scholarly journals A near-global, high resolution land surface parameter dataset for the variable infiltration capacity model

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Jacob R. Schaperow ◽  
Dongyue Li ◽  
Steven A. Margulis ◽  
Dennis P. Lettenmaier
Keyword(s):  
Land Surface ◽  
Global Scale ◽  
Radiation Budget ◽  
Soil Parameters ◽  
Variable Infiltration Capacity ◽  
Infiltration Capacity ◽  
Vic Model ◽  
Spatial Coverage ◽  
Land Surface Parameter ◽  
Vegetation Parameters

AbstractHydrologic models predict the spatial and temporal distribution of water and energy at the land surface. Currently, parameter availability limits global-scale hydrologic modelling to very coarse resolution, hindering researchers from resolving fine-scale variability. With the aim of addressing this problem, we present a set of globally consistent soil and vegetation parameters for the Variable Infiltration Capacity (VIC) model at 1/16° resolution (approximately 6 km at the equator), with spatial coverage from 60°S to 85°N. Soil parameters derived from interpolated soil profiles and vegetation parameters estimated from space-based MODIS measurements have been compiled into input files for both the Classic and Image drivers of the VIC model, version 5. Geographical subsetting codes are provided, as well. Our dataset provides all necessary land surface parameters to run the VIC model at regional to global scale. We evaluate VICGlobal’s ability to simulate the water balance in the Upper Colorado River basin and 12 smaller basins in the CONUS, and their ability to simulate the radiation budget at six SURFRAD stations in the CONUS.

scholarly journals Comprehensive Evaluation of the Variable Infiltration Capacity (VIC) Model in the North American Land Data Assimilation System

2018 ◽  
Vol 19 (11) ◽  
pp. 1853-1879 ◽  
Author(s):  
Youlong Xia ◽  
David M. Mocko ◽  
Shugong Wang ◽  
Ming Pan ◽  
Sujay V. Kumar ◽  
...  
Keyword(s):  
Land Surface ◽  
Comprehensive Evaluation ◽  
Model Performance ◽  
Variable Infiltration Capacity ◽  
Infiltration Capacity ◽  
Vic Model ◽  
The North ◽  
Land Data Assimilation ◽  
Land Data Assimilation System ◽  
Data Assimilation System

Abstract Since the second phase of the North American Land Data Assimilation System (NLDAS-2) was operationally implemented at NOAA/NCEP as part of the production suite in August 2014, developing the next phase of NLDAS has been a key focus of the NCEP and NASA NLDAS teams. The Variable Infiltration Capacity (VIC) model is one of the four land surface models of the NLDAS system. The current operational NLDAS-2 uses version 4.0.3 (VIC403), the research NLDAS-2 used version 4.0.5 (VIC405), and the NASA Land Information System (LIS)-based NLDAS uses version 4.1.2.l (VIC412). The purpose of this study is to evaluate VIC403 and VIC412 and check if the latter version has better performance for the next phase of NLDAS. Toward this, a comprehensive evaluation was conducted, targeting multiple variables and using multiple metrics to assess the performance of different model versions. The evaluation results show large and significant improvements in VIC412 over the southeastern United States when compared with VIC403 and VIC405. In other regions, there are very limited improvements or even deterioration to some degree. This is partially due to 1) the sparseness of USGS streamflow observations for model parameter calibration and 2) a deterioration of VIC model performance in the Great Plains (GP) region after a model upgrade to a newer version. Overall, the model upgrade enhances model performance and skill scores for most parts of the continental United States; exceptions include the GP and western mountainous regions, as well as the daily soil moisture simulation skill, suggesting that VIC model development is on the right path. Further efforts are needed for scientific understanding of land surface physical processes in the GP, and a recalibration of VIC412 using reasonable reference datasets is recommended.

scholarly journals The Variable Infiltration Capacity Model, Version 5 (VIC-5): Infrastructure improvements for new applications and reproducibility

2018 ◽  
Author(s):  
Joseph J. Hamman ◽  
Bart Nijssen ◽  
Theodore J. Bohn ◽  
Diana R. Gergel ◽  
Yixin Mao
Keyword(s):  
Climate Modeling ◽  
Source Code ◽  
Model Development ◽  
Global Scale ◽  
Hydrologic Model ◽  
Variable Infiltration Capacity ◽  
Infiltration Capacity ◽  
Data Set ◽  
Vic Model ◽  
Macro Scale

Abstract. The Variable Infiltration Capacity (VIC) model is a macro-scale semi-distributed hydrologic model. VIC development began in the early 1990s and the model has since been used extensively for basin- to global-scale applications that include hydrologic data set construction, trend analysis of hydrologic fluxes and states, data evaluation and assimilation, forecasting, coupled climate modeling, and climate change impact assessment. Ongoing operational applications of the VIC model include the University of Washington's drought monitoring and forecasting systems and NASA's Land Data Assimilation System. This paper documents the development of VIC version 5 (VIC-5), which includes a major reconfiguration of the legacy VIC source code to support a wider range of modern hydrologic modeling applications. The VIC source code has been moved to a public GitHub repository to encourage participation by the broader user and developer communities. The reconfiguration has separated the core physics of the model from the driver source code, where the latter is responsible for memory allocation, pre- and post-processing and input/output (I/O). VIC-5 includes four drivers that use the same core physics modules, but which allow for different methods for accessing this core to enable different model applications. Finally, VIC-5 is distributed with robust test infrastructure, components of which routinely run during development using cloud-hosted continuous integration. The work described here provides an example to the model development community for extending the life of a legacy model that is being used extensively. The development and release of VIC-5 represents a significant step forward for the VIC user community in terms of support for existing and new model applications, reproducibility, and scientific robustness.

scholarly journals The Variable Infiltration Capacity model version 5 (VIC-5): infrastructure improvements for new applications and reproducibility

2018 ◽  
Vol 11 (8) ◽  
pp. 3481-3496 ◽  
Author(s):  
Joseph J. Hamman ◽  
Bart Nijssen ◽  
Theodore J. Bohn ◽  
Diana R. Gergel ◽  
Yixin Mao
Keyword(s):  
Climate Modeling ◽  
Source Code ◽  
Model Development ◽  
Global Scale ◽  
Hydrologic Model ◽  
Variable Infiltration Capacity ◽  
Infiltration Capacity ◽  
Vic Model ◽  
Capacity Model ◽  
Significant Step

Abstract. The Variable Infiltration Capacity (VIC) model is a macroscale semi-distributed hydrologic model. VIC development began in the early 1990s and the model has since been used extensively for basin- to global-scale applications that include hydrologic dataset construction, trend analysis of hydrologic fluxes and states, data evaluation and assimilation, forecasting, coupled climate modeling, and climate change impact assessment. Ongoing operational applications of the VIC model include the University of Washington's drought monitoring and forecasting systems and NASA's Land Data Assimilation System. This paper documents the development of VIC version 5 (VIC-5), which includes a major reconfiguration of the legacy VIC source code to support a wider range of modern hydrologic modeling applications. The VIC source code has been moved to a public GitHub repository to encourage participation by the broader user and developer communities. The reconfiguration has separated the core physics of the model from the driver source code, whereby the latter is responsible for memory allocation, preprocessing and post-processing, and input–output (I–O). VIC-5 includes four drivers that use the same core physics modules, but which allow for different methods for accessing this core to enable different model applications. Finally, VIC-5 is distributed with robust test infrastructure, components of which routinely run during development using cloud-hosted continuous integration. The work described here provides an example to the model development community for extending the life of a legacy model that is being used extensively. The development and release of VIC-5 represents a significant step forward for the VIC user community in terms of support for existing and new model applications, reproducibility, and scientific robustness.

Hydroclimatic Response of Watersheds to Urban Intensity: An Observational and Modeling-Based Analysis for the White River Basin, Indiana

2010 ◽  
Vol 11 (1) ◽  
pp. 122-138 ◽  
Author(s):  
Guoxiang Yang ◽  
Laura C. Bowling ◽  
Keith A. Cherkauer ◽  
Bryan C. Pijanowski ◽  
Dev Niyogi
Keyword(s):  
River Basin ◽  
Land Surface ◽  
Great Influence ◽  
Flow Distribution ◽  
Surface Characteristics ◽  
Infiltration Capacity ◽  
Vic Model ◽  
White River ◽  
Urban Model ◽  
Streamflow Regime

Abstract Impervious surface area (ISA) has different surface characteristics from the natural land cover and has great influence on watershed hydrology. To assess the urbanization effects on streamflow regimes, the authors analyzed the U.S. Geological Survey (USGS) streamflow data of 16 small watersheds in the White River [Indiana (IN)] basin. Correlation between hydrologic metrics (flow distribution, daily variation in streamflow, and frequency of high-flow events) and ISA was investigated by employing the nonparametric Mann–Kendall method. Results derived from the 16 watersheds show that urban intensity has a significant effect on all three hydrologic metrics. The Variable Infiltration Capacity (VIC) model was modified to represent ISA in urbanized basins using a bulk parameterization approach. The model was then applied to the White River basin to investigate the potential ability to simulate the water and energy cycle response to urbanization. Correlation analysis for individual VIC grid cells indicates that the VIC urban model was able to reproduce the slope magnitude and mean value of the USGS streamflow metrics. The urban model also reproduced the urban heat island (UHI) seen in the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature products, especially for the grids encompassing the city of Indianapolis, IN. The difference of the hydrologic metrics obtained from the VIC model with and without urban representation indicates that the streamflow regime in the White River has been modified because of urban development. The observed data, together with model analysis, suggested that 3%–5% ISA in a watershed is the detectable threshold, beyond which urbanization effects start to have a statistically significant influence on streamflow regime.

scholarly journals The Effect of Soil and Vegetation Parameters in the ECMWF Land Surface Scheme

2004 ◽  
Vol 5 (6) ◽  
pp. 1131-1146 ◽  
Author(s):  
H. Richter ◽  
A. W. Western ◽  
F. H. S. Chiew
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Weather Prediction ◽  
Lower Boundary ◽  
Soil Parameters ◽  
Model Parameters ◽  
Lower Boundary Condition ◽  
Land Surface Scheme ◽  
Vegetation Parameters ◽  
Surface Scheme

Abstract Numerical Weather Prediction (NWP) and climate models are sensitive to evapotranspiration at the land surface. This sensitivity requires the prediction of realistic surface moisture and heat fluxes by land surface models that provide the lower boundary condition for the atmospheric models. This paper compares simulations of a stand-alone version of the European Centre for Medium-Range Weather Forecasts (ECMWF) land surface scheme, or the Viterbo and Beljaars scheme (VB95), with various soil and vegetation parameter sets against soil moisture observations across the Murrumbidgee River catchment in southeast Australia. The study is, in part, motivated by the adoption of VB95 as the operational land surface scheme by the Australian Bureau of Meteorology in 1999. VB95 can model the temporal fluctuations in soil moisture, and therefore the moisture fluxes, fairly realistically. The monthly model latent heat flux is also fairly insensitive to soil or vegetation parameters. The VB95 soil moisture is sensitive to the soil and, to a lesser degree, the vegetation parameters. The model exhibits a significant (generally wet) bias in the absolute soil moisture that varies spatially. The use of the best Australia-wide available soils and vegetation information did not improve VB95 simulations consistently, compared with the original model parameters. Comparisons of model and observed soil moistures revealed that more realistic soil parameters are needed to reduce the model soil moisture bias. Given currently available continent-wide soils parameters, any initialization of soil moisture with observed values would likely result in significant flux errors. The soil moisture bias could be largely eliminated by using soil parameters that were derived directly from the actual soil moisture observations. Such parameters, however, are only available at very few point locations.

scholarly journals Estimation of baseflow parameters of variable infiltration capacity model with soil and topography properties for predictions in ungauged basins

2011 ◽  
Vol 8 (4) ◽  
pp. 7017-7053 ◽  
Author(s):  
Z. Bao ◽  
J. Liu ◽  
J. Zhang ◽  
G. Fu ◽  
G. Wang ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Model Simulation ◽  
Parameters Estimation ◽  
Model Parameters ◽  
Ungauged Basins ◽  
Variable Infiltration Capacity ◽  
Infiltration Capacity ◽  
Ungauged Catchments ◽  
Vic Model ◽  
Predictions In Ungauged Basins

Abstract. Equifinality is unavoidable when transferring model parameters from gauged catchments to ungauged catchments for predictions in ungauged basins (PUB). A framework for estimating the three baseflow parameters of variable infiltration capacity (VIC) model, directly with soil and topography properties is presented. When the new parameters setting methodology is used, the number of parameters needing to be calibrated is reduced from six to three, that leads to a decrease of equifinality and uncertainty. This is validated by Monte Carlo simulations in 24 hydro-climatic catchments in China. Using the new parameters estimation approach, model parameters become more sensitive and the extent of parameters space will be smaller when a threshold of goodness-of-fit is given. That means the parameters uncertainty is reduced with the new parameters setting methodology. In addition, the uncertainty of model simulation is estimated by the generalised likelihood uncertainty estimation (GLUE) methodology. The results indicate that the uncertainty of streamflow simulations, i.e., confidence interval, is lower with the new parameters estimation methodology compared to that used by original calibration methodology. The new baseflow parameters estimation framework could be applied in VIC model and other appropriate models for PUB.

scholarly journals Simulation of permafrost and seasonal thaw depth in the JULES land surface scheme

2011 ◽  
Vol 5 (3) ◽  
pp. 773-790 ◽  
Author(s):  
R. Dankers ◽  
E. J. Burke ◽  
J. Price
Keyword(s):  
Land Surface ◽  
The Arctic ◽  
Soil Parameters ◽  
Active Layer Thickness ◽  
Organic Carbon Content ◽  
Land Surface Scheme ◽  
Spatial Coverage ◽  
Soil Temperatures ◽  
Thaw Depth ◽  
Surface Scheme

Abstract. Land surface models (LSMs) need to be able to simulate realistically the dynamics of permafrost and frozen ground. In this paper we evaluate the performance of the LSM JULES (Joint UK Land Environment Simulator), the stand-alone version of the land surface scheme used in Hadley Centre climate models, in simulating the large-scale distribution of surface permafrost. In particular we look at how well the model is able to simulate the seasonal thaw depth or active layer thickness (ALT). We performed a number of experiments driven by observation-based climate datasets. Visually there is a very good agreement between areas with permafrost in JULES and known permafrost distribution in the Northern Hemisphere, and the model captures 97% of the area where the spatial coverage of the permafrost is at least 50%. However, the model overestimates the total extent as it also simulates permafrost where it occurs sporadically or only in isolated patches. Consistent with this we find a cold bias in the simulated soil temperatures, especially in winter. However, when compared with observations on end-of-season thaw depth from around the Arctic, the ALT in JULES is generally too deep. Additional runs at three sites in Alaska demonstrate how uncertainties in the precipitation input affect the simulation of soil temperatures by affecting the thickness of the snowpack and therefore the thermal insulation in winter. In addition, changes in soil moisture content influence the thermodynamics of soil layers close to freezing. We also present results from three experiments in which the standard model setup was modified to improve physical realism of the simulations in permafrost regions. Extending the soil column to a depth of 60 m and adjusting the soil parameters for organic content had relatively little effect on the simulation of permafrost and ALT. A higher vertical resolution improves the simulation of ALT, although a considerable bias still remains. Future model development in JULES should focus on a dynamic coupling of soil organic carbon content and soil thermal and hydraulic properties, as well as allowing for sub-grid variability in soil types.

scholarly journals Application of Variable Infiltration Capacity Model (Vic) for Calculatingdrought Iindicators for Binh Thuan Province

2018 ◽  
Vol 34 (1S) ◽  
Author(s):  
Nguyen Quang Hung ◽  
Le Duc Khanh
Keyword(s):  
Water Exchange ◽  
Water Resources Planning ◽  
Variable Infiltration Capacity ◽  
Drought Forecasting ◽  
Infiltration Capacity ◽  
Vic Model ◽  
Variable Infiltration Capacity Model ◽  
Capacity Model ◽  
Exchange Processes ◽  
Resources Planning

Abstract: Drought is a complex natural hazard;so far, there have been some different ways to assess the level of drought in different aspects. In this study, the Variable Infiltration Capacity Model (VIC) was used to calculate the relative humidity changes of soil in Binh Thuan province based on surface water exchange processes. The simulation results of the VIC model are then used to calculate drought indicators to assess the drought situation in Binh Thuan province. The results of the study show that drought occurrences of the study basin are high, complicated, clearly showing the effect of rainfall, temperature and vegetation cover to water exchange, soil moisture. The results of the study serve as a basis for the development of drought forecasting tools for agricultural production planning and water resources planning and planning.   Keyword: Drought, VIC model, relative soil humidity, Bình Thuận

scholarly journals Comparing Evapotranspiration from Eddy Covariance Measurements, Water Budgets, Remote Sensing, and Land Surface Models over Canadaa,b

2015 ◽  
Vol 16 (4) ◽  
pp. 1540-1560 ◽  
Author(s):  
Shusen Wang ◽  
Ming Pan ◽  
Qiaozhen Mu ◽  
Xiaoying Shi ◽  
Jiafu Mao ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Eddy Covariance ◽  
Land Surface ◽  
Water Budget ◽  
Hybrid Approach ◽  
Surface Model ◽  
Infiltration Capacity ◽  
Mountainous Regions ◽  
Community Land Model ◽  
Spatial Coverage

Abstract This study compares six evapotranspiration ET products for Canada’s landmass, namely, eddy covariance EC measurements; surface water budget ET; remote sensing ET from MODIS; and land surface model (LSM) ET from the Community Land Model (CLM), the Ecological Assimilation of Land and Climate Observations (EALCO) model, and the Variable Infiltration Capacity model (VIC). The ET climatology over the Canadian landmass is characterized and the advantages and limitations of the datasets are discussed. The EC measurements have limited spatial coverage, making it difficult for model validations at the national scale. Water budget ET has the largest uncertainty because of data quality issues with precipitation in mountainous regions and in the north. MODIS ET shows relatively large uncertainty in cold seasons and sparsely vegetated regions. The LSM products cover the entire landmass and exhibit small differences in ET among them. Annual ET from the LSMs ranges from small negative values to over 600 mm across the landmass, with a countrywide average of 256 ± 15 mm. Seasonally, the countrywide average monthly ET varies from a low of about 3 mm in four winter months (November–February) to 67 ± 7 mm in July. The ET uncertainty is scale dependent. Larger regions tend to have smaller uncertainties because of the offset of positive and negative biases within the region. More observation networks and better quality controls are critical to improving ET estimates. Future techniques should also consider a hybrid approach that integrates strengths of the various ET products to help reduce uncertainties in ET estimation.

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