Monitoring network design with MLPG-TLBO hybrid model (case study Birjand, Iran)

Abstract As the groundwater quantitative monitoring aimed to determine factors affecting aquifer behavior plays an important role in its regional management, studying temporal and spatial level variations requires a comprehensive network. Effort has been made this study introduce new linked simulation–optimization method, named MLPG-TLBO quantitatively monitor Birjand optimal points for piezometers. This model uses meshless local Petrov Galerkin (MLPF) method simulation part teaching–learning-based optimization (TLBO) part. The objective function, study, is minimize difference between observed piezometers obtained computationally by model. Since coupled independent from meshing, it eliminates mesh-dependent shortcomings and, hence, yields more accurate results. It calibrated validated previous area studies led acceptable By implementing aquifer, positions of ten were determined mostly areas where density extraction wells was lower. Finally, RMSE both FDM be 0.334 m 1.483 10 value shown 0.423 reduction compared value. quite meaningful as shows good performance designing network aquifer.