Journal
JOURNAL OF HYDROLOGY
Volume 558, Issue -, Pages 328-340Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jhydrol.2018.01.011
Keywords
Spatio-temporal optimization; Water quality monitoring network; Reservoir; Value of information theory; Entropy theory; Evidential Reasoning method
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This paper presents a new methodology for optimizing Water Quality Monitoring (WQM) networks of reservoirs and lakes using the concept of the value of information (VOI) and utilizing results of a calibrated numerical water quality simulation model. With reference to the value of information theory, water quality of every checkpoint with a specific prior probability differs in time. After analyzing water quality samples taken from potential monitoring points, the posterior probabilities are updated using the Baye's theorem, and VOI of the samples is calculated. In the next step, the stations with maximum VOI is selected as optimal stations. This process is repeated for each sampling interval to obtain optimal monitoring network locations for each interval. The results of the proposed VOl-based methodology is compared with those obtained using an entropy theoretic approach. As the results of the two methodologies would be partially different, in the next step, the results are combined using a weighting method. Finally, the optimal sampling interval and location of WQM stations are chosen using the Evidential Reasoning (ER) decision making method. The efficiency and applicability of the methodology are evaluated using available water quantity and quality data of the Karkheh Reservoir in the southwestern part of Iran. (C) 2018 Elsevier B.V. All rights reserved.
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