This research aims to assess the hydrogeochemical evolution of the groundwater in Oued souf valley for drinking and irrigation purposes. To achieve this, 49 groundwater samples from the complex terminal were examined and treated concurrently with multivariate statistical methods, geostatistical modeling and the WQI (water quality index). Focusing on the physico-chemical parameters, Q mode clustering analysis detected four major water groups, where the mineralization augmented from group 1 to group 4. The hydro-chemical type was the same, Ca-Mg-Cl-SO4 for all the groups. Calcite, dolomite, anhydrite, and gypsum would be the dominant reactions with the undersaturation of evaporates minerals, based on geochemical modeling, while the carbonate minerals are precipitating. Geostatistical analysis using ordinary Kriging demonstrated the exponential semi-variogram model fitted for EC (electrical conductivity), Ca2+ (calcium), Mg2+ (magnesium), K+ (potassium), HCO3− (bicarbonate), Cl− (chloride), and SO42− (sulfate). At the same time, the rational quadratic model was the best-fitted semi-variogram model for Na+ (sodium) and NO3− (nitrate). EC, SO42−, and NO3− have a strong spatial structure, while Ca2+, Na+, K+, and HCO3− have a moderate spatial structure. Moreover, there was a weak spatial structure for Mg2+ and Cl−. The WQI shows that CT (complex terminal groundwater aquifers) are not suitable for drinking and their quality for irrigation fluctuates from excellent to moderate quality.
An increasing amount of CO2 emissions from the household sector of Iran led us to analyze the inequality and understand the possible driving force behind the CO2 emissions. The study of inequality provides information to policy-makers to point policies in the right direction. By considering the differences in the socio-economic factors of provinces, the study aims to analyze the inequality in CO2 emissions and different kinds of energy consumption, including oil, gas and electricity, for the household sector of Iran’s provinces between 2000 and 2017. For this aim, the Theil index and Kaya factor, as a simple and common method, were considered to evaluate the inequality in both CO2 emissions and energy consumption, and determine the driving factor behind CO2 emissions. According to the results, inequality in oil and natural gas consumption were increasing, electricity was almost constant; however, CO2 emissions experienced a decreasing trend for the study period. The Theil index changed from 0.4 to 0.65 for oil, from 0.18 to 0.22 for natural gas, from 0.17 to 0.15 for electricity, and from 0.2 to 0.14 for CO2 emissions between 2001 and 2017. In addition, the results of the inequality study indicated that most of the inequalities belong to within-group inequalities in energy consumption and CO2 emissions. The results of the Kaya factor indicate that the second factor, energy efficiency, with a 0.21 value was the main driving factor of inequalities in CO2 emissions; however, the first factor, energy consumption, can be a potential factor for inequality in the following years, as it increased from 0.00 to 0.11 between 2001 and 2017. It seems that by removing the energy subsidy policy in 2010 and 2013, low-standard and energy-wasting old vehicles were the most effective factors of energy inefficiency in the household sector, which need more accurate policy-making.
Outdoor recreation has grown rapidly in recent years, with an increasing preference for areas in good ecological condition. Since lakes represent some of the most important wetlands, providing a wide variety of ecosystem services, they have become a very popular destination. The present study aimed to assess the water quality of the largest artificial lake in Hungary (Kisköre Reservoir—Lake Tisza), and the role of ecological status in tourism development. Monthly water sampling from the basins of the lake (Tiszavalk, Poroszló, Sarud and Abádszalók basins) took place from April–November 2021 and in 2022. The majority of samples from the river section and from the lake are classified as Ca2+-HCO3− type or mixed Ca2+-Na+-HCO3− type. According to the results, the water quality of each basin is considered excellent or good. Rapid warming of the shallow water of the basins was detected during the summer months, resulting in different hydrochemical characteristics (pH, NH4-N, NO2-N, NO3-N, PO4-P, CODcr BOI5) compared to the river section. Differences in the plant nutrient and oxygen balance component groups have been revealed with hierarchical and two-step cluster analysis as well. The results demonstrated that the hydrochemical properties of the lake’s water are substantially influenced by the filling of the lake in spring from the River Tisza and the significant lowering (1.2 m) of the water level in the autumn each year, allowing the drainage of stagnant water, the removal of accumulated sediments and the oxidation of organic matter. The number of tourists on Lake Tisza has increased rapidly over the last decade, confirming that a wide range of ecosystem services have a significant attractive impact on waterfront activities and ecotourism.
Since the beginning of the 1980s, several regions in the northern Sahara of Algeria have been confronting the rising groundwater. Among all these regions, Oued Souf Valley represented one of the most acute affected by this phenomenon. Due to the natural topography and the insufficient/weakness of water management and miscoordination between different sectors that are represented by intensive exploitation of deep groundwater reservoirs which returns to the shallow aquifer, absence of sewage and drainage network, leakage from drinking water supply system, the groundwater has raised to the surface or near to the surface, affecting the traditional cultural environment and urban areas and degrading all socio-economic aspects of the Oued Souf habitants. To preserve the Oued Souf environment, a vertical drainage system has been constructed. Consequently, in this research, an evaluation of the vertical drainage system performance and its impact on groundwater level stabilization has been performed by mapping the water table of the phreatic groundwater level using geostatistical modeling using ordinary kriging (OK) interpolation method, which has been applied to analyze the spatial and temporal structure of groundwater level fluctuation. Meanwhile, hierarchical cluster analysis (HCA) was applied for grouping the wells based on the groundwater fluctuations for 2008, 2009, 2014, 2016, 2018, and 2021. However, the vertical drainage system reflected a significant decline of groundwater from 2009 to 2018 due to the important drained volumes through it but another rising phenomenon might be threatening the region in the near future and this is what was indicated in the 2021 groundwater level data. Cluster analysis has generated four groups based on their fluctuation means that are increasing from the first group to the fourth group ascendingly. The first cluster grouped the drains that have a shallow depth (average mean of 5.91 mbgl) and declined over the clusters. The clusters are spatially combined with significant separation of the fourth cluster which represents the deepest group (12.89 mbgl). Based on this research, several factors are influencing the stability of the phreatic groundwater level and even the performance of the drainage system, the most important of which is the overexploitation from deep groundwater reservoirs such as complex terminal and continental intercalary (in drinking and irrigation) and even the illegal use of the phreatic groundwater with important quantities for irrigation and illegal industries.
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