An interval multistage water allocation model for crop different growth stages under inputs uncertainty

Chen, Shu; Shao, Dongguo; Gu, W; Xu, Baoli; Li, Haoxin; Fang, Longzhang

doi:10.1016/j.agwat.2017.03.001

Cited by 25 publications

(6 citation statements)

References 46 publications

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“…The problem is compounded by the fact that instances of lower than average water supply often coincide with higher than average need for irrigation. A wide range of mathematical programming techniques have been applied, individually and in combination, to support irrigation planning including multistage stochastic programming (28% of articles on irrigation in the sample including [34,54,173]), stochastic dynamic programming (25% of articles on irrigation in the sample including [12,22,158]), inexact programming, including fuzzy and interval-based programming, (36% of articles on irrigation in the sample, for example [35,105,152]) and nonlinear programming (14% of articles on irrigation in the sample including [10,25]). The problem has been studied at various levels ranging from the farm level [22,83,92] to the level of a large water system or country [107,144,221].…”

Section: Agricultural Irrigationmentioning

confidence: 99%

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: Agricultural Irrigationmentioning

confidence: 99%

Review of Mathematical Programming Applications in Water Resource Management Under Uncertainty

Archibald

Marshall

2018

Environ Model Assess

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“…A broad description shows China as the country with the most agricultural water allocation research, probably due to the resource scarcity and the high demand from users in the region [15]. Environmental sciences, engineering, and agricultural sciences comprise the main subareas, grouping 66% of the works.…”

Section: Resultsmentioning

confidence: 99%

Multistage Stochastic Programming to Support Water Allocation Decision-Making Process in Agriculture: A Literature Review

Marquez

Sarmiento

Lamos

2022

The 1st International Online Conference on Agriculture—Advances in Agricultural Science and Technology

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“…• Multistage stochastic programming: Some studies use this method. For example, the work in [21] developed an interval multistage water allocation model to optimize water allocation between different growth stages to obtain the maximum food production in reservoir irrigation systems characterized by inputs' uncertainties. The study developed by [22] considered a fuzzy probability distribution based multistage stochastic robust programming method.…”

Section: Mathematical Programming Modelling Applied To Water Systems:mentioning

confidence: 99%

Solution Approaches for the Management of the Water Resources in Irrigation Water Systems with Fuzzy Costs

Sanchís

Díaz‐Madroñero

Jiménez

et al. 2019

Water

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Currently, the management of water networks is key to increase their sustainability. This fact implies that water managers have to develop tools that ease the decision-making process in order to improve the efficiency of irrigation networks, as well as their exploitation costs. The present research proposes a mathematical programming model to optimize the selection of the water sources and the volume over time in water networks, minimizing the operation costs as a function of the water demand and the reservoir capacity. The model, which is based on fuzzy methods, improves the evaluation performed by water managers when they have to decide about the acquisition of the water resources under uncertain costs. Different fuzzy solution approaches have been applied and assessed in terms of model complexity and computational efficiency, showing the solution accomplished for each one. A comparison between different methods was applied in a real water network, reaching a 20% total cost reduction for the best solution.

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An interval multistage water allocation model for crop different growth stages under inputs uncertainty

Cited by 25 publications

References 46 publications

Review of Mathematical Programming Applications in Water Resource Management Under Uncertainty

Review of Mathematical Programming Applications in Water Resource Management Under Uncertainty

Multistage Stochastic Programming to Support Water Allocation Decision-Making Process in Agriculture: A Literature Review

Solution Approaches for the Management of the Water Resources in Irrigation Water Systems with Fuzzy Costs

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