IntroductionFinding the Potential of Groundwater resources is one of the basic principles in water resources management. The aim of this research is to determine the Potential of Groundwater using support vector machine learning (SVM) models as well as metaheuristic algorithms (hybrid support vector machine model and the bee metaheuristic optimization algorithm (SVM-BA) and hybrid model of the support vector machine and particle swarm optimization algorithm (SVM-PSO).Materials and methodsThe factors of elevation, slope, aspect, topographic humidity index, distance from stream, drainage density, distance from fault, lithology, topographic position index, land roughness index, relative slope position and flow convergence index were selected in Bojnurd region. Information on the location of 359 springs was received from the regional water company. Random division algorithm was used to divide training points (70%) and validation points (30%). Based on the removal sensitivity analysis, the importance and contribution of the input variables in determining the Groundwater Potential were determined. The accuracy of the models was evaluated in two stages of training and validation based on the receiver operating characteristic (ROC) curve method.ResultsThe evaluation of the accuracy of the models based on the evaluation criteria of the area under curve (AUC) showed that the prediction accuracy of the hybrid model of the support vector machine and the particle swarm optimization algorithm (SVM-PSO) is 0.945 more than other models (SVM: 0.918 and SVM-BA: 0.932). Based on the results of the superior model, the high Potential class and the very high Potential class accounted for 7.75% and 38.66% of the area respectively. Among the factors, relative slope position with 14.5%, distance from the fault with 13.4% and lithology with 12.3% were the most important in predicting Groundwater Potential.Discussion and ConclusionBased on the results of this research, the support vector machine model has a high performance, and two optimization algorithms, the bee metaheuristic and particle swarm optimization algorithm, strengthen the predictive power of the model. Also machine learning models can identify the relationship between the environmental factors and the water supply of the springs and determine their role by using the available data. The relative slope position factor was identified as the most important variable and the distance from the fault factor was considered as the second most important variable in the present study. The results of the research showed that the faults in the region play an important role in aquifer recharge, storage and flow of Groundwater. The lithological factor was also introduced by the model as the third important variable in identifying the state of Groundwater Potential. In this research, by presenting the Groundwater Potential map, it is possible to plan and verify land use planning for the Bojnurd watershed.

Exploration of Groundwater resources requires recognition of regions and their Potential sources. Because of high importance in the karstic regions and their significant role in providing needed water, efforts to explore new sources of Karst, is inevitable. Checking discontinuities is always an important issue in karst studies. Because of high discontinuities in rock masses, permeable areas will be created, they cause appropriate Groundwater paths to flow. Recognition of these regions is possible through geophysical methods based on physical characteristics of these areas such as density or resistivity. Using geophysical methods in water and geotechnical methods has less history to oil field investigations and mining exploration, but has been accelerated in recent years. In this research we have tried to investigate the usage of various geophysical methods, such as how to detect and identify underground water using these methods. We can noted of  geophysical applied methods for Groundwater potentiometric such as geoelectric methods, ground penetrating radar, electromagnetic, gravitometry, magnetic and seismic surveys.

Determination of corrosion and scaling Potential is one of the most important quality aspects of Groundwater resources in different uses. Therefore, the aim of this research work was to determine the corrosion and scaling Potential of Marvdasht Plain Groundwater using Langelier saturation and Ryznar stability indices and their mapping through GIS. For this purpose, 49 agricultural wells were sampled for five years and total hardness (TH), total dissolved solids (TDS), total alkalinity (TA) and pH were measured. The ordinary kriging geostatistical method was applied for mapping the Langelier saturation and Ryznar stability indices and their components. The results showed that the spherical model was most fitted for these indices. The eefective domin varied from 15752 to 32711 m for the components and the spatial correlation class changed from good to fair. The mean Langelier index was 0. 58 showing low to fair scaling Potential. The mean Ryznar index was 6. 2 indicating low corrosion Potential of Marvdasht Plain Aquifer. Based on the zoning maps, the northern parts of the area showed the highest TH and TDS components followed by Langelier index, showing fair scaling Potential. In this part, the effect of carbonate formations was evaluated as the probable contributor of the increasing the Langelier index. In general, the Marvdasht Groundwater has fair quality in terms of corrosion and scaling Potential.

Developing trend in South Khorasan Province in recent years in one hand and being located in arid and semi-arid areas on the other hand demands for effective water resource strategies more than ever. One strategy for water resources management is to identify areas with different water Potentials so that to allocate them according to their capacity. The goal of this research was the water Potential zonation in South Khorasan Province using effective factors in Groundwater aquifer recharge by the help of fuzzy logic and GIS technics. Sixteen factors were used in 4 groups (geology, hydrology, geography and human) each classified in 5 classes from low to very high Potential. Finally 43 basins of the province were classified based on the Groundwater Potential maps. The results were then correlated with the data from the exploration wells. The water Potential map of the province was accordingly prepared. The results showed that about 17% (27×103 km2) of the province area have a high or very high water Potential classes that match with the quaternary sediments and areas with high fracture density. Also very low Potential class correlate with high areas, hard lithology, and desert areas.

Climate change is probably going to affect Groundwater resources, in Sub-Saharan ccountries (SSA) in Africa either directly, by means of changing precipitation patterns, or indirectly through the combination of changing precipitation patterns with evolving land-use practices and water request. West Africa has, over the past few decades, experienced a sharp decline in rainfall and average annual flow of watercourses. A break in the rainfall pattern was observed around 1968-1972. 1970 is considered as the turning point after which the decline in average rainfall worsened from minus 15% to minus 30% depending on the zone. This situation led to the drifting of isohyets by about 200 km to the south. A 1° C increment in temperature could change overflow by 10%, expecting that precipitation levels stay consistent. Any reduction in Groundwater recharge will intensify the impact of sea-level rise in coastal aquifers. For various reasons and at various levels, West African countries are dependent on one another. Over the past few decades, this interdependence has not only generated tension, but has also led to a dialogue and cooperation process. Only one country (Burkina Faso) are below the international standard for water scarcity (1, 700 m3 of renewable fresh water per year per person); On the other hand, there are major problems in terms of availability at the desired time and place. According to the Global Water Partnership, the withdrawal level of renewable water resources in West Africa (excluding Cameroon and Chad) is currently at 11 billion m3 per year for an available 1, 300 billion m3, which is less than 1%. Agriculture uses 75% of these withdrawals, domestic consumption 17%, and industry 7%. Although it is by far the highest in proportion, agricultural use of water resources is low. Out of the 75. 5 million hectares of arable land in West Africa, only 1. 2% (917, 000 ha) is developed for irrigation, and 0. 8% (635, 000 ha) is used effectively.

Extended Abstract Introduction: Drought and population increase are important factors that have caused more attention to ground water. Groundwater is one of the most valuable natural resources that affect human health, economic development and environmental diversity. Due to several inherent characteristics, these waters have become a very important and reliable source of water supply in developed and developing countries. Over the years, the importance of ground water due to the ever-increasing need for water has led to unscientific exploitation of ground water and the creation of water stress conditions. This alarming situation requires a cost-effective technique for proper assessment of Groundwater resources and planning for the management of these resources. Geographic information system (GIS) and hierarchical analysis are samples of these tools. The purpose of this research is to prepare the ground water Potential map using hierarchical analysis in the Ilam Dam watershed. Materials and Methods: For this purpose, seven criteria of geology, slope, land use, soil, drainage density, lineament and precipitation were selected to identify the Potential areas of ground water. The selection of these parameters is due to the effect that each of these factors has on the ground water. Geological features are important in controlling the infiltration of water into the ground due to the weathering, porosity and fracture that occur in them. On the other hand, increasing the slope of the land causes an increase in runoff. As drainage density increases, permeability decreases. Agricultural, forest and pasture land use can increase infiltration, but residential areas increase runoff due to impervious surfaces. Sandy and loamy soils have a high permeability coefficient, and finally, the higher the rainfall in the region, the higher the Groundwater level. In order to prepare these layers, ArcGIS and remote sensing (RS) were used. First, by using the digital elevation model (DEM), the slope of the area, the drainage density in five classes were prepared. By using Landsat 8 satellite images of 2020 and in the environment of RS software, the land use of the region was created in five classes of agriculture, forest, pasture, bare soil and residential areas using a supervised classification method. Kappa coefficient confirmed 93% classification accuracy. The rainfall map of the watershed was also obtained from the synoptic and rain gauge station that existed in and around the basin. Finally, the geology map was prepared from the digital geological map in the GIS environment and the soil map from the Natural Resources Organization. After preparing these layers in the GIS, using the opinion of experts regarding the valuation of these criteria, each of these criteria was given grades from 1 to 9. Then, this valuation was transferred to Expert Choice software to determine the weight, and the weight of each criterion was obtained. Then, using these weights as well as raster layers created in the GIS environment and using the weighted overlay method, these layers were superimposed and the ground water Potential map was obtained. Results: The results showed that geology criteria and land use have the most weight with 0. 347 and 0. 191, respectively, and soil and precipitation with 0. 062 and 0. 054 have the least importance for ground water Potential. A big part of the watershed has medium to high Potential for ground water. This part has a lot of forest and pasture cover, moderate slope (20-40 degrees) and high drainage density and high amount of precipitation, which is consistent with the results of Suri et al. (2016). A significant part of the basin has loam and sand soil, which have high permeability and can absorb water and increase the Groundwater level. Kazhdomi formation has medium to high Potential and Bangestan group formation has low Potential. Discussion and Conclusion: In general, the final map has four Potentials, including very low, low, medium to high, and very high, which respectively account for 0. 98%, 41. 8%, 55. 9%, and 1. 32% of the study area. Medium to high Potential has the largest area. In general, the north of the watershed has medium to high Potential, the south of the watershed has low Potential, and a small part of the east of the study area has high Potential of ground water. Preparing a map of ground water Potential in watersheds can be a suitable strategy for exploiting these resources.