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.

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 Effect of year-to-year variability of leaf area index on variable infiltration capacity model performance and simulation of streamflow during drought

2014 ◽  
Vol 11 (9) ◽  
pp. 10515-10552 ◽  
Author(s):  
Z. K. Tesemma ◽  
Y. Wei ◽  
M. C. Peel ◽  
A. W. Western
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Model Performance ◽  
Hydrologic Model ◽  
Variable Infiltration Capacity ◽  
Infiltration Capacity ◽  
Area Index ◽  
Vic Model ◽  
Monthly Streamflow

Abstract. This study assessed the effect of using observed monthly leaf area index (LAI) on hydrologic model performance and the simulation of streamflow during drought using the variable infiltration capacity (VIC) hydrological model in the Goulburn–Broken catchment of Australia, which has heterogeneous vegetation, soil and climate zones. VIC was calibrated with both observed monthly LAI and long-term mean monthly LAI, which were derived from the Global Land Surface Satellite (GLASS) observed monthly LAI dataset covering the period from 1982 to 2012. The model performance under wet and dry climates for the two different LAI inputs was assessed using three criteria, the classical Nash–Sutcliffe efficiency, the logarithm transformed flow Nash–Sutcliffe efficiency and the percentage bias. Finally, the percentage deviation of the simulated monthly streamflow using the observed monthly LAI from simulated streamflow using long-term mean monthly LAI was computed. The VIC model predicted monthly streamflow in the selected sub-catchments with model efficiencies ranging from 61.5 to 95.9% during calibration (1982–1997) and 59 to 92.4% during validation (1998–2012). Our results suggest systematic improvements from 4 to 25% in the Nash–Sutcliffe efficiency in pasture dominated catchments when the VIC model was calibrated with the observed monthly LAI instead of the long-term mean monthly LAI. There was limited systematic improvement in tree dominated catchments. The results also suggest that the model overestimation or underestimation of streamflow during wet and dry periods can be reduced to some extent by including the year-to-year variability of LAI in the model, thus reflecting the responses of vegetation to fluctuations in climate and other factors. Hence, the year-to-year variability in LAI should not be neglected; rather it should be included in model calibration as well as simulation of monthly water balance.

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 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

On the exploration of alternative spatial representation for land models; a vector-based setup for the Variable Infiltration Capacity model

2020 ◽  
Author(s):  
Shervan Gharari ◽  
Martyn Clark
Keyword(s):  
High Resolution ◽  
Spatial Heterogeneity ◽  
Spatial Data ◽  
Land Surface ◽  
Spatial Representation ◽  
Variable Infiltration Capacity ◽  
Infiltration Capacity ◽  
Data Set ◽  
Wide Range ◽  
Model Setup

<p>Land models are increasingly used as the backbone of the terrestrial hydrology as they cover a wide range of processes (from rainfall/runoff processes to carbon cycle). The recent improvements in high-resolution spatial data set including detailed digital elevation models, DEMs, and land cover and soil type maps are encouraging the modelers to set up the land surface models at the highest resolution possible. However, this high-resolution setup does not often coincide with rigorous model diagnostics and also the “optimal” spatial representation based on the context of modeling (e.g. streamflow). A model can be seen as a tool to interpolate or extrapolate our knowledge in time and space and therefore it remains an important aspect of land surface modeling to which level the spatial heterogeneity can be represented in a model so that the states and fluxes “improve” given the context of modeling. The representation of spatial data in our models has important implications including (1) removing the unnecessarily computational burden from model setups which in turn results in better assessment of uncertainty and sensitivity analysis of the parameters on a less computational expensive model. (2) Proper corresponding between the communications of spatial variability while avoiding overconfidence in the nature of model response on illogically smallest units.</p><p>In this study, in contrast to the often used grid-based model setup, we use the concept of vector-based group response units (GRUs) for setting up the Variable Infiltration Capacity, the VIC model, and vector-based MizuRoute routing scheme. We explore the added information by stepwise inclusion of more detailed spatial data and higher resolution forcing data while the vector-based routing setup remains identical for each of the configurations. Using this flexible workflow we explore three major questions:</p><ul><li>1- How the performance of model changes in the calibration mode for various configuration of spatial heterogeneity representation and forcing resolution given the context of modeling, for example, streamflow simulations or snow water equivalent spatial pattern?</li> <li>2- How well a simplified version of a more complex model in spatial representation can reproduce its own simulation? The answer to this question will provide us with iso-performing model setups, configurations of forcing distribution and spatial heterogeneity representation, and the possible loss in the performance metric given the context of modeling under the simplification decisions.</li> <li>3- How the model performs across various configurations of spatial data and forcing resolutions with a given set of so-called physically parameters that are often considered to be identical for GRUs with the same physical characteristics, soil, vegetation type, elevation zone, slope and aspect, varies?</li> </ul><p>Our findings indicate that the optimal spatial representation in the context of modeling, streamflow, for example, may very well be much less computationally demanding than the model setup that contains all the details with the highest resolution of the data. In a complementary attempt, it is shown that the often good performing parameter sets are able to reproduce good performing simulation in comparison to the model setup with the highest model resolution.</p>

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 Integration of 2D Lateral Groundwater Flow into the Variable Infiltration Capacity (VIC) Model and Effects on Simulated Fluxes for Different Grid Resolutions and Aquifer Diffusivities

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 663
Author(s):  
Johanna M. Scheidegger ◽  
Christopher R. Jackson ◽  
Sekhar Muddu ◽  
Sat Kumar Tomer ◽  
Rosa Filgueira
Keyword(s):  
Groundwater Flow ◽  
Water Table ◽  
Large Scale ◽  
Hydrological Cycle ◽  
Soil Column ◽  
Global Scale ◽  
Grid Resolution ◽  
Variable Infiltration Capacity ◽  
Infiltration Capacity ◽  
Model Average

Better representations of groundwater processes need to be incorporated into large-scale hydrological models to improve simulations of regional- to global-scale hydrology and climate, as well as understanding of feedbacks between the human and natural systems. We incorporated a 2D groundwater flow model into the variable infiltration capacity (VIC) hydrological model code to address its lack of a lateral groundwater flow component. The water table was coupled with the variably saturated VIC soil column allowing bi-directional exchange of water between the aquifer and the soil. We then investigated how variations in aquifer properties and grid resolution affect modelled evapotranspiration (ET), runoff and groundwater recharge. We simulated nine idealised, homogenous aquifers with different combinations of transmissivity, storage coefficient, and three grid resolutions. The magnitude of cell ET, runoff, and recharge significantly depends on water table depth. In turn, the distribution of water table depths varied significantly as grid resolution increased from 1° to 0.05° for the medium and high transmissivity systems, resulting in changes of model-average fluxes of up to 12.3% of mean rainfall. For the low transmissivity aquifer, increasing the grid resolution has a minimal effect as lateral groundwater flow is low, and the VIC grid cells behave as vertical columns. The inclusion of the 2D groundwater model in VIC will enable the future representation of irrigation from groundwater pumping, and the feedbacks between groundwater use and the hydrological cycle.

A two-stage surrogate model based on ANN and AdaBoost for multi-objective parameter optimization of the Variable Infiltration Capacity model

2020 ◽  
Author(s):  
Yue-Ping Xu ◽  
Haiting Gu ◽  
Ma Di
Keyword(s):  
River Basin ◽  
Surrogate Model ◽  
Stage Model ◽  
Variable Infiltration Capacity ◽  
Infiltration Capacity ◽  
Two Stage ◽  
Nsga Ii ◽  
Xiangjiang River ◽  
Vic Model ◽  
Multi Objective

<p>Distributed hydrologic models have been widely used for its functional diversity and rationality in theory. However, calibration of distributed models is computationally expensive with a large number of model runs, even if an efficient multi-objective algorithm is employed. To alleviate the burden of computation, we develop a two-stage surrogate model by coupling backpropagation neural network with AdaBoost to calibrate the parameters of the Variable Infiltration Capacity (VIC) model. The first stage model selects the parameter sets with simulated outputs in the crucial range and the second stage model estimates the values of outputs accurately with the parameter sets picked out by the first stage model. The developed surrogate model is tested in three different river basins in China, namely the Lanjiang River basin (LJR), the Xiangjiang River basin (XJR) and the Upper Brahmaputra River basin (UBR). With sufficient samples generated by ε-NSGA II, the surrogate model performs very well with a low error rate of classification (ER) and root mean square error (RMSE). The streamflow simulated with the surrogate model is nearly the same as that from the original VIC model, indicating that the surrogate model does gain a remarkable speedup compared with the original VIC model.</p>

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