Fuzzy Optimization Model for Waste Load Allocation in a River with Total Maximum Daily Load (TMDL) Planning

Abstract

In traditional waste load allocation (WLA) decision making, water quality-related constraints must be satisfied. Fuzzy models, however, can be useful for policy makers to make the most reasonable decisions in an ambiguous environment, considering various surrounding environments. We developed a fuzzy WLA model that optimizes the satisfaction level by using fuzzy membership functions and minimizes the water quality management cost for policy decision makers considering given environmental and socioeconomic conditions. The fuzzy optimization problem was formulated using a max–min operator. The fuzzy WLA model was applied to the Yeongsan River basin, which is located in the southwestern part of the Korean Peninsula and Korean TMDLs were applied. The results of the fuzzy model show that the pollutant load reduction should be increased in the Gwangju 1 and Gwangju 2 wastewater treatment plants (WWTPs) and in subcatchments with high pollutant load. In particular, it is necessary to perform advanced wastewater treatment to decrease the load of 932 kg ultimate biochemical oxygen demand (BODu)/day in the large-capacity Gwangju 1 WWTP and reduce the BODu emission concentration from 4.3 to 2.7 mg/L during the low-flow season. The satisfaction level of the fuzzy model is a relatively high at 0.81.

A new fuzzy approach and bankruptcy theory in risk estimation in Waste Load Allocation

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Groundwater quality for irrigation in an arid region—application of fuzzy logic techniques

“…Indeed, fuzzy logic (FL) techniques are highly used and show a higher capability in capturing complex environmental problems related to groundwater (e.g., McKone and Deshpande 2005;Agoubi et al 2016;Duhalde et al 2018;Tafreshi et al 2018;Jaiswal and Ballal 2020;Jha et al 2020;Arasteh and Farjami 2021;Kord and Arshadi 2022), proving their strength to overcome non-linearity, ambiguity, and uncertainty of environmental issues (Agoubi et al 2016;Tirupathi et al 2019). Moreover, several previous research works have applied and verified the importance of fuzzy logic techniques to converge an ambiguous decision into a state of acceptance (Cho and Lee 2020). Fuzzy logic has ability to convert vagueness, uncertainty, and variability to a mathematical structure and is widely used in groundwater quality evaluation, usually combined with geostatistical tools and GIS approaches (e.g., Ostovari et al 2014;Khashei-Siuki and Sarbazi 2015;Li et al 2018;Jafari and Nikoo 2019;Shwetank and Chaudhary 2019;Jha et al 2020;Pathak and Bhandary 2020).…”