Understanding hydrologic changes: application of the VIC model

Vimal MishraVimal MishraAssistant ProfessorAssistant Professor

Indian Institute of Technology (IIT), Gandhinagar

vmishra@iitgn.ac.inhttps://sites.google.com/site/vimalmishraiitgandhinagar/

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Climate Change and Water Resources

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• Water is in the eye of climate management storm (IPCC, 2007)

• Global warming and related climate changes are expected to present significant challenges over the next century

• The impacts of climate change on water resource:a) Quantity- less or moreb) Extremes – droughts and floodsc) Frequency- intensified challenges

Science Questions

• How have hydrologic conditions associated with soil moisture, evapotranspiration, groundwater, snow cover, and streamflow changed during the last 50 years?

• How will water availability and water storage change in space and time under the projected future climate change?

• Will hydrologic extremes be more frequent, wide spread, and more intense?

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Key Impacts

• Surface water [ streamflow, soil moisture, ET, Snow and Glaciers levels of reservoirs/lakes]

• Groundwater [recharge rates, groundwater table]

• Droughts [ indicators, areal extents, severity, and frequency]

• Floods [return levels, flash flooding, damage to infrastructure]

• Key areas [ Agriculture, Hydropower, Water Storage and Water Availability]

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Hydrologic Modeling of Climate Change Impacts

• Climate forcing (spatial resolution)

• Data for calibration and evaluation (groundwater, surface water, water quality)

• Land use/land cover projections

• Cropping systems/patterns and irrigation demands

• Water management and reservoir operations

• Evaluation of uncertainty

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THE VARIABLE INFILTRATION CAPACITY (VIC) MODEL

Liang et al. (1994), Cherkauer et al., 2003Mishra et al., 2010; Mishra and Cherkauer, 2010

The VIC model: Main Features

The VIC model (Liang et al. 1994) is a large scale semi-distributed model

It has several features that are common to other land surface models (LSMs) used in the global climate models (GCMs)

The land surface is modeled using the large ( > 1 km) flat grid cells

Sub-grid heterogeneity (elevation, land cover) is handled using statistical distributions

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Meteorological Forcing

Can use any combination of daily or sub-daily meteorogolical forcings, from point observations, gridded observations, or reanalysis fields

At minimum, VIC requires daily {precipitation, max/min air temperature, and wind speed}

If incoming shortwave radiation or humidity are not supplied as forcings, VIC can estimate them via the algorithms of Kimball et al. (1997), Thornton and Running (1999), and Thornton et al. (2000)

VIC can disaggregate daily forcings to sub-daily as needed (further details available in Bohn et al., 2012b)

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Basin delineation Prepare input files ( meteorological data, soil,

vegetation parameters) Compilation of code (written in C language) Running VIC for the basin of interest Output variables at each grid cell Use Routing model to rout flow at the location of

interest

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Running the VIC Model

Representation of Various Components

Lakes and Wetlands Irrigation Reservoirs Groundwater Cold Season Process ( soil frost, snow, and glaciers)

Applications: Monitoring and Prediction Climate Change Impacts Impacts of Land Cover and Land Use Human Modifications ( Irrigation, reservoirs etc)

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Rosenberg et al., 2012

Groundwater ConditionsColorado Basin

Irrigation and Reservoir

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Irrigated AreaChange in Evapotranspiration (ET)

Haddland et al. (2007)

Application: Drought Monitoring and Prediction

Mishra (in review)

Mishra et al. (in revision)

Application: Retrospective Analysis

Application: Streamflow ForecastingRole of Data Assimilation in real time forecast

Observed

No Assimilation

With Assimilation

Mishra et al. (2011)

Climate Change: how reliable are the GCMs?

Ensemble Mean Percentage Bias (1961-1990)

Mishra (in preparation)

Precipitatio

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emperatur

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HOW RELIABLE ARE GCMS?

Mishra (in preparation)

Model Simulations Using Bias Corrected Data

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Bias Corrected and Spatial Downscaling (BCSD) Approach (Wood et al., 2002; 2004)

Monsoon Season (JJAS)

Hydrologic Impacts of Climate Change

Multimodel Ensemble Mean Change for the Near (2010-2039)

Hydrologic Impacts of Climate Change

Multimodel Ensemble Mean Change for the Near (2010-2039)

Hydrologic Impacts of Climate Change

Multimodel Ensemble Mean Change for the Mid (2040-2069)