Poster Session 1 Flood Prediction, Analysis, Decision Support, and Management—Posters

Monday, 13 January 2020: 4:00 PM-6:00 PM
Hall B (Boston Convention and Exhibition Center)
Host: 34th Conference on Hydrology
David Gochis, NCAR, Boulder, CO
Kristie Franz, Iowa State University, Ames, IA

A number of regional and national real-time flood forecasting systems are emerging for a variety of different flood-related applications. These new systems are taking advantage of new national hydrologic data standards, new advances in supercomputing availability and improvements in model parameterizations and meteorological forcing datasets. This session encourages contributions from all sectors of the AMS enterprise (academic, government and the private sector) who have built and deployed such systems. Additionally, contributions are welcome from researchers who have developed novel methodologies to sense and model flood generation dynamics at a variety of time and space scales. Research and application contributions from within the U.S. as well as internationally are also encouraged.

Please note that there is a different session in this conference on heavy precipitation events, flood risk under climate change (see "Heavy Precipitation and Flood Risk under a Changing Climate").

Utilizing Dual-Pol Digital Precipitation Rate to Predict Flash Flooding in Central Kentucky and Southern Indiana
Melissa Piper, Iowa State Univ., Ames, IA; and A. Schoettmer and T. Funk

Heavy Rainfall Event in Central Vietnam in December 2018 and QPE/QPF at VNMHA
Kazuo Saito, Japan Meteorological Business Support Center, Tokyo, Japan; Meteorological Reserch Institute, Tsukuba, Japan; Atmosphere and Ocean Research Institute, Kashiwa, Japan; and D. D. Tien, M. K. Hung, and L. Duc

Handout (1.5 MB)

Leveraging the "Analysis of Record for Calibration" to Improve Precipitation and Temperature Inputs for Hydrologic Modeling
Tyler Madsen, NOAA/NWS/Middle Atlantic River Forecast Center, State College, PA; and S. M. Reed and T. Rodgers

Handout (3.2 MB)

Assessment of Hydrologic Predictions Based on a Mix-and-Match Framework Using Multimodel and Multiprecipitation Forcing Data
Bong-Chul Seo, Univ. of Iowa, Iowa City, IA; and W. F. Krajewski and F. Quintero

Generation of WRF-Hydro Probabilistic Streamflow Forecasts by Shifting Ensemble QPF Based on a Climatology of Forecast Rainfall Displacement Errors
Kyle K. Hugeback, Iowa State Univ., Ames, IA; and B. M. Kiel, W. A. Gallus Jr., and K. J. Franz

Application of WRF-Hydro for Retrospective Seasonal Streamflow Simulations Using WRF-Hydro at Lake George, New York
Mukul Tewari, IBM Thomas J. Watson Research Center, Yorktown Heights, NY; and C. D. Watson, A. B. Buoro, V. W. Moriarty, and L. Treinish

The Community WRF-Hydro Modeling System Updates to the New Version 5.1.1/National Water Model Version 2.0 and New Supporting Tools for Pre - and Postprocessing
Molly McAllister, NCAR, Boulder, CO; NCAR, Boulder, CO; and D. J. Gochis, M. Barlage, R. Cabell, M. Casali, A. Dugger, K. FitzGerald, L. Karsten, J. McCreight, A. RafieeiNasab, L. Read, K. Sampson, D. Yates, and Y. Zhang

Streamflow Prediction Combining WRF-Hydro Modeling with LSTM
Kyeungwoo Cho, Yonsei Univ., Seoul, Korea, Republic of (South); and Y. Kim

Leveraging Novel Data Analytics for Clear Communication in South Carolina’s Extreme Precipitation and Flood Alert System
Katie L. Ward, MetStat, Inc., Fort Collins, CO; and T. W. Parzybok, B. Allen, V. Bahls, H. Mizzell, and M. Griffin

A Climatological Geospatial Analysis of Storm-Based Flash Flood Warnings across the CONUS
Katarina L. Christian, CIMMS, Norman, OK; and J. D. Hardy

Decoupling the Hydroclimatological Conditions before and during the Recent Flooding Event in the Missouri River Basin
Manas Khan, Univ. of Nebraska—Lincoln, Lincoln, NE; and C. Wunderlin, P. Sarzaeim, W. Ou, and F. Munoz-Arriola

Implementation and Evaluation of Channel Infiltration in the NOAA National Water Model for Semiarid Environments
Timothy M. Lahmers, The Univ. of Arizona, Tucson, AZ; and P. Hazenberg, H. V. Gupta, C. L. Castro, D. J. Gochis, A. Dugger, D. Yates, L. Read, L. Karsten, Y. H. Wang, R. J. Zamora, and B. A. Cosgrove

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner