A5042943987- Meteorological Phenomena and Simulations
- Hydrology and Watershed Management Studies
- Flood Risk Assessment and Management
- Precipitation Measurement and Analysis
- Hydrological Forecasting Using AI
- Hydrology and Drought Analysis
- Climate variability and models
- Soil Moisture and Remote Sensing
- Tropical and Extratropical Cyclones Research
- Reservoir Engineering and Simulation Methods
- Cryospheric studies and observations
- Environmental Monitoring and Data Management
- Oceanographic and Atmospheric Processes
- Fault Detection and Control Systems
- Target Tracking and Data Fusion in Sensor Networks
- Water Quality Monitoring Technologies
- Water resources management and optimization
- Flow Measurement and Analysis
- Hydrology and Sediment Transport Processes
- Scientific Computing and Data Management
- Anomaly Detection Techniques and Applications
- Remote Sensing and LiDAR Applications
- Seismic Imaging and Inversion Techniques
- Coastal and Marine Dynamics
- Groundwater flow and contamination studies
The University of Texas at Arlington
2014-2023
Electronics and Telecommunications Research Institute
2022
Cooperative Institute for Mesoscale Meteorological Studies
2019
University of Oklahoma
2019
NOAA National Severe Storms Laboratory
2019
Kumoh National Institute of Technology
2019
Chonnam National University
2018
The University of Texas at Austin
2017-2018
Korea Institute of Energy Research
2018
Yonsei University
2018
Abstract. Data assimilation (DA) holds considerable potential for improving hydrologic predictions as demonstrated in numerous research studies. However, advances DA have not been adequately or timely implemented operational forecast systems to improve the skill of forecasts better informed real-world decision making. This is due part a lack mechanisms properly quantify uncertainty observations and models real-time forecasting situations conduct merging data way that efficient transparent...
Abstract. In addition to the uncertainty in future boundary conditions of precipitation and temperature (i.e. meteorological uncertainty), parametric structural uncertainties hydrologic models model initial uncertainties) constitute a major source error prediction. As such, accurate accounting both is critical producing reliable probabilistic this paper, we describe evaluate statistical procedure that accounts for short-range (1 5 days ahead) ensemble streamflow prediction (ESP). Referred as...
Abstract. A procedure is presented to construct ensemble forecasts from single-value of precipitation and temperature. This involves dividing the spatial forecast domain total period into a number parts that are treated as separate events. The divided hydrologic sub-basins. time periods, one for each model step. For event archived values corresponding observations used joint distribution observations. conditional given represent probability events may occur forecast. subsequently create...
Cokriging is used to merge rain gage measurements and radar rainfall data. The cokriging estimators included are ordinary, universal, disjunctive. To evaluate the estimators, two simulation experiments performed. first experiment assumes that high‐quality fields ground truth fields. From each field, multiple combinations of measurement field artificially generated with varying network density error characteristics rainfall. second uses a stochastic space‐time model generate assumed various...
Abstract This paper evaluates a nonparametric technique for estimating the conditional probability distribution of predictand given vector predictors. In current application, predictors are formed from multimodel ensemble simulated streamflows, such that hydrologic uncertainties modelled independently any forcing uncertainties. The is based on Bayesian optimal linear estimation indicator variables and analogous to cokriging (ICK) in geostatistics. By developing estimators observed variable...
Abstract This paper presents a strategy for diagnostic verification of hydrologic ensembles, based on the selection summary metrics (which could be extended to more detailed metrics) and analysis relative contribution different sources error. Such conducted with Ensemble Verification System (EVS) is illustrated case study experimental precipitation streamflow ensemble reforecasts over 24‐year period. The EVS proposed as flexible modular tool HEPEX test‐bed evaluate existing emerging methods...
Various estimation procedures using ordinary, universal, and disjunctive cokriging are evaluated in merging rain gage measurements radar rainfall data. The the simulation experiments were described part 1 (Seo et al., this issue) of two‐part work. In part, detail. An objective comparison scheme, devised to compare a large number estimators, is also described. results presented focusing upon (1) potential radar‐gage over radar‐only gage‐only under widely varying conditions network density...
Abstract. Data assimilation (DA) holds considerable potential for improving hydrologic predictions as demonstrated in numerous research studies. However, advances DA have not been adequately or timely implemented into operational forecast systems to improve the skill of forecasts better inform real-world decision making. This is due part a lack mechanisms properly quantify uncertainty observations and models real-time forecasting situations conduct merging data way that efficient transparent...
This paper comparatively assesses the performance of five data assimilation techniques for three-parameter Muskingum routing with a spatially lumped or distributed model structure. The used include direct insertion (DI), nudging scheme (NS), Kalman filter (KF), ensemble (EnKF) and asynchronous (AEnKF), which are applied to river reaches in Texas Louisiana, USA. For both routing, results from KF, EnKF AEnKF sensitive error specification. As expected, DI outperformed other models case...
Hurricane Harvey was one of the most extreme weather events to occur in Texas, USA; there a huge amount urban flooding city Houston and adjoining coastal areas. In this study, we reanalyze spatiotemporal evolution inundation during using high-resolution two-dimensional flood modeling. This study’s domain includes bayou basins around metropolitan area. The model uses dynamic wave method terrain data 10-m resolution. It is forced by radar-based quantitative precipitation estimates. To evaluate...
Abstract A novel multiscale postprocessor for ensemble streamflow prediction, MS-EnsPost, is described and comparatively evaluated with the existing in National Weather Service’s Hydrologic Ensemble Forecast Service, EnsPost. MS-EnsPost uses data-driven correction of magnitude-dependent bias simulated flow, regression using observed flows over a range temporal aggregation scales, generation parsimonious error modeling. For comparative evaluation, 139 basins eight River Centers United States...