Understanding groundwater table using a statistical model

Su, Yan; Yu, Shu; Wu, Yu-bai; De-feng, Pan; Dong, Jiagen

doi:10.1016/j.wse.2018.03.003

Cited by 29 publications

(10 citation statements)

References 13 publications

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“…Multiple linear regression (MLR) refers to statistical techniques to predict a variable of interest based on the value of two or more variables. It seeks to express the regression model between two or more explanatory variables and an explained variable by fitting a linear equation to the observed data (Dougha and Hasbaia 2019;Yan et al 2018). MLR is a statistical tool that aims to analyze the relation (association) between a dependent variable which is treated as a function of several independent variables (x 1 , x 2 , x 3 …x p ) (Montgomery and Peck 1992;Myers 1990;Neter et al 1985;Galton 1885).…”

Section: Multiple Linear Regressionmentioning

confidence: 99%

Geochemical processes of groundwater salinization in an arid area, southeastern Tunisia

et al. 2021

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Salinization is an environmental issue that affects different regions worldwide. Geochemical approaches and statistical tools are combined to investigate the origin and process of groundwater salinization in Menzel Habib shallow aquifer. The inland aquifer from Menzel Habib area is in the northwest of Gabès, southeastern Tunisia. A total of twenty-five water samples were selected and collected in the study area. Physicochemical parameters (electrical conductivity, pH, total dissolved solids) were measured in situ, and major ions (Na, Mg, Ca, K, Cl, SO 4 , HCO 3 , F, and Br) were determined. The obtained results show a Na-Cl groundwater dominant facies (60%), Na-SO 4 (36%), and mixed water type (4%). Thus, a correlation between total dissolved solids and major ions shows the contribution of SO 4 , Cl, Na, Ca, and Mg in groundwater salinization. The salinization of groundwater is due to the dissolution of Triassic evaporites, which are related to the tectonic context of the region, and to the cationic exchange. Furthermore, statistical approaches, especially principal component analysis, reveal that the high groundwater mineralization is due to the evaporite dissolution. Multiple linear regression leads to establish a model linking total dissolved solids to the different chemical elements involved in groundwater salinization.Keyword Salinization . Groundwater . Geochemical approaches . Principal component analysis . Multiple linear regression .

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Section: Multiple Linear Regressionmentioning

confidence: 99%

Geochemical processes of groundwater salinization in an arid area, southeastern Tunisia

et al. 2021

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“…Regression analysis was used to predict groundwater levels (Sahoo & Jha 2013;Yan et al 2018;Kommineni et al 2020), recharge (Lorenz & Delin 2007), and groundwater quality (Chenini & Khemiri 2009). In this work, a multi-regression analysis was used to estimate both river filtrate portion (Equation (4)) and minimum travel time (Equation ( 5)) as functions of pumping rate and distance between the pumping well and the river (Figure 9).…”

Section: Multi-regression Analysismentioning

confidence: 99%

Studying the effect of design parameters on riverbank filtration performance for drinking water supply in Egypt: a case study

Mamdouh

Wahaab²,

Khalifa

et al. 2021

Water Supply

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Riverbank filtration (RBF) is an affordable technique to provide drinking water with adequate quality. The ultimate objective of this study is to facilitate the transferability and application of this sustainable technique in Egypt. In this work, a numerical model was constructed using Groundwater Modeling System (GMS) to study the effect of four design parameters on the RBF performance parameters (i.e., river filtrate portion and travel time) with the aid of MODPATH and ZONEBUDGET. The design parameters were; (1) the pumping rates of the RBF wells, (2) number of operating wells, (3) distance between wells and the river, and (4) the spacing between wells. This study was focused on the hydraulic aspects of the technique. The results demonstrated that; (1) the river filtrate portion exceeds 75% regardless the design conditions. (2) The hydraulic performance of RBF technique is highly controlled by the production capacity of the wells and their positions relative to the surface water systems; the spacing between wells has a minimum effect. Two equations were developed to estimate the river filtrate portion and minimum travel time as functions of pumping rate and distance between the pumping well and the river.

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“…The other independent variable is the number of months since the commencement of the observation. The output (dependent variable) of the model is the water table depth, for which sufficient data from forty-nine (49) wells, both of shallow and deeper aquifers, are collected every three (3) or nine (9) months during a sampling period of 7 to 10 years. The regression coefficients estimated by the model represent the impact and the trend rate of the groundwater level rise or fall over time.…”

Section: Introductionmentioning

confidence: 99%

“…Six wells at an experimental site covering a region of 17 km 2 are used to collect water table elevation data every fifteen minutes on a weekly basis while hydrogeological data and site specific data are also used. In another experimental research [9], a statistical model is suggested for the investigation of the groundwater level response to precipitation, evaporation, river stage and tide level. Daily water table data are selected from twelve (12) wells in a shallow unconfined aquifer of a farmland covering an area of 50 × 150 m 2 for one year.…”

Section: Introductionmentioning

confidence: 99%

Relating Hydro-Meteorological Variables to Water Table in an Unconfined Aquifer via Fuzzy Linear Regression

Papadopoulos¹,

Spiliotis²,

Gkiougkis³

et al. 2021

Environments

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This study aims to assess the short-term response of groundwater to the main hydro-meteorological variables of drought in a coastal unconfined aquifer. For this purpose, a multiple fuzzy linear regression-based methodology is implemented in order to relate rainfall, streamflow and the potential evapotranspiration to groundwater. Fuzzy regression analysis is recommended when there is a lack of data. The uncertainty of the system is incorporated into the regression coefficients which, in this study, are considered to be fuzzy symmetrical triangular numbers. Two objective functions are used producing a fuzzy band in which all the observed data must be included. The first objective function, based on Tanaka’s model, minimizes the total width of the produced fuzzy band. The second one includes the first while additionally minimizing the distance between the central value of the fuzzy output of the model and the observed value. Validity of the model is checked through suitability measures. The present methodology is applied at the east part of the Nestos River Delta in the Prefecture of Xanthi (Greece), where the observed values of the depth of groundwater level of four wells are examined.

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Understanding groundwater table using a statistical model

Cited by 29 publications

References 13 publications

Geochemical processes of groundwater salinization in an arid area, southeastern Tunisia

Geochemical processes of groundwater salinization in an arid area, southeastern Tunisia

Studying the effect of design parameters on riverbank filtration performance for drinking water supply in Egypt: a case study

Relating Hydro-Meteorological Variables to Water Table in an Unconfined Aquifer via Fuzzy Linear Regression

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