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• W2106396957 abstract "One partial solution to the problem of ever-increasing demands on our water resources is optimal allocation of available water. A non-linear programming (NLP) optimization model with an integrated soil water balance was developed. This model is the advanced form of a previously developed one in which soil water balance was not included. The model also has the advantage of low computer run-time, as compared to commonly used dynamic programming (DP) models that suffer from dimensionality. The model can perform over different crop growth stages while taking into account an irrigation time interval in each stage. Therefore, the results are directly applicable to real-world conditions. However, the time trend of actual evapotranspiration (AET) for individual time intervals fluctuates more than that for growth-stage AETs. The proposed model was run for the Ardak area (45 km NW of the city of Mashhad, Iran) under a single cropping cultivation (corn) as well as a multiple cropping pattern (wheat, barley, corn, and sugar beet). The water balance equation was manipulated with net applied irrigation water to overcome the difficulty encountered with incorrect deep percolation. The outputs of the model, under the imposed seasonal irrigation water shortages, were compared with the results obtained from a simple NLP model. The differences between these two models (simple and integrated) became more significant as irrigation water shortage increased. Oversimplified assumptions in the previous simple model were the main causes of these differences. Copyright © 2004 John Wiley & Sons, Ltd. L'allocation optimale des ressources d'eau disponibles est une réponse partielle au problème de la demande sans cesse croissante de consommation d'eau. Un modèle d'optimisation à programmation non linéaire (NLP) qui intègre un bilan hydrique a été développé. Ce modèle est une version avancée d'un modéle précédent qui n'intégrait pas ce bilan hydrique. Il présente l'avantage de nécessiter moins de puissance informatique en comparaison des modèles à programmation dynamique (DP) généralement utilisés. Le modèle peut s'appliquer à différentes étapes de la croissance des cultures et prend en compte des fréquences d'irrigation variables. Ainsi, les résultats sont directement applicables aux conditions réelles. Le modèle proposé a été utilisé sur une seule culture (maïs) dans la région d'Ardak à 45 km nord-ouest de Mashad, Iran, et sur de multiples cultures (blé, orge, maïs, betterave sucrière). L'équation de bilan hydrique a été calibrée pour maîtriser les difficultés rencontrées avec des mesures d'infiltration incorrectes. Les résultats du modèle, dans le cadre de restrictions d'irrigation saisonnière imposées, ont été comparés avec ceux obtenus par un modèle simple NLP. Les différences entre ces deux modèles (simple et intégré) deviennent plus significatives à mesure que les restrictions d'irrigation augmentent. Les hypothèses trop simplistes du modèle simple sont la cause de ces différences. Copyright © 2004 John Wiley & Sons, Ltd." @default.
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• W2106396957 date "2004-01-29" @default.
• W2106396957 modified "2023-09-23" @default.
• W2106396957 title "Linear and non-linear optimization models for allocation of a limited water supply" @default.
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• W2106396957 doi "https://doi.org/10.1002/ird.108" @default.
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