. Precision and sustainable agriculture, involve not only new production methods, but also complex systems that integrates biological, technological and economical factors in a flexible environment, to cope with the uncertainty of nature. This form of agriculture aims to optimise proficiency and environmental protection, by assessing together forecasts for risk, damages and profit. One aspect to consider in order to reach that purpose,is the availability of good irrigation systems (Walker, 2002). Improving water efficiency in irrigated agriculture is a priority for better environmental and economic performance, specially to avoid soils lixiviation and its consequent nutrient content loss, reducing the required amount of water and optimising the timing of application (Howell, 2001). Among numerous methods, hybrid biophysical/decisional simulation models are effective tools for evaluating and comparing irrigation strategies under different weather conditions. Nevertheless, optimising irrigation strategies for some specified agro-environmental expected criteria represents a computationally hard problem. In this paper we propose a new approach for optimising the parameters of seed-fruit irrigation strategies, represented by structured decision rules simulated with the management-oriented model IRGSIM 1.0. We introduce a stochastic simulation-optimisation partitioning method, which it is designed to completely explore by sampling the domain of the strategy parameters. This exploration is based on a hierarchical decomposition of the domain that heuristically guides the search toward optimal regions, allowing to consider high dimensional optimisation problems. Firstly, we evaluate a irrigation strategy by comparison with a systematic grid search on a simple two-parameter problem in cultivars areas located in southern Argentine, in order to optimise the expectation of the direct gain margin, and using 20 years of weather records as input data. We obtain very similar results that confirm the sound behaviour of the partitioning method. Then, we apply our approach to a more complex optimisation problem that involves an eight-parameters strategy, for which the systematic grid search method is not effective. The best strategy we obtain shows a 32 ha-1 increase in the gain margin compared to a basic strategy proposed by irrigation advisors (Cox, 1996; Bergez, 2002). The partitioning algorithm is also used in the specific hydraulic contexts concerning the available flow rate. A numerical model for simulation of infiltration and groundwater flow in a different porous media with variable saturation level is also incorporated. The different optimal parameters obtained for each context arein good agreement with the expert knowledge of irrigation advisors. Finally, we conclude discussing some limitations and possible improvements of the presented work. References Bergez, J.E., Deumier, J.M., Lacroix, B., Leroy, P., Wallach, D., 2002. Improving irrigation schedules by using a biophysical and a decisional model. Eur. J. Agron. 16, 123?135. Cox, P.G., 1996. Some issues in the design of agricultural decision support systems. Agric. Syst. 52, 355? 381. Howell, T.A., 2001. Enhancing water use eficiency in irrigated agriculture. Agron. J. 93, 281?289. Walker, D., 2002. Decision support, learning and rural resource management. Agric. Syst. 73, 113?127.