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 Revisiting parameter sensitivities in the Variable Infiltration Capacity model

2021 ◽  
Author(s):  
Ulises Sepúlveda ◽  
Pablo A. Mendoza ◽  
Naoki Mizukami ◽  
Andrew J. Newman
Keyword(s):  
Aridity Index ◽  
Mean Annual Precipitation ◽  
Model Parameters ◽  
Variable Infiltration Capacity ◽  
Infiltration Capacity ◽  
Climate Type ◽  
Area Index ◽  
Vic Model ◽  
Variable Infiltration Capacity Model ◽  
Capacity Model

Abstract. Despite the Variable Infiltration Capacity (VIC) model being used for decades in the hydrology community, there are still model parameters whose sensitivities remain unknown. Additionally, understanding the factors that control spatial variations in parameter sensitivities is crucial given the increasing interest to obtain spatially coherent parameter fields over large domains. In this study, we investigate the sensitivities of 43 soil, vegetation and snow parameters in the VIC model for 101 catchments spanning the diverse hydroclimates of continental Chile. We implement a hybrid local-global sensitivity analysis approach, using eight model evaluation metrics to quantify sensitivities, with four of them formulated from runoff time series; two characterizing snow processes, and the remaining two based on evaporation processes. Our results confirm an over-parameterization for the processes analysed here, with only 12 (i.e., 28 %) parameters found as sensitive, distributed among soil (7), vegetation (2) and snow (3) model components. Correlation analyses show that climate variables – in particular, mean annual precipitation and aridity index – are the main controls on parameter sensitivities. Additionally, our results highlight the influence of the leaf area index on simulated hydrologic processes – regardless on the dominant climate types – and the relevance of hard-coded snow parameters. Based on correlation results and the interpretation of spatial sensitivity patterns, we provide guidance on the most relevant parameters for model calibration according to the target processes and the prevailing climate type. Overall, the results presented here contribute to improved understanding of model behaviour across watersheds with diverse physical characteristics that encompass a wide hydroclimatic gradient from hyper-arid to humid systems.

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 Assessing water resources in China using PRECIS projections and a VIC model

2012 ◽  
Vol 16 (1) ◽  
pp. 231-240 ◽  
Author(s):  
G. Q. Wang ◽  
J. Y. Zhang ◽  
J. L. Jin ◽  
T. C. Pagano ◽  
R. Calow ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Temporal Distribution ◽  
Annual Runoff ◽  
Model Parameters ◽  
Infiltration Capacity ◽  
Climate Conditions ◽  
Vic Model ◽  
Sustainable Water Resources Management ◽  
The Impact

Abstract. Climate change is now a major environmental and developmental issue, and one that will increase the challenge of sustainable water resources management. In order to assess the implications of climate change for water resources in China, we calibrated a Variable Infiltration Capacity (VIC) model with a resolution of 50×50 km2 using data from 125 well-gauged catchments. Based on similarities in climate conditions, soil texture and other variables, model parameters were transferred to other areas not covered by the calibrated catchments. Taking runoff in the period 1961–1990 as a baseline, we studied the impact of climate change on runoff under three emissions scenarios, A2, B2 and A1B. Model findings indicate that annual runoff over China as a whole will probably increase by approximately 3–10% by 2050, but with quite uneven spatial and temporal distribution. The prevailing pattern of "north dry and south wet" in China is likely to be exacerbated under global warming.

scholarly journals Toward high-spatial resolution hydrological modeling for China: Calibrating the VIC model

2019 ◽  
Author(s):  
Bowen Zhu ◽  
Xianhong Xie ◽  
Chuiyu Lu ◽  
Shanshan Meng ◽  
Yi Yao ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Hydrological Modeling ◽  
Model Parameters ◽  
Data Simulation ◽  
Infiltration Capacity ◽  
Vic Model ◽  
Spatial And Temporal Distributions ◽  
Modeling Studies ◽  
Estimation Scheme

Abstract. High-resolution hydrological modeling is important for understanding fundamental terrestrial processes associated with the effects of climate variability and human activities on water resources availability. However, the spatial resolution of current hydrological modeling studies is mostly constrained to a relative coarse resolution (~ 10–100 km) and they are therefore unable to address many of the water-related issues facing society. In this study, a high resolution (0.0625º, ~ 6 km) hydrological modeling for China was developed based on the Variable Infiltration Capacity (VIC) model, spanning the period from January of 1970 to June of 2016. Distinct from other modeling studies, the parameters in the VIC model were updated using newly developed soil and vegetation datasets, and an effective parameter estimation scheme was used to transfer parameters from gauged to ungauged basins. Simulated runoff, evapotranspiration (ET), and soil moisture (SM) were extensively evaluated using in-situ observations, which indicated that there was a great improvement due to the updated model parameters. The spatial and temporal distributions of simulated ET and SM were also consistent with remote sensing retrievals. Moreover, this high-resolution modeling is capable of capturing flood and drought events with respect to their timing, duration, and spatial extent. This study shows that the hydrological datasets produced from this high-resolution modeling are useful for understanding long-term climate change and water resource security. It also has great potential for coupling with the China Land Data Simulation System to achieve real-time hydrological forecasts across China.

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

Model adequacy tests for improving predictions in ungauged basins

2020 ◽  
Author(s):  
Cristina Prieto ◽  
Nataliya Le Vine ◽  
Dmitri Kavetski ◽  
César Álvarez ◽  
Raúl Medina
Keyword(s):  
Time Series ◽  
Hydrological Model ◽  
Flow Time ◽  
Flow Index ◽  
Model Parameters ◽  
Ungauged Basins ◽  
Ungauged Catchments ◽  
Subsequent Work ◽  
Study Results

<p>Flow prediction in ungauged catchments is a major unresolved challenge in scientific and engineering hydrology. Meeting this challenge is made difficult by the uncertainty in the “regionalization” model used to transpose hydrological data (e.g., flow indices) from gauged to ungauged basins, and by the uncertainty in the hydrological model used to predict streamflow in the ungauged basin. This study combines recent advances in flow index selection, regionalization via machine learning methods, and a Bayesian inference framework. In addition, it proposes two new statistical metrics, “DistanceTest” and “InfoTest”, to assess the adequacy of a model before estimating its parameters. “DistanceTest” quantifies whether a model (hydrological or regionalization) is likely to reproduce the available hydrological information in a catchment. “InfoTest” is based on Bayes Factors and quantifies the information added by a model (hydrological or regionalization) over prior knowledge about the available hydrological information in a catchment). The proposed adequacy tests can be seen as a prerequisite for a model (hydrological or regionalization) being considered capable of providing meaningful and high quality flow time series predictions in ungauged catchments. If a model is found inadequate a priori and rejected, the modeler is spared the effort in estimating the model parameters, which can be a substantial saving.</p><p>The proposed regionalization approach is applied to 92 northern Spain catchments, with 16 catchments treated as ungauged. It is found that (1) a small number of PCs capture approximately 87% of variability in the flow indices, and (2) adequacy tests with respect to regionalized information are indicative of (but do not guarantee) the ability of a hydrological model to predict flow time series. The adequacy tests identify the regionalization of flow index PCs as adequate in 12 of 16 catchments but the hydrological model as adequate in only 1 of 16 catchments. In addition, the case study results suggest that the hydrological model is the main source of uncertainty in comparison to the regionalization model, and hence should receive the main priority in subsequent work at the case study catchments.</p>

scholarly journals Enhancing Physical Similarity Approach to Predict Runoff in Ungauged Watersheds in Sub-Tropical Regions

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 528 ◽  
Author(s):  
Santiago Narbondo ◽  
Angela Gorgoglione ◽  
Magdalena Crisci ◽  
Christian Chreties
Keyword(s):  
Weather Conditions ◽  
Climatic Conditions ◽  
Model Parameters ◽  
Ungauged Basins ◽  
Physical Similarity ◽  
Tropical Regions ◽  
Runoff Prediction ◽  
Tropical Areas ◽  
Rainfall Runoff Model ◽  
Predictions In Ungauged Basins

Regionalization techniques have been comprehensively discussed as the solution for runoff predictions in ungauged basins (PUB). Several types of regionalization approach have been proposed during the years. Among these, the physical similarity one was demonstrated to be one of the most robust. However, this method cannot be applied in large regions characterized by highly variable climatic conditions, such as sub-tropical areas. Therefore, this study aims to develop a new regionalization approach based on an enhanced concept of physical similarity to improve the runoff prediction of ungauged basins at country scale, under highly variable-weather conditions. A clustering method assured that watersheds with different hydrologic and physical characteristics were considered. The novelty of the proposed approach is based on the relationships found between rainfall-runoff model parameters and watershed-physiographic factors. These relationships were successively exported and validated at the ungauged basins. From the overall results, it can be concluded that the runoff prediction in the ungauged basins was very satisfactory. Therefore, the proposed approach can be adopted as an alternative method for runoff prediction in ungauged basins characterized by highly variable-climatic conditions.

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