Stochastic vs deterministic programming in water management: the value of flexibility

Yousaf Muhammad () and Georg Pflug ()

Annals of Operations Research, 2014, vol. 223, issue 1, 309-328

Abstract: In the paper we develop a two stage scenario-based stochastic programming model for water management in the Indus Basin Irrigation System (IBIS). We present a comparison between the deterministic and scenario-based stochastic programming model. Our model takes stochastic inputs on hydrologic data i.e. inflow and rainfall. We divide the basin into three rainfall zones which overlap on 44 canal commands. Data on crop characteristics are taken on canal command levels. We then use ten-daily and monthly time intervals to analyze the policies. This system has two major reservoirs and a complex network of rivers, canal head works, canals, sub canals and distributaries. All the decisions on hydrologic aspects are governed by irrigation and agricultural development policies. Storage levels are maintained within the minimum and maximum bounds for every time interval according to a power generation policy. The objective function is to maximize the expected revenue from crops production. We discuss the flexibility of two stochastic optimization models with varying time horizon. Copyright Springer Science+Business Media New York 2014

Keywords: Indus Basin Irrigation System; Stochastic modeling in water systems; Water resources management; Stochastic vs deterministic programming (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/s10479-013-1455-8

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