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

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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.

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Acknowledgements

We are greatly thankful to Dalia Bach from the University of Columbia, who helped us a lot to improve this paper. Thanks to referee for his value suggestions.

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Authors and Affiliations

  1. Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan

    Yousaf Shad Muhammad

  2. University of Vienna, Universität Strasse 5/3, 1010, Wien, Austria

    Georg C. Pflug

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  1. Yousaf Shad Muhammad
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  2. Georg C. Pflug
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Correspondence to Yousaf Shad Muhammad.

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This research work is sponsored by Higher Education Commission (HEC), Pakistan.

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Muhammad, Y.S., Pflug, G.C. Stochastic vs deterministic programming in water management: the value of flexibility. Ann Oper Res 223, 309–328 (2014). https://doi.org/10.1007/s10479-013-1455-8

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