141. Tanim, A.H., E. Goharian, and H. Moradkhani (2022), Integrated socio-environmental vulnerability assessment of coastal hazards using data-driven and multi-criteria analysis approaches, Nature, Scientific Reports, doi: 10.1038/s41598-022-15237-z.

140. Muñoz DF, H. Moftakhari, M. Kumar, and H. Moradkhani (2022), Compound Effects of Flood Drivers, Sea Level Rise, and Dredging Protocols on Vessel Navigability and Wetland Inundation Dynamics, Frontiers in Marine Science, 9:906376. doi: 10.3389/fmars.2022.906376.

139. Engstrom, J., P. Abbaszadeh, D. Keellings,  P. Deb, and H. Moradkhani, (2022), Wildfires in the Arctic and tropical biomes: what is the relative role of climate?, Natural Hazards, doi: 10.1007/s11069-022-05452-2.

138. Price, A., R. Pathak, G. Guthrie, M. Kumar, H. Moftakhari, H. Moradkhani, D. Nadolnyak, and N. Magliocca (2022), Multi-Level Influences on Center-Pivot Irrigation Adoption in Alabama, Frontiers in Sustainable Food Systems.

137. Alipour, A., F. Yarveisi, H. Moftakhari, J.Y., Song, and H. Moradkhani, (2022), A Multivariate Scaling System is Essential to Characterize the Tropical Cyclones’ Risk, Earth's Future, doi: 10.1029/2021EF002635.

136. Deb, P., P. Abbaszadeh, and H. Moradkhani, (2022), An ensemble data assimilation approach to improve farm-scale actual evapotranspiration estimation, Agricultural and Forest Meteorology, doi:10.1016/j.agrformet.2022.108982

135. Alipour, A., K., Jafarzadegan, and H. Moradkhani, (2022), Global sensitivity analysis in hydrodynamic modeling and flood inundation mapping, Environmental Modeling and Software, doi:10.1016/j.envsoft.2022.105398.

134. Gavahi, K., P. Abbaszadeh, and H. Moradkhani, (2022),  How does precipitation data influence the land surface data assimilation for drought monitoring?,  Science of the Total Environment, doi:10.1016/j.scitotenv.2022.154916.

133. Jafarzadegan, K., D. Muñoz, H. Moftakhari, J. Gutenson, G. Savant, H. Moradkhani, (2022), Real-time coastal flood hazard assessment using DEM-based hydrogeomorphic classifiers, Nat. Hazards Earth Syst. Sci., doi:10.5194/nhess-22-1419-2022.

132. Deb, P., H. Moradkhani, X. Han, P. Abbaszadeh, L. Xu (2022), Assessing Irrigation Mitigation Impacts on Crop Yields with and Integrated Modeling Framework, Journal of Hydrology, doi:10.1016/j.jhydrol.2022.127760.

131. Song, J., P. Abbaszadeh, P. Deb, and H. Moradkhani (2022), Unraveling the relationship between tropical storms and agricultural drought, Earth's Future, doi: 10.1029/2021EF002417.

130. Abbaszadeh, P., K. Gavahi, A. Alipour, P. Deb, H. Moradkhani (2022), Bayesian Multi-modeling of Deep Neural Nets for Probabilistic Crop Yield Prediction, Agricultural and Forest Meteorology 314, 108773, doi:10.1016/j.agrformet.2021.108773.

129. Karimiziarani, M., Jafarzadegan, K., Abbaszadeh, P., Shao, W., H. Moradkhani (2022), Hazard Risk Awareness and Disaster Management: Extracting the Information Content of Twitter Data, Sustainable Cities and Society, doi:10.1016/j.scs.2021.103577.

128. Muñoz, D.F., P. Abbaszadeh, H. Moftakhari, and H. Moradkhani (2021), Accounting for uncertainties in compound flood hazard assessment: The value of data assimilation, Coastal Engineering, doi:10.1016/j.coastaleng.2021.104057.

127. Zhang, C., P. Abbaszadeh, L. Xu, H. Moradkhani, Q. Duan, W. Gong (2021), A combined Optimization-Assimilation Framework to Enhance the Predictive Skill of Common Land ModelWater Resources Research, doi: 10.1029/2021WR029879

126. Jafarzadegan, K., A. Alipour, K. Gavahi, Hamed. Moftakhari, and H. Moradkhani (2021) Toward improved river boundary conditioning for simulation of extreme floods , Advances in Water Resources, doi:10.1016/j.advwatres.2021.104059

125. Jafarzadehan, K., P. Abbaszadeh, and H. Moradkhani (2021) Sequential Data Assimilation for Real-Time Probabilistic Flood Inundation Mapping, Hydrol. Earth Syst. Sci., 25, 4995–5011, doi: 10.5194/hess-25-4995-2021.

124. Gavahi, K., P. Abbaszadeh, and H. Moradkhani (2021), DeepYield: A combined convolutional neural network with long short-term memory for crop yield forecasting, Expert Systems with Applications, doi: 10.1016/j.eswa.2021.115511

123. Engstrom, J., S. Praskievicz, B. Bearden, and H. Moradkhani (2021), Decreasing water resources in Southeastern U.S. as observed by the GRACE satellites, Water Policy, doi:10.2166/wp.2021.039

122. Zarekarizi, M, H. Yan, A. Ahmadalipour, H. Moradkhani (2021), A Probabilistic Framework for Agricultural Drought Forecasting Using the Ensemble Data Assimilation and Bayesian Multivariate Modeling, Book Series: Geophysical Monograph Series, Book, doi: 10.1002/9781119427339.ch8

121. Munoz, D., P. Munoz, H. Moftakhari, and H.Moradkhani (2021) From Local to Regional Compound Flood Mapping with Deep Learning and Data Fusion Techniques, Science of The Total Environment, doi: 10.1016/j.scitotenv.2021.146927

120. Abbaszadeh, P., H. Moradkhani, K. Gavahai, S. Kumar, C. Hain, X. Zhan, Q. Duan, C. Peters-Lidard, and M. Karimiziarani (2021) High-Resolution SMAP Satellite Soil Moisture Product: Exploring the Opportunities, Bulletin of the American Meteorological Society, doi: 10.1175/BAMS-D-21-0016.1

119. Zhang, C., Q. Duan, P. Yeh, Y. Pan, H. Gong, H. Moradkhani, W. Gong, X. Lei, W. Liao, L. Xu, Z. Huang, L. Zheng, and X. Guo (2021) Sub-regional groundwater storage recovery in North China Plain after the South-to-North water diversion project, Journal of Hydrology, doi:10.1016/j.jhydrol.2021.126156

118. Munoz, D., P. Munoz, A. Alipour, H. Moftakhari, H.Moradkhani, and B. Mortazavi (2021) Fusing multi-source data to estimate the effects of urbanization, sea level rise and hurricane impacts on long-term wetland change dynamics IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, doi: 10.1109/JSTARS.2020.3048724

117. Xu, L., N. Chen, X. Zhang, H. Moradkhani, C. Zhang, and C. Hu (2020) In-situ and triple-collocation based evaluations of eight global root zone soil moisture products, Remote Sensing of Environment, doi: 10.1016/j.rse.2020.112248. 

116. Deb, P., H.Moradkhani, P. Abbaszadeh, A. Kiem, J. Engstrom, D. Keellings, and A. Sharma (2020) Causes of the widespread 2019 – 2020 Australian bushfire season Earth's Future, doi: 10.1029/2020EF001671.

115. Xu, L., C. Zhang, H. Moradkhani, P. Chu, X. Zhang (2020) Potential precipitation predictability decreases under future warming, Geophysical Research Letters, doi: 10.1029/2020GL090798.

114. Moftakhari, H., W. Shao, H. Moradkhani, A. AghaKouchak, B. Sanders, R. Matthew, S. Jones, and J. Orbinski (2020) Enabling incremental adaptation in disadvantaged communities: polycentric governance with a focus on non-financial capital, Climate Policy, doi: 10.1080/14693062.2020.1833824

113. Shao, W., H. Moftakhari, H. Moradkhani (2020) Comparing public perceptions of sea level rise with scientific projections across five states of the U.S. Gulf Coast region, Climatic Change, doi: 10.1007/s10584-020-02893-1

112. Gavahi, K., P. Abbaszadeh, H. Moradkhani, X. Zhan, and C. Hain (2020) Multivariate Assimilation of Remotely Sensed Soil Moisture and Evapotranspiration for Drought Monitoring, Journal of Hydrometeorology, doi: 10.1175/JHM-D-20-0057.1

111. Xu, Lei., P.Abbaszadeh, H. Moradkhani, N. Chen, X. Zhang (2020) Continental drought monitoring using satellite soil moisture, data assimilation and an integrated drought index, Remote Sensing of Environment, doi: 10.1016/j.rse.2020.112028

110. Abbaszadeh, P., K. Gavahi, and H. Moradkhani (2020) Multivariate Remotely Sensed and In-situ Data Assimilation for Enhancing Community WRF-Hydro Model Forecasting, Advances in Water Resources, doi:10.1016/j.advwatres.2020.103721

109. Engstrom, J., K. Jafarzadegan, and H. Moradkhani (2020) Drought Vulnerability in the United States: An Integrated Assessment, Water, doi:10.3390/w12072033 

108. Yin, J., X. Zhan, J. Liu, H. Moradkhani, L. Fang, J. Walker (2020), Development and Validation of a Near Real Time One-kilometer Resolution SMAP Soil Moisture Data ProductHydrological Processes, doi: 10.1002/hyp.13857

107. Jafarzadegan, K., and H. Moradkhani (2020), Regionalization of stage-discharge rating curves for hydrodynamic modeling in ungauged basinsJournal of Hydrology, doi:10.1016/j.jhydrol.2020.125165.

106. Munoz, D.F., H. Moftakhari, and H. Moradkhani (2020), Compound Effects of Flood Drivers and Wetland Elevation Correction on Flood Hazard AssessmentWater Resources Research, doi:10.1029/2020WR027544.

105. Keellings, D. , and H. Moradkhani (2020), Spatiotemportal Evolution of Heat Wave Severity and Coverage Across the United States, Geophysical Research Letters. doi: 10.1029/2020GL087097

104. Song, J. ,A.Alipour, H.Moftakhari, and H. Moradkhani (2020),Toward a more effective hurricane hazard communication, Environmental research letters. doi: 10.1088/1748-9326/ab875f

103. Xu, L. , N. Chen, H. Moradkhani, X Zhang, and C.Hu (2020), Improving global monthly and daily precipitation estimation by fusing gauge observations, remote sensing and reanalysis datasets, Water resources research. doi:10.1029/2019WR026444.

102. Alipour, A. , A. Ahmadalipour, and H. Moradkhani (2020), Assessing Flash Flood Hazard and Damages in the Southeast U.S., Journal of Flood Risk Management. doi: 10.1111/JFR3.12605.

101. Alipour, A. , A. Ahmadalipour, P. Abbaszadeh, and H. Moradkhani (2020), Leveraging machine learning for predicting flash flood damages in the Southeast US, Environmental Research Letter. 15, 2, doi:10.1088/1748-9326/ab6edd

100. Khajehei, S., A. Ahmadalipour, W. Shao, and H. Moradkhani (2020), A Place-based Assessment of Flash Flood Hazard and Vulnerability in the Contiguous United States10:448, Nature, Scientific Reports. doi: 10.1038/s41598-019-57349-z.

99. Jafazadegan, K., V. Merwade, and H. Moradkhani (2020), Combining clustering and classification for the regionalization of environmental model parameters: Application to floodplain mapping in data-scarce regions, Environmental Modelling and Software. doi: 10.1016/j.envsoft.2019.104613.

98. Almamalachy, Y.S., Al-Quraishi, A., and H.Moradkhani (2020), Agricultural drought monitoring over Iraq utilizing MODIS products, Environmental Remote Sensing and GIS in Iraq, 253-278. https://doi.org/10.1007/978-3-030-21344-2_11

97. Hameed, M., Ahmadalipour, A., and H. Moradkhani (2019), Drought and food security in the middle east: An analytical framework, Agricultural and Forest Meteorology, Volume 281, doi: 10.1016/j.agrformet.2019.107816.

96. Ahmadalipour, A., and H. Moradkhani (2019), A data-driven analysis of flash flood hazard, fatalities, and damages over the CONUS during 1996-2017, Journal of Hydrology, doi: 10.1016/j.jhydrol.2019.124106.

95. Schelf K.E., H. Moradkhani, and U. Lall (2019), Atmospheric Circulation Patterns Associated with extreme United States Floods Identified via Machine Learning, Nature, Scientific Reports, doi:10.1038/s41598-019-43496-w.

94. Hameed, M., H. Moradkhani, A. Ahmadalipour, H. Moftakhari, P. Abbaszadeh, A. Alipour (2019), A Review of the 21st Century Challenges in the Food-Energy-Water Security in the Middle East, Water, 11, 682; doi:10.3390/w11040682.

93. Ahmadi, B., A. Ahmadalipour, G. Tootle, and H. Moradkhani (2019), Remote sensing of water use efficiency and terrestrial drought recovery across the CONUS, Remote Sensing, 11, 731; doi:10.3390/rs11060731

92. Abbaszadeh, P., H. Moradkhani, and D.N. Daescu (2019), The Quest for Model Uncertainty Quantification: A Hybrid Ensemble and Variational Data Assimilation Framework, Water Resources Research, 55, doi: 10.1029/2018WR023629.

91. Ahmadi, B., and H. Moradkhani (2019), Revisiting Hydrological Drought Propagation and Recovery Considering Water Quantity and Quality, Hydrological Processes, doi: 10.1002/hyp.13417.

90. Ahmadalipour, A., H. Moradkhani, A. Casteletti, N. Magliocca (2019), Future drought risk in Africa: Integrating vulnerability, climate change, and population growth, Science of the Total Environment, 662, 672-686, doi: 10.1016/j.scitotenv.2019.01.278.

89. Ahmadi, B., A. Ahmadalipour, and H. Moradkhani (2019), Hydrological Drought Persistence and Recovery in the CONUS: a Multi-stage Framework Considering Water Quantity and Quality, Water Research, 150, 97-10, doi: 10.1016/j.watres.2018.11.052.

88. Abbaszadeh, P., H. Moradkhani, X. Zhan (2019), Downscaling SMAP Radiometer Soil Moisture over the CONUS Using an Ensemble Learning Method, Water Resources Research, 54. doi:10.1029/2018WR023354.

87. Ahmadalipour, A., H. Moradkhani, M. Kumar (2019), Mortality risk from heat-stress expected to hit poorest nations the hardest, Climatic Change, 152, 3–4, pp 569–579, doi:10.1007/s10584-018-2348-2.

86. Yan, H., M Zarekarizi, and H. Moradkhani (2018), Toward Improving Drought Monitoring using the Remotely Sensed Soil Moisture Assimilation: A Parallel Particle Filtering Framework, Remote Sensing of Environment, 216:456-471, doi: 10.1016/j.rse.2018.07.017

85. Ahmadalipour, A., and H. Moradkhani (2018) Multi-dimensional assessment of drought vulnerability across Africa: 1960-2100. Science of the Total Environment. 664:520-535. doi: 10.1016/j.scitotenv.2018.07.023.

84. Irannezhad, M., H. Moradkhani and B. Kløve (2018), Spatio-temporal Variability and Trends in Extreme Temperature Events in Finland over the Recent Decades: Influence of Northern Hemisphere Teleconnection Patterns, Advances in Meteorology, doi: 10.1155/2018/7169840.

83. Pathiraja, S., Anghileri, D., Burlando, P., Sharma, A., Marshall, L., and Moradkhani, H. (2018): Time-varying parameter models for catchments with land use change: the importance of model structure, Hydrol. Earth Syst. Sci., 22, 2903-2919, doi: 10.5194/hess-22-2903-2018.

82. Ahmadalipour, A., and H. Moradkhani (2018), Escalating heat-stress mortality risk due to global warming in the Middle East and North Africa (MENA), Environment International, 117, 215–225

81. Moradkhani H., Nearing G., Abbaszadeh P., Pathiraja S. (2018), Fundamentals of Data Assimilation and Theoretical Advances. In: Duan et al. (eds), Handbook of Hydrometeorological Ensemble Forecasting. Springer, Berlin, Heidelberg, doi: 10.1007/978-3-642-40457-3_30-1.

80. Pathiraja, S., H. Moradkhani, L. Marshall, A. Sharma, G, Geenens (2018), Data Driven Model Uncertainty Estimation in Data Assimilation, Water Resources Research, doi: 10.1002/2018WR022627.

79. Abbaszadeh, P., H. Moradkhani, and H. Yan (2018), Enhancing Hydrologic Data Assimilation by Evolutionary Particle Filter and Markov Chain Monte Carlo , Advances in Water Resources, 111, 192-204, doi: 10.1016/j.advwatres.2017.11.011.

78. Bracken, C., K.D. Holman, B. Rajagopalan, and H. Moradkhani (2018), A Bayesian hierarchical approach to multivariate nonstationary hydrologic frequency analysis, Water Resources Research, doi: 10.1002/2017WR020403.

77. Hameed, M., A. Ahmadalipour, H. Moradkhani (2018), Apprehensive Drought Characteristics over Iraq: Results of a Multidecadal Spatiotemporal Assessment, Geosciences, Special Issue Drought Monitoring and Prediction, 8, 8, 58.

76. Pathiraja, S., D. Anghileri, P. Burlando, A. Sharma, L. Marshall, and H. Moradkhani (2018), Insights on the impact of systematic model errors on data assimilation performance in changing catchments, Advances in Water Resources, 113,202-222.

75. Kiani, S., M. Irannezhad, A-K Ronkanen, H. Moradkhani, B. Kløve (2018), Effects of recent temperature variability and warming on the Oulu-Hailuoto ice road season in the northern Baltic Sea, Cold Regions Science and Technology, 15, 1-8.

74. Ahmadalipour, A., and H. Moradkhani (2017), Analyzing the uncertainty of ensemble-based gridded observations in land surface simulations and drought assessment , J. of Hydrology, doi:10.1016/j.jhydrol.2017.10.059.

73. Khajehei, S., A., Ahmadalipour, H. Moradkhani (2017), An Effective Post-Processing of the North American Multi-Model Ensemble (NMME) Precipitation Forecasts over the Continental US, Climate Dynamics, doi 10.1007/s00382-017-3934-0.

72. Zarekarizi, M., H. Moradkhani, A. Rana (2017), Precipitation Extremes and their relation to climatic indices in the Pacific Northwest USA, Climate Dynamics, doi: 10.1007/s00382-017-3888-2.

71. Ahmadalipour, H. Moradkhani, M. Demirel (2017), A comparative assessment of projected meteorological and hydrological droughts: Elucidating the role of temperature, J. of Hydrology, 553 (2017) 785–797.

70. Ahmadalipour, A., H. Moradkhani, A. Rana (2017), Accounting for downscaling and model uncertainty in fine-resolution seasonal climate projections over the Columbia River Basin, Climate Dynamics, doi: 10.1007/s00382-017-3639-4.

69. Yan, H., H. Moradkhani, and M. Zarekarizi (2017), A Probabilistic Drought Forecasting Framework: A Combined Dynamical and Statistical Approach, Journal of Hydrology, 548, 291–304, doi: 0.1016/j.jhydrol.2017.03.004

68. Irannezhad, M., Chen, D., Kløve, B. and H. Moradkhani (2017), Analysing the Variability and Trends of Precipitation Extremes in Finland and Their Connection to Atmospheric Circulation Patterns, International Journal of Climatology, doi:10.1002/joc.5059.

67. Irannezhad, M., Ahmadi, B., Kløve, B. and H. Moradkhani (2017), Atmospheric Circulation Patterns Explaining Climatological Drought Dynamics in the Boreal Environment of Finland, 1962-2011, International Journal of Climatology, doi: 10.1002/joc.5039.

66. Khajehei, S. and H. Moradkhani (2017), Towards an Improved Ensemble Precipitation Forecast: A Probabilistic Post-processing Approach, Journal of Hydrology, 546, 476–489.

65. Ahmadalipour, A. and H. Moradkhani and M. Svoboda (2016), Centennial drought outlook over the CONUS using NASA-NEX downscaled climate ensemble, International Journal of Climatology, doi: 10.1002/joc.4859.

64. Tongal, H., M., Demirel, and H. Moradkhani (2016), Analysis of dam-induced cyclic patterns on river flow dynamics, 62(4), 626-641, Hydrologic Sciences, doi:10.1080/02626667.2016.1252841.

63. Yan, H., and H. Moradkhani (2016), Combined Assimilation of Streamflow and Satellite Soil Moisture with the Particle Filter and Geostatistical Modeling, Advances in Water Resources, 94 364–378, doi:10.1016/j.advwatres.2016.06.002.

62. Ahmadalipour, A., H. Moradkhani, H. Yan, M. Zarekarizi (2016), Remote Sensing of Drought: Vegetation, Soil Moisture and Data Assimilation, Remote Sensing of Hydrological Extremes, Springer International Publishing Switzerland 2017, DOI 10.1007/978-3-319-43744-6_7.

61. Pathiraja, S., L. Marshall, A. Sharma, and H. Moradkhani (2016), Detecting non-stationary hydrologic model parameters in a paired catchment system using Data Assimilation, Advances in Water Resources, 94, 103–119, doi:10.1016/j.advwatres.2016.04.021.

60. Rana, A., H. Moradkhani, Y. Qin (2016), Understanding the Joint Behavior of Temperature and Precipitation for Climate Change Impact Assessment, Theoretical and Applied Climatology, doi: 10.1007/s00704-016-1774-1.

59. Pathiraja, S., L. Marshall, A. Sharma, and H. Moradkhani (2016), Hydrologic Modeling in Dynamic catchments: A Data Assimilation Approach, Water Resources Research, doi: 10.1002/2015WR017192.

58. Rana, A., and H. Moradkhani (2016), Spatial, temporal and frequency based climate change assessment in Columbia River Basin using multi downscaled-Scenarios, Climate Dynamics, 47:579–600, doi:10.1007/s00382-015-2857-x.

57. Madadgar, S. and H. Moradkhani (2016), Copula Function and Drought, Handbook of Drought and Water Scarcity, Vol. 1: Principles of Drought and Water Scarcity, Francis and Taylor.

56. Ahmadalipour, A., A., Rana, H. Moradkhani, and A. Sharma (2015), Multi-Criteria Analysis of CMIP5 GCMs for Climate Change Impact Analysis over the Columbia River Basin, Theoretical and Applied Climatology, doi:10.1007/s00704-015-1695-4.

55. Demirel, M., and H. Moradkhani (2015), Assessing the Impact of CMIP5 Climate Multi-Modeling on Estimating the Precipitation Seasonality and Timing, Climatic Change, doi:10.1007/s10584-015-1559-z.

54. Yan, H., and H. Moradkhani (2015), Toward more Robust Extreme Flood Prediction by Bayesian Hierarchical and Multimodeling, Natural Hazards, doi:10.1007/s11069-015-2070-6.

53. DeChant, C.M., and H. Moradkhani (2015), On the Assessment of Reliability in Probabilistic Hydro-meteorological Event Forecasting, Water Resources Research, doi: 10.1002/2014WR016617.

52. Najafi, M.R. and H. Moradkhani (2015), Multi-Model Ensemble Analysis of the Runoff Extremes for Climate Change Impact Assessments, Journal of Hydrology, doi:10.1016/j.jhydrol.2015.03.045.

51. Yan, H., C.M. DeChant, and H. Moradkhani (2015), Improving Soil Moisture Profile Prediction with the Particle Filter-Markov Chain Monte Carlo Method, IEEE Transaction on Geoscience and Remote Sensing, DOI: 10.1109/TGRS.2015.2432067.

50. Najafi, M.R. and H. Moradkhani (2015), Towards Ensemble Combination of Seasonal Streamflow Forecasts, Journal of Hydrologic Engineering, 10.1061/(ASCE)HE.1943-5584.0001250.

49. DeChant C.M., and H. Moradkhani (2015), Analyzing the Sensitivity of Drought Recovery Forecasts to Land Surface Initial Conditions, Journal of Hydrology, special issue on Drought, 526, 89–100, DOI:10.1016/j.jhydrol.2014.10.021.

48. Madadgar, S. and H. Moradkhani (2014), Improved Bayesian Multi-modeling: Integration of Copulas and Bayesian Model Averaging, Water Resources Research, 50, 9586–9603, DOI: 10.1002/2014WR015965.

47. Madadgar, S., H. Moradkhani, and D. Garen (2014), Towards Improved Post-processing of Hydrologic Forecast Ensembles, Hydrological Processes, 28 (1), 104-122, DOI: 10.1002/hyp.9562.

46. Seo, DJ, Y Liu, H. Moradkhani, A. Weerts (2014), Ensemble prediction and data assimilation for operational hydrology, Journal of Hydrology, special issue, 519, 2661–2662, DOI:10.1016/j.jhydrol.2014.11.035.

45. Yan, H., and H. Moradkhani (2014), A Regional Bayesian Hierarchical Model for Flood Frequency Analysis, Stochastic Environmental Research and Risk Assessment, DOI: 10.1007/s00477.014.0975.3.

44. DeChant C.M., and H. Moradkhani (2014), Toward a Reliable Prediction of Seasonal Forecast Uncertainty: Addressing Model and Initial Condition Uncertainty with Ensemble Data Assimilation and Sequential Bayesian Combination, Journal of Hydrology, special issue on Ensemble Forecasting and data assimilation, 519, 2967-2977, DOI: 10.1016/j.jhydrol.2014.05.045.

43. Samuel, J., P. Coulibaly, G. Dumedah, H. Moradkhani (2014), Assessing Model State Variation in Hydrologic Data Assimilation, Journal of Hydrology, 513, 127–141, DOI: 10.1016/j.jhydrol.2014.03.048.

42. DeChant, C.M. and H. Moradkhani (2014), Hydrologic Prediction and Uncertainty Quantification, Handbook of Engineering Hydrology: Modeling, Climate Change, and Variability, CRC press, Taylor & Francis Group, pp. 387–414.

41. Madadgar, S., and H. Moradkhani (2014), Spatio-temporal Drought Forecasting within Bayesian Networks, Journal of Hydrology, 512, 134-146, DOI: 10.1016/j.jhydrol.2014.02.039.

40. Najafi, M.R. and H. Moradkhani (2014), A Hierarchical Bayesian Approach for the Analysis of Climate Change Impact on Runoff Extremes, Hydrological Processes, 28, 6292–6308, DOI: 10.1002/hyp.10113.

39. Madadgar, S. and H. Moradkhani (2013), A Bayesian Framework for Probabilistic Drought Forecasting, Journal of Hydrometeorology, special issue of Advances in Drought Monitoring, 14, 1685–1705, DOI: 10.1175/JHM-D-13-010.1

38. Najafi M.R. and H. Moradkhani (2013), Analysis of Runoff Extremes using Spatial Hierarchical Bayesian Modeling, Water Resources Research, 49, 1–15, DOI:10.1002/wrcr.20381.

37. Montzka, C., J. Grant, H. Moradkhani, H.J., Hendricks Franssen, L. Weihermüller, M. Drusch, and H. Vereecken (2013), Estimation of radiative transfer parameters from L-Band passive microwave brightness temperatures using data assimilation, Vadose Zone Hydrology, Special Issue of Remote Sensing, doi:102136/vzj2012.0040.

36. Jaeger, W.K., A. Platinga, H. Chang, J. McDonnell H. Moradkhani, D. Hulse, R. Hagerty, et al. (2013), Toward a formal definition of water scarcity in natural-human systems, Water Resources Research, vol. 49, 1–12, doi:10.1002/wrcr.20249.

35. Samadi S.Z., C.A. Wilson, H. Moradkhani (2013), Uncertainty Analysis of Statistical Downscaling Models Using Hadley Centre Coupled Model, Journal of Theoretical and Applied Climatology, 1-18, doi:10.1007/s00704-013-0844-x.

34. Fattahi, M.H., N. Talebbeydokhti, H. Moradkhani, Nikooee (2013), Revealing the chaotic nature of river flow, Iranian Journal of Science and Technology, Transaction of Civil Engineering., Vol. 37, No. C+, pp 437-456

33. Madadgar, S., and H. Moradkhani, (2013), Drought Analysis under Climate Change using Copula, Journal of Hydrologic Engineering, 18 (7), doi:http://dx.doi.org/10.1061/(ASCE)HE.1943-5584.0000532.

32. Liu, Y., A.H. Weerts, M. Clark, H.J. Hendricks Franssen, S. Kumar, H. Moradkhani, D.J. Seo, D. Schwanenberg, P. Smith, A. I. J. M. van Dijk, N. van Velzen, M. He, H. Lee, S. J. Noh, O. Rakovec,, P. Restrepo, (2012), Toward Advancing Data Assimilation in Operational Hydrologic Forecasting and Water Resources Management: Current Status, Challenges, and Emerging Opportunities, Hydrol. Earth Syst. Sci., 16, 3863-3887.

31. Chang, H., I. Jung, A. Strecker, D. Wise, M. Lafranz, V. Shandas, H. Moradkhani, A. Yeakly Y. Pan, R. Bean, G. Johnson, M. Psaris (2013), Water Supply, Demand, and Quality Indicators for Assessing the Spatial Distribution of Water Resource Vulnerability in the Columbia River Basin, USA, Atmosphere and Ocean, 1–18, http://dx.doi.org/10.1080/07055900.2013.777896.

30. Moradkhani, H., C.M. DeChant and S. Sorooshian (2012), Evolution of Ensemble Data Assimilation for Uncertainty Quantification using the Particle Filter-Markov Chain Monte Carlo Method, Water Resources Research,48,W12520, doi:10.1029/2012WR012144.

29. Leisenring, M., and H. Moradkhani (2012), Analyzing the Uncertainty of Suspended Sediment Load Prediction Using Sequential Monte Carlo Methods, Journal of Hydrology, 468-469, p268-282, 10.1016/j.jhydrol.2012.08.049.

28. Jung, I., H. Moradkhani, and H. Chang (2012), Uncertainty Assessment of Climate Change Impact for Hydrologically Distinct River Basins, Journal of Hydrology, 466-467, p73-87, 10.1016/j.jhydrol.2012.08.002.

27. 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, 27, 2579–2590, DOI: 10.1002/hyp.937.

26. Najafi, M.R., H. Moradkhani, and T. Piechota (2012), Ensemble Streamflow Prediction: Climate Signal Weighting vs. Climate Forecast System Reanalysis, Journal of Hydrology, 442–443 (p105–116),http://dx.doi.org/10.1016/j.jhydrol.2012.04.003.

25. 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, vol. 48, W04518, doi:10.1029/2011WR011011.

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

23. DeChant, C., 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.

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

21. DeChant, C., H. Moradkhani (2011), Radiance Data Assimilation for operational Snow and Streamflow Forecasting, Advances in Water Resources, 34, 351–364.

20. 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 (14) 1-26.

19. Montzka, C., H. Moradkhani, L. Weihermuller, M. Canty, H.J. Hendricks Franssen, and H. Vereecken (2011), Hydraulic Parameter Estimation by Remotely-sensed top Soil Moisture Observations with the Particle Filter, Journal of Hydrology, 399 (3-4), 410-421.

18. Leisenring, M., H. Moradkhani (2011), Snow Water Equivalent Estimation using Bayesian Data Assimilation Methods, Stochastic Environmental Research and Risk Assessment, 25 (2), 253-270.

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

16. 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.

15. Moradkhani H., R.G., Baird, and S. Wherry (2010), Assessment of Climate Change on Floodplain Mapping and Hydrologic Ecotones, Journal of Hydrology, 395, 264–278.

14. Najafi, M., Z. Kavianpour, B. Najafi, M.R. Kavianpour, and H. Moradkhani (2010), 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.

13. Moradkhani, H., M. Meier, (2010), Long-Lead Water Supply Forecast using Large-scale Climate Predictors and Independent Component Analysis, J. of Hydrologic Engineering, 15(10), 744-762.

12. Ebtehaj, M., H. Moradkhani, 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.

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

10. H. Moradkhani, T. 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.

9. 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.

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

7. 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, Part 1, 1-24, DOI: 10.1007/978-3-540-77843-1-1.

6. 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.

5. 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.

4. Moradkhani, H. (2005), Assimilating Scatterometer Soil Moisture Data into Conceptual Hydrologic Models at the Regional Scale, Hydrol. Earth Syst. Sci., 2, S1236-S1240.

3. 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.

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

1.  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.

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