Plenary Lecture

Watershed Land Use – Land Cover Changes Detection Using an Inverse Method

Professor Vahid Nourani
Department of Water Resources Engineering
Faculty of Civil Engineering
University of Tabriz
Iran
E-mail: nourani@tabrizu.ac.ir

Abstract: This research investigated Land Use and Land Cover (LULC) changes and its effect on outlet runoff via an inverse method. For this purpose, a conceptual Rainfall-Runoff model was applied to the delineated sub-watersheds of the basin to generate different outflows by altering the Storage Coefficient (SC) of the model for each sub-watershed as the representative of LULC. Then, the relation between SC values and outflow time series was simulated by artificial neural network (ANN) and method. In this way, in order to ignore redundant information and reduce the dimension of input vector, Wavelet-Entropy (WE) values of the outflow sub-series were computed and used as the inputs of the ANN model to compute SCs of the subwatersheds as the outputs. The trained multi-output ANN model as an inverse method could be then used to predict the SC values (as representative of LULC) of the sub-watersheds using the observed time series of runoff at the outlet. The obtained results showed that the proposed inverse method could reliably detect not only the location but also the severity of LULC changes by prediction of SC values in the coming future years. For validation of the method, a comparison was also performed between the obtained results and recorded changes via normalized difference vegetation index (NDVI) and land use classification, extracted from Landsat images. The comparison approved the ability of the proposed method for LULC change detection in a way that deforestation and cropland increasing of the sub-watersheds from 1990 to 2013 were aligned with the SC reduction e.g., 26% decrease of SC for downstream sub-watershed versus 53% decrease and 21% increase of forest and crop lands, respectively.

Brief Biography of the Speaker: 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 as an Assistant Professor from 2005- 2009; as Associate Professor from 2009-2014; as a Professor from 2014 and with Dept. of Civil Eng., University of Minnesota, USA at 2011 as visiting associate professor. In this period, 63 Ph.D. and M.S. students were graduated under his technical supervision. His research interests include rainfall-runoff modeling, Artificial Intelligence applications to water resources engineering, Hydroinformatics and computational hydraulics. His researches outcomes have been published as 102 Journal articles, 2 books, 7 book chapters and more than 120 papers presented in international and national conferences. Currently he is Associate Editor for Journal of Hydrology and director of Excellence Center in Hydroinformatics at Tabriz University.

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