Prof. Vahid Nourani received his B.Sc. and M.S. degrees in Civil Engineering from University of Tabriz, Iran in 1998 and 2000, respectively. He then continued his graduate study in Civil and Environmental Engineering in the field of Hydrology at Shiraz University, Iran and Tohoku University, Japan and was graduated in 2005. Prof. Nourani was with the Faculty of Civil Engineering, University of Tabriz from 2005; with Department of Civil Engineering, University of Minnesota, USA at 2011 as visiting Associate Professor and as Adjunct Professor with Near East University (Cyprus) and Charles Darwin University (Australia) from 2017 and 2022, respectively. In this period, 101 Ph.D. and M.S. students were graduated under his technical supervision. His research interests include rainfall-runoff modeling, Artificial Intelligence applications to hydro-environmental engineering, Hydroinformatics and computational hydraulics. His researches outcomes have been published as 252 Journal articles, 2 books, 16 book chapters, more than 200 papers presented in international and national conferences and 7 international projects. Currently he is Editor-in-Chief for Journal of Civil & Env. Eng. (Tabriz Univ.), Associate Editor for Journal of Hydrology and AQUA (IWA), Guest Editor for several JCR Journals, and director of Excellence Center in Hydroinformatics. In 2021, Prof. Nourani was ranked as 11035 among world’s top 2% scientists reported by the Stanford University and in 2022 he was granted the PIFI’s professorial fellowship of Chinese Academy of Science.He has H-index 52. He currently is a visiting professor in DPRI at Kyoto University, Japan.
Application of softcomputing for validation of water distribution network models
In order to make correct and reliable management decisions, it is necessary and inevitable to obtain the variation of possible results in water distribution networks and also knowing the uncertainty of the desired parameters. The purpose of this research is to investigate the uncertainty of model parameters in qualitative simulation of urban water distribution networks to achieve accurate design of urban infrastructure and their maximum utilization. To this purpose, the hydraulic and qualitative parameters of the network including Hyzen-Williams coefficient, pipe diameter, node demand, wall and bulk decay coefficients were considered as uncertain parameters. For evaluation of the network reliability, nodal pressure reliability index (NPRI) and nodal chlorine reliability index (NCRI) with different coefficients of variation (CV) were used. For calibrating and modelling the proposed method, Kaleybar City water distribution network was considered as a case study. The results show that by using these methods based on data uncertainty, possible future adverse conditions can be predicted more quickly and accurately as a probabilistically.
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