Optimizing Water Allocation under Uncertain System Conditions for Water and Agriculture Future Scenarios  in Alfeios River Basin (Greece)—Part B: Fuzzy-Boundary Intervals Combined with Multi-Stage Stochastic  Programming Model

Oases are vital habitat areas for both humans and wild plants and animals in desert areas of arid Northwestern China. The efficient management of oasis water resources, especially groundwater resources, is very important for the environmental sustainability and economic development of the region. Pumping wells play a vital role in the oasis groundwater supply; therefore, optimizing the layout of these wells is essential for water resource management. In this study, we present a novel optimization methodology that implements a genetic algorithm and nonlinear programming model for the layout of pumping wells. The methodology was tested and evaluated in the real oasis case study of Qira Oasis located in southern Xinjiang Province, China. The optimization result shows that only 68 pumping wells are required for irrigation purposes of Qira Oasis, and this layout reduces the number of current pumping wells strongly by 59%. Thus, a large number of pumping wells can be closed to save resources. The optimizing method presented in this research is mathematically general and can be applied to other oasis areas without any obstacles. This method can provide decision-makers and managers with key information to ensure the optimal management and safety of valuable groundwater resources in oases.

Section: Introductionmentioning

confidence: 99%

A New Optimization Method for the Layout of Pumping Wells in Oases: Application in the Qira Oasis, Northwest China

Liu

Shen

Zhao

et al. 2019

“…The objective problem is structured as in Models (3) and (4). The mathematical formulation of the optimization problem is presented thoroughly in the second paper [44] of this work, which describes and analyzes the FBISP programming method as proposed by [1].…”

Section: Formulation Of the Optimization Problem For The Alfeios Rivementioning

confidence: 99%

Optimizing Water Allocation under Uncertain System Conditions in Alfeios River Basin (Greece), Part A: Two-Stage Stochastic Programming Model with Deterministic Boundary Intervals

Bekri

Disse

Yannopoulos

2015

Self Cite

Abstract:The enactment of the Water Framework Directive, constituting the basis of the European water policy, introduced various challenges and complexities for water resources management. River basins are exposed to a plethora of environmental stresses, resulting in degradation of their quantitative and qualitative status. This led to the reduction of clean available water, increasing competition among water users and imposing the need for optimal water allocation for each river unit. In most countries (including those in the Mediterranean), water resources management is characterized by lack of effective operational strategies combined with the absence of permanent measuring systems and low financial means, hampering the implementation of efficient river monitoring. Therefore, water resources management is indicated by high uncertainty and by imprecise and limited data, which may be easily approximated through estimates of intervals. In the present work, optimal water allocation under uncertain system conditions is undertaken for the Alfeios River Basin (Greece) based on an inexact two-stage stochastic programming methodology developed by Huang and Loucks (2000). It combines ordinary two-stage stochastic programming with uncertainties expressed as deterministic boundary intervals. Stable intervals for optimized water allocation targets and probabilistic water allocation and shortages are estimated under a baseline scenario and four water and agricultural policy future scenarios. OPEN ACCESSWater 2015, 7 5306

“…Models have been developed with the specific goal of aiding water supply decision makers who face complex decisions that require consideration of many different factors. Bekri, et al [20] developed an optimal water allocation optimization model using fuzzy-boundary-interval linear programming methodology. The model adopted the uncertainty of the random water inflows through the simultaneous generation of stochastic equal-probability hydrologic scenarios using various inflow scenarios applied on the Alfeios River Basin (Greece) to enhance the attitude of decision makers.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization Model for Agricultural Reclaimed Water Allocation Using Mixed-Integer Nonlinear Programming

Aljanabi

Mays

Fox

2018

Reclaimed water (RW) is a reliable alternative water supply for irrigation in the agricultural sector, which is the predominant consumer of water in Iraq. A mixed-integer nonlinear programming reclaimed water allocation optimization model was developed to maximize the net benefit generated from the cultivation of different types of crops, comparing the use of reclaimed water type A (tertiary treated water), and reclaimed water type B (secondary treated water). The model was solved using the Algorithms for coNTinuous/Integer Global Optimization of Nonlinear Equations (ANTIGONE) optimizer in the general algebraic modeling system (GAMS). A total of 84 agricultural farms located on 5300 ha to the south of Baghdad, Iraq were available for irrigation with reclaimed water. Analysis considered varying quantities of available reclaimed water and different irrigation efficiencies (45-85%). The net benefits from using lower quantities of reclaimed water were similar for both types of reclaimed water, and the highest net benefit crop was cultivated on 384 ha. As the quantities of water increased, the amount of cultivated land increased and the net benefit per hectare decreased as the model required the cultivation of more crops with lower economic value. Irrigation with reclaimed water has potential to increase agricultural and economic activity adjacent to Baghdad.