Search Results (3)

In order to evaluate and project the quality of groundwater utilized for irrigation in the Sahara aquifer in Algeria, this research employed irrigation water quality indices (IWQIs), artificial neural network (ANN) models, and Gradient Boosting Regression (GBR), alongside multivariate statistical analysis and a geographic information system (GIS), to assess and forecast the quality of groundwater used for irrigation in the Sahara aquifer in Algeria. Twenty-seven groundwater samples were examined using conventional analytical methods. The obtained physicochemical parameters for the collected groundwater samples showed that Ca²⁺ > Mg²⁺ > Na⁺ > K⁺, and Cl⁻ > SO₄²⁻ > HCO₃⁻ > NO₃⁻, owing to the predominance of limestone, sandstone, and clay minerals under the effects of human activity, ion dissolution, rock weathering, and exchange processes, which indicate a Ca-Cl water type. For evaluating the quality of irrigation water, the IWQIs values such as irrigation water quality index (IWQI), sodium adsorption ratio (SAR), Kelly index (KI), sodium percentage (Na%), permeability index (PI), and magnesium hazard (MH) showed mean values of 47.17, 1.88, 0.25, 19.96, 41.18, and 27.87, respectively. For instance, the IWQI values revealed that 33% of samples were severely restricted for irrigation, while 67% of samples varied from moderate to high restriction for irrigation, indicating that crops that are moderately to highly hypersensitive to salt should be watered in soft soils without any compressed layers. Two-machine learning models were applied, i.e., the ANN and GBR for IWQI, and the ANN model, which surpassed the GBR model. The findings showed that ANN-2F had the highest correlation between IWQI and exceptional features, making it the most accurate prediction model. For example, this model has two qualities that are critical for the IWQI prediction. The outputs’ R² values for the training and validation sets are 0.973 (RMSE = 2.492) and 0.958 (RMSE = 2.175), respectively. Finally, the application of physicochemical parameters and water quality indices supported by GIS methods, machine learning, and multivariate modeling is a useful and practical strategy for evaluating the quality and development of groundwater. Full article

This study aims to analyze the chemical composition of Lioua’s groundwater in order to determine the geological processes influencing the composition and origin of its chemical elements. Therefore, chemometrics techniques, such as multivariate statistical analysis (MSA) and time series methods (TSM) are used. Indeed, MSA includes a component analysis (PCA) and a cluster analysis (CA), while autocorrelation analysis (AA), supplemented by a simple spectral density analysis (SDA), is used for the TMS. PCA displays three main factors explaining a total variance (TV) of 85.01 %. Factors 1, 2, and 3 are 68.72%, 11.96%, and 8.89 % of TV, respectively. In the CA, total dissolved solids (TDS) and electrical conductivity (EC) controlled three groups. The elements SO₄²⁻, K⁺, and Ca²⁺ are closely related to TDS, the elements Na⁺, Cl⁻, and Mg²⁺ are closely related to CE, while HCO³⁻ and NO³⁻ indicate the dissociation of other chemical elements. AA shows a linear interrelationship of EC, Mg²⁺, Na⁺, K⁺, Cl⁻, and SO₄²⁻. However, NO₃⁻ and HCO₃⁻ indicate uncorrelated characteristics with other parameters. For SDA, the correlograms of Mg²⁺, Na⁺, K⁺, Cl⁻, and SO₄²⁻ have a similar trend with EC. Nonetheless, pH, Ca²⁺, HCO₃⁻ and NO₃⁻ exhibit multiple peaks related to the presence of several distinct cyclic mechanisms. Using these techniques, the authors were able to draw the following conclusion: the geochemical processes impacting the chemical composition are (i) dissolution of evaporated mineral deposits, (ii) water–rock interaction, and (iii) evaporation process. In addition, the groundwater exhibits two bipolar characteristics, one recorded with negative and positive charges on pH and Ca⁺ and another recorded only with negative charges on HCO₃⁻ and NO₃⁻. On the other hand, SO₄²⁻, K⁺, Ca²⁺, and TDS are the major predominant elements in the groundwater’s chemical composition. Chloride presence mainly increases the electrical conductivity of water. The lithological factor is dominant in the overall mineralization of the Plio Quaternary surface aquifer waters. The origins of HCO₃⁻ and NO₃⁻ are as follows: HCO₃⁻ has a carbonate origin, whereas NO₃^– has an anthropogenic origin. The salinity was affected by Mg²⁺, SO₄²⁻, Cl⁻, Na⁺, K⁺, and EC. Ca²⁺, HCO₃⁻, and NO₃⁻ result from human activity such as the usage of fertilizers, the carbonate facies outcrops, and domestic sewage. Full article

The risk related to embankment dam breaches needs to be evaluated in order to prepare emergency action plans. The physical and hydrodynamic parameters of the flood wave generated from the dam failure event correspond to various breach parameters, such as width, slope, and formation time. This study aimed to simulate the dam breach failure scenario of the Yabous dam (northeast Algeria) and analyze its influence on the related areas (urban and natural environments) downstream of the dam. The simulation was completed using the sensitivity analysis method to assess the impact of breach parameters and flooding on the dam break scenario. The flood wave propagation associated with the dam break was simulated using the one-dimensional HEC-RAS hydraulic model. This study applied a sensitivity analysis of three breach parameters (slope, width, and formation time) on five sites selected downstream of the embankment dam. The simulation showed that the maximum flow of the flood wave recorded at the level of the breach was 8768 m³/s, which gradually attenuated along the river course to reach 1972.7 m³/s at about 8.5 km downstream the dam. This study established the map of flood risk areas that illustrated zones threatened by the flooding wave triggered by the dam failure due to extreme rainfall events. The sensitivity analysis showed that flood wave flow, height, and width revealed positive and similar changes for the increases in adjustments (±25% and ±50%) of breach width and slope in the five sites. However, flood wave parameters of breach formation time showed significant trends that changed in the opposite direction compared to breach slope and width. Meanwhile, the adjustments (±25% and ±50%) of the flood hydrograph did not significantly influence the flood parameters downstream of the dam. In the present study, the HEC-RAS 1-D modeling demonstrated effectiveness in simulating the propagation of flood waves downstream of the dam in the event of dam failure and highlighted the impact of the breach parameters and the flood hydrographical pattern on flood wave parameters. Full article