Development of DRASTIC Method Considering Land Use to Analyze the Potential of Aquifer Pollution in Semi-Arid Regions

Groundwater vulnerability assessment is important in order to prioritize these resources from the perspective of exploitation, management and control of pollution in different areas. The purpose of this study was to evaluate the qualitative vulnerability of Birjand plain aquifer using DRASTIC-LU model. In this research, the DRASTIC base model with the land use parameter of the developed lands was used. In this method, the basic model parameters including groundwater depth, net nutrition, aquifer environment, soil type, topography, unsaturated area constituents, and hydraulic guidance were analyzed in GIS environment along with land use variable as a model development based on standard weights and the vulnerability zoning map was prepared. Vulnerability zoning map of DRASTIC-LU model showed that 62.27, 25.07, 17.17, and 2.38% of the area have low to medium, medium to high, low and high vulnerability, respectively. In addition, the sensitivity analysis of the model used to evaluate the assigned weights was performed. To validate the model, the correlation of the model with the nitrate concentration was performed; the obtained correlation of 86% indicated the appropriate correlation of this model with the nitrate concentration as an indicator of groundwater pollution

GIS-Based Flood Risk Zoning Based On Data-Driven Models

Increasing the occurrence of floods, especially in cities, and the risks to human, financial, and environmental risks due to its, make flood risk zoning of great importance. The purpose of this study is to estimate the flood risk of the Maneh and Samalghan based on determining effective criteria and spatial and non-spatial data-driven models. The criteria used in this research include Modified Fournier Index, Topographic Position Index, Curve Number, Flow Accumulation, Slope, Digital elevation model, Topographic Wetness Index, Vertical Overland Flow Distance, Horizontal Overland Flow Distance, and Normalized difference vegetation index. The novelty of this study is to present new combination approaches to determine the effective criteria in flood risk zoning (Maneh and Samalghan). In this regard, the geographically weighted regression (GWR) with exponential and bi-square kernels and artificial neural network (ANN) combined with a binary particle swarm optimization algorithm (BPSO). The best value of the fitness function (1-R2) for ANN, GWR with the exponential kernel, and GWR with bi-square kernel was obtained 0.1757, 0.0461, and 0.0097, respectively, Which indicates higher compatibility of the bi-square kernel than the other models. It was also found that the criteria used have a significant effect on the rate of flooding in the study area

Geostatistical Evaluation with Drinking Groundwater Quality Index (DGWQI) in Birjand Plain Aquifer

Groundwater is the main source of drinking water in the semi-arid regions of Iran. Therefore, monitoring the quality of this valuable resource is vital. Hence, the purpose of this study was to investigate and prepare a groundwater quality map of Birjand located in the semi-arid region of eastern Iran using GIS-based geostatistical analysis with Drinking Groundwater Quality Index (DGWQI). For this purpose, the collected groundwater quality data of 27 agricultural wells during the years 2014-2019 were used. The results of spatial analysis show that 63% of the aquifer area was in the appropriate quality category, 18% in the poor category, 10% in the very poor category and 9% of the aquifer area was in the non-drinking category. Sensitivity analysis indicated that Mg2+, EC, and TDS parameters with the highest mean change index of 18.98, 20.68 and 19.04 were the most sensitive parameters in calculating DGWQI, respectively. Error evaluation calculated by R2 and RMSE methods on conventional kriging and spherical variogram models showed good performance for spatial analysis of all parameters including DGWQI, Mg2+, EC, and TDS. The DGWQI map shows that the western and southwestern parts of the aquifer do not have good quality conditions for extracting drinking water