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Hydrology & Water Resources Laboratory

Dwindling water resources, increasing susceptibility to hydrologic, hydrometeorological and hydroclimatological extremes, and climate change and variability demand more accurate and reliable water information and put increasingly higher premium on actionable predictive water information. HWRL focuses on integrative hydrologic prediction and water resources information research for sustainable and resilient management and planning of water resources and hazards.

Recent Publications (2013~)

Habibi, H., Nasab, A.R., Norouzi, A., Nazari, B., Seo, D.-J., Muttiah, R., Davis, C., 2016. High Resolution Flash Flood Forecasting for the Dallas-Fort Worth Metroplex. JWMM. doi:10.14796/JWMM.C401

Kim, B., Seo, D.-J., Noh, S.J., Prat, O.P., Nelson, B.R., 2016. Improving Multisensor Estimation of Heavy-to-Extreme Precipitation via Conditional Bias-Penalized Optimal Estimation. J. Hydrol. in press.

Lee, H., Seo, D.-J., Noh, S. J., 2016. A weakly-constrained data assimilation approach to address rainfall-runoff model structural inadequacy in streamflow prediction. J. Hydrol. in press.

Nelson, B.R., Prat, O.P., Seo, D.-J., Habib, E., 2016. Assessment and Implications of NCEP Stage IV Quantitative Precipitation Estimates for Product Intercomparisons. Wea. Forecasting 31, 371–394.

Noh, S. J., Lee, S., An, H., Kawaike, K., Nakagawa, H. 2016. Ensemble urban flood simulation in comparison with laboratory-scale experiments: Impact of interaction models for manhole, sewer pipe, and surface flow. Adv. Water Resour. 97, 25-37.

Norouzi, A., Habibi, H., Nazari, B., Noh, S.J., Seo, D.-J., Zhang, Y., 2016. On Scale-Dependent Sensitivity of Frequency of Mean Areal Runoff in Urban Areas to Precipitation, Imperviousness and Soil, and Their Variations. J. Hydrol. in review.

Seo, D.-J., Saifuddin, M., 2016. Conditional bias-penalized Kalman filter for improved estimation and prediction of extremes. Stochastic Environmental Research and Risk Assessment, in review.

Zhang, Y., Reed, S., Gourley, J.J., Cosgrove, B., Kitzmiller, D., Seo, D.-J., Cifelli, R., 2016. The impacts of climatological adjustment of quantitative precipitation estimates on the accuracy of flash flood detection. J. Hydrol. in press.

Zhang, Y., Seo, D.-J., 2016. Recursive Estimators of Mean-areal and Local Bias in Precipitation Products that Account for Conditional Bias. Adv. Water Resour. in review.

Lee, H., Seo, D.-J., Zhang, Y., 2015. Utilizing satellite precipitation estimates for streamflow forecasting via adjustment of mean field bias in precipitation data and assimilation of streamflow. J. of Hydrol. 529, 779-794.

Rafieeinasab, A., Norouzi, A., Kim, S., Habibi, H., Nazari, B., Seo, D.-J., Lee, H., Cosgrove, B., Cui, Z., 2015. Toward high-resolution flash flood prediction in large urban areas – Analysis of sensitivity to spatiotemporal resolution of rainfall input and hydrologic modeling. J. Hydrol. Hydrologic Applications of Weather Radar 531, Part 2, 370–388.

Rafieeinasab, A., Norouzi, A., Seo, D.-J., Nelson, B., 2015. Improving high-resolution quantitative precipitation estimation via fusion of multiple radar-based precipitation products. J. Hydrol. 531, 320–336.

Zhang, Y., Seo, D.-J., Habib, E., McCollum, J., 2015. Differences in scale-dependent, climatological variation of mean areal precipitation based on satellite and radar-gauge observations. J. Hydrol. 522, 35–48. doi:10.1016/j.jhydrol.2014.11.077

Brown, J.D., Wu, L., He, M., Regonda, S., Lee, H., Seo, D.-J., 2014. Verification of temperature, precipitation, and streamflow forecasts from the NOAA/NWS Hydrologic Ensemble Forecast Service (HEFS): 1. Experimental design and forcing verification. J. Hydrol. 519, Part D, 2869–2889.

Brown, J.D., He, M., Regonda, S., Wu, L., Lee, H., Seo, D.-J., 2014. Verification of temperature, precipitation, and streamflow forecasts from the NOAA/NWS Hydrologic Ensemble Forecast Service (HEFS): 2. Streamflow verification. J. Hydrol. 519, Part D, 2847–2868.

Kim, S., Seo, D.-J., Riazim H., Shin, C., 2014. Improving water quality forecasting via data assimilation – Application of maximum likelihood ensemble filter to HSPF, J. Hydrol. 519(D), 2797-2809.

Rafieeinasab, A., Seo, D.-J., Lee, H., Kim, S., 2014. Comparative evaluation of maximum likelihood ensemble filter and ensemble Kalman filter for real-time assimilation of streamflow data into operational hydrologic models. J. Hydrol. 519, Part D, 2663–2675.

Seo, D.-J., Liu, Y., Moradkhani, H., Weerts, A., 2014. Ensemble prediction and data assimilation for operational hydrology (Editorial). J. Hydrol. Special Issue on Ensemble Prediction and Data Assimilation for Operational Hydrology, 519, 2661–2662.

Seo, D., Siddique, R., Ahnert, P., 2014. Objective Reduction of Rain Gauge Network via Geostatistical Analysis of Uncertainty in Radar-Gauge Precipitation Estimation. J. Hydrol. Eng. 20, 04014050. doi:10.1061/(ASCE)HE.1943-5584.0000969

Demargne, J., L. Wu, S. Regonda, J. Brown, H. Lee, M. He, D.-J. Seo, R. Hartman, H. Herr, M. Fresch, J. Schaake, and Y. Zhu, 2014. The Science of NOAA’s Operational Hydrologic Ensemble Forecast Service, Bulletin of the American Meteorological Society, doi: 10.1175/BAMS-D-12-00081.1.

Regonda, S., D.-J. Seo and B. Lawrence, 2013. Short-term Ensemble Streamflow Forecasting Using Operationally-Produced Single-valued Streamflow Forecasts - A Hydrologic Model Output Statistics (HMOS) Approach, Journal of Hydrology, 497(8), 80-96.

Seo D-J. 2013. Conditional bias-penalized kriging. Stochastic Environmental Research and Risk Assessment, January 2013, 27(1), 43-58.

Recent Presentations (2013~)

Saifuddin, M., Seo, D.-J., Lee, H., Noh, S. J., 2017. Improving estimation and prediction of extremes using conditional bias penalized Kalman filter, 97th American Meteorological Society Annual Meeting, Seattle, WA.

Habibi, H., Nazari, B., Norouzi, A., Noh, S. J., Seo, D.-J., Sinha, S., Yu. X., Bartos, M., Kerkez, B., Lakshman, L., Zink, M., Lyons, E., Philips, B., Jangyodsuk, P., Gao, J., 2017. Integrated sensing and prediction of flash floods for the Dallas-Fort Worth Metroplex (DFW), 97th American Meteorological Society Annual Meeting, Seattle, WA.

Limon, R. A., Kim, S., Seo, D.-J., Fincannon, T., Winguth, A., Blaylock, L., Lampe, M. B., Brown, J., Philpott, A., and Bell, F. 2017. 12A.5 Improving Reservoir Management in North Central Texas using Ensemble Forecasting, AMS Meeting,  Seattle, WA.

Noh, S. J., Nazari, B., Habibi, H., Norouzi, A., Nabatian, M., Seo, D.-J., Bartos, M., Kerkez, B., Zink, M., Lee, J., 2016. iSPUW: integrated sensing and prediction of urban water for sustainable cities, American Geophysical Union 2016 Fall Meeting, San Francisco, CA.

Fincannon, T., Winguth, A., Seo, D.-J., 2017. 14B.5 Improving Prediction of Drought Indices in the North Texas Region by Utilizing Regional Climatology and Global Climate Indices, AMS Meeting, Seattle, WA.

Norouzi, A. Habibi, H., Nazari, B., Noh, S. J. Seo, D.-J. , Zhang, Y., 2016. H23J-1709: On Flood Frequency in Urban Areas under Changing Conditions and Implications on Stormwater Infrastructure Planning and Design, AGU Meeting, San Francisco, CA.

Behzad Nazari, Dong-Jun Seo, Seongjin Noh, 2016. H24B-08: Real-time inundation mapping in large urban areas via downscaling of coarse-resolution model output, AGU Meeting, San Francisco, CA.

Hamideh Habibi, Amir Norouzi, Ahmari Habib, Dong-Jun Seo, 2016. H41B-1311: Integrated modeling of storm drain and natural channel networks for real-time flash flood forecasting in large urban areas, AGU Meeting, San Francisco, CA.

Kim, S., Limon, A. R., Alizadeh, B., Seo, D.-J., Fincannon, T., Winguth, A., Brown, J. Blaylock, L., Lampe, M., Philpott, A., Bell, F., 2016. H53I-08: Integrating Ensemble Forecasts of Precipitation and Streamflow into Decision Support for Reservoir Operations in North Central Texas, AGU Meeting, San Francisco, CA.

Seo, D.-J., 2016. Integrated sensing and prediction of urban water, ASCE Fort Worth Branch Meeting, Oct 18, Fort Worth, TX. (invited)

Seo, D.-J., 2016. Hydrologic Applications of Weather Radar – An  Urban View,  National  Weather Service, National Water Center, Jul 7, Silver Spring, MD.

Seo, D.-J., 2016. Hydrologic  Applications of Weather Radar – An  Urban View, Iowa Institute of Hydraulic Research Seminar, University of Iowa, Mar 4, Iowa City, IA. (invited)

Kim, S., Limon, R. A., Seo, D.-J., Fincannon, T., Winguth, A., Brown, J., 2016. Assessing the value of ensemble forecasts of precipitation and streamflow in water management in North Central Texas, EWRI, West Palm Beach, FL.

Kim, S. Seo, D.-J. Sadeghi, H., Philpott, A., Bell, F. Fincannon, T., Winguth, A., Limon, A. R., Blaylock, L., Brown, J., Fang, N., Clingenpeel, G., 2016. Climate forecast-aided drought decision support for North Central Texas, AMS Meeting, New Orleans, LA.

Lee, S., Noh, S. J., Lee, J., Seo, D.-J., 2016. Hyper-resolution urban flood modeling using high-resolution radar precipitation and LiDAR data, American Geophysical Union 2016 Fall Meeting, San Francisco, CA.

Lee, J., Dhakal, B., Noh, S. J., Seo, D.-J., 2016. Integrated control of landscape irrigation and rainwater harvesting for urban water management, American Geophysical Union 2016 Fall Meeting, San Francisco, CA.

Noh, S. J., Mazzoleni, M., Lee, H., Liu, Y., Seo, D.-J., Solomatine, D., 2016. Real-time assimilation of observations from heterogeneous sensors into hydrologic routing models, Hydroinformatics 2016, Incheon, South Korea.

Seo, D.-J., Fang, Z., Yu, X., Gao, J., Kerkez, B., Zink, M., Noh, S. J., Lee, J., 2016. iSPUW: integrated sensing and prediction of urban water for sustainable cities, Hydroinformatics 2016, Incheon, South Korea.

Noh, S. J., Rakovec, O., Kumar, R., Samaniego, L., Seo, D.-J., 2016. Streamflow hindcasting in European river basins via mesoscale hydrologic model (mHM) and ensemble-based data assimilation, Hydroinformatics 2016, Incheon, South Korea.

Noh, S. J., Mazzoleni, M., Lee, H., Liu, Y., Seo, D.-J., Solomatine, D., Kerkez, B., 2016. Real-time assimilation of crowdsourced observations into hydrologic routing models for improved river forecasting, ASCE EWRI Congress 2016, FL.

Habibi, H., Nazari, B., Norouzi, A., Seo, D.-J., Noh, S. J., Jangyodsuk, P., Gao, J., Muttiah, R., Chen, H., Chandrasekar, V., Lyons, E., Philips, B., Kerkez, B., Zink, M., 2016. Real-time flash flood forecasting for the Dallas-Fort Worth Metroplex (DFW), 96th American Meteorological Society Annual Meeting, Seattle, USA.

Seo et al. 2014. Data assimilation in ensemble water forecasting – Challenges and opportunities (invited). 10th Anniversary HEPEX Workshop, College Park, MD, June 24-26.

Seo, D.-J., R. Siddique, Y. Zhang and  D. Kim, 2014. Improving Real-Time Estimation of Heavy-to-Extreme Precipitation Using Rain Gauge Data via Conditional Bias-Penalized Optimal Estimation. NWS/OHD Seminar, Silver Spring, MD, May 22.

Rafieei Nasab, A., A. Norouzi, D.-J. Seo, S. Kim, H. Chen, V. Chandrasekar, B. Cosgrove, A. Cannon, 2014. High-resolution flash flood forecasting for large urban areas – Sensitivity to scale of precipitation input and model resolution, International Symposium on Weather Radar and Hydrology, Reston, VA.

Rafieei Nasab, A., A. Norouzi, T. Mathew, D.-J. Seo, H. Chen, V. Chandrasekar, P. Rees, B. Nelson, 2014. Comparative evaluation of multiple radar-based QPEs for North Texas, International Symposium on Weather Radar and Hydrology, Reston, VA.

Nazari, B., D.-J. Seo, R. Muttiah, C. Davis, 2014. Hydraulic modeling for inundation mapping using radarrainfall data - A case study for the City of Fort Worth, WRaH 2014, Reston, VA.

Seo, D.-J., M. Saharia, R. Corby, F. Bell and J. Brown, 2013. Increasing lead time in short-range ensemble streamflow forecasting via the Hydrologic Ensemble Forecast Service (HEFS), AGU Annual Meeting, San Francisco (Invited).

Seo, D.-J., S. Kim, H. Riazi and C. Shin, 2013. Improving Water Quality Forecasting via Real-Time Data Assimilation, EPA Region 6 Water Quality Modeling Conference & Workshop, Dallas, TX (Invited).

Seo, D.-J., A. Rafieeinasab, B. Nazari, A. Norouzi, V.  Chandrasekar, H. Chen, S. Kim, J. Gao, P. Jangyodsuk, and C.  Davis, 2013. High-resolution  flash flood forecasting for large urban areas. International Workshop on Rain Radar and its Hydrologic Application, Korea Institute of Construction Technology, Goyang, Korea (Invited).

Saharia, M., D.-J. Seo, R. Corby and F. Bell, 2013. Increasing lead time in short-range streamflow forecasting via the Hydrologic Ensemble Forecast Service (HEFS). NWS/OHD Seminar, Silver Spring, MD.

Rafieeinasab,  A.,  A. Norouzi, H. Chen, D.-J. Seo, V. Chandrasekar and A.  Cannon, 2013. High-resolution flash flood forecasting for the City of Fort Worth. NWS/OHD Seminar, Silver Spring, MD.

Chandrasekar, V.,  H. Chen, D.-J. Seo, 2013. Impacts of Polarimetric CASA Radar Observations on a Distributed Hydrologic Model, EGU General Assembly, Vienna, Austria.

Chandrasekar, V., H. Chen, B. Philips, D.-J. Seo, F. Junyent, A. Bajaj, M. Zink, J. McEnery, Z. Sukheswalla, A. Cannon, E. Lyons, D. Westbrook, 2013. The CASA Dallas Fort Worth Remote Sensing Network ICT for Urban Disaster Mitigation, EGU General Assembly, Vienna, Austria.

Saharia, M., D.-J. Seo, R. Corby, K. He, 2013.  Short-Range Ensemble Streamflow Forecasting for Upper Trinity River, AGU Meeting of the Americas, Cancun, Mexico.

S. Kim, D.-J. Seo, H. Riazi, and C. Shin, 2013. Improving water quality forecasting with HSPF via ensemble data assimilation. AGU Meeting of the Americas, Cancun, Mexico.

Siddique, R, D.-J. Seo, Y. Zhang, D. Kim, 2013. Improving analysis of heavy to extreme precipitation with conditional bias-penalized optimal estimation, 27th Conference on Hydrology, AMS Annual Meeting, Cancun,  Mexico.

Rafieeinasab, A., D.-J. Seo, R. Corby, P. McKee,  2013. Evaluation of the NWS Distributed Hydrologic Model over the Trinity River Basin in Texas, 27th Conference on Hydrology, AMS  Annual Meeting, Austin, TX.