A geostatistical approach for groundwater head monitoring network optimisation: case of the Sfax superficial aquifer (Tunisia) (original) (raw)
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Journal of Geographic Information System, 2015
Growing water scarcity is one of the major challenges of the 21st century, especially in arid and semi-arid climates such as our study area. The efficient, sustainable and integrated groundwater management plays a key role for conserving this vital resource. In order to overcome this issue, the study of aquifer system's behavior seems necessary. For this purpose, the areal piezometric level map is an essential tool. As piezometric level data are spatially limited in sample points, the spatial interpolation and geostatistics are the best way to produce the needed map. Several methods exist allowing to approach real values with varying degrees of accuracy. This work aims to compare and evaluate spatial interpolation methods for groundwater level of Haouz using a dataset of 39 piezometers. The deterministic methods used in this study are Inverse Distance Weighted (IDW) and Radial Basis Functions (RBF) and the probabilistic ones are ordinary kriging (OK), simple kriging (SK) and universal kriging (UK). This study shows the difficulty of having a key role to choose the suitable method for given input dataset. The best model remains the one that, after comparing several methods, offers the best accuracy, which is assessed using Cross-validation and statistical indicators. The results reveals that ordinary kriging with trend removal technique is the optimal method in this case. It indicates the superiority of this technique with a decrease in Root Mean Square Error (RMSE) up to 61.67%. It underestimates groundwater level with an average of 2.8%, which is reliable. The areal piezometric level and associated prediction standard error maps give additional information and recommendations that characterize the studied aquifer system and will ultimately improve sustainable groundwater management.
Evaluation and optimisation of groundwater observation networks using the Kriging methodology
Environmental Modelling & Software, 2006
Groundwater simulation models have nowadays a decisive role in the development and application of rational water policies. Since the accuracy of the simulation depends strongly on the available data, the task of optimising the observation networks is of great importance. In this paper an application is presented aiming at the optimisation of groundwater level observation networks and the improvement of the quality rather than the quantity of the obtained data. This technique is based on the application of the Kriging methodology and the evaluation of its results in conjunction with the statistical analysis of the available groundwater level data. This procedure that involves different analysis methods of the available data, such as estimation of the interpolation error, data crossvalidation and time variation, is applied to a case study in order to demonstrate the potential of improvement of the quality of the observation network.
Application of Geostatistical Methods to Estimate Groundwater Level Fluctuations
International journal of Advanced Biological and Biomedical Research, 2018
Keeping the water table at a favorable level is quite significant for a sustainable management of groundwater plans. Various management measures need to know the spatial and temporal behavior of groundwater. Therefore, the measurement of groundwater levels are generally carried out at spatially random locations in the field; whereas, most of the groundwater models requires these measurement at a pre-specified grid. Geostatistical techniques could produce an accurate map of groundwater level. Naishaboor plain with 4190 sq km was selected due to presence of over 48 observation wells, mostly with more than 20 years of record. A universal kriging and co-kriging - with level of surface as auxiliary variable - estimator has been used to model groundwater level for three kind of climate condition (wet, normal and dry) and three levels (maximum, average and minimum). The result showed the Gaussian model selected as the best variogram. Furthermore, the RMSE and MRE indicated that kriging met...
International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, 1995
The purpose of this paper is to optimize a network of observation wells in southeast of Austria, developed for monitoring groundwater level and groundwater resource in this area. As groundwater level data are collected over time, problems arise in defining an overall variogram valid for the whole period of observation, which is needed to estimate groundwater level properly. This paper compares three approaches -arithmetic mean of every series, general relative variogram and principal component analysis -to calculate an overall variogram and discusses the differences between the approaches in optimizing the network for the above mentioned area. Universal kriging was then used to map the minimum error variance estimates for each of these three approaches. General relative variogram appeared to give the best results.
Research Square (Research Square), 2022
Groundwater monitoring of an aquifer performed by an observation well network plays an important role in the management of groundwater resources in which, if the number of wells is small, the calculation of groundwater level is less accurate, and if the number of observation wells is high, the cost of drilling and maintenance of wells and the cost of measurement will increase. This study aimed to identify observation wells' number and optimal density in an aquifer using classical statistics and geostatistical techniques. The Sarfiroozabad aquifer with 45 observation wells was selected as a case study, in which the effective range of each observation well was determined through examination of the coefficients of water table variations in parallel profiles perpendicular to the longitudinal axis of the aquifer and examining geostatistical items including variograms related to water table variations by specifying the optimal number of observation wells. Classical statistics and geostatistics showed the same effective range for wells in the northern aquifer. According to the observations, to obtain the optimal number and density of observation wells, at least 6 observation wells shall be added to the northern aquifer, while only one well should be added to the southernmost part of the southern aquifer and six wells should be eliminated that reduces the cost of sampling. Also, by adding essential wells, the accuracy of groundwater estimation increases which helps better manage groundwater resources.
2018
Ziel der Arbeit ist die Untersuchung neuer Ansätze und Verbesserung bestehender Methoden für das Grundwassermonitoring, wobei statistische, geostatistische und hydrogeologische Methoden eingesetzt werden. Neue Ansätze wurden formuliert, bestehende Methoden verbessert und für eine räumliche und zeitliche Optimierung von Grundwassermessnetzen integriert und anhand des Datensatzes von Bitterfeld-Wolfen getestet. Für die räumlich-zeitliche Optimierung des Überwachungsmessnetzes wurden uni- und multivariate Statistik angewendet. Ein geostatistischer raum-zeitlicher Algorithmus wurde zur Identifikation überzähliger Messstellen genutzt. Basis sind die Informationen naheliegender Messstellen, die den kontaminierten Bereich zwei- und dreidimensional im Quartär und Tertiär wiedergeben. Für die Optimierung wurden auch ein stationäres Strömungs- und ein instationäres Transportmodell genutzt. Die Einflussfaktoren für die Optimierung des Monitoring-Netzwerkes wurden ebenfalls untersucht. In der A...
2019
Aims: Overexploitation of groundwater (GW) resources leads to lowering of the water table and widespread shallow groundwater contamination, particularly in semi-arid and arid regions of the world. The region of Mahdia, located in the Sahel of Tunisia, is a semi-arid region characterized by its limited surface water and groundwater resources. Overexploitation of groundwater in some shallow aquifers has been detected lately in the region due to the increase of population and human activities. This study aimed to figure out spatial and temporal changes in groundwater elevations through using geostatistical techniques. Methods and Results: In line with the determined objective, data from 102 groundwater observation wells, located in the Mahdia region in Tunisia, were used in this study. The Regional Commissariat for Agricultural Development of Mahdia (CRDA) provided us with the data of groundwater depth observations from 2005 to 2017, surface elevation and coordinates of the groundwater...
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.
Application and evaluation of universal kriging for optimal contouring of groundwater levels
This paper deals with the application of universal kriging to interpolate water table elevations from their measurements at random locations. Geographic information system tools were used to generate the continuous surface of water table elevations for the Carlsbad area alluvial aquifer located to the southeast of New Mexico, USA. Water table elevations in the 38 monitoring wells that are common to 1996 and 2003 irrigation years follows normal distribution. A generalized MATLAB code was developed to generate omni-directional and directional semi-variograms (at 22.5 • intervals). Low-order polynomials were used to model the trend as the water table profile exhibits a south-east gradient. Different theoretical semivariogram models were tried to select the base semi-variogram for performing geostatistical interpolation. The contour maps of water table elevations exhibit significant decrease in the water table from 1996 to 2003. Statistical analysis performed on the estimated contours revealed that the decrease in water table is between 0.6 and 4.5 m at 90% confidence. The estimation variance contours show that the error in estimation was more than 8 m 2 in the west and south-west portions of the aquifer due to the absence of monitoring wells. sure of capability of these predictions . The spatial variability of the random
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