Spatial distribution of regionalized variables on reservoirs and groundwater resources based on geostatistical analysis using GIS: case of Rmel-Oulad Ogbane aquifers (Larache, NW Morocco) (original) (raw)
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Spatial analyses of groundwater level differences using geostatistical modeling
Environmental and Ecological Statistics, 2013
The purpose of this study was to determine and evaluate the spatial changes in the depletion of groundwater level differences by using geostatistical methods based on data from 58 groundwater wells during the period from April 1999 to April 2008 in the study area. Geostatistical methods have been used widely as a convenient tool to make decision on the management of groundwater levels. To evaluate the spatial changes in the level of the groundwater, geographic information system is used for the application of universal kriging method with cross-validation leading to the estimation of groundwater levels. The resulting prediction mappings identify the locations of groundwater level fluctuations of the study area. The average range of variogram (spherical model) for the spatial analysis is about 9,200 m. Results of universal kriging for groundwater level differences drops were underestimated by 15 %. Crossvalidation errors are within an acceptable level. The maps show that this area of high decrease of groundwater level is located at the southwest. Kriging model helps also to detect sensitively risk prone areas for groundwater withdrawing. Such areas must be protected with an effective management procedure for future groundwater exploitations.
Arabian Journal of Geosciences, 2013
The scarcity of water is one of the main issues in Saudi Arabia. In particular, the extreme climate in the form of less frequent rainfall affects the groundwater availability. Moreover, groundwater has been depleted by the increase in population. In this research, the spatial distribution of groundwater quality has been developed, and the prediction of groundwater chemical parameters has been made using geostatistical analysis in geographic information system (GIS) software. The study area is Madrakah village as the recharge area of Wadi Usfan located in the western region of Saudi Arabia. Ordinary kriging method was applied to map the spatial distribution of the groundwater chemistry. Most of the groundwater is not suitable for drinking purposes. Groundwater chemical parameters are decreasing toward the eastern part of Madrakah village. In predicting groundwater chemistry distribution maps, data transformation has been executed to reduce the skewness on most of the chemical parameters. The best semivariogram model for every parameter varies based on the root mean square error (RMSE) criterion. The groundwater chemical parameters, i.e., Na + , Mg 2+ , Cl − , conductivity, salinity, and total dissolved solid (TDS), have a strong spatial dependence, while, NO 3 − and temperature have a moderate and weak spatial dependence, respectively.
Spatial groundwater quality assessment using geostatistics in Puntland, Somalia
International Journal of Scientific and Technological Research , 2019
Groundwater is an essential source of drinking and farming in Puntland state of Somalia. Puntland suffers from major water scarcity, the lack of safe drinking water in Puntland is a frequent problem. The objective of this study is to assess the groundwater quality using geostatistical algorithm based on Geographic Information System (GIS). In this research, we utilized ordinary kriging interpolation technique for generating the spatial distribution of groundwater parameters. Experimental semivariogram were tested for different models to identify the best fitted semivariogram model for each parameter and best fitted semivariogram models was chosen based on the lowest value of root mean square error (RMSE) value. The final map indicates that the majority groundwater quality in the study area are not suitable for drinking purposes in according to WHO water quality standards. The results of the research shows that it is vital to develop monitoring tools and management strategies for the groundwater in the region.
Best applicable geostatistical model for interpolating groundwater-levels in El-Obour city, Egypt
The lack of data, mainly in the field of hydrogeology and groundwater especially, makes it necessary to implement a special estimation technique to overcome this shortage. Nowadays, geostatistics have become a popular mean to describe spatial patterns and to predict the value of unmeasured locations (Kriging). Many types of Kriging could be used such as ordinary, simple, universal Kriging. Each type has a different underlying assumption. The aim of this paper is to put a methodology that could be used for identifying the most suitable geostatistical model for interpolating groundwater-level data collected from District VI, El-Obour city using geographical information systems (GIS) to generate a prediction error map with good accuracy that could be used further on designing and/or optimizing the existing monitoring network. The procedure has to 1) build all available geostatistical models depending on Hierarchy Stepwise criteria, 2) compare them using cross-validation statistical parameters, and 3) choose the best suitable model for the study area. It was found that 1) the ordinary Kriging method, 2) fitted with a Gaussian function, 3) of groundwater-level skewed data normalized using Box-Cox with a power parameter equal to 2, and 4) no trend removal, all of them together compose the best matched model for the studied area.
Mapping the spatio-temporal distribution of water quality parameters is a crucial step in optimum utilization of groundwater resources. In this study we use information of 172 pizometric wells in Shiraz city, southern Iran to investigate the spatial variability of groundwater quality parameters (EC, SAR, TDS and Na) in 2005 and 2009. In order to do so, first the experimental semivariograms of selected parameters are calculated using GS + software and the best semivariogram models are fitted to the experimental data. The results showed that groundwater quality data are strongly spatially correlated over the study region. Spatial structure of all parameters except SAR 2005 follow a spherical model. For SAR in 2005 a Gaussian model is the best semivariogram model. Kriging approach via ArcGIS software is used to interpolate and map groundwater quality parameters. Groundwater qualitative map for agricultural purpose is produced through combining EC and SAR estimation maps considering US salinity laboratory standard. According to the generated maps, eastern parts have higher concentration of EC, TDS and SAR than other parts of the study area that could be duo to existence of salt lake there. The results showed that groundwater quality has slightly decreased from 2005 to 2009.
Geocarto International, 2019
This study developed a novel framework for integrating time series modeling with geographic information system (GIS). For the first time, procedures of four statistical tests, i.e., t-test of stationarity, Cumulative Deviation test of homogeneity, Autocorrelation Technique of persistence, and Variance-Corrected Mann-Kendall test of trend, are implemented in GIS platform to enable use of raster dataset. Application of developed framework is demonstrated by exploring time series characteristics of pre-and post-monsoon groundwater levels in an Indian arid region. Raster dataset of 22-year (1996-2017) groundwater levels are generated using four best-fit geostatistical models, according to mean absolute error, root mean square error, correlation coefficient and modified index of agreement. Increasing groundwater level trends in central and southern parts are attributed to abrupt change-points in annual rainfall that enhanced groundwater recharge. The developed framework can be adopted in other parts of the world to explore groundwater-level dynamics in spatially-distributed manner.
Environmental Monitoring and Assessment, 2019
This paper highlights the advantages of multivariate statistical and geostatistical methods to compile the hydro-geochemical properties of groundwater. A total of 123 samples were collected from wells located in Saveh aquifer, in 2015. Seven parameters including total dissolved solids (TDS), sodium adsorption ratio(SAR), electrical conductivity (EC), sodium (Na +), total hardness (TH), chloride (Cl −) , and sulfate (SO 4 2−) were analyzed, compiled, and interpreted statistically and geostatistically. At first, factor analysis gave rise to produce a factor representing 94% of the variability. Also, variography was calculated and compiled to define spatial regression and experimental variograms were plotted by GS + software, then, the best theoretical models were fitted on the variograms and an estimation map was prepared based on geostatistical relationship presented in the paper. Smoothing effect is one of the main drawbacks of forward geostatistical methods, on the contrary, inversed methods are subjected to no smoothing effect. Results showed that geostatistical inversed methods could reveal more reliable results than forward methods. Eventually, the map of the estimated factor, as well as error maps, was compiled. According to the evaluation of fractal dimensions, the estimated factor explained the variability of all hydrogeochemical parameters and groundwater quality was categorized as the safe, normal, and anomalous class, ranged from − 1.10 to 1.10, 1.11 to 3.1, and more than 3.1, respectively.
Spatial analyses of groundwater levels using universal kriging
Journal of Earth System Science, 2007
For water levels, generally a non-stationary variable, the technique of universal kriging is applied in preference to ordinary kriging as the interpolation method. Each set of data in every sector can fit different empirical semivariogram models since they have different spatial structures. These models can be classified as circular, spherical, tetraspherical, pentaspherical, exponential, gaussian, rational quadratic, hole effect, K-bessel, J-bessel and stable. This study aims to determine which of these empirical semivariogram models will be best matched with the experimental models obtained from groundwater-table values collected from Mustafakemalpasa left bank irrigation scheme in 2002. The model having the least error was selected by comparing the observed water-table values with the values predicted by empirical semivariogram models. It was determined that the rational quadratic empirical semivariogram model is the best fitted model for the studied irrigation area.
Environmental Processes, 2021
The present study is an attempt to implement several spatial interpolation methods for the distribution of groundwater level in a wider area with multiple aquifers having variable hydraulic characteristics. Moreover, the goal of this study is to compare the results of these methods and check their accuracy and reliability, considering mainly the physical meaning of the outcome. Finally, we try to figure out which of these methods manage to identify hydrogeological features like groundwater divides, hydraulic conductivity barriers and no flow boundaries, and to highlight the hydraulic relationship between aquifers. Exploratory Spatial Data Analysis proved to be a necessary step prior to the implementation of spatial interpolation methods, since normalization of datasets, removal of general trends and data declustering was necessary for the proper implementation of geostatistical methods and reduction of the uncertainty of the results. Inverse Distance Weight, Radial basis functions, ...
Geostatistical Analysis of Spatial and Temporal Variations of Groundwater Level
Environmental Monitoring and Assessment, 2006
Groundwater and water resources management plays a key role in conserving the sustainable conditions in arid and semi-arid regions. Applying management tools which can reveal the critical and hot conditions seems necessary due to some limitations such as labor and funding. In this study, spatial and temporal analysis of monthly groundwater level fluctuations of 39 piezometric wells monitored during 12 years was carried out. Geostatistics which has been introduced as a management and decision tool by many researchers has been applied to reveal the spatial and temporal structure of groundwater level fluctuation. Results showed that a strong spatial and temporal structure existed for groundwater level fluctuations due to very low nugget effects. Spatial analysis showed a strong structure of groundwater level drop across the study area and temporal analysis showed that groundwater level fluctuations have temporal structure. On average, the range of variograms for spatial and temporal analysis was about 9.7 km and 7.2 months, respectively. Ordinary and universal kriging methods Keywords water resources management. groundwater level fluctuations. geostatistics. kriging. spatial analysis. temporal analysis