نویسندگان | Mohammad Akbari,, |
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نشریه | Journal of Beijing University of Technology |
شماره صفحات | 1338-1359 |
شماره سریال | 47 |
شماره مجلد | 12 |
نوع مقاله | Full Paper |
تاریخ انتشار | 2021 |
رتبه نشریه | ISI |
نوع نشریه | چاپی |
کشور محل چاپ | چین |
نمایه نشریه | Scopus |
چکیده مقاله
Assessment of groundwater vulnerability to prioritize these resources from the perspective of exploitation, management, and control of pollution in different areas is important. The purpose of this study is to estimate groundwater vulnerability (nitrate concentration) of the Birjand plain aquifer based on DRASTIC-LU parameters and spatial and non-spatial data-driven methods. The novelty of this study is to present new combination approaches to determine the effective DRASTIC-LU parameters in groundwater vulnerability zoning (Birjand plain aquifer). In this regard, geographically weighted regression (GWR) with exponential and bi-square kernels and artificial neural network (ANN) were combined with a binary particle swarm optimization algorithm (BPSO). The best value of the fitness function (1-R2) for ANN, GWR with exponential kernel, and GWR with bi-square kernel was obtained 0.1060, 0.07453, and 0.0069, respectively, Which indicates higher compatibility of the bi-square kernel than the other methods. It was also found that the DRASTIC-LU parameters have a significant effect on the rate of groundwater vulnerability and estimation of the nitrate concentration in the study area.
tags: groundwater vulnerability; DRASTIC-LU parameters; geographically weighted regression (GWR); artificial neural network (ANN); binary particle swarm optimization (BPSO) algorithm; data-driven models