H
Hossein Zeinivand
Researcher at Lorestan University
Publications - 32
Citations - 1536
Hossein Zeinivand is an academic researcher from Lorestan University. The author has contributed to research in topics: Watershed & Surface runoff. The author has an hindex of 12, co-authored 32 publications receiving 1017 citations. Previous affiliations of Hossein Zeinivand include Vrije Universiteit Brussel & United States Department of Agriculture.
Papers
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Journal ArticleDOI
Groundwater potential mapping at Kurdistan region of Iran using analytic hierarchy process and GIS
Omid Rahmati,Aliakbar Nazari Samani,Mohamad Mahdavi,Hamid Reza Pourghasemi,Hossein Zeinivand +4 more
TL;DR: In this article, a standard methodology has been applied to delineate groundwater resource potential zonation based on integrated analytical hierarchy process (AHP), geographic information system (GIS), and remote sensing (RS) techniques in Kurdistan plain, Iran.
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Flood susceptibility mapping using frequency ratio and weights-of-evidence models in the Golastan Province, Iran
TL;DR: In this article, the authors investigated the application of the frequency ratio (FR) and weights-of-evidence (WofE) models for flood susceptibility mapping in the Golestan Province, Iran.
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Flood hazard zoning in Yasooj region, Iran, using GIS and multi-criteria decision analysis
TL;DR: In this article, the authors assess the efficiency of analytical hierarchical process (AHP) to identify potential flood hazard zones by comparing with the results of a hydraulic model, and the normalized weights of criteria/parameters were determined based on Saaty's nine-point scale and its importance in specifying flood hazard potential zones using the AHP and eigenvector methods.
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Spatial prediction of flood-susceptible areas using frequency ratio and maximum entropy models
TL;DR: In this paper, the authors investigate the application of modeling the flood in watersheds and reducing the damages caused by this natural disaster, which is one of the primary objectives of watershed management.
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Applicability of generalized additive model in groundwater potential modelling and comparison its performance by bivariate statistical methods
TL;DR: In this paper, the authors evaluated the performance of the generalized additive model (GAM) and compared it with three popular GIS-based bivariate statistical methods, namely Frequency Ratio (FR), Statistical Index (SI) and Weight-of-Evidence (WOE), for producing groundwater spring potential map (GSPM) in Lorestan Province Iran.