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M. Reza Ghanbarpour

Researcher at Trinity College (Connecticut)

Publications -  14
Citations -  242

M. Reza Ghanbarpour is an academic researcher from Trinity College (Connecticut). The author has contributed to research in topics: Floodplain & Autoregressive integrated moving average. The author has an hindex of 9, co-authored 14 publications receiving 218 citations. Previous affiliations of M. Reza Ghanbarpour include Alberta Environment & Trinity College, Dublin.

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Floodplain Inundation Analysis Combined with Contingent Valuation: Implications for Sustainable Flood Risk Management

TL;DR: In this paper, the authors presented the results of open-ended contingent valuation method (CVM) to estimate the residents' maximum willingness to pay (WTP) for flood insurance and structural flood control measures in the Neka River Basin in Northern Iran.
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Floodplain Mapping Using Hydraulic Simulation Model in GIS

TL;DR: In this article, a methodology was applied to integrate hydraulic simulation model, HEC-RAS and GIS analysis for delineation of flood extents and depths within a selected reach of Zaremroud River in Iran Floodplain modeling is a recently new and applied method in river engineering discipline and is essential for prediction of flood hazards.
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Stochastic modeling of surface stream flow at different time scales: sangsoorakh karst basin, iran

Abstract: Karstic watersheds are one of the most important areas for water supply. Because the role of groundwater contribution to surface water flow in karst watersheds is not well understood, the commonly used hydrologic models in most regular basins do not provide satisfactory estimates of runoff in karstic regions. This paper uses time-series analysis to model karstic flow in the Sangsoorakh karst drainage basin in the Karkheh subbasin of southwest Iran. The comparison of model forecasting performance was conducted based upon graphical and numerical criteria. The results indicate that autoregressive integrated moving average (ARIMA) models perform better than deseasonalized autoregressive moving average (DARMA) models for weekly, monthly and bimonthly flow forecasting applications in the study area.
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Spatial variability of heavy metals in surficial sediments: Tajan River Watershed, Iran

TL;DR: In this paper, the authors assessed the spatial distribution of heavy metal concentrations (Al, As, Cd, Co, Cr, Cs, Fe, Ni, Sn and Zn) in the sediments of the Tajan River Watershed.
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Prioritizing Long-term Watershed Management Strategies Using Group Decision Analysis

TL;DR: In this paper, an integrated framework for prioritizing watershed management strategies is proposed and a case study is employed to highlight the challenges of using group decision analysis in strategic planning and to illustrate the interaction between different stakeholders on watershed issues.