H41A:
Advances in Hydrologic Prediction to Support Water and Energy Applications II Posters

Submit an Abstract to this Session



Session ID#: 24297

Session Description:
Recent advances in computational resources, hydrologic science and data, and ensemble NWP have brought major developments in hydrologic forecasting, especially in the areas of modeling (ranging from lumped conceptual frameworks to hyper-resolution physically-oriented platforms), and the refinement of ensemble techniques for estimating forecast uncertainty -- supporting risk-based decision-making in flood mitigation, water/energy management, drought and other sectors.  We invite contributions related to:

  • Approaches for ensemble hydro-meteorological forecasting, including processing of meteorological forecasts, implementation, evaluation and comparison of hydrologic/hydraulic models including calibration, data assimilation, forecast post processing, and other relevant topics.
  • The utility of ensemble forecasts to support the management of water and energy systems (incl. optimization), or application decision needs in other water-related sectors.
  • Integration of uncertainty/error/verification analysis into operational water-energy applications to support real-time decision-making.

Presentations may range from individual methods to systems or services, from local to global scales. This session supports the Hydrologic Ensemble Prediction Experiment (www.hepex.org).

Primary Convener:  Andrew W Wood, National Center for Atmospheric Research, CGD Laboratory, Boulder, United States
Conveners:  Nathan M Barber, Tennessee Valley Authority, Norris, TN, United States, Nathalie Voisin, Pacific Northwest National Laboratory, Richland, WA, United States and Firas Saleh, Stevens Institute of Technology, Davidson Laboratory, Deptartment of Civil, Environmental and Ocean Engineering, Union City, NJ, United States
Chairs:  Andrew W Wood, National Center for Atmospheric Research, CGD Laboratory, Boulder, United States, Nathan M Barber, NOAA/NWS/Ohio River Forecast Center, Morrow, United States, Nathalie Voisin, Pacific Northwest National Laboratory, Richland, WA, United States and Firas Saleh, Stevens Institute of Technology, Davidson Laboratory, Deptartment of Civil, Environmental and Ocean Engineering, Union City, NJ, United States
OSPA Liaison:  Andrew W Wood, National Center for Atmospheric Research, CGD Laboratory, Boulder, United States

Cross-Listed:
  • A - Atmospheric Sciences
  • IN - Earth and Space Science Informatics
  • NH - Natural Hazards
Index Terms:

1816 Estimation and forecasting [HYDROLOGY]
1860 Streamflow [HYDROLOGY]
1873 Uncertainty assessment [HYDROLOGY]
1880 Water management [HYDROLOGY]

Abstracts Submitted to this Session:

Forecasting of Seasonal Rainfall using ENSO and IOD teleconnection with Classification Models (215789)
Thushara De Silva, Vanderbilt University, Nashville, TN, United States and George M Hornberger, Vanderbilt University, Vanderbilt Institute for Energy & Environment, Civil and Environmental Engineering, Earth & Environmental Sciences, Nashville, TN, United States
Can rainfall be predicted at decadal timescales? (268929)
Dipayan Choudhury1, Ashish Sharma2, Alexander Sen Gupta3, Rajeshwar Mehrotra1 and Bellie Sivakumar4, (1)University of New South Wales, Sydney, NSW, Australia, (2)University of New South Wales, School of Civil and Environmental Engineering, Sydney, NSW, Australia, (3)ARC Centre of Excellence for Climate Extremes, Sydney, NSW, Australia, (4)University of California Davis, Department of Land, Air and Water Resources, Davis, CA, United States
Application of Statistical Downscaling Techniques to Predict Rainfall and Its Spatial Analysis Over Subansiri River Basin of Assam, India (278866)
Swapnali Barman, Water Resources Department, Govt. of Assam, Guwahati, India and Rajib Kumar Bhattacharjya, Indian Institute of Technology Guwahati, Department of Civil Engineering, Guwahati, India
Recognition of predictors for mid-long term runoff prediction based on lasso (238373)
Shuai Xie and Yuefei Huang, Tsinghua University, Beijing, China
GLUE Analysis and Optimal Operation for Diyala River Basin in Iraq Using Variable Infiltration Capacity Model (243704)
Saddam Waheed Sr, Colorado State University, Fort Collins, CO, United States and Jorge Ramirez, Colorado State University, Civil and Environmental Engineering, Fort Collins, CO, United States
Nationwide validation of ensemble streamflow forecasts from the Hydrologic Ensemble Forecast Service (HEFS) of the U.S. National Weather Service (258002)
Hak Su Lee1,2, Yuqiong Liu2, James Ward2,3, James Brown4, Alexander Maestre5,6, Hank Herr2, Mark A Fresch2, Ernie Wells2, Seann M Reed7 and Eric Jones8, (1)LEN Technologies, Oak Hill, United States, (2)NOAA/NWS/OWP, Silver Spring, United States, (3)CyberData Technologies Inc., Herndon, United States, (4)Hydrologic Solutions Limited, Southampton, United Kingdom, (5)NOAA/NWS Office of Water Prediction, National Water Center, Tuscaloosa, AL, United States, (6)University Corporation for Atmospheric Research, Boulder, CO, United States, (7)NOAA/NWS/MARFC, State College, PA, United States, (8)NOAA/NWS/ABRFC, Tulsa, OK, United States
Multi-model analysis in hydrological prediction (260547)
Martine Lanthier1, Richard Arsenault2 and François Brissette1, (1)École de Technologie Supérieure, Montreal, QC, Canada, (2)Rio Tinto, Quebec Power Operations, Jonquiere, QC, Canada
Ensemble Simulation of Sierra Nevada Snowmelt Runoff Using a Regional Climate Modeling Approach (266501)
Nataniel Holtzman, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States, Tamlin Pavelsky, University of North Carolina at Chapel Hill, Earth, Marine and Environmental Sciences, Chapel Hill, NC, United States and Melissa Wrzesien, Ohio State University Main Campus, Columbus, United States
A parallel calibration utility for WRF-Hydro on high performance computers (275344)
Jiali Wang1, Cheng Wang2 and Veerabhadra Rao Kotamarthi1, (1)Argonne National Laboratory, Argonne, United States, (2)Argonne National Laboratory, Environmental Science Division, Lemont, IL, United States
Parameter Identification for a Distributed Hydrological Model Using the GLUE Method (278935)
Aynom Tesfay Tweldebrahn, University of Oslo, Oslo, Norway, John F. Burkhart, University of Oslo, Department of Geosciences, Oslo, Norway, Thomas Schuler, Univ Oslo, Department of Geosciences, Oslo, Norway and Gaute Lappegard, Statkraft, Oslo, Norway
Attaining insight into interactions between hydrologic model parameters and geophysical attributes for national-scale model parameter estimation (286113)
Naoki Mizukami, National Center for Atmospheric Research, Hydrometeorological Applications Program, Research Applications Laboratory, Boulder, CO, United States, Martyn P Clark, Hydrometeorological Applications Program, Research Applications Laboratory, National Center for Atmospheric Research, Boulder, CO, United States, Andrew James Newman, NSF National Center for Atmospheric Research, Boulder, United States, Andrew W Wood, National Center for Atmospheric Research, Boulder, CO, United States and Ethan D Gutmann, NSF National Center for Atmospheric Research, Hydrometeorological Applications Program, Research Applications Laboratory, Boulder, United States
Distributed HUC-based modeling with SUMMA for ensemble streamflow forecasting over large regional domains. (289005)
Manabendra Saharia, National Center for Atmospheric Research, Research and Applications Laboratory, Boulder, CO, United States, Andrew W Wood, National Center for Atmospheric Research, Boulder, CO, United States, Martyn P Clark, Hydrometeorological Applications Program, Research Applications Laboratory, National Center for Atmospheric Research, Boulder, CO, United States, Andrew Bennett, Oak Ridge National Laboratory, Oak Ridge, TN, United States, Bart Nijssen, University of Washington, Seattle, WA, United States, Elizabeth Clark, University of California Los Angeles, Los Angeles, CA, United States and Andrew James Newman, NSF National Center for Atmospheric Research, Boulder, United States
Combining Satellite Measurements and Numerical Flood Prediction Models to Save Lives and Property from Flooding (245696)
Firas Saleh, Stevens Institute of Technology, Davidson Laboratory, Deptartment of Civil, Environmental and Ocean Engineering, Union City, NJ, United States, PierreAndré Garambois, INRAE, RECOVER, Aix-en-Provence, France and Sylvain Biancamaria, LEGOS, Toulouse, France
Sensitivity of power system operations to projected changes in water availability due to climate change: the Western U.S. case study (247755)
Nathalie Voisin1, Jordan Macknick2, Tao Fu3, Matthew O'Connell4, Tian Zhou1 and Gregory Brinkman4, (1)Pacific Northwest National Laboratory, Richland, WA, United States, (2)National Laboratory of the Rockies, Golden, United States, (3)Pacific Northwest National Laboratory, EED/Hydrology, Richland, WA, United States, (4)National Renewable Energy Laboratory Golden, Golden, CO, United States
Prediction of Agriculture Drought Using Support Vector Regression Incorporating with Climatology Indices (253075)
Ye Tian, Nanjing University of Information Science & Technology, Nanjing, China and Yue-ping Xu, Zhejiang University, Institute of Water Science and Engineering, Hangzhou, China
Data Assimilation using observed streamflow and remotely-sensed soil moisture for improving sub-seasonal-to-seasonal forecasting (263360)
Sankar Arumugam, North Carolina State University Raleigh, Department of Civil, Construction, and Environmental Engineering, Raleigh, NC, United States, Amir Hossein Mazrooei, North Carolina State University, Raleigh, NC, United States, Venkataraman Lakshmi, University of Virginia, Civil and Environmental Engineering, Charlottesville, VA, United States and Andrew W Wood, National Center for Atmospheric Research, Boulder, CO, United States
A Regionalization Approach to select the final watershed parameter set among the Pareto solutions (260798)
Gi-Hyeon Park1, Paul D. Micheletty2, Shaun Carney3, Jonathan Quebbeman4 and Gerald N Day4, (1)Research Triangle Institute, Research Triangle Park, United States, (2)Research Triangle Institute, Research Triangle Park, NC, United States, (3)Riverside Technology Inc., Fort Collins, CO, United States, (4)RTI International, Fort Collins, CO, United States
Eco-morphological Real-time Forecasting tool to predict hydrodynamic, sediment and nutrient dynamic in Coastal Louisiana (242926)
Francesca Messina, Water Institute of the Gulf, Baton Rouge, LA, United States, Ehab A Meselhe, Tulane University, New Orleans, United States, Lora Buckman, Deltares, Delft, Netherlands and Daniel Twight, Notre Dame, IN, United States

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