Application of acceptance probability method in assessment of groundwater quality monitoring network (Case Study Mashhad aquifer)

Document Type : Technical Note (5 pages)

Authors

1 MSC. Student in Water Engineering Department, University of Birjand, Birjand, Iran.

2 Associate Professor of Sciences and Water Engineering Department, University of Birjand, Birjand, Iran.

3 Assistant Professor of Sciences and Water Engineering Department, University of Birjand, Birjand, Iran.

4 Member Research Staff of the Hydroinformatic Department, East Water and Environmental Research Institute (EWERI), Mashhad, Iran

Abstract

Groundwater is known to be main resources of agricultural ‎A change in groundwater quality due to wrong groundwater withdrawal management may ‎be caused to deteriorate other water resources. Quality assessment and precise monitoring ‎of the groundwater table is of a great importance. so create a proper network for groundwater quality monitoring wells to determine the minimum number of samples saves costs as well. In this research, a ‎method was used based on Kriging concept and probability function of normal distribution ‎to evaluate the performance of Mashhad plain's observatory well. This approach is based on ‎a percentage of region's area criteria with Ap accuracy compliance. first, spatial structure ‎of the sampling well's chlorine concentration was extracted by analyzing them using grid ‎semi-variogram and then observation well network was evaluated using algorithm of the acceptance probability method. The results showed that the performance of the existing network or the acceptance accuracy at the probability of 80 percent to 72/1 percent is obtained. The results also showed that of 80 wells about the analysis, using only 35 wells carefully observed in the probability level service network eighty percent against all existing wells and the remaining wells 45 impact of very little increase in the accuracy of the estimation of the spatial variations of chlorine in the aquifer of Mashhad. As a result by performing optimization by the method described for the current network and with the 45-point displacement or removal, the number 16 proposed points increases the acceptance accuracy from 72/1% to 100%.

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