Planning an Agricultural Water Resources Management System: A Two-Stage Stochastic Fractional Programming Model

Cui, Liang; Li, Yongping; Huang, Guohe

doi:10.3390/su7089846

Cited by 16 publications

(10 citation statements)

References 26 publications

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“…There is a need for efficient and sustainable water allocations to support economic development. Fractional programming has been proposed as a method for striking a compromise between the conflicting goals of maximising the benefit from the exploitation of water resources and sustainable water resource management [38,108,171,172].…”

Section: Water Allocationmentioning

confidence: 99%

“…Li et al [108] also consider the ratio of the benefit from water use and water shortages (for example, for domestic and environmental uses). Cui et al [38] apply fractional programming to the management of water for agricultural uses in the Zhangweinan River Basin, China. They argue that the model provides insight on the trade-off between the economic benefits and system reliability, which helps to support sustainable water resource management.…”

Section: Water Allocationmentioning

confidence: 99%

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Review of Mathematical Programming Applications in Water Resource Management Under Uncertainty

Archibald

Marshall

2018

Environ Model Assess

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Economic development, variation in weather patterns and natural disasters focus attention on the management of water resources. This paper reviews the literature on the development of mathematical programming models for water resource management under uncertainty between 2010 and 2017. A systematic search of the academic literature identified 448 journal articles on water resource management for examination. Bibliometric analysis is employed to investigate the methods that researchers are currently using to address this problem and to identify recent trends in research in the area. The research reveals that stochastic dynamic programming and multistage stochastic programming are the methods most commonly applied. Water resource allocation, climate change, water quality and agricultural irrigation are amongst the most frequently discussed topics in the literature. A more detailed examination of the literature on each of these topics is included. The findings suggest that there is a need for mathematical programming models of large-scale water systems that deal with uncertainty and multiobjectives in an effective and computationally efficient way.

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Section: Water Allocationmentioning

confidence: 99%

Section: Water Allocationmentioning

confidence: 99%

Review of Mathematical Programming Applications in Water Resource Management Under Uncertainty

Archibald

Marshall

2018

Environ Model Assess

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show abstract

“…This forecast estimates the f surface water available in the future for CPSO. tradeoff between predefined strategies and the associated adaptive adjustments [27] . The TSP model can correct the decision in the first stage through making the decision in the second stage after the random event happened in order to reduce the decision risk and obtain the best compromise schemes [28,29] .…”

Section: Runoff Predictionmentioning

confidence: 99%

Integrated uncertain models for runoff forecasting and crop planting structure optimization of the Shiyang River Basin, north-west China

Zhang

Guo

et al. 2018

Front. Agr. Sci. Eng.

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To improve the accuracy of runoff forecasting, an uncertain multiple linear regression (UMLR) model is presented in this study. The proposed model avoids the transfer of random error generated in the independent variable to the dependent variable, as this affects prediction accuracy. On this basis, an inexact two-stage stochastic programming (ITSP) model is used for crop planting structure optimization (CPSO) with the inputs that are interval flow values under different probabilities obtained from the UMLR model. The developed system, in which the UMLR model for runoff forecasting and the ITSP model for crop planting structure optimization are integrated, is applied to a real case study. The aim of the developed system is to optimize crops planting area with limited available water resources base on the downstream runoff forecasting in order to obtain the maximum system benefit in the future. The solution obtained can demonstrate the feasibility and suitability of the developed system, and help decision makers to identify reasonable crop planting structure under multiple uncertainties.

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“…The past reviews on optimization models are mainly focused on the following sections: irrigation management, crop pattern adjustment, and water resource allocation, etc. [13,14]. The past studies on water resource allocation mainly concentrate on water distribution during crop growth or water distribution among different crops.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Water Consumption Distribution Based on Crop Suitability in the Middle Reaches of Heihe River

Wang

Peng

et al. 2018

Sustainability

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Optimizing regional crop water consumption is considered to be a significant approach for increasing yields and reducing water consumption. This paper proposes a single-objective linear programming model which couples the distributed water consumption model with crop suitability. The impacts of meteorological, topographic, and soil factors were taken into account in both the distributed water consumption model and the crop suitability. The developed model was applied to a real case study in the middle reaches of Heihe River basin, in the northwest of China. In the optimization model, the net benefit which combined the water consumption with crop suitability was regarded as the objective function, while the limits on available water and planting area were set as the constraints. Optimal results regarding crop distribution and water consumption were generated for dry, normal, and wet hydrological years. Two optimization strategies were analyzed, including one with a fixed area of each crop and the other with a fixed total planting area. Economic analyses showed that net income under both optimization strategies increased by 31% and 33%, respectively. Although water consumption increased slightly in both optimization scenarios, the unit water income and unit area income were much higher than in the pre-optimization conditions. The obtained results are valuable for supporting the adjustment of planting patterns and the identification of desired plans for sustainable irrigation water allocation.

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Planning an Agricultural Water Resources Management System: A Two-Stage Stochastic Fractional Programming Model

Cited by 16 publications

References 26 publications

Review of Mathematical Programming Applications in Water Resource Management Under Uncertainty

Review of Mathematical Programming Applications in Water Resource Management Under Uncertainty

Integrated uncertain models for runoff forecasting and crop planting structure optimization of the Shiyang River Basin, north-west China

Optimization of Water Consumption Distribution Based on Crop Suitability in the Middle Reaches of Heihe River

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