scholarly journals Impact Assessment of Spatial Resolution of Radar Rainfall and a Distributed Hydrologic Model on Parameter Estimation

2014 ◽  
Vol 34 (5) ◽  
pp. 1443-1454 ◽  
Author(s):  
Seong Jin Noh ◽  
Shin Woo Choi ◽  
Yun Seok Choi ◽  
Kyung Tak Kim
Keyword(s):  
Parameter Estimation ◽  
Impact Assessment ◽  
Spatial Resolution ◽  
Hydrologic Model ◽  
Radar Rainfall ◽  
Distributed Hydrologic Model

scholarly journals Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

2011 ◽  
Vol 15 (12) ◽  
pp. 3809-3827 ◽  
Author(s):  
A. Atencia ◽  
L. Mediero ◽  
M. C. Llasat ◽  
L. Garrote
Keyword(s):  
Sensitivity Analysis ◽  
Time Resolution ◽  
Heavy Rainfall ◽  
Flash Flood ◽  
Probabilistic Approach ◽  
Great Influence ◽  
Hydrologic Model ◽  
Radar Rainfall ◽  
Distributed Hydrologic Model ◽  
Correction Technique

Abstract. The performance of a hydrologic model depends on the rainfall input data, both spatially and temporally. As the spatial distribution of rainfall exerts a great influence on both runoff volumes and peak flows, the use of a distributed hydrologic model can improve the results in the case of convective rainfall in a basin where the storm area is smaller than the basin area. The aim of this study was to perform a sensitivity analysis of the rainfall time resolution on the results of a distributed hydrologic model in a flash-flood prone basin. Within such a catchment, floods are produced by heavy rainfall events with a large convective component. A second objective of the current paper is the proposal of a methodology that improves the radar rainfall estimation at a higher spatial and temporal resolution. Composite radar data from a network of three C-band radars with 6-min temporal and 2 × 2 km2 spatial resolution were used to feed the RIBS distributed hydrological model. A modification of the Window Probability Matching Method (gauge-adjustment method) was applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation by computing new Z/R relationships for both convective and stratiform reflectivities. An advection correction technique based on the cross-correlation between two consecutive images was introduced to obtain several time resolutions from 1 min to 30 min. The RIBS hydrologic model was calibrated using a probabilistic approach based on a multiobjective methodology for each time resolution. A sensitivity analysis of rainfall time resolution was conducted to find the resolution that best represents the hydrological basin behaviour.

scholarly journals A large-scale, high-resolution hydrological model parameter data set for climate change impact assessment for the conterminous US

2014 ◽  
Vol 18 (1) ◽  
pp. 67-84 ◽  
Author(s):  
A. A. Oubeidillah ◽  
S.-C. Kao ◽  
M. Ashfaq ◽  
B. S. Naz ◽  
G. Tootle
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Impact Assessment ◽  
Spatial Resolution ◽  
Climate Impact ◽  
Hydrologic Model ◽  
Model Parameters ◽  
Data Set ◽  
Model Parameter ◽  
Climate Impact Assessment

Abstract. To extend geographical coverage, refine spatial resolution, and improve modeling efficiency, a computation- and data-intensive effort was conducted to organize a comprehensive hydrologic data set with post-calibrated model parameters for hydro-climate impact assessment. Several key inputs for hydrologic simulation – including meteorologic forcings, soil, land class, vegetation, and elevation – were collected from multiple best-available data sources and organized for 2107 hydrologic subbasins (8-digit hydrologic units, HUC8s) in the conterminous US at refined 1/24° (~4 km) spatial resolution. Using high-performance computing for intensive model calibration, a high-resolution parameter data set was prepared for the macro-scale variable infiltration capacity (VIC) hydrologic model. The VIC simulation was driven by Daymet daily meteorological forcing and was calibrated against US Geological Survey (USGS) WaterWatch monthly runoff observations for each HUC8. The results showed that this new parameter data set may help reasonably simulate runoff at most US HUC8 subbasins. Based on this exhaustive calibration effort, it is now possible to accurately estimate the resources required for further model improvement across the entire conterminous US. We anticipate that through this hydrologic parameter data set, the repeated effort of fundamental data processing can be lessened, so that research efforts can emphasize the more challenging task of assessing climate change impacts. The pre-organized model parameter data set will be provided to interested parties to support further hydro-climate impact assessment.

scholarly journals Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

2010 ◽  
Vol 7 (5) ◽  
pp. 7995-8043 ◽  
Author(s):  
A. Atencia ◽  
M. C. Llasat ◽  
L. Garrote ◽  
L. Mediero
Keyword(s):  
Hydrological Model ◽  
Radar Data ◽  
Hydrologic Model ◽  
Rainfall Data ◽  
Distributed Hydrological Model ◽  
Probability Matching ◽  
Radar Rainfall ◽  
Distributed Hydrologic Model ◽  
Surface Data ◽  
Distributed Hydrological Models

Abstract. The performance of distributed hydrological models depends on the resolution, both spatial and temporal, of the rainfall surface data introduced. The estimation of quantitative precipitation from meteorological radar or satellite can improve hydrological model results, thanks to an indirect estimation at higher spatial and temporal resolution. In this work, composed radar data from a network of three C-band radars, with 6-minutal temporal and 2 × 2 km2 spatial resolution, provided by the Catalan Meteorological Service, is used to feed the RIBS distributed hydrological model. A Window Probability Matching Method (gage-adjustment method) is applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation in both convective and stratiform Z/R relations used over Catalonia. Once the rainfall field has been adequately obtained, an advection correction, based on cross-correlation between two consecutive images, was introduced to get several time resolutions from 1 min to 30 min. Each different resolution is treated as an independent event, resulting in a probable range of input rainfall data. This ensemble of rainfall data is used, together with other sources of uncertainty, such as the initial basin state or the accuracy of discharge measurements, to calibrate the RIBS model using probabilistic methodology. A sensitivity analysis of time resolutions was implemented by comparing the various results with real values from stream-flow measurement stations.

scholarly journals A large-scale, high-resolution hydrological model parameter dataset for climate change impact assessment for the conterminous United States

2013 ◽  
Vol 10 (7) ◽  
pp. 9575-9613 ◽  
Author(s):  
A. A. Oubeidillah ◽  
S.-C. Kao ◽  
M. Ashfaq ◽  
B. Naz ◽  
G. Tootle
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Impact Assessment ◽  
Spatial Resolution ◽  
Climate Change Impact ◽  
Hydrologic Model ◽  
Model Parameters ◽  
Climate Change Impact Assessment ◽  
Macro Scale ◽  
Change Impact

Abstract. To extend geographical coverage, refine spatial resolution, and improve modeling efficiency, a computation- and data-intensive effort was conducted to organize a comprehensive hydrologic dataset with post-calibrated model parameters for hydro-climate impact assessment. Several key inputs for hydrologic simulation, including meteorologic forcings, soil, land class, vegetation, and elevation, were collected from multiple best-available data sources and organized for 2107 hydrologic Subbasins (HUC8s) in the conterminous US at refined 1/24° (~ 4 km) spatial resolution. Using high performance computing for intensive model calibration, a high-resolution parameter dataset was prepared for the macro-scale Variable Infiltration Capacity (VIC) hydrologic model. The VIC simulation was driven by DAYMET daily meteorological forcing and was calibrated against the USGS WaterWatch monthly runoff observations for each HUC8. The results showed that this new parameter dataset may help reasonably simulate runoff at most of the US HUC8 Subbasins. Based on this exhaustive calibration effort, it is now possible to accurately estimate the required resources for further model improvement across the entire conterminous US. We anticipate that through this hydrologic parameter dataset, the repeated effort of fundamental data processing can be lessened, so that research efforts can be emphasized on the more challenging climate change impact assessment.

scholarly journals Evaluation of a Distributed Streamflow Forecast Model at Multiple Watershed Scales

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1279
Author(s):  
Tyler Madsen ◽  
Kristie Franz ◽  
Terri Hogue
Keyword(s):  
Local Population ◽  
Model Performance ◽  
Forecast Model ◽  
Hydrologic Model ◽  
Laboratory Research ◽  
Discharge Data ◽  
Distributed Hydrologic Model ◽  
Verification Period ◽  
Silver Spring

Demand for reliable estimates of streamflow has increased as society becomes more susceptible to climatic extremes such as droughts and flooding, especially at small scales where local population centers and infrastructure can be affected by rapidly occurring events. In the current study, the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) (NOAA/NWS, Silver Spring, MD, USA) was used to explore the accuracy of a distributed hydrologic model to simulate discharge at watershed scales ranging from 20 to 2500 km2. The model was calibrated and validated using observed discharge data at the basin outlets, and discharge at uncalibrated subbasin locations was evaluated. Two precipitation products with nominal spatial resolutions of 12.5 km and 4 km were tested to characterize the role of input resolution on the discharge simulations. In general, model performance decreased as basin size decreased. When sub-basin area was less than 250 km2 or 20–40% of the total watershed area, model performance dropped below the defined acceptable levels. Simulations forced with the lower resolution precipitation product had better model evaluation statistics; for example, the Nash–Sutcliffe efficiency (NSE) scores ranged from 0.50 to 0.67 for the verification period for basin outlets, compared to scores that ranged from 0.33 to 0.52 for the higher spatial resolution forcing.

Continuous streamflow simulation with the HRCDHM distributed hydrologic model

2004 ◽  
Vol 298 (1-4) ◽  
pp. 61-79 ◽  
Author(s):  
Theresa M. Carpenter ◽  
Konstantine P. Georgakakos
Keyword(s):  
Hydrologic Model ◽  
Distributed Hydrologic Model ◽  
Streamflow Simulation
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