Improving Performance Criteria in the Water Resource Systems Based on Fuzzy Approach

Reliability, resilience, and vulnerability (RRV) have been widely used as the performance criteria of a water supply system in the studies conducted over the last three decades. This study attempts to modify the traditional method commonly applied to estimate these criteria using fuzzy logic thereby the performance criteria of the points with the threshold and intermediate values are more accurately estimated. Traditional methods (RRV-Fixed) of estimating these criteria are based on the fixed threshold values to represent the functionality of a water supply system, using a binary system to identify the periods a system fails to supply the water demands. The employment of this binary system may be taken into account as a weakness of the evaluating system, especially when water portion met is close to the threshold values. The present study develops a new method named RRV-Fuzzy, to ameliorate the weaknesses of the traditional RRV-Fixed estimating system.The method is designated as Fuzzy Performance Criteria built upon the traditional RRV formulae with improvements made to their structures using fuzzy membership functions. The efficiency of the proposed method is verified via implementation on two case studies including a theoretical and a real-world water basin. A comparison of the proposed RRV-Fuzzy and the traditional RRV-Fixed methods confirms the efficiency of the proposed method with regard to the improvements achieved in the relevant estimations, validating the new approach to be quite effective and practicable.

Automated summary

Reliability, resilience, and vulnerability (RRV) are commonly used as performance criteria for water supply systems. This study introduced a new method named RRV-Fuzzy, which improved upon the weaknesses of the traditional RRV-Fixed estimating system by incorporating fuzzy logic and fuzzy membership functions to more accurately estimate system performance criteria. The proposed method was tested on theoretical and real-world case studies, demonstrating its efficiency and effectiveness in improving relevant estimations.