Extraction and Preference Ordering of Multireservoir Water Supply Rules in Dry Years

Abstract

This paper presents a new methodology of combined use of the nondominated sorting genetic algorithm II (NSGA-II) and the approach of successive elimination of alternatives based on order and degree of efficiency (SEABODE) in identifying the most preferred multireservoir water supply rules in dry years. First, the suggested operation rules consists of a two-point type time-varying hedging policy for a single reservoir and a simple proportional allocation policy of common water demand between two parallel reservoirs. Then, the NSGA-II is employed to derive enough noninferior operation rules (design alternatives) in terms of two conflicting objectives (1) minimizing the total deficit ratio (TDR) of all demands of the entire system in operation horizon, and (2) minimizing the maximum deficit ratio (MDR) of water supply in a single period. Next, the SEABODE, a multicriteria decision making (MCDM) procedure, is applied to further eliminate alternatives based on the concept of efficiency of order k with degree p. In SEABODE, the reservoir performance indices and water shortage indices are selected as evaluation criteria for preference ordering among the design alternatives obtained by NSGA-II. The proposed methodology was tested on a regional water supply system with three reservoirs located in the Jialing River, China, where the results demonstrate its applicability and merits.

Extraction of Urban Water Bodies from High-Resolution Remote-Sensing Imagery Using Deep Learning

“…Step 3. According to Equations (14) and (16), the sum of β t (i, j) and α t (i, j) is calculated and the iteration begins.…”

“…Image classification methods such as supervised or machine learning are often used to extract water bodies from remote-sensing images [14]. Generally, machine-learning methods include neural network and support vector machine, and unsupervised classification methods include k-means clustering and ISODATA clustering methods [15,16]. The above algorithms are mainly used on low spatial resolution remote-sensing images.…”

Reservoir Operation Policy based on Joint Hedging Rules

“…To minimize the impact of drought and the consequent shortages in current and future water supply, the hedging rules are used to balance the shortage in water supply with the storage target [7,8]. As the relationship between the damage and the shortage is nonlinear, by reducing the supply of reservoir when supply capacity is small [9], HR can store some water in the reservoir for future usage and reduce the possibility of large shortage damage from water shortage in future [10][11][12]. HR and SOP are shown in Figure 1.…”

Research on Hedging Rules Based on Water Supply Priority and Benefit Loss of Water Shortage—A Case Study of Tianjin, China

“…For optimum operations, several rules as well as many simulations and optimization models have been presented, such as real option model, linear decision rule, pack rule, space rule, standard operation policy (SOP), hedging rules (HR) and so on. The SOP is the most common water supply strategy for reservoirs that meet water demand [1]. To fully meet the water demand at present, the SOP saves excess water until abandonment occurs.…”