Ground-water Quality Monitoring Wells Research Articles

A drought index based on groundwater quantity and quality: Application of multivariate copula analysis

In this paper, a new Groundwater Quantity-Quality-based Drought Index (GQQI) is developed based on multivariate Copula analysis of groundwater quantity and quality indicators. For evaluating the developed index, its temporal and spatial distribution is studied and compared to those of some other indices, such as Standardized Salinity Index (SSI), Standardized Groundwater Index (SGI), and Standardized Water level Index (SWI). The proposed index is applied for the temporal and spatial evaluation of the quantity and quality of groundwater in theLake Urmia basin, having 1084 piezometric and 935 groundwater quality monitoring wells. For a more comprehensive analysis of drought, 24 marginal and 26 joint probability distribution functions are driven. Based on the results, the developed GQQI is correlated with drought indices of SSI, SGI, and SWI by 88%, 86%, and 61%, respectively. Moreover, the values of the developed drought index indicates the occurrence of more severe droughts, compared to those detected by other drought indices. This can be resulted from considering the combined effects of groundwater quantity and quality using the proposed index. In addition, the multivariate GQQI can spatially and temporally represent the drought severity over the basin, and identify severe and extreme drought conditions better than other univariate drought indices.

Susceptibility Prediction of Groundwater Hardness Using Ensemble Machine Learning Models

Groundwater resources, unlike surface water, are more vulnerable to disturbances and contaminations, as they take a very long time and significant cost to recover. So, predictive modeling and prevention strategies can empower policymakers for efficient groundwater governance through informed decisions and recommendations. Due to the importance of groundwater quality modeling, the hardness susceptibility mapping using machine learning (ML) models has not been explored. For the first time, the current research aimed to predict groundwater hardness susceptibility using the ML models. The performance of two ensemble models of boosted regression trees (BRT) and random forest (RF) is investigated through the arrangement of a comparative study with multivariate discriminant analysis (MDA). According to the hardness values in 135 groundwater quality monitoring wells, the hard and soft water are determined; then, 11 predictor variables including distance from the sea (DFS), land use, elevation, distance from the river (DFR), depth to groundwater (DTGW), pH, precipitation (PCP), evaporation (E), groundwater level (GWL), curvature, and lithology are used for predicting the groundwater hardness susceptibility map. Results indicated that the variables of DFR, DTGW, elevation, and DFS had a higher contribution to the modeling process. So, the high harness areas are mostly related to low elevations, low DTGW, and proximity to river and sea, which facilitate the percolation conditions for minerals containing calcium or magnesium into groundwater.

Unexpected nationwide nitrate declines in groundwater of Korea

AbstractElevated levels of nitrate in groundwater are an important concern for health and the environment. The overapplication of nitrogen fertilizer to croplands is one of the major sources of high nitrate content in groundwater. In this study, we analyse the nitrate concentrations in Korean groundwater based on data from groundwater quality monitoring wells (n = 1,022–2,072), which were sampled twice annually over a recent 13‐year analysis period (2001–2013). We report that groundwater nitrate levels are decreasing, despite steadily increasing groundwater use. The maximum nitrate concentration decreased from 168.91 to 48.11 mg/L, whereas the mean values also show a gradual decreasing trend. Non‐parametric Mann–Kendall tests on nitrate concentrations also confirm the decreasing trend. The nitrate decrease is more clearly evident in agricultural groundwater as compared to domestic and drinking groundwaters. This decrease of nitrate in groundwater coincides with a large decline in nitrogen fertilizer application due to reduced cropland areas, more sustainable agricultural practices, and progressive improvement of sewage disposal services. This study proposes that the long‐term adoption of best practices in agriculture has had a positive impact on groundwater nitrate control.

Role of groundwater protection planning in groundwater governance: A case study from North India

In the present case study, impact of urbanization and industrial development on the shallow groundwater regime of Saharanpur town of Uttar Pradesh in India is examined with the aim of planning groundwater protection for better governance. The hazardous physicochemical and bacteriological parameters and heavy metals detected in the shallow aquifer include harmful pathogens like fecal coliforms, heavy metals like cadmium, chromium, nitrates and sulphates. An assessment of ground water vulnerability using the well known DRASTIC method has confirmed that the shallow groundwater in some central and southern localities of Saharanpur town fall in the medium risk zones. Further, using field data of 32 electrical resistivity soundings, the protective capacity of the unconfined aquifer is assessed in terms of a ‘total longitudinal conductance’ of the semi-pervious to impervious sediments overlying the unconfined aquifer. However, some areas aligned along a northwest-southeast and in the western parts of the town seem to have relatively higher protective capacity against infiltrating waste pollutants. A ground water protection planning map prepared by combining the DRASTIC map and the ‘potentially hazardous pollutants’ map has brought out the need to install eleven new groundwater quality monitoring wells in the town at locations near the line sources and point sources of pollution. This approach can be readily employed by the decision makers in framing sound guidelines for groundwater protection and governance.

Hydrochemical Research of Groundwater for Irrigation Purpose in North-Western Zone, Bangladesh

The suitability of groundwater for irrigation is reliant upon the effect of different component dissolved in groundwater. The standard limits of the different components (major cations and anions, trace elements) within groundwater for irrigation vary locally. A baseline study involving analysis of five groundwater quality monitoring wells in the North-Western zone of Bangladesh was carried out in order to evaluate their suitability for agricultural purposes. From these monitoring different parameters of groundwater from 1973 to 1996 were found. In addition, groundwater quality data of different depth of 20 Deep Tube wells within the study area are also collected to know the existing condition of groundwater quality. Water samples from the wells are accumulated and scrutinized for pH, Electrical Conductivity (EC), Total Dissolved Solids (TDS), Na<SUP>+</SUP>, K<SUP>+</SUP>, Ca<SUP>2+</SUP>, Mg<SUP>2+</SUP>, HCO<SUB>3</SUB><SUP>-</SUP>, Cl<SUP>-</SUP>, SO4<SUP>2-</SUP> and Sodium Adsorption Ratio (SAR).

토양측정망 운영목적에 따른 토양측정망 지점 선정 방안 연구

This study developed the classification of National Soil Quality Monitoring Network (NSQM) and its site selection criteria to meet the recently established purposes of the NSQM. The NSQM were suggested by this study to classify into the sixpurposes site groups from the current classification of land uses. The six purposes site groups were 1) intensive observation sites, 2) contaminant loading sites, 3) human activity sites, 4) background sites, 5) river soil sites, and 6) sites near the groundwater quality monitoring wells. Furthermore, this study developed the site selection criteria of NSQM utilizing the accumulated NSQM data, road traffic data, chemical emission data, census, soil information, and the literature related to soil quality variation due to contaminant loads. For selecting suitable sites for NSQM, this study used road traffic, chemical emission, the distance from the contaminant sources, and population information as specific criteria. The suggested site classification and criteria were appled for the current 100 NSQM sites for evaluation. Forty sites were met to the criteria suggested by this study, but sixty sites were not met to the criteria. However, some of the sixty sites also included the obscure sites that their addresses were not apparent to find them.

Entropy and Multi-Objective Based Approach for Groundwater Quality Monitoring Network Assessment and Redesign

Selection of the number and location of groundwater quality monitoring wells may require the consideration of different aspects such as: monitoring objectives, temporal frequency of monitoring, and monitoring costs. These aspects were examined using observations of groundwater quality variables made twice a year in 124 wells in the northern part of the Gaza Strip, where groundwater is of the best quality. Considering these features the groundwater quality monitoring network was assessed and redesigned using entropy. The assessment procedure was based on expressing transinformation as a function of distance between wells. It was found that the number and location of groundwater quality monitoring wells varied if these aspects were embedded in the assessment and redesign procedure.

Spatial assessment and redesign of a groundwater quality monitoring network using entropy theory, Gaza Strip, Palestine

Using entropy theory, a methodology was developed for the evaluation and redesign of groundwater quality monitoring wells in the Gaza Strip in Palestine. Essential to the methodology is the development of a Transinformation Model (TM) which yields the amount of information transfer and the dependency between the wells as a function of distance. The TM parameters, such as the minimum transinformation and the range, were employed for evaluating the network which revealed that most of the distances between wells were less than the range. It also indicated that a high percentage of redundant information existed in the network. Therefore, the network was reduced by superimposing a square pattern over the monitored area and selecting one well per square block in a stratified pattern. The methodology was tested using the chloride data collected from 1972–2000 from 417 groundwater quality monitoring wells in the Gaza Strip. The number of the groundwater quality monitoring wells in the Gaza Strip was reduced by 53%, while there was 26% redundant information based on the minimum existing distance between wells. This methodology is meant to help monitor the groundwater quality (salinity) in the Gaza Strip.

Characterizing the spatial variability of groundwater quality using the entropy theory: II. Case study from Gaza Strip

AbstractThis paper, the second in the series, uses the entropy theory to describe the spatial variability of groundwater quality data sets. The application of the entropy theory is illustrated using the chloride observations obtained from a network of groundwater quality monitoring wells in the Gaza Strip, Palestine. The application involves calculating information measures, such as transinformation, the information transfer index and the correlation coefficient. These measures are calculated using a discrete approach, in which contingency tables are used. An exponential decay fitting approach was applied to the discrete models. The analysis shows that transinformation, as a function of distance, can be represented by the exponential decay curve. It also indicates that, for the data used in this study, the transinformation model is superior to the correlation model for characterizing the spatial variability. Copyright © 2004 John Wiley &amp; Sons, Ltd.