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 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 Extreme runoff response to short-duration convective rainfall in South-West Germany

2011 ◽  
Vol 8 (6) ◽  
pp. 10739-10780
Author(s):  
V. Ruiz-Villanueva ◽  
M. Borga ◽  
D. Zoccatelli ◽  
L. Marchi ◽  
E. Gaume ◽  
...  
Keyword(s):  
High Resolution ◽  
Flash Flood ◽  
Rain Gauge ◽  
Hydrologic Model ◽  
West Germany ◽  
Structure Evolution ◽  
Model Parameters ◽  
Distributed Hydrological Model ◽  
Precipitation Frequency ◽  
South West

Abstract. The 2 June 2008 flood-producing storm on the Starzel river basin in South-West Germany is examined as a prototype for organized convective systems that dominate the upper tail of the precipitation frequency distribution and are likely responsible for the flash flood peaks in this region. The availability of high-resolution rainfall estimates from radar observations and a rain gauge network, together with indirect peak discharge estimates from a detailed post-event survey, provides the opportunity to study the hydrometeorological and hydrological mechanisms associated with this extreme storm and the ensuing flood. Radar-derived rainfall, streamgauge data and indirect estimates of peak discharges are used along with a distributed hydrologic model to reconstruct hydrographs at multiple locations. The influence of storm structure, evolution and motion on the modeled flood hydrograph is examined by using the "spatial moments of catchment rainfall" (Zoccatelli et al., 2011). It is shown that downbasin storm motion had a noticeable impact on flood peak magnitude. Small runoff ratios (less than 20%) characterized the runoff response. The flood response can be reasonably well reproduced with the distributed hydrological model, using high resolution rainfall observations and model parameters calibrated at a river section which includes most of the area impacted by the storm.

The influence of system boundaries and baseline in climate impact assessment of forest products

2018 ◽  
Vol 24 (1) ◽  
pp. 160-176 ◽  
Author(s):  
Diego Peñaloza ◽  
Frida Røyne ◽  
Gustav Sandin ◽  
Magdalena Svanström ◽  
Martin Erlandsson
Keyword(s):  
Impact Assessment ◽  
Forest Products ◽  
Climate Impact ◽  
System Boundaries ◽  
Climate Impact Assessment

scholarly journals How evaluation of global hydrological models can help to improve credibility of river discharge projections under climate change

2020 ◽  
Vol 163 (3) ◽  
pp. 1353-1377 ◽  
Author(s):  
Valentina Krysanova ◽  
Jamal Zaherpour ◽  
Iulii Didovets ◽  
Simon N. Gosling ◽  
Dieter Gerten ◽  
...  
Keyword(s):  
Impact Assessment ◽  
Model Evaluation ◽  
Model Performance ◽  
Poor Performance ◽  
Climate Impact ◽  
Hydrological Models ◽  
Weighted Mean ◽  
Climate Impact Assessment ◽  
Ensemble Mean ◽  
The Mean

AbstractImportance of evaluation of global hydrological models (gHMs) before doing climate impact assessment was underlined in several studies. The main objective of this study is to evaluate the performance of six gHMs in simulating observed discharge for a set of 57 large catchments applying common metrics with thresholds for the monthly and seasonal dynamics and summarize them estimating an aggregated index of model performance for each model in each basin. One model showed a good performance, and other five showed a weak or poor performance in most of the basins. In 15 catchments, evaluation results of all models were poor. The model evaluation was supplemented by climate impact assessment for a subset of 12 representative catchments using (1) usual ensemble mean approach and (2) weighted mean approach based on model performance, and the outcomes were compared. The comparison of impacts in terms of mean monthly and mean annual discharges using two approaches has shown that in four basins, differences were negligible or small, and in eight catchments, differences in mean monthly, mean annual discharge or both were moderate to large. The spreads were notably decreased in most cases when the second method was applied. It can be concluded that for improving credibility of projections, the model evaluation and application of the weighted mean approach could be recommended, especially if the mean monthly (seasonal) impacts are of interest, whereas the ensemble mean approach could be applied for projecting the mean annual changes. The calibration of gHMs could improve their performance and, consequently, the credibility of projections.

High-resolution pan-European multi-model simulations of hydrologic states and fluxes

2020 ◽  
Author(s):  
Bibi S Naz ◽  
Wendy Sharples ◽  
Klaus Goergen ◽  
Stefan Kollet
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Groundwater Flow ◽  
Hydrologic Model ◽  
Hydrological Processes ◽  
Model Parameters ◽  
Time Step ◽  
European Continent ◽  
Model Simulations ◽  
Community Land Model

<p> <span>High-resolution large-scale predictions of hydrologic states and fluxes are important for many regional-scale applications and water resource management. However, because of uncertainties related to forcing data, model structural errors arising from simplified representations of hydrological processes or uncertain model parameters, model simulations remain uncertain. To quantify this uncertainty, multi-model simulations were performed at 3km resolution over the European continent using the Community Land Model (CLM3.5) and the ParFlow hydrologic model. While Parflow uses a similar approach as CLM in simulating the snow, vegetation and land-atmosphere exchange processes, it simulates three-dimensional variably saturated groundwater flow solving Richards equation and overland flow with a two-dimensional kinematic wave approximation. </span><span>The </span><span>CLM</span><span>3.5</span><span> uses a simple groundwater model to account for groundwater recharge and discharge processes. Both models were driven with the COSMO-REA6 reanalysis dataset at 6km resolution for the time period from 2000 to 2006 at an hourly time step, and both used the same datasets for the static input variables (such as topography, vegetation and soil properties). The performance of both models was analyzed through comparisons with independent observations including satellite-derived and in-situ soil moisture, evapotranspiration, river discharge, water table depth and total water storage datasets. Overall, both models capture the interannual variability in the hydrologic states and fluxes well, however differences in performance between models showed the uncertainty associated with the representation of hydrological processes, such as groundwater flow and soil moisture and its control on latent and sensible heat fluxes at the surface.</span></p>

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