RESUMEN
Coastal aquifer vulnerability assessment (CAVA) studies are essential for mitigating the effects of seawater intrusion (SWI) worldwide. In this research, the vulnerability of the coastal aquifer in the Lahijan region of northwest Iran was investigated. A vulnerability map (VM) was created applying hydrogeological parameters derived from the original GALDIT model (OGM). The significance of OGM parameters was assessed using the mean decrease accuracy (MDA) method, with the current state of SWI emerging as the most crucial factor for evaluating vulnerability. To optimize GALDIT weights, we introduced the biogeography-based optimization (BBO) and gray wolf optimization (GWO) techniques to obtain to hybrid OGM-BBO and OGM-GWO models, respectively. Despite considerable research focused on enhancing CAVA models, efforts to modify the weights and rates of OGM parameters by incorporating deep learning algorithms remain scarce. Hence, a convolutional neural network (CNN) algorithm was applied to produce the VM. The area under the receiver-operating characteristic curves for OGM-BBO, OGM-GWO, and VMCNN were 0.794, 0.835, and 0.982, respectively. According to the CNN-based VM, 41% of the aquifer displayed very high and high vulnerability to SWI, concentrated primarily along the coastline. Additionally, 32% of the aquifer exhibited very low and low vulnerability to SWI, predominantly in the southern and southwestern regions. The proposed model can be extended to evaluate the vulnerability of various coastal aquifers to SWI, thereby assisting land use planers and policymakers in identifying at-risk areas. Moreover, deep-learning-based approaches can help clarify the associations between aquifer vulnerability and contamination resulting from SWI.
Asunto(s)
Aprendizaje Profundo , Agua Subterránea , Monitoreo del Ambiente/métodos , Agua de Mar , AlgoritmosRESUMEN
In this study, to increase the accuracy of determining the parameters of groundwater balance and finally the aquifer reservoir deficit, WA + as a new water accounting system has been applied by calculating six sheets in the Plasjan basin, central Iran. According to the results, the volume of rainfall and transfer flow to the basin was 548.8 MCM in the water year 2016-2017, which entered the hydrological cycle as input. Moreover, the results of FAO's Water Productivity Open-Access Portal (WaPOR) product showed that evapotranspiration was equal to 465 MCM, of which 345 and 120 MCM belonged to green water and blue water, respectively, at the basin level. The results of the WaPOR product showed that 264 MCM of evapotranspiration was beneficial, while the rest was non-beneficial in the basin. Finally, investigating the runoff and utilization of water resources showed that the return flow to surface water and groundwater resources was 35.5 MCM and 62 MCM, respectively. Therefore, the aquifer deficit was estimated to be 56.3 MCM based on the results of the WA + system. By calculating the evapotranspiration using remote sensing in WA + , the return water flow was estimated at 28%, being more accurate compared to the classical groundwater balance. Consequently, the amount of aquifer deficit calculated by the WA + method was accurate according to the balance and the aquifer hydrograph. The findings of this study show that as a suitable tool, the water accounting system can reduce the uncertainty of groundwater balance calculations.
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Agua Subterránea , Agua , Monitoreo del Ambiente/métodos , Recursos Hídricos , Abastecimiento de AguaRESUMEN
Unplanned pumping of groundwater in the past two decades has caused many regional problems and tensions, leading to seawater intrusion into coastal aquifers. The main objective of this paper is the use of a Multi-Criteria Decision-Making (MCDM) approach combining with numerical simulation for reducing seawater intrusion in the Tajan coastal aquifer located on the southern seashores of the Caspian Sea, Iran, taking into account economic, social, and environmental issues. The MODFLOW code was used to simulate the groundwater flow. MT3DMS and SEAWAT codes were used to simulate the solute transport and seawater intrusion. A 10-year period from 2010 to 2020 was simulated for evaluating the current conditions and forecasting the future conditions of the aquifer. The results indicated an increase in the extent of seawater intrusion. To assess the proposed eleven curative solutions, the economic, social, and environmental criteria such as efficiency of applying of curative solutions in improvement of the aquifer's water level and efficiency of applying of curative solutions on reduction in the extent of the seawater intrusion were weighted using the Analytic Hierarchy Process (AHP) method. The results of the AHP method showed that the criterion of efficiency of applying of curative solutions in improvement of the aquifer's water level with the weight of 0.311 was the most important one. Three multi-criteria decision making methods namely, Simple Additive Weighting (SAW), Technique for Order Performance by Similarity (TOPSIS), and VIse Kriterijumska Optimizacija kompromisno Resenje (VIKOR) were utilized to select the best curative solution. The solution of 10% reduction of pumping rate and the construction of Gelvard dam in the SAW and TOPSIS methods and the solution of 3% reduction of pumping rate and the construction of Gelvard dam in the VIKOR method ranked first. Combined techniques namely, the Rank Average Method, Borda's Method, and Copeland's Method were used to develop a consensus on prioritizing curative solutions for the Tajan Aquifer. The results of these techniques showed that the solution of 10% reduction in pumping rate along with the construction of the Gelvard dam was the best. The results of simulating this solution demonstrated a 1.91 m improvement in the groundwater level of the aquifer in the MODFLOW code and a 361.5-m recede in seawater intrusion length along the coast in the SEAWAT code.
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Agua Subterránea , Toma de Decisiones , Monitoreo del Ambiente , Irán , Agua de Mar , AguaRESUMEN
The objective of the present study was to investigate the concentration of metals (cadmium, lead, chromium, zinc, copper, and iron) were measured in groundwater at 30 sites from the Birjand flood plain of eastern Iran during the November 2010; identify any relationships between metals and pH, total hardness. Metal concentrations in the groundwater samples were decreased in sequence of Zn > Fe > Cu > Cr > Pb > Cd, respectively. The results showed that the overall mean concentrations of Cd, Pb, and Cr were at 0.000, 0.023, and 0.049 mg l(-1), respectively. The mean concentration of Cu, Zn, and Fe were 0.109, 0.192, and 0.174 mg l(-1), respectively. Results also indicated that there were correlations among Cd, Cu, and Zn metals.