H51F:
Advances in Hydrologic Prediction Toward Water Resources Decision Making II Posters

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Session ID#: 13135

Session Description:
Numerous efforts have been made recently to improve short term, medium range and inter-annual hydroclimatic forecasts in terms of accuracy, information content, and spatial and temporal resolution and scope. This session is particularly focused on understanding and improving meteorological and hydrological predictability, how their uncertainties can translate into water resources decision-making, and onto other sectors (e.g. agriculture, energy). We encourage contributions that describe specific techniques and end-to-end systems, related to:

  • Hydroclimatic Forecasts: hydrological modeling, model parameter estimation, downscaling and calibration of forecasts, data assimilation, post-processing for streamflow forecasts
  • Decision support strategies: end-to-end approaches for water resources planning and management, optimization of operations, visualization and communication under uncertainty
  • Application to other sectors e.g. customization for hydropower operations optimization/unit dispatch/new assets siting.

Perspectives on climate change influences in these areas are also welcome. This session is offered in support of the Hydrologic Ensemble Prediction Experiment (HEPEX; www.hepex.org).

Primary Convener:  Andrew W Wood, National Center for Atmospheric Research, CGD Laboratory, Boulder, United States
Conveners:  Nathalie Voisin, Pacific Northwest National Laboratory, Richland, WA, United States, Paul J Block, University of Wisconsin Madison, Department of Civil and Environmental Engineering, Madison, United States and Maria-Helena Ramos, IRSTEA, Antony Cedex, France
Chairs:  Andrew W Wood, National Center for Atmospheric Research, CGD Laboratory, Boulder, United States, Maria-Helena Ramos, IRSTEA, Antony Cedex, France, Nathalie Voisin, Pacific Northwest National Laboratory, Richland, WA, United States and Paul J Block, University of Wisconsin Madison, Department of Civil and Environmental Engineering, Madison, United States
OSPA Liaison:  Maria-Helena Ramos, IRSTEA, Antony Cedex, France

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

1816 Estimation and forecasting [HYDROLOGY]
1840 Hydrometeorology [HYDROLOGY]
1860 Streamflow [HYDROLOGY]
1880 Water management [HYDROLOGY]

Abstracts Submitted to this Session:

Implementing Verification Procedures on a Calibrated vs non-Calibrated Streamflow for Agricultural Drought Forecast (197784)
Daniel Rico1, Gerald Corzo2, Juan Chacon3 and Francisco Munoz-Arriola1, (1)University of Nebraska Lincoln, Lincoln, NE, United States, (2)UNESCO-IHE Institute for Water Education, Delft, Netherlands, (3)UNESCO-IHE� Institute for Water Education, HYDROINFORMATICS, Delft, Netherlands
Integrating predictive information into an agro-economic model to guide agricultural management (136316)
Ying Zhang, University of Wisconsin Madison, Madison, WI, United States and Paul J Block, University of Wisconsin Madison, Department of Civil and Environmental Engineering, Madison, United States
Operational Research: Evaluating Multimodel Implementations for 24/7 Runtime Environments (171476)
John Faulkner Burkhart1,2, Sigbjørn Helset3, Yisak Sultan Abdella3 and Gaute Lappegard3, (1)University of Oslo, Geosciences, Oslo, Norway, (2)University of California, Merced, Sierra Nevada Research Institute, Merced, CA, United States, (3)Statkraft, Oslo, Norway
Incorporation of a Stochastic Weather Generator to Further Inform Ensemble Streamflow Prediction in the Colorado River Basin (138812)
William P Miller, NOAA, Boulder, CO, United States, Andrew Verdin, Ph.D., P.H., University of Colorado at Boulder, Boulder, United States and Janelle Hakala, University of North Dakota, Grand Forks, ND, United States
Role of Hydrological Ensemble Forecasts in Operational Decision Making (184227)
Venkatsundar Ramaswamy1, Firas Saleh1, Nickitas Georgas2 and Alan F Blumberg3, (1)Stevens Institute of Technology, Davidson Laboratory, Deptartment of Civil, Environmental and Ocean Engineering, Union City, NJ, United States, (2)Stevens Institute of Technology, Davidson Laboratory, Deptartment of Civil, Environmental and Ocean Engineering, Hoboken, United States, (3)Jupiter Intelligence, New York, NY, United States
A New Artificial Neural Network Enhanced by the Shuffled Complex Evolution Optimization with Principal Component Analysis (SP-UCI) for Water Resources Management (153051)
Negin Hayatbini1, Mohammad Faridzad2, Tiantian Yang2, Ata Akbari Asanjan2, Xiaogang Gao2 and Soroosh Sorooshian1, (1)University of California, Irvine, Department of Civil and Environmental Engineering, Irvine, United States, (2)University of California Irvine, Irvine, CA, United States
Medium-term hydrologic forecasting in mountain basins using forecasting of a mesoscale numerical weather model (179053)
Lina Mabel Castro Heredia1, Francisco I Suarez2, Bonifacio Fernandez3 and Tamara Maass3, (1)Pontifical Catholic University of Valpara�so, Valparaiso, Chile, (2)Pontificia Universidad Católica de Chile, Santiago, Chile, (3)Pontifical Catholic University of Chile, Santiago, Chile
Using additional external inputs to forecast water quality with an artificial neural network for contamination event detection in source water (187244)
Franziska Schmidt, University of California Berkeley, Berkeley, CA, United States and Shuming Liu, Tsinghua University, Beijing, China
Improving medium-range ensemble streamflow forecasts through statistical post-processing (138571)
Pablo A. Mendoza1, Andrew W Wood1, Elizabeth Clark2, Bart Nijssen3, Martyn P Clark4, Maria-Helena Ramos5 and Nathalie Voisin6, (1)National Center for Atmospheric Research, Boulder, CO, United States, (2)University of California Los Angeles, Los Angeles, CA, United States, (3)University of Washington Seattle Campus, Seattle, WA, United States, (4)National Center for Atmospheric Research, Boulder, United States, (5)IRSTEA, Antony Cedex, France, (6)Pacific Northwest National Laboratory, Richland, WA, United States
Quantifying the Impact of the 2015-2016 El Niño Event on California’s Historic Drought to Improve Water Resource Management (184338)
Brittany N Zajic1, Justin Lawrence1, Lauryn Gutowski1, Nick Joseph Rousseau1, John T Reager II2, Mark E Jackson3, Jayme L Laber3 and John L Dumas3, (1)NASA DEVELOP Program, Jet Propulsion Laboratory, Pasadena, CA, United States, (2)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States, (3)NOAA National Weather Service, Oxnard, CA, United States
Temporal rainfall estimation using input data reduction and model inversion (193487)
Ashley James Wright1, Jasper A Vrugt2, Jeffrey P Walker3 and Valentijn R N Pauwels1, (1)Monash University, Melbourne, Australia, (2)University of California Irvine, Irvine, United States, (3)Monash University, Department of Civil Engineering, Clayton, VIC, Australia
Improved short range forecasting by blending techniques using extrapolation and NWP model forecasts (170433)
Min Jang, Joon Bum Jee, Sangil Kim and Jeong Gyun Park, Hankuk University of Foreign Studies, Yongin, Korea, Republic of (South)
Simulation of the water balance of boreal watersheds of northeastern British Columbia, Canada using MIKE SHE, an integrated hydrological model (117586)
Sina Abadzadesahraei, University of Northern British Columbia, Natural Resources and Environmental Studies, Prince George, BC, Canada, Stephen Déry, University of Northern British Columbia, Prince George, BC, Canada and John F Rex, Ministry of Forests and Lands, Prince George, BC, Canada
Analysis of long term precipitation patterns and trends over Maritime continent on different land categories using WRF model (131190)
Saurabh kumar Singh, Edmond Y Lo and Xiaosheng Qin, Nanyang Technological University, Singapore, Singapore
EFFECT OF SOIL HYDROLOGIC PROPERTIES ON APRIORI AND CALIBRATED PARAMETERS FOR SACRAMENTO MODEL SIMULATION WITH TEST OF PARAMETER TRANSFERABILITY WITHIN CLUSTERS IN EASTERN UNITED STATES (194621)
Wafa Chouaib II, PhD candidate, Forest Resources management, Vancouver, Canada and Younes Alila, University of British Columbia, Forest Resource Management, Vancouver, BC, Canada
Sensitivity of Hydrologic Extremes to Spatial Resolution of Meteorological Forcings: A Case Study of the Conterminous United States (142020)
Shih-Chieh Kao1,2, Bibi S Naz3, Sudershan Gangrade4,5, Moetasim Ashfaq1,6 and Deeksha Rastogi6,7, (1)Oak Ridge National Laboratory, Climate Change Science Institute, Oak Ridge, TN, United States, (2)Oak Ridge National Laboratory, Environmental Science Division, Oak Ridge, TN, United States, (3)Research Centre Jülich (FZJ), Institute of Bio- and Geosciences, Agrosphere (IBG-3), Jülich, Germany, (4)University of Tennessee, Knoxville, Knoxville, TN, United States, (5)Oak Ridge National Laboratory, Oak Ridge, TN, United States, (6)Oak Ridge National Laboratory, Computational Sciences and Engineering Division, Oak Ridge, TN, United States, (7)University of Tennessee, Knoxville, TN, United States
Model calibration for changing climates: lessons from Australian droughts. (145647)
Keirnan Fowler1, Murray Cameron Peel2, Andrew William Western2 and Lu Zhang3, (1)University of Melbourne, Department of Infrastructure Engineering, Parkville, Australia, (2)University of Melbourne, Department of Infrastructure Engineering, Parkville, VIC, Australia, (3)CSIRO Land and Water, Canberra, Australia
Catchments as non-linear filters: evaluating data-driven approaches for spatio-temporal predictions in ungauged basins (196241)
Dino G. Bellugi1, Christopher Tennant2 and Laurel Larsen2, (1)University of California Berkeley, Geography, Berkeley, United States, (2)University of California Berkeley, Geography, Berkeley, CA, United States
On the need to improve the Uncertainty of River Flow Projections in the Yongdam Watershed, South Korea (170491)
Getachew Tegegne Damtew1, Dong Kwan Park2, Youngil Kim2 and Young-Oh Kim2, (1)Seoul National University, Seoul, Korea, Republic of (South), (2)Seoul National University, Civil and Environmental Engineering, Seoul, Korea, Republic of (South)

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