Abstract

Optimal water resource allocation can go some way to overcoming water deficiencies; however, its achievement is complex due to conflicting hierarchies and uncertainties, such as water availability (WA) and water demand (WD). This study develops a robust water withdrawal scheme for drought regions that can balance the trade-offs between the sub-areas and water use participants, ensure sustainable regional system development, and guarantee robust solutions for future uncertainties. A bi-level affinely adjustable robust counterpart (AARC) programming framework was developed in which the regional authority as the leader allocates water to the sub-areas to maximize the intra- and intergenerational equity, and the sub-areas as the followers allocate water to their respective water departments to maximize their economic benefits and minimize water shortages. A case study from Neijiang, China, is given to illustrate the applicability and feasibility of this framework. The novelty of this study is to propose a sustainable bi-level AARC regional water allocation framework which integrates intra- and inter-generational equity of regional water use and priority rules reflected by goal preference programming between water departments under uncertainties of WA and WD simultaneously in water deficient regions.

Highlights

  • Optimal regional water resource allocation has been found to be an effective approach to mitigating regional water scarcity (Dai et al 2018), alleviating the contradictions between limited fresh clean water resources and growing water demand (Tan et al 2010), and ensuring sustainable water resources management (Chen et al 2013)

  • These criteria were chosen for the following reasons: (1) as water resource consumption is positively proportional to the population, population growth inevitably leads to increased water use, and as production and daily life water must be guaranteed, population levels are an appropriate index for balanced resource allocation; (2) socio-economic development cannot be separated from the water resource support that is, no industry can survive without water resources, and the better the development, the greater the demand for water

  • From the regional total economic benefits for the various uncertainty sets shown in Fig. 4, it can be seen that the results were sensitive to fluctuations in water availability (WA) and water demand (WD), with the maximum being 4,733,704 CNY, 653,504 CNY higher than the minimum with a 16% fluctuation

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Summary

Introduction

Optimal regional water resource allocation has been found to be an effective approach to mitigating regional water scarcity (Dai et al 2018), alleviating the contradictions between limited fresh clean water resources and growing water demand (Tan et al 2010), and ensuring sustainable water resources management (Chen et al 2013). Optimal water resources allocation is an extraordinary sophisticated system, especially when it comes to contradictory situations between water supply and demand because there is a hierarchical decision and the need to consider sustainable development, that is, both present and future generations need to be considered. The complexities and uncertainties associated with the hierarchical resource allocation process and the need to ensure sustainability have not always been fully considered when seeking to develop optimal regional water rights allocation schemes in drought-prone regions. The research objectives for this paper are: (i) to conceptualize a bi-level, multi-stage, optimal water resources allocation framework for arid and semi-arid regions; (ii) to construct an adjustable robust optimization management model using affine decision rules that considers the water deficiency uncertainties (WA/WD); and (iii) to apply the bi-level, multi-stage AARC optimization approach to a case study in a drought-prone region of China.

Problem statement
Model Formulation
Upper-level constraints
Lower-level objective
Lower-level constraints
Global optimization model
Problem solutions
Case study
Managerial suggestions
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