Surface Water Quality Analysis using Fuzzy Logic Approach: A Case of Inter-provincial Irrigation Network in Vietnam

Abstract

Water quality assessment plays an essential role in sustainable management and development of river systems. However, this process is highly complicated that requires professional expertise. The fuzzy water quality index (FWQI) based on fuzzy logic is computational method categorizing water quality into various categories for different water uses. In this study, a method based on fuzzy inference systems (FIS) to assess water quality in the Nhue River, an inter-provincial irrigation network in Northern Vietnam, using fuzzy logic is proposed. Nine fuzzy variables namely dissolved oxygen (DO), biological oxygen demand (BOD5), chemical oxygen demand (COD), pH, ammonium (), phosphates (), total suspended solids (TSS), turbidity, and total coliform (Tco) on the potable quality of the river water are employed for the quality assessment. The fuzzy inference system is composed by 3250 rules with a score from 0 to 100 and five verbal categories. The FWQI was validated by comparison with Vietnam national water quality index. The result of the study clearly shows that the Fuzzy Inference System (FIS) approach was a practical, simple and useful tool to assess surface water quality in river as well as irrigation networks.