Waste load allocation for water quality management of a heavily polluted river using linear programming

Abstract

A waste load allocation model using linear programming has been developed for economic water quality management. A modified Qual2e model was used for water quality calculations and transfer coefficients were derived from the calculated water quality. This allocation model was applied to the heavily polluted Gyungan River, located in South Korea. For water quality management of the river, two scenarios were proposed. Scenario 1 proposed to minimise the total waste load reduction in the river basin. Scenario 2 proposed to minimise waste load reduction considering regional equity. Waste loads, which have to be reduced at each sub-basin and WWTP, were determined to meet the water quality goal of the river. Application results of the allocation model indicate that advanced treatment is required for most of the existing WWTPs in the river basin and construction of new WWTPs and capacity expansion of existing plants are necessary. Distribution characteristics of pollution sources and pollutant loads in the river basin was analysed using Arc/View GIS.

A river water quality management model for optimising regional wastewater treatment using a genetic algorithm

“…Because the transfer coefficient is calculated linearly as the water quality response in the river resulting from the release of pollution loads, it cannot properly represent the non-linearity of water quality calculations in the water quality model and the water quality calculation itself is incorrect. A recent study by Cho et al (2002) illustrated this fact. In that study, a WQMM was developed using a transfer coefficient and linear programming; the transfer coefficient was also calculated from the Qual2e model.…”

A Review of Water Quality Optimisation Models and Techniques

“…The developed model was applied to Senator Nilo Coelho Project in Brazil. [4] developed a waste load allocation LP model for economic water quality management. [5] developed an inexact chance-constrained linear programming (ICCLP) model for optimal water pollution management at the watershed scale.…”

“…They developed two ensemble learning techniques specifically for dealing with imbalanced data, where the base learners are trained by adjusting the ratio between the classes. Their first algorithm focused on oversampling the minority class, while the second focused on under-sampling the For economic water quality management Heavily Polluted Gyungan River in South Korea [4] For optimal water pollution management Lake Qionghai Watershed in China [5] Integer Programming For ground-water remediation Wells [6] Nonlinear Programming For stream water quality management Changsha section of Xiangjiang River [7] For water quality management Unspecified [8] For synthesis and optimisation of water treatment processes…”

Waste Load Allocation Method for Total Maximum Daily Load Program of a Polluted River

“…The water quality variations at Yeongbon A, Yeongbon B, and Whangyong A according to the level of pollution load abatement in each subbasin of the target points were assessed through the transfer coefficient (Bishop and Grenny, 1976;Burn, 1989;Cho et al, 2003). The constraints of the optimization problem were constructed using the transfer coefficient to reach the water quality goal.…”