Saman Razavi
Cited by
Cited by
Review of surrogate modeling in water resources
S Razavi, BA Tolson, DH Burn
Water Resources Research 48 (7), 2012
What do we mean by sensitivity analysis? The need for comprehensive characterization of “global” sensitivity in E arth and E nvironmental systems models
S Razavi, HV Gupta
Water Resources Research 51 (5), 3070-3092, 2015
Numerical assessment of metamodelling strategies in computationally intensive optimization
S Razavi, BA Tolson, DH Burn
Environmental Modelling & Software 34, 67-86, 2012
A new framework for comprehensive, robust, and efficient global sensitivity analysis: 1. Theory
S Razavi, HV Gupta
Water Resources Research 52 (1), 423-439, 2016
A new formulation for feedforward neural networks
S Razavi, BA Tolson
IEEE Transactions on neural networks 22 (10), 1588-1598, 2011
Progressive Latin Hypercube Sampling: An efficient approach for robust sampling-based analysis of environmental models
R Sheikholeslami, S Razavi
Environmental Modelling & Software 93, 109-126, 2017
Introductory overview: Optimization using evolutionary algorithms and other metaheuristics
HR Maier, S Razavi, Z Kapelan, LS Matott, J Kasprzyk, BA Tolson
Environmental modelling & software 114, 195-213, 2019
Evaluation of Integrated Multisatellite Retrievals for GPM (IMERG) over southern Canada against ground precipitation observations: A preliminary assessment
ZE Asong, S Razavi, HS Wheater, JS Wong
Journal of hydrometeorology 18 (4), 1033-1050, 2017
Toward understanding nonstationarity in climate and hydrology through tree ring proxy records
S Razavi, A Elshorbagy, H Wheater, D Sauchyn
Water Resources Research 51 (3), 1813-1830, 2015
Inter-comparison of daily precipitation products for large-scale hydro-climatic applications over Canada
JS Wong, S Razavi, BR Bonsal, HS Wheater, ZE Asong
Hydrology and Earth System Sciences 21 (4), 2163-2185, 2017
Reducing the computational cost of automatic calibration through model preemption
S Razavi, BA Tolson, LS Matott, NR Thomson, A MacLean, FR Seglenieks
Water Resources Research 46 (11), 2010
VARS-TOOL: A toolbox for comprehensive, efficient, and robust sensitivity and uncertainty analysis
S Razavi, R Sheikholeslami, HV Gupta, A Haghnegahdar
Environmental modelling & software 112, 95-107, 2019
Revisiting the basis of sensitivity analysis for dynamical earth system models
HV Gupta, S Razavi
Water Resources Research 54 (11), 8692-8717, 2018
Enhanced identification of a hydrologic model using streamflow and satellite water storage data: A multicriteria sensitivity analysis and optimization approach
F Yassin, S Razavi, H Wheater, G Sapriza‐Azuri, B Davison, A Pietroniro
Hydrological Processes 31 (19), 3320-3333, 2017
An efficient framework for hydrologic model calibration on long data periods
S Razavi, BA Tolson
Water Resources Research 49 (12), 8418-8431, 2013
Introductory overview of identifiability analysis: A guide to evaluating whether you have the right type of data for your modeling purpose
JHA Guillaume, JD Jakeman, S Marsili-Libelli, M Asher, P Brunner, ...
Environmental Modelling & Software 119, 418-432, 2019
Historical drought patterns over Canada and their teleconnections with large-scale climate signals
ZE Asong, HS Wheater, B Bonsal, S Razavi, S Kurkute
Hydrology and Earth System Sciences 22 (6), 3105-3124, 2018
Long‐lead seasonal rainfall forecasting using time‐delay recurrent neural networks: a case study
M Karamouz, S Razavi, S Araghinejad
Hydrological Processes: An International Journal 22 (2), 229-241, 2008
Global sensitivity analysis for high-dimensional problems: How to objectively group factors and measure robustness and convergence while reducing computational cost
R Sheikholeslami, S Razavi, HV Gupta, W Becker, A Haghnegahdar
Environmental modelling & software 111, 282-299, 2019
Multicriteria sensitivity analysis as a diagnostic tool for understanding model behaviour and characterizing model uncertainty
A Haghnegahdar, S Razavi, F Yassin, H Wheater
Hydrological processes 31 (25), 4462-4476, 2017
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