Evaluation and optimal redesigning of river water-quality monitoring networks (RWQMN) using geostatistics approach (case study: Karun, Iran)

Water-quality monitoring networks (WQMNs) are principal to planning and management of water resources. However, constructing and maintaining monitoring stations as well as analyzing the acquired data are costly processes. A well-designed network is one that provides the greatest possible amount of data from the fewest number of stations, so that the overall cost of monitoring is reduced. In this study, WQMN sampling locations of the Karun River, in south-western Iran were evaluated by simultaneously applying two geostatistical methods: ordinary kriging (OK) and sequential Gaussian simulation (SGS). In the evaluation, kriging estimations, and their variances and realizations of the concentrations of two main water-quality variables [electrical conductivity (EC) and dissolved oxygen (DO)] were considered. The results showed that the system of sampling locations should be modified to reach an optimized network. It is necessary to set up stations or increase sampling frequency in some existing stations when adjacent ones are far away or when some polluters exist nearby. The combining of the two techniques (OK and SGS) applied simultaneously was evaluated in this study to evaluate the existing WQMN. The results showed that this process applies to evaluating and optimizing other WQMNs as well.