Papers in review

Montzka, C., J. Grant, H. Moradkhani, H. Hendricks Franssen, L. Weihermüller, M. Drusch, and H. Vereecken, Estimation of radiative transfer parameters from SMOS brightness temperatures using data assimilation: implication on soil moisture retrieval, Vadose Zone Hydrology.

Moradkhani H., C.M. DeChant and S. Sorooshian, Evolution of Ensemble Data Assimilation for Uncertainty Quantification using the Particle Filter-Markov Chain Monte Carlo Method, Water Resources Research.

Liu, Y., A.H. Weerts, M. Clark, H.J. Hendricks Franssen, S. Kumar, H. Moradkhani, D.J. Seo, D. Schwanenberg, T. Goethals, P. Smith, R. Hartman, P. Restrepo, Toward Advancing Data Assimilation in Operational Hydrologic Forecasting and Water Resources Management: Current Status, Challenges, and Emerging Opportunities”, Hydrology and Earth System Science Discussion, Special Issue.

Madadgar, S., H. Moradkhani, and D. Garen, Towards Improved Reliability and Reduced Uncertainty of Hydrologic Ensemble Forecasts Using Multivariate Post-processing, Hydrological Processes.

Jaeger, W.K., A.J. Plantinga, H. Chang, G. Grant, D. Hulse, J. McDonnell, H. Moradkhani, A.T. Morzillo, P. Mote, A. Nolin, M. Santelmann, J. Wu, Toward a formal definition of water scarcity in natural-human systems, Water Resources Research.

Leisenring, M., and H. Moradkhani, Analyzing the Uncertainty of Suspended Sediment Load Prediction Using Sequential Data Assimilation, Journal of Hydrology.

Chang, H. I. Jung, A. Strecker, D. Wise, M. Lafranz, V. Shandas, H. Moradkhani, A. Yeakly, Y. Pan, R. Bean, G. Johnson, M. Psaris, Multidomensional Assessment of the Spatial Distribution of Water Resources Vulnerability in the Columbia River Basin, USA, Atmosphere and Ocean, special issue on Columbia River Basin.

Jung, I., H. Moradkhani, and H. Chang, Uncertainty Assessment of Climate Change Impact for Hydrologically Distinct River Basins, Journal of Hydrology.

Journal Papers

Najafi, M.R., and H. Moradkhani, T. Piechota (2012), Ensemble Streamflow Prediction: Climate Signal Weighting vs. Climate Forecast System Reanalysis, Journal of Hydrology, 442–443 (2012) 105–116.

Halmstad, A., M.R. Najafi, and H. Moradkhani (2012), Analysis of Precipitation Extremes with the Assessment of Regional Climate Models over the Willamette River Basin-U.S., Hydrological Processes, in Press.

Madadgar, S., and H. Moradkhani (2012), Drought Analysis under Climate Change using Copula, Journal of Hydrologic Engineering, in press.

DeChant, C. M., and H. Moradkhani (2012), Examining the Effectiveness and Robustness of Data Assimilation Methods for Calibration and Quantification of Uncertainty in Hydrologic forecasting,Water Resources Research, 48,W04518,doi:10.1029/2011WR011011.

Parrish, M., H. Moradkhani, C.M. DeChant (2012), Toward Reduction of Model Uncertainty: Integration of Bayesian Model Averaging and Data Assimilation, Water Resources Research,48, W03519, doi:10.1029/2011WR011116.

DeChant, C.M, and H. Moradkhani (2011), Improving the Characterization of Initial Condition for Ensemble Streamflow Prediction Using Data Assimilation, Hydrol. Earth Syst. Sci., 15, 3399-3410, doi: 10.5194/hess-15-3399.

Najafi, M., H. Moradkhani and I. Jung (2011),Assessing the Uncertainties of Hydrologic Model Selection in Climate Change Impact Studies, Hydrological Processes, 25(18), 2814-2826.

DeChant, C.M, and H. Moradkhani (2011), Radiance Data Assimilation for Operational Snow and Streamflow Forecasting using the Particle Filter, Advances in Water Resources, 34 (3), 351-364.

Jung, I., H. Chang, and H. Moradkhani (2011), Quantifying Uncertainty in Urban Flooding Analysis by Combined Effect of Climate and Land use Change Scenarios, Hydrology and Earth System Science 15, 617-633, doi:10.5194/hess-15-617.

Najafi, M.R., Z. Kavianpour, B. Najafi, M.R. Kavianpour, and H. Moradkhani, (2011), Air Demand in Gated Tunnels, a Bayesian Approach to Merge Various Predictions, Journal of Hydroinformatics, 14(1), 152–166, doi:10.2166/hydro.2011.108, 2011.

Risley, J., H. Moradkhani, L. Hay, and S. Markstrom (2011), Statistical Trends in Watershed Scale Response to Climate Change in Selected Basins Across the United States”, AMS Earth Interaction, 15, 617–633.

Najafi, M., Moradkhani H., and Wherry, S., (2011), Statistical Downscaling of Precipitation using Machine Learning with Optimal Predictor Selection, Journal of Hydrologic Engineering, 16(8), 650-664.

Montzka, C., H. Moradkhani, L. Weihermuller, M. Canty, H.J. Hendricks Franssen, H. Vereecken, (2011), Hydraulic Parameter Estimation by Remotely-sensed top Soil Moisture Observations with the Particle Filter, Journal of Hydrology, 399, 410–421.

Leisenring, M., H. Moradkhani (2011), Snow Water Equivalent Estimation using Bayesian Data Assimilation Methods, Stochastic Environmental Research and Risk Assessment, 25 (2), 253-270, DOI: 10.1007/s00477-010-0445-5.

Moradkhani H., R.G. Baird, and S. Wherry, (2010), Assesment of Climate Change Impact on Floodplain and Hydrologic Ecotones, Journal of Hydrology, 395, 264-278.

Moradkhani, H., and M. Meier (2010), Long-Lead Water Supply Forecast using Large-scale Climate Predictors and Independent Component Analysis", J. of Hydrologic Engineering,15(10), doi: 10.1061/ASCE-HE.1943-5584.0000246.

Ebtehaj, M., H. Moradkhani, and H.V. Gupta (2010), Improving Robustness of Hydrologic Parameter Estimation by the Use of Moving Block Bootstrap Resampling, Water Resources Research, 46, W07515, doi:10.1029/2009WR007981.

Sillars, D., H. Moradkhani, and N. Tymvios, (2010), Field Investigation of Success Factors of Fish Passageways in Oregon, Transportation Research Record, No., 2170, 9-17.

Hsu, K., H. Moradkhani, and S. Sorooshian (2009), A Sequential Bayesian Approach for Hydrologic Model Selection and Prediction", Water Resources Research, 45, W00B12, doi:10.1029/2008WR006824.

Moradkhani, H. (2008), Hydrologic Remote Sensing and Land Surface Data Assimilation", Sensors, 8, 2986-3004, DOI: 10.3390/s8052986.

Moradkhani, H. K. Hsu, Y. Hong, and S. Sorooshian, (2006), Investigating the Impact of Remotely Sensed Precipitation and Hydrologic Model Uncertainties on the Ensemble Streamflow Forecasting, Geophys. Res. Lett., Vol. 33, No. 12, L12401, 10.1029/2006GL026855.

Hong Y., K. Hsu, H. Moradkhani, and S. Sorooshian (2006), Uncertainty Quantification of Satellite Precipitation Estimation and Monte Carlo Assessment of the Error Propagation into Hydrologic Response, Water Resources Research, VOL. 42, W08421, doi:10.1029/2005WR004398.

Moradkhani, H., K. Hsu, H.V. Gupta, and S. Sorooshian (2005), Uncertainty Assessment of Hydrologic Model States and Parameters: Sequential Data Assimilation Using Particle Filter, Water Resources Research, 41, W05012, doi:10.1029/2004WR003604.

Moradkhani, H., S. Sorooshian, H.V. Gupta, and P. Houser (2005), Dual State-Parameter Estimation of Hydrological Models using Ensemble Kalman Filter, Advances in Water Resources, 28, 2,135-147.

Moradkhani, H., K. Hsu, H.V., Gupta, and S. Sorooshian (2004), Improved Streamflow Forecasting Using Self-Organizing Radial Basis Function Artificial Neural Network, Journal of Hydrology, 295/1-4, 246-262.

Moradkhani, H. (2002), Optimum Storage Reallocation and Gate operation in Multipurpose Reservoirs, Water Engineering Research, International J. of Korean Water Resources Association, 3, 1.

Book Chapters

Moradkhani, H., and T. Meskele (2009), Probabilistic Assessment of the Satellite Rainfall Retrieval Error Translation to Hydrologic Response, in Satellite Applications for Surface Hydrology, Springer, Water Science and Technology Library, DOI 10.1007/978-90-481-2915-7, pp 229-242.

Moradkhani, H. and S. Sorooshian (2008), General Review of Rainfall-Runoff Modeling: Model Calibration, Data Assimilation, and Uncertainty Analysis, in Hydrological Modeling and Water Cycle, Coupling of the Atmospheric and Hydrological Models, Springer, Water Science and Technology Library, Volume 63, pp 1-23.

Other Refereed Publications

Montzka, C., Hendricks-Franssen, H.-J., Drusch, M., Moradkhani, H., Weihermüller, L., et al., Vanderborght, J., and Vereecken, H., “Estimation Of Radiative Transfer Parameters For Soil Moisture Retrieval From SMOS Brightness Temperatures – A Synthetic 1d Experiment With The Particle Filter”, IEEE International Geosciences and Remote Sensing Symposium, Vancouver, Canada, August 2011.

Najafi, M., and H. Moradkhani, "Improved Ensemble Streamflow Prediction using a New ESP Weighting Scheme", EWRI Congress, Palm Spring, CA, May 2011.

Madadgar, S., Moradkhani, H., " Improving the Ensemble Streamflow Prediction by Adjusting Hydrologic Ensemble Traces ", EWRI Congress, Palm Spring, CA, May 2011.

Najafi, M., Moradkhani H., and Jung, I., " Combined Effect of Global Climate Projection and Hydrologic Model Uncertainties on the Future Changes of Streamflow", EWRI Congress, Providence, RI, 2010.

Jung, I., Moradkhani, H., Chang, H., "Quantifying Hydrological Uncertainty for Rain- and Snow-Dominated Watersheds with Adaptation Strategy", EWRI Congress, Providence, RI, 2010.

Najafi, M., Moradkhani H., and Wherry, S., "Optimal Selection of GCM Predictors combined with a new procedure for Statistical Downscaling of Precipitation", EWRI Congress, Providence, RI, 2010.

Moradkhani, H., Chang, H., "Future climate projections related to hydrology and water resources", Chapter 3 in Oregon Climate Assessment Report, K.D. Dello and P.W. Mote (eds).2010.

Sillars, D., H. Moradkhani, N., Tymvios, "Field Investigation of Fish Passageway Success Factors in Oregon", Transportation Research Board Annual Meeting, Washington DC., Jan. 2010.

Montzka, C., M., Canty, H.H. Franssen, H. Moradkhani, L. Weihermüller and H. Vereecken, "Assessing the value of remotely sensed top soil moisture measurements for soil moisture profile estimation with data assimilation approaches", ESA living planet Symposium, Norway, June 2009.

Ebtehaj, M., and H. Moradkhani, "Parameter Uncertainty Estimation of Hydrologic Models Using Bootstrap Resampling", EWRI Congress, Kansas City, May 2009.

Meskele, T., and H. Moradkhani, "Impacts of different Rainfall Estimates on Hydrological simulation", EWRI Congress, Kansas City, May 2009.

Meier, M., and H. Moradkhani, "Statistical or Ensemble Seasonal Streamflow Forecast? An Intercomparison and Evaluation of Current Forecasting Procedures", EWRI Congress, Kansas City, May 2009.

Moradkhani, H., K., Hsu, and S. Sorooshian, "Toward Improved Hydrologic Prediction with Reduced Uncertainty using Sequential Multi-Model Combination", EWRI Congress, Hawaii, May 2008.

Quinn, S., H., Moradkhani, D., Sillars and T., Smith, "Lessons from Fish Passage Waterways in Oregon and Factors for Improving their Construction", EWRI Congress, Hawaii, May 2008.

Ashouri, H., A. Abrishamchi, H., Moradkhani, and M. Tajrishy, "Assessment of Interannual and Interdecadal Climate Variability Effects on Water Supply in Zayandehrood River Basin, Iran", The First International Conference on Water Resources and Climate Change, Sultanate of Oman, 2008.

Moradkhani, H., and Sorooshian, S., "Ensemble Hydrologic Prediction: in “High Performance Computing for Hydrologic Sciences”, Consortium of Universities for Advancement of Hydrologic Science (CUAHSI), 2006.

Moradkhani, H., N.K. Ajami, K.L. Hsu, S. Sorooshian, “On Particle Filtering Monte Carlo Approach to Sequential Hydrolometeorological Data Assimilation”, proceeding of American Meteorological Society, San Diego, CA, Jan 2005.

Ajami, N.K., Q. Duan, H. Moradkhani, S. Sorooshian, “Recursive Bayesian Model Combination for Streamflow Forecasting”, proceeding of American Meteorological Society, San Diego, CA, Jan 2005.

Moradkhani, H., Sorooshian, S., Gupta, H., Houser, P.R., Hsu, K., "Sequential Data Assimilation framework for Hydrologic State-Parameter Estimation and Ensemble Forecasting", CAHMDA-II, International Workshop on The Terrestrial Water Cycle: Modeling and Data Assimilation Across Catchment Scales, October 2004.