Content area

Abstract

This study aims to develop an effective model for reservoir water allocation under conditions of uncertainty. To identify a practical method that increases the benefits by optimizing the water allocation policies while reducing the costs by optimizing the water transfer scheme, several stochastic programming models (EOQ-TSP models) were developed by integrating economic order quantity (EOQ) models into a two-stage stochastic programming (TSP) framework. The EOQ-TSP models are advantageous for analyzing the effects of the water inventory scheme on the reservoir water allocation benefits and better at optimizing water allocation policies while also considering uncertainties regarding different flow levels and different water inventory conditions in a water supply-inventory-demand system. Finally, the feasibility of the developed EOQ-TSP models was demonstrated by applying the models to a real-world case study. The results show that the benefits of the optimal water allocation policy will be further increased by optimizing the water transfer scheme, and these proposed models will be helpful for systematizing reservoir water management and identifying optimal reservoir water allocation plans in uncertain environments.

Details

Title
Inventory Theory-Based Stochastic Optimization for Reservoir Water Allocation
Author
Xu, Yaowen 1 ; Fu, Qiang 1 ; Zhou, Yan 1 ; Li, Mo 1 ; Ji, Yi 1 ; Li, Tianxiao 1 

 School of Water Conservancy & Civil Engineering, Northeast Agricultural University, Harbin, Heilongjiang, People’s Republic of China; Key Laboratory of Efficient Utilization of Agricultural Water Resources of Agriculture Ministry, Northeast Agricultural University, Harbin, Heilongjiang, China 
Pages
3873-3898
Publication year
2019
Publication date
Sep 2019
Publisher
Springer Nature B.V.
ISSN
09204741
e-ISSN
15731650
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2275701186
Copyright
Water Resources Management is a copyright of Springer, (2019). All Rights Reserved.