Hybrid fuzzy multi-criteria decision making to solve the irrigation water allocation problem in the Tunisian case

2019 ◽  
Vol 176 ◽  
pp. 102644 ◽  
Author(s):  
Mohamed Ali Elleuch ◽  
Makram Anane ◽  
Jalel Euchi ◽  
Ahmed Frikha
Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 125
Author(s):  
Sintayehu Legesse Gebre ◽  
Dirk Cattrysse ◽  
Jos Van Orshoven

The water allocation problem is complex and requires a combination of regulations, policies, and mechanisms to support water management to minimize the risk of shortage among competing users. This paper compiles the application of multi-criteria decision-making (MCDM) related to water allocation. In this regard, this paper aims to identify and to discern the pattern, distribution of study regions, water problem classifications, and decision techniques application for a specific water allocation problem. We applied a systematic literature review study from 2000 to 2019 by using four literature databases (Web of Science, Scopus, Science Direct, and Google Scholar). From 109 papers, 49 publications have been identified and information extracted. This study reveals that in the past two decades the application of MCDM in the area of water allocation has increased particularly after 2014. Around 65% and 12% of study papers were conducted in Asia and Europe, respectively. Water shortage, water use management, and water quality were consecutively the most top-ranked discussed water problems. NSGA II (non-dominated sorting genetic algorithm), GA (genetic algorithm), and LP (linear programming) are the more often applied decision methods to solve water allocation problems. The key findings of this study provide guidelines for future research studies.


Water ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 1031 ◽  
Author(s):  
Zehao Yan ◽  
Mo Li

Agricultural water scarcity is a global problem and this reinforces the need for optimal allocation of irrigation water resources. However, decision makers are challenged by the complexity of fluctuating stream condition and irrigation quota as well as the dynamic changes of the field water cycle process, which make optimal allocation more complex. A two-stage chance-constrained programming model with random parameters in the left- and right-hand sides of constraints considering field water cycle process has been developed for agricultural irrigation water allocation. The model is capable of generating reasonable irrigation allocation strategies considering water transformation among crop evapotranspiration, precipitation, irrigation, soil water content, and deep percolation. Moreover, it can deal with randomness in both the right-hand side and the left-hand side of constraints to generate schemes under different flow levels and constraint-violation risk levels, which are informative for decision makers. The Yingke irrigation district in the middle reaches of the Heihe River basin, northwest China, was used to test the developed model. Tradeoffs among different crops in different time periods under different flow levels, and dynamic changes of soil moisture and deep percolation were analyzed. Scenarios with different violating probabilities were conducted to gain insight into the sensitivity of irrigation water allocation strategies on water supply and irrigation quota. The performed analysis indicated that the proposed model can efficiently optimize agricultural irrigation water for an irrigation district with water scarcity in a stochastic environment.


Water ◽  
2016 ◽  
Vol 8 (6) ◽  
pp. 251 ◽  
Author(s):  
Haoxin Li ◽  
Dongguo Shao ◽  
Baoli Xu ◽  
Shu Chen ◽  
Wenquan Gu ◽  
...  

2012 ◽  
Vol 26 (5) ◽  
pp. 1183-1200 ◽  
Author(s):  
Lei Jin ◽  
Guohe Huang ◽  
Yurui Fan ◽  
Xianghui Nie ◽  
Guanhui Cheng

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