Risk Aversion Based Inexact Stochastic Dynamic Programming Approach for Water Resources Management Planning under Uncertainty

Zhenfang Liu,Yang Zhou,Gordon Huang,Bin Luo

doi:10.3390/su11246926

Zhenfang Liu, Yang Zhou + Show 2 more

Open Access

https://doi.org/10.3390/su11246926

Copy DOI

Journal: Sustainability	Publication Date: Dec 5, 2019
Citations: 4	License type: CC BY 4.0

Affiliation: Hunan University, Shenzhen University

Abstract

In this study, a dual interval robust stochastic dynamic programming (DIRSDP) method is developed for planning water resources management systems under uncertainty. As an extension of the existing interval stochastic dynamic programming (ISDP) method, DIRSDP can deal with two-stage stochastic programming (TSP)-based planning problems associated with dynamic features, input uncertainties, and multistage concerns. Compared with other optimization methods dealing with uncertainties, the developed DIRSDP method has advantages in addressing uncertainties with complex presentations and reflecting decision makers’ risk-aversion attitudes within its optimization process. Parameters in the DIRSDP model can be represented as probability distributions as well as single and/or dual intervals. Decision makers’ risk-aversion attitudes can be reflected through restricting the deviation of the recourse costs to a tolerance level. Water-allocation plans can then be developed based on the analysis of tradeoffs between the system benefit and solution robustness. The developed method is applied to a case of water resources management planning. The solutions are reasonable, indicating applicability of the developed methodology.

Highlights

Controversial and conflict-laden water allocation issues between competing water users have challenged water resource managers for many decades
Two-stage stochastic programming (TSP) was reported as an effective tool for water resources planning under uncertainty [9,10,11,12,13,14,15,16,17,18]
Solution Method In Model (21)–(27), when water-allocation targets (x ) in stage t − 1 are determined under given expansion options, x in stage t under option k can be approached by the following dual interval robust stochastic programming (DIRSP) submodel: 3. Solution Method In Model (21)–(27), when water-allocation targets in stage t − 1 are determined under given expansion options, xtik in stage t under option k can be approached by the following dual interval robust stochastic programming (DIRSP) submodel: m mn ptjC±ti y±tijk i=1 i=1 j=1 subject to: m i=1 xtik − y±tijk

Summary

Introduction

Controversial and conflict-laden water allocation issues between competing water users (e.g., municipal, industrial, and agricultural) have challenged water resource managers for many decades. An imbalance between increasing consumption from the users and decreasing acquisition of water resources is one of major challenges [1] Such an imbalance will be exacerbated by climate change, population growth, urbanization, environmental contamination, technology development, and other impact factors. These impacts introduce uncertainty into water resources management decision making, leading to potential risks associated with economic losses and eco-environment degradation and thereby moving backwards sustainable development [2]. In the abovementioned TSP approaches, the total expected value of the second-stage costs (e.g., economic penalties or recourse costs) is measured without considering and controlling the variabilities of the costs under different possible water-delivery scenarios. S. et al [20] introduced a concept of upper partial mean (UPM) as a new measure of the variability of the cost

Objectives

Methods

Conclusion