Related Experiment Video
Updated: Jul 7, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
River water quality management using an integrated multi-objective optimization-simulation approach based on
Omid Babamiri1, Yagob Dinpashoh2
1Department of Water Engineering, University of Tabriz, Tabriz, Iran. babamiri@tabrizu.ac.ir.
Abstract:
The aim of this research is to allocate the river's self-purification (acceptance capacity of pollution) fairly between the beneficiaries (pollutant sources) using bankruptcy theory. For this purpose, four bankruptcy rules (CAE, CEL, P, and TAL) were called using the link of the water quality simulation model (QULA2Kw) to an evolutionary optimization algorithm (multi-objective imperialist competition algorithm (MOICA)). The objective functions were reducing polluters' wastewater treatment costs and preventing biochemical oxygen demand (BOD) violations of the standard level along the river. The applicability of the approach is demonstrated by the case study that was carried out on the Dez River in Iran. According to the results, the CEL scenario is the most effective method for the Dez River when taking into account the most optimal state for both objective functions (selecting the best compromise solution from the Pareto front). This is because it has the lowest violation value of the standard level for BOD along the river when compared to other scenarios. Alternatively, when considering Solution 20, which focuses on the maximum cost of treating the polluters while staying within the acceptable level of pollution in the river, the results indicated that the CEA rule emerged as the most favorable option. This is due to its lower treatment cost (156.9 (1000$)) and higher pollution discharge to the river (681.91 g/s).
Related Concept Videos
Design Example: Analyzing Capacity Contours for Flood Risk Assessment
Typical Model Studies
Modeling and Similitude
Rapidly Varying Flow
Gradually Varying Flow
Design Example: Creating a Hydraulic Model of a Dam Spillway

