Optimal water allocation and distribution management in irrigation networks under uncertainty by multi‐stage stochastic case study: Irrigation and drainage networks of Maroon^*

Abstract

In the present research the aim was to prepare a spatial and temporal optimization model for allocating irrigation water and cropping pattern in the Maroon irrigation and drainage networks, which are located in the province of Khoozestan, under uncertainty. Hydrometrical data were gathered from the Maroon network station. Meteorological data were prepared from Idenak station in Behbahan City during 2006-2016. Therefore a model was designed and developed to maximize the total gross benefit of the irrigation networks of Maroon. The presented model is capable of adjusting the optimal water distribution among networks, crops and their different growing stages, determining water shortage, allocating surplus water, and the gross benefit under three scenarios of arid, normal and wet years in two sub-models of actual intra-network optimal management and optimal management from the reservoir output to the inside network by applying multi-stage stochastic programming under uncertainty. The findings show the priority of the second sub-model over the first run. In the upper and lower bounds model it was illustrated that the cropping areas were increased by respectively 33 and 19%, and of course the benefit amount had an increase of 67 and 7% in the second sub-model. K E Y W O R D S irrigation water allocation, multi-stage stochastic programming, spatial and temporal optimization, uncertainty Résumé Dans la présente recherche, l'objectif était de préparer un modèle d'optimisation spatiale et temporelle pour l'allocation de l'eau d'irrigation et le modèle de culture dans les réseaux d'irrigation et de drainage de Maroon, qui sont situés dans la province du Khoozestan, sous incertitude. Des données * Gestion optimale de l'allocation et de la distribution de l'eau dans les réseaux d'irrigation en cas d'incertitude par la méthode stochastique à plusieurs niveaux. Étude de cas: réseaux d'irrigation et de drainage de Marun.

Robust programming for basin-level water allocation with uncertain water availability and policy-driven scenario analysis

“…Interval programming [16] Interval numbers [17] Intervals with random boundaries Stochastic programming [18] Probability distributions and fuzzy variables [19] Interval numbers with probability distributions [20] Interval numbers with probability distributions [21] Interval numbers with probability distributions Fuzzy programming [22] Fuzzy sets [23] Fuzzy sets [24] Fuzzy interval sets Deterministic programming - [25] Deterministic parameter - [ 26] Deterministic parameter - [ 27] Deterministic parameter sidering uncertainties, SO requires exact PDFs of uncertain parameters; however, lacked for most cases in practice due to the information barriers. In comparison, a RO problem starts with an uncertainty set, which can be shaped in multiple ways, e.g.…”