Spatial Assessment of Groundwater Quality Monitoring Wells Using Indicator Kriging and Risk Mapping, Amol-Babol  Plain, Iran

Narany, Tahoora Sheikhy; Ramli, Mohammad Firuz; Aris, Ahmad Zaharin; Sulaiman, Wan Nor Azmin; Fakharian, Kazem

doi:10.3390/w6010068

Cited by 47 publications

(12 citation statements)

References 32 publications

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“…Due to the high cost of sampling in ocean, an optimization method is needed to improve the efficiency of the outdated monitoring network with a limited number of sites. Because the movement and transfer mechanisms within marine environments are not entirely clear, statistical methods are often used to optimize marine environmental monitoring networks (Lin and Rouhani 2001, Shen and Wu 2013, Sheikhy Narany et al 2013. In space-time sampling, Gruijter et al (2006) distinguished several basic design types, including static, independent synchronous, static-synchronous, supplemented panel, and serially alternating.…”

Section: Introductionmentioning

confidence: 99%

A stratified optimization method for a multivariate marine environmental monitoring network in the Yangtze River estuary and its adjacent sea

Gao

Wang

Fan

et al. 2015

International Journal of Geographical Information Science

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An efficient monitoring network is very important in accessing the marine environmental quality and its protection and management. In an estuary, there are fronts that separate distinctly different water masses and affect material transport, nutrient distribution, pollutant aggregation, and diffusion. This stratified heterogeneous surface neither satisfies the stationary requirements of kriging, nor can be handled adequately by removing a spatially continuous trend. This article presents a stratified optimization method for a multivariate monitoring network. In this method, principal component analysis (PCA) was used to reduce the dimensionality of the correlated targets, and the mean of surface with nonhomogeneity (MSN) method was adopted to produce the best linear unbiased estimator for a spatially stratified heterogeneous surface that failed to satisfy the requirements for a kriging estimate. The existing monitoring network in the Yangtze River estuary and its adjacent sea, which was designed by purposive sampling year ago was optimized as an illustration. The optimization consisted of two steps: reduce the redundant monitoring sites and then optimally add new sites to the remaining sites. After optimization, the inclusion of 51 sites in the monitoring network was found to produce a smaller total estimated error than that of the current network, which has 70 sites; moreover, the use of 55 sites can produce a higher precision of estimation for all three principal components (PCs) than that of the current 70 sites. The results demonstrated that the proposed method is suitable for optimizing environmental monitoring sites that have dominant stratified nonhomogeneity and that involve multiple factors.

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Section: Introductionmentioning

confidence: 99%

A stratified optimization method for a multivariate marine environmental monitoring network in the Yangtze River estuary and its adjacent sea

Gao

Wang

Fan

et al. 2015

International Journal of Geographical Information Science

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“…For the analyzed area, empirical (experimental) variogram was drawn, which presents dependencies between the variance and distance between the sampling points [28]. The obtained experimental variogram is characterized by quite a regular shape, which probably results from the number of the analyzed measuring points.…”

Section: Water Network Infrastructure Variantsmentioning

confidence: 99%

Geostatistical Methods in Water Distribution Network Design - A Case Study

Potyralla

2019

Ecological Chemistry and Engineering S

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Modeling of the loads of water supply networks and their subsequent forecasting is an element necessary for making optimum decisions in the process of planning the development and operation of the water supply networks. The results of this modeling are decisive for the selection of the diameters of the pipelines and their arrangement on the water demand area. This study presents the results of estimation of average values of loads for the selected investment variants. The aim of the article is to present the possibility of simulations and analyses of the geostatistical interpolation methods. Data input in the model regarded the fragment of the real water supply network administered by the Municipal Water and Sewerage Company in Warszawa. Results of the computer analyses for the presented investment variants were related to the operating data of the water supply network and the data on water demand for the years 2014-2017 and 2018-2025. The aim of this paper is to present the advantages of GIS for the water supply systems and to prove that using the appropriate IT system, with provision of proper data processing, may lead to decisions which are optimum in view of the established, often very complex criteria.

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“…Dutta et al (1998) employed the vulnerability index (calculated with the DRASTIC method proposed by Aller et al 1987), industry and stream network coverage, and data of some sampled water quality parameters to suggest different monitoring alternatives, but considered only the parameter with the largest variance in the optimization process. Narany et al (2013) presented a methodology that combines, through a geographic information system, a risk map (calculated from the vulnerability index and land use) and a map of the groundwater nitrate thresholds exceedance probability (obtained with indicator kriging); the highest combined index represents areas in which there is a very strong probability of elevated nitrate concentrations and therefore a higher risk of contamination. The monitoring network was proposed by a visual procedure; the authors concluded that a monitoring network design should consider both the risks and the current state of contamination.…”

Section: Introductionmentioning

confidence: 99%

A Geostatistical Methodology to Evaluate the Performance of Groundwater Quality Monitoring Networks Using a Vulnerability Index

et al. 2015

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A geostatistics-based methodology is proposed to evaluate existing groundwater quality monitoring networks by considering the spatial correlation of various physicochemical parameters and the aquifer vulnerability index simultaneously, using the weighted normalized estimate error variance of all variables as the optimization criterion to be minimized. The DRASTIC method was chosen to determine the vulnerability index. The methodology requires a covariance matrix for each variable that is obtained from a geostatistical analysis of the corresponding data. Each matrix is normalized to give the same initial weight to each parameter, whereas different weights can be specified later during the optimization process, depending on the monitoring goals. The vulnerability index is used in the evaluation to include areas within the aquifer that are highly susceptible to contamination. Two optimization strategies are presented. In the first strategy, the vulnerability index is included as an additional variable during the optimization process and more weight is assigned to this variable than to the others. In the second strategy, the optimization process seeks to minimize the total weighted variance, prioritizing the areas with the highest vulnerability index val-B Hugo Júnez-Ferreira 123 Math Geosci ues. For the estimation, the static Kalman filter, which requires an initial estimate, was chosen and its error covariance matrix for each variable is involved in the evaluation. Employing successive-inclusions optimization, the contribution of each monitoring well in reducing the estimate error variance for all parameters at predefined estimation points is evaluated and those that reduce the variance the most are retained in the optimal monitoring network.

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Spatial Assessment of Groundwater Quality Monitoring Wells Using Indicator Kriging and Risk Mapping, Amol-Babol Plain, Iran

Cited by 47 publications

References 32 publications

A stratified optimization method for a multivariate marine environmental monitoring network in the Yangtze River estuary and its adjacent sea

A stratified optimization method for a multivariate marine environmental monitoring network in the Yangtze River estuary and its adjacent sea

Geostatistical Methods in Water Distribution Network Design - A Case Study

A Geostatistical Methodology to Evaluate the Performance of Groundwater Quality Monitoring Networks Using a Vulnerability Index

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