Application of artificial intelligence in groundwater ecosystem protection: a case study of Semnan/Sorkheh plain,Iran

Groundwater ecosystems have unparalleled environmental value. Accurate modeling of groundwater level (GWL) fluctuations is a vital requirement for the protection of the groundwater ecosystems. The GWL modeling is a challenge due to complexities of the underground geological structure. Among the various modeling methods, artificial intelligence (AI)-based approaches serve as desirable alternatives due to their distinctive and potent properties. One of the most practical AI-based approaches is an artificial neural network (ANN) model. The purpose of the current study was to apply time delay neural networks (TDNN) with different network structures and input delays to model the GWL fluctuations. The variables used in the construction and validation of the models were average weekly GWL from January 2002 to January 2013 in two monitoring sites in Semnan/Sorkheh plain, Iran. The study area is an arid region, where overutilization of groundwater threatens the water security in this area. The computational results of the current research demonstrated that the TDNN model is a practical tool in modeling time-series GWL compared to the other state-of-the-art AI-based approaches. Future studies are recommended to explore application of proposed model for more sustainable and effective Groundwater Resources Management (GWRM).

     

Fuzzy AHP approach for prioritizing electronic waste management options: a case study of Tehran,Iran

Environmental Science and Pollution Research - Electronic waste (E-waste) can be considered as challenging solid waste streams especially in some developing countries, including Iran. Several...     

Application of analytical hierarchy process (AHP) to assess options of energy recovery from municipal solid waste: a case study in Tehran,Iran

Journal of Material Cycles and Waste Management - In the current study, a model was established based on AHP method for assessment of different alternatives for energy recovery from the waste in...