Kuo, S.-F.S.-F.KuoCHEN-WUING LIUMerkley, G.P.G.P.Merkley2018-09-102018-09-102001http://www.scopus.com/inward/record.url?eid=2-s2.0-0035212702&partnerID=MN8TOARShttp://scholars.lib.ntu.edu.tw/handle/123456789/293843This work presents a model based on the on-farm irrigation scheduling and the simulated annealing (SA) optimization method for agricultural water resource management. The proposed model is applied to an irrigation project located in Delta, Utah of 394.6 ha area for optimizing economic profits, simulating the water demand and crop yields and estimating the related crop area percentages with specified water supply and planted area constraints. The application of SA to irrigated project planning in this study can be divided into nine steps: (1) to receive the output from the on-farm irrigation scheduling module; (2) to enter three simulated annealing parameters; (3) to define the design 'chromosome' representing the problem; (4) to generate the random initial design 'chromosome'; (5) to decode the design 'chromosome' into a real number; (6) to apply constraints; (7) to apply an objective function and a fitness value; (8) to implement the annealing schedule by the Boltzmann probability; and (9) to set the 'cooling rate' and criterion for termination. The irrigation water requirements from the on-farm irrigation scheduling module are: (1) 1067.9, 441.7, and 471.8 mm for alfalfa, barley and maize, respectively, in one unit command area; and (2) 1039.5, 531.4, 490.9, and 539.4 mm for alfalfa, barley, maize and wheat, respectively, in the other unit command area. The simulation results demonstrate that the most appropriate parameters of SA for this study are as follows: (1) initial simulation 'temperature' of 1000; (2) number of moves equal to 90; and (3) 'cooling rate' of 0.95. © 2001 Silsoe Research Institute.[SDGs]SDG6Hordeum vulgare subsp. vulgare; Medicago sativa; Triticum aestivum; Zea maysjournal article10.1006/jaer.2001.0723