Revisiting parameter sensitivities in the Variable Infiltration Capacity model

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.

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

Hydrologic 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.

Impact of climate change on monthly streamflow in the Verde River Basin using two hydrological models

This study assessed the impact of climate change on monthly streamflow in the Verde River Basin, located in the Grande River Basin headwater. For this purpose, the SWAT and VIC hydrological models were used to simulate the monthly streamflow under RCP4.5 and RCP8.5 scenarios, obtained by Regional Climate Models Eta-HadGEM2-ES, Eta-CanESM2 and Eta-MIROC5 in the baseline period (1961-2005) and three time-slice (2011-2040, 2041-2070, and 2071-2099) inputs. At the end of the century, the Eta-HadGEM2-ES showed larger decrease of precipitation in both radiative scenarios, with an annual reduction of 17.4 (RCP4.5) and 32.3% (RCP8.5), while the Eta-CanESM2 indicated major warming, with an annual increase of 4.7 and 10.2°C under RCP4.5 and RCP8.5, respectively. As well as precipitation changes, the Eta-HadGEM2-ES also showed greater impacts on streamflow under RCP4.5 for the first time-slice (2011-2040), with an annual decrease of 58.0% for both hydrological models, and for the RCP8.5 scenario by the end the century (2071-2099), with an annual reduction of 54.0 (VIC model) and 56.8% (SWAT model). Regarding monthly streamflow, the Eta-HadGEM2-ES and Eta-CanESM2 inputs indicated decrease under the RCP8.5 scenario by the end the century, varying from 7.2 to 66.3 % (VIC model) and 37.0 to 64.7% (SWAT model). In general, Eta-MIROC5 presented the opposite in terms of direction in the simulations with both hydrological models at the end of the century. Combined effects of climate models, hydrological model structures and scenarios of climate change should be considered in assessments of uncertainties of climate change impacts.

Contribution of Snow-Melt Water to the Streamflow over the Three-River Headwater Region, China

Snowmelt water is essential to the water resources management over the Three-River Headwater Region (TRHR), where hydrological processes are influenced by snowmelt runoff and sensitive to climate change. The objectives of this study were to analyse the contribution of snowmelt water to the total streamflow (fQ,snow) in the TRHR by applying a snowmelt tracking algorithm and Variable Infiltration Capacity (VIC) model. The ratio of snowfall to precipitation, and the variation of the April 1 snow water equivalent (SWE) associated with fQ,snow, were identified to analyse the role of snowpack in the hydrological cycle. Prior to the simulation, the VIC model was validated based on the observed streamflow data to recognize its adequacy in the region. In order to improve the VIC model in snow hydrology simulation, Advanced Scanning Microwave Radiometer E (ASMR-E) SWE product data was used to compare with VIC output SWE to adjust the snow parameters. From 1971 to 2007, the averaged fQ,snow was 19.9% with a significant decreasing trend over entire TRHR (P<0.05).The influence factor resulted in the rate of change in fQ,snow which were different for each sub-basin TRHR. The decreasing rate of fQ,snow was highest of 0.24%/year for S_Lantsang, which should be due to the increasing streamflow and the decreasing snowmelt water. For the S_Yangtze, the increasing streamflow contributed more than the stable change of snowmelt water to the decreasing fQ,snow with a rate of 0.1%/year. The April 1 SWE with the minimum value appearing after 2000 and the decreased ratio of snowfall to precipitation during the study period, suggested the snow solid water resource over the TRHR was shrinking. Our results imply that the role of snow in the snow-hydrological regime is weakening in the TRHR in terms of water supplement and runoff regulation due to the decreased fQ,snow and snowfall.

Compound Events of Tropical Cyclone and Flooding in India

&lt;p&gt;India is severely affected by tropical cyclones (TC) each year, which generates intense rainfall and strong winds leading to flooding. Most of the TC induced floods have been attributed to heavy rain associated with them. Here we show that both rainfall and elevated antecedent soil moisture due to temporally compounding tropical cyclones cause floods in the major Indian basins. We assess each basin's response to observed TC events from 1980 to 2019 using the Variable Infiltration Capacity (VIC) model. The VIC model was calibrated (R2 &gt; 0.5) and evaluated against observed hourly streamflow for major river basins in India. We find that rainfall due to TC does not result in floods in the basin, even for rainfall intensities similar to the monsoon period. However, TCs produce floods in the basins, when antecedent soil moisture was high. Our findings have implications for the understanding of TC induced floods, which is crucial for disaster mitigation and management.&lt;/p&gt;

Flood forecasting system for Brahmaputra river basin

&lt;p&gt;Assam has always been India&amp;#8217;s most flood prone state due to the presence of Brahmaputra river, which is very unstable in terms of its flow direction witnessing 12 major floods from 1950 to 2012. Flooding in the basin has affected around 2.75 million of people and 0.27 million hectares of agricultural land on an average causing catastrophic damage to human life and infrastructure. In this study, we analysed all the major floods across the Brahmaputra river in the past 70 years and established the dependency within discharge and atmospheric parameters. Variable Infiltration Capacity (VIC) model was set up to simulate the flow at two stations namely Yangcun, China and Bahadurabad, Bangladesh. We&amp;#160; used near surface meteorological data for driving land surface modelling systems from 1901 to 2016 as input parameters to the VIC model. To avoid the discontinuity of data after 2016, we used ECMWF reanalysis (ERA5) data for the period of 2016 to 2020. After obtaining the continuous simulated discharge for 120 years, we established the relationship between the observed and simulated discharge data for which the R-squared and Nash Sutcliffe coefficient values were 0.83 and 0.78 respectively. Comparing the simulated discharge with the observed extreme discharge at various locations on the river, we apply the model to address future flood situations.&lt;/p&gt;

Developing semi-distributed hydrological models for streamflow forecasting in upper Narmada River basin

&lt;p&gt;Short-term streamflow forecast is important for various hydrological applications such as, estimating inflow to reservoirs, sending alarms in case of extreme events like flood and flash floods etc. Flooding events in last few years in the Indian subcontinent emphasized the importance of more accurate streamflow forecasts and the possible benefit of high-resolution Numerical Weather Prediction (NWP) models has been confirmed. In India, National Center for Medium Range Weather Forecasting (NCMRWF) provides rainfall forecasts from its UK Met office Unified Model based deterministic model (NCUM), and ensemble prediction system (NEPS). The comparison of NCMRWF with the forecast from other agencies such as Japan Metrological Agency (JMA)and European Center for Medium Range Forecast (ECMWF) have been addressed in this work. Global NWP models developed by different international agencies applydifferent algorithms, initial and boundaries conditions.The usefulness of several forecasts in streamflow forecasting is still being investigated in India. Recent studies on streamflow forecasting by using different NWP models shows that the performance of streamflow forecasts directly depends on the skill of NWP models. Hydrological model also plays a vital role in stream flow forecasting, because different hydrological model have different structure, parameters and algorithms to simulate the flow.&lt;/p&gt;&lt;p&gt;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160; In this study we use the Soil and Water Assessment Tool (SWAT) a Hydrological Response Unit (HRU&amp;#8217;s) based hydrological model. HRU is the area that contains similar type of soil, land use and slope properties in a subbasin. For comparison, the streamflow generated from the forecasted rainfall by NWP, we select three different NWP models namely JMA, ECMWF and NCMRWF for streamflow forecasting. Manot watershed part of Narmada River basin in central India is selected as the study area for this study. Streamflow is examined for monsoon (June to September) period of 2018 at multiple lead times i.e. 1 to 5 days. Rain-gauge based gridded Indian Meteorological Department (IMD) rainfall product is used as observed data in SWAT. All rainfall products are at 0.25*0.25-degree spatial resolution. The preliminary comparison between the simulated streamflow and the observation shows that the stream flow patterns produced by various forecast products are in good comparison with high peaks. Our results also indicate that the forecast accuracy of NCMRWF is closely comparable with other forecast products for all lead time. In addition, the setup of Variable Infiltration Capacity (VIC), the hydrological model for Streamflow forecasting is in progress. The VIC model is a grid-based model with variable infiltration soil layers and each of this layer characterizes the soil hydrological responses and heterogeneity in land cover classes. For routing, VIC model divides the whole basin into grides and water balance is calculated at the outlet of each and every grid and the flow simulate according to the flow direction. This model considers both the baseflow and the surface flow. The detailed results of ongoing work will be presented at the conference.&lt;/p&gt;

Simulating human impacts on global water resources using VIC-5

Questions related to historical and future water resources and scarcity have been addressed by several macroscale hydrological models. One of these models is the Variable Infiltration Capacity (VIC) model. However, further model developments were needed to holistically assess anthropogenic impacts on global water resources using VIC. Our study developed VIC-WUR, which extends the VIC model using (1) integrated routing, (2) surface and groundwater use for various sectors (irrigation, domestic, industrial, energy, and livestock), (3) environmental flow requirements for both surface and groundwater systems, and (4) dam operation. Global gridded datasets on sectoral demands were developed separately and used as an input for the VIC-WUR model. Simulated national water withdrawals were in line with reported Food and Agriculture Organization (FAO) national annual withdrawals (adjusted R2 > 0.8), both per sector and per source. However, trends in time for domestic and industrial water withdrawal were mixed compared with previous studies. Gravity Recovery and Climate Experiment (GRACE) monthly terrestrial water storage anomalies were well represented (global mean root-mean-squared error, RMSE, values of 1.9 and 3.5 mm for annual and interannual anomalies respectively), whereas groundwater depletion trends were overestimated. The implemented anthropogenic impact modules increased simulated streamflow performance for 370 of the 462 anthropogenically impacted Global Runoff Data Centre (GRDC) monitoring stations, mostly due to the effects of reservoir operation. An assessment of environmental flow requirements indicates that global water withdrawals have to be severely limited (by 39 %) to protect aquatic ecosystems, especially with respect to groundwater withdrawals. VIC-WUR has potential for studying the impacts of climate change and anthropogenic developments on current and future water resources and sector-specific water scarcity. The additions presented here make the VIC model more suited for fully integrated worldwide water resource assessments.