206 Publications (Page 8 of 9)
2008
Toward Improved Hydrologic Prediction with Reduced Uncertainty Using Sequential Multi-Model CombinationMoradkhani, H.⋅Moradkhani, Hamid⋅Hsu, K.⋅Hsu, K.⋅Sorooshian, S. and Sorooshian, S.American Society of Civil Engineers
2006
Investigating the impact of remotely sensed precipitation and hydrologic model uncertainties on the ensemble streamflow forecastingMoradkhani, Hamid⋅Hsu, K.⋅Hong, Yang and Sorooshian, SorooshGeophysical Research Letters, vol. 33, (no. 12), pp. [n.p.], 2006.
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Uncertainty quantification of satellite precipitation estimation and Monte Carlo assessment of the error propagation into hydrologic responseHong, Yang⋅Hsu, Kuo Lin⋅Moradkhani, Hamid and Sorooshian, SorooshWater Resources Research, vol. 42, (no. 8), pp. W08421 (15 p, 2006.
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2004
Improved streamflow forecasting using self-organizing radial basis function artificial neural networksMoradkhani, Hamid⋅Hsu, K.-l.⋅Gupta, Hoshin and Sorooshian, SorooshJournal of Hydrology (Amsterdam), vol. 295, (no. 14), pp. 246-262, 2004.
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Improved streamflow forecasting using self-organizing radial basis function artificial neural networksMoradkhani, Hamid⋅Hsu, K.-l.⋅Gupta, Hoshin and Sorooshian, SorooshJournal of Hydrology, vol. 295, (no. 1-4), pp. 246-262, 2004.
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n.d.no date or unknown
3D estimation of metal elements in sediments of the Caspian Sea with moving least square and radial basis function interpolation methodsZarif Sanayei, H.R.⋅Talebbeydokhti, N. and Moradkhani, H.(no. 5), pp. 1661-1673, 2015.
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A hierarchical Bayesian approach for the analysis of climate change impact on runoff extremesNajafi, M.R. and Moradkhani, H.(no. 26), pp. 6292-6308, 2014.
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Analysis of dam-induced cyclic patterns on river flow dynamicsTongal, H.⋅Demirel, M.C. and Moradkhani, H.(no. 4), pp. 626-641, 2017.
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A regional Bayesian hierarchical model for flood frequency analysisYan, H. and Moradkhani, H.(no. 3), pp. 1019-1036, 2014.
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Assessing model state and forecasts variation in hydrologic data assimilationSamuel, J.⋅Coulibaly, P.⋅Dumedah, G. and Moradkhani, H.pp. 127-141, 2014.
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Assessing the impact of CMIP5 climate multi-modeling on estimating the precipitation seasonality and timingDemirel, M.C. and Moradkhani, H.(no. 2), pp. 357-372, 2016.
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Bayesian Model Averaging for Flood Frequency AnalysisYan, H. and Moradkhani, H.(pp. 1886-1895). 2014
Combined assimilation of streamflow and satellite soil moisture with the particle filter and geostatistical modelingYan, H. and Moradkhani, H.pp. 364-378, 2016.
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Daily discharge forecasting using least square support vector regression and regression treeSahraei, Sh.⋅Zare Andalani, S.⋅Zakermoshfegh, M.⋅Nikeghbal Sisakht, B.⋅Talebbeydokhti, N. and Moradkhani, H.(no. 2), pp. 410-422, 2015.
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Drought analysis under climate change using copulaMadadgar, S. and Moradkhani, H.(no. 7), pp. 746-759, 2013.
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Ensemble combination of seasonal streamflow forecastsNajafi, M.R. and Moradkhani, H.(no. 1), 2016.
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Ensemble prediction and data assimilation for operational hydrologySeo, D.-J.⋅Seo, Dong Jun⋅Liu, Yuqiong⋅Liu, Y.⋅Moradkhani, Hamid⋅Moradkhani, H.⋅Weerts, A. and Weerts, Albrecht(no. PD), pp. 2661-2662, 2015.
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Examining the Reliability of Hydrologic Drought-Risk Forecasting at Seasonal TimescalesDeChant, C. and Moradkhani, H.(pp. 2336-2346). 2014
General Review of Rainfall-Runoff Modeling: Model Calibration, Data Assimilation, and Uncertainty AnalysisMoradkhani, Hamid and Sorooshian, Soroosh(pp. 1–24). Springer Berlin Heidelberg
Hydrologic modeling in dynamic catchments: A data assimilation approachPathiraja, S.⋅Marshall, L.⋅Sharma, A. and Moradkhani, H.(no. 5), pp. 3350-3372, 2016.
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Improved Bayesian multimodeling: Integration of copulas and Bayesian model averagingMadadgar, S. and Moradkhani, H.(no. 12), pp. 9586-9603, 2014.
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Improving soil moisture profile prediction with the particle filter-Markov chain Monte Carlo methodYan, H.⋅DeChant, C.M. and Moradkhani, H.(no. 11), pp. 6134-6147, 2015.
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Multi-model ensemble analysis of runoff extremes for climate change impact assessmentsNajafi, M.R. and Moradkhani, H.pp. 352-361, 2015.
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