Moncef Zairi

Minimization of environmental risk of landfill site using fuzzy logic, analytical hierarchy process, and weighted linear combination methodology in a geographic information system environment

This paper presents a GIS-based multi-criteria site selection for municipal solid waste landfilling in Ariana Region, Tunisia. Based on the regional characteristics, literature related to disposal sites and waste management, local expert, data availability and assessments via questionnaires, 15 constraints, and 5 factors were built in the hierarchical structure for landfill suitability by multi-criteria evaluation. The factors are divided into environmental and socio-economic groups. The methodology is used for preliminary assessment of the 20-year most useful lifetime suitable landfilling sites by combining fuzzy set theory, weighted linear combination (WLC) and analytic hierarchy process (AHP) in a GIS environment. The criteria standardization is undertaken by application of different fuzzy membership functions. The fuzzy membership functions shape and their control points are chosen through assessment of expert opinion. The weightings of each selection criterion are assigned depending on the relative importance using the AHP methodology. The WLC approach is applied for alternative landfill sites prioritization. The results of this study showed five potential candidate sites, which are generated when the environmental factors are valued higher than socio-economic factors. These sites are ranked in descending order using the ELECTRE III method. However, the final decision will require further detailed geotechnical and hydrogeological analyses toward the protection of groundwater as well as surface water.

Multivariate statistical and geostatistical techniques for assessing groundwater salinization in Sfax, a coastal region of eastern Tunisia

AbstractIn this study, we investigate the ability to combine a multivariate statistical analysis with the cokriging method to point out the groundwater salinization in the coastal Sfax aquifer (eastern Tunisia). First, multivariate statistical analysis such as principal component analysis (PCA) and cluster analysis were performed on 75 water samples. PCA identifies three main processes influencing groundwater chemistry which are seawater intrusion, water–rock interaction, and contamination by nitrates, these three factors accounted for 76% of total variance of the groundwater. Furthermore, cokriging is applied to take into account spatial dependence between the studied variables. Five variables were processed: concentration of sulfates, chlorides, sodium and the sodium adsorption ratio, as primary variables, and the more numerous data for total dissolved solid, as auxiliary variables. The generated spatial variability maps highlighted the high-risk zone of groundwater contamination of the superficial aqui...

Groundwater levels time series sensitivity to pluviometry and air temperature: a geostatistical approach to Sfax region, Tunisia

In this paper, the pattern of groundwater level fluctuations is investigated by statistical techniques for 24 monitoring wells located in an unconfined coastal aquifer in Sfax (Tunisia) for a time period from 1997 to 2006. Firstly, a geostatistical study is performed to characterize the temporal behaviors of data sets in terms of variograms and to make predictions about the value of the groundwater level at unsampled times. Secondly, multivariate statistical methods, i.e., principal component analysis (PCA) and cluster analysis (CA) of time series of groundwater levels are used to classify groundwater hydrographs regard to identical fluctuation pattern. Three groundwater groups (A, B, and C) were identified. In group “A,” water level decreases continuously throughout the study periods with rapid annual cyclic variation, whereas in group “B,” the water level contains much less high-frequency variation. The wells of group “C” represents a steady and gradual increase of groundwater levels caused by the aquifer artificial recharge. Furthermore, a cross-correlation analysis is used to investigate the aquifer response to local rainfall and temperature records. The result revealed that the temperature is more affecting the variation of the groundwater level of group A wells than the rainfall. However, the second and the third groups are less affected by rainfall or temperature.

Aquifer vulnerability and seawater intrusion risk using GALDIT, GQISWI and GIS: case of a coastal aquifer in Tunisia

Due to increase in population and agricultural activities, the Sfax coastal aquifer is under tremendous stress and seawater intrusion becomes a serious concern. This situation needs an assessment of aquifer vulnerability and seawater intrusion risk. A new approach for vulnerability mapping using GALDIT, groundwater quality index for seawater intrusion (GQISWI), geostatistics, the Ghyben–Herzberg model and GIS was developed. The model is used to determine the trend of groundwater contamination by seawater intrusion in the coastal aquifer in Sfax basin (Tunisia). Vulnerability assessment method is recognized through assessing weight and ratings of the GALDIT relevant parameter. A second vulnerability map was realized based upon the groundwater quality index for seawater intrusion integrating the water quality parameters for delineating seawater intrusion in the aquifer. The validation of GQISWI and GALDIT vulnerability maps was undertaken through comparison of areas of high Jones Ratio, chloride and TDS concentration and their relative vulnerability index. The Ghyben–Herzberg model has been used to predict the actual seawater intrusion extend and evaluate the freshwater–saltwater dynamics. The results reveal that the coastal area is currently undergoing seawater intrusion and its northern part is the most affected one by this contamination.

Efficiency of Aquifer Artificial Recharge from Hill Dam by Analytical Method

Tunisian areas suffer from regular water shortage and the increase of groundwater exploitation rates, causing a continuous decrease of groundwater level as a consequence of aquifers overexploitation.

Optimal Groundwater Sampling Design for Nitrate Monitoring by Geostatistical Analysis and Vulnerability Mapping

The approaches for groundwater monitoring network design can be classified as hydrogeologic and statistical.

Spatial Distribution of Methane Emissions at Bizerte Active Landfill (Northern Tunisia)

Atmospheric methane has adverse effects on the surrounding environment and can affect human life.

A Hydrogeological Information System (HISM) Design and Implementation for Groundwater Management of Monastir, Tunisia

A Decision Support System (DSS) for groundwater resources management is developed for the Monastir region. It is a hydrogeological relational database joined with a Hydrogeological Information System (HISM) which enables fast and effective processing of large volumes of spatial data from multiple sources. The HISM has a great management capacity; it ensures the conversion from the geographic coordinates to the planimetric coordinates. It allows adding, modifying, deleting and editing data (Rainfall, piezometric and geochemical). It also ensures the storage and editing of the digitized and/or generated cartographic database.

Piezometry mapping accuracy based on elevation extracted from various spatial data sources

Any hydrogeological conceptual model of an aquifer requires a piezometric map to enable defining flow direction, hydraulic gradient, groundwater recharge and discharge zones. Thus, the piezometric head calculation requires an accurate assessment of the elevation and the depth to water in monitoring wells. The main concern of aquifer managers remains the elevation estimate with a satisfactory accuracy, particularly in developing countries, where a lack of well surveying data is frequently encountered. A solution to this situation may be found in the use of digital elevation models (DEMs). In the present paper, a methodology to extract well elevations from DEMs based on datasets from Shuttle Radar Topography Mission (SRTM), Google Earth and digitized topographic map is presented. Statistical analyses of the elevations derived from a topographic field survey and the relative DEMs and piezometric map comparisons are used to assess the elevation accuracy. The DEM generated from the topographic map (TopoDEM) resulted in the closest match to the surveyed one with a correlation coefficient of 0.98 and a root mean square error of 0.76. The elevation from SRTM and Google Earth DEMs lead to an underestimation of the piezometry with the poorest performance from Google Earth DEM.