Revising river water quality monitoring networks using discrete entropy theory: the Jajrood River experience

Abstract

This paper aims at evaluating and revising the spatial and temporal sampling frequencies of the water quality monitoring system of the Jajrood River in the Northern part of Tehran, Iran. This important river system supplies 23% of domestic water demand of the Tehran metropolitan area with population of more than 10 million people. In the proposed methodology, by developing a model for calculating a discrete version of pair-wise spatial information transfer indices (SITIs) for each pair of potential monitoring stations, the pair-wise SITI matrices for all water quality variables are formed. Also, using a similar model, the discrete temporal information transfer indices (TITIs) using the data of the existing monitoring stations are calculated. Then, the curves of the pair-wise SITI versus distance between monitoring stations and TITI versus time lags for all water quality variables are derived. Then, using a group pair-wise comparison matrix, the relative weights of the water quality variables are calculated. In this paper, a micro-genetic-algorithm-based optimization model with the objective of minimizing a weighted average spatial and temporal ITI is developed and for a pre-defined total number of stations, the best combination of monitoring stations is selected. The results show that the existing monitoring system of the Jajrood River should be partially strengthened and in some cases the sampling frequencies should be increased. Based on the results, the proposed approach can be used as an effective tool for evaluating, revising, or redesigning the existing river water quality monitoring systems.

Spatial sampling on streams: principles for inference on aquatic networks

“…Efficient management and monitoring of natural resources requires informative data (Mahjouri and Kerachian, 2011), with inferences for spatial data affected substantially by the spatial configuration of sampled sites (Zimmerman, 2006); hence, a common issue in spatial statistics is how to choose an "optimal" set of sample locations (Zhu and Stein, 2006). Optimality for spatial sampling designs depends on the characteristics of the target spatial domain and intended inference.…”

Entropy Applications to Water Monitoring Network Design: A Review

“…Several water quality monitoring strategies, including two methods that utilized entropy measures [42,45], were recently reviewed by Behmel et al [15]. This review found that identifying a single approach to water quality monitoring network design would be virtually impossible.…”

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A probabilistic water quality index for river water quality assessment: a case study

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