New Water and Biotic Quality Assessment Indices for a tropical reservoir based on fuzzy logic

Abstract The complexity of evaluating the quality of an aquatic environment with its numerous variables has resulted in several quality indexes to synthesize all information in a single value. However, most of these indexes are based on few environmental variables, losing information from other relevant variables. This article presents a new model capable of representing the quality level of a tropical oligo-mesotrophic reservoir on a numerical scale, considering the subjectivity implicit in the concept of quality, and involving several physical, chemical and biological variables. The proposed model, called "Fuzzy Indices for Water Quality Assessment and Biotics" (FUZZY-WBQAI), is based on fuzzy inference systems, providing a way to deal with the uncertainty between the quality categories. A computational tool was developed, which automatically assesses the quality of water, considering different methodologies that depend on the stratification conditions and the longitudinal zone of the reservoir. The model calculates two indices: one for water quality and one biotic that uses metrics from the fish assembly. The model was effective in revealing the decrease in water quality in summer months with higher temperature and precipitation. The effect of the mixture of the stratified reservoir in winter in decreasing the water quality in an area of fish cultivation was highlighted. The biotic index was sensitive to spatial changes in the environmental quality of the reservoir. The results were considered satisfactory, in agreement with the specialized knowledge, and can provide a rapid diagnosis of water conditions in oligo-mesotrophic reservoirs in the tropics.

摘要 水生环境质量评价涉及诸多变量，其复杂性催生了多种可将多维度信息整合为单一数值的水质指数。然而，绝大多数此类指数仅基于少量环境变量，会丢失其他相关变量所承载的信息。
本文提出一种新型模型，可在数值标度上表征热带贫中营养型水库（tropical oligo-mesotrophic reservoir）的质量等级。该模型兼顾水质概念中隐含的主观性，同时纳入多项物理、化学与生物变量。
所提出的模型命名为“水质与生物评价模糊指数（Fuzzy Indices for Water Quality Assessment and Biotics, FUZZY-WBQAI）”，其基于模糊推理系统，能够有效处理水质分级间的不确定性问题。
本研究开发了一款计算工具，可自动开展水质评价，该工具支持多种适配水库分层状态与纵向区域的评价方法。
该模型可计算两类指数：一类用于水质评价，另一类为生物指数，其采用鱼类群落相关指标。
模型有效揭示了气温与降水量更高的夏季，水库水质出现下降的规律。
研究还凸显了冬季分层水库水体混合作用会导致鱼类养殖区水质下降的效应。
该生物指数对水库环境质量的空间变化具有良好敏感性。
研究结果符合专业领域的既有认知，表现令人满意，可为热带贫中营养型水库的水体状况提供快速诊断依据。