Watershed-based Midwest Climate Change Vulnerability Assessment Tool

Exposure

Hydrology

Precipitation

Temperature

Adaptive Capacity

For more details on each of the indicators please refer to the 'Background' tab at the top of the page.

*Note: Select "All" from Show entries before downloading the table above.

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The shapefiles and model outputs used to create the vulnerability map can be found at the ScienceBase page for our project.


Introduction

Climate change has and is projected to continue to alter historic regimes of temperature, precipitation, and hydrology. To better understand the combined impacts of climate change from a land management perspective and spatially identify where the most extreme changes are anticipated to occur, we worked in collaboration with United States Fish and Wildlife Service managers to develop a climate change vulnerability map for the Midwestern United States. The map is intended for use by regional administrators to help them work cross programmatically to prioritize locations needing support for adaptation planning and for managers to help them grapple with the impacts projected climate scenarios have on the hydrology of management units as they develop adaptation strategies. The vulnerability map is watershed-based (Hydrologic Unit Code-8) and combines fifteen climate change impact and five adaptive capacity metrics that were selected by United States Fish and Wildlife Service natural resource managers based upon known and anticipated impacts to species and habitats.

Climate Change Models and Scenarios

We used two Representative Concentration Pathways (RCPs), RCP 4.5 & 8.5. RCP 4.5 represents a scenario where greenhouse gas concentrations increase more slowly and decline around mid-century as a result of climate change mitigation strategies. RCP 8.5 represents a scenario where no mitigation policies are employed, and greenhouse gas emission continue to increase through the end of the century. These two RCPs encompass the likely trajectory of end of century radiative forcing.

We used five climate models that were Localized Constructed Analogs (LOCA) downscaled datasets from phase five of the Climate Model Intercomparing Project (CMIP5). The models were selected using the EPA’s Locating and Selecting Scenarios Online (LASSO) tool to visualize the variation in the suite of LOCA CMIP5 climate models for US EPA Regions 5 and 7. The criteria we used in selecting climate models was to capture the range in projected changes in annual temperature and precipitation across regions and RCPs. The five LOCA downscaled climate models we selected were: CanESM2, CCSM4, GISS-E2-R, HadGEM2-ES, and MIROC5. Grid cell size was roughly 36 km2, and values were averaged across each watershed. We used mid-century as our future period (2040-2059), and 1986-2005 for our historic period.

Watershed Model

We used the Hydrologic and Water Quality System (HAWQS) version 1.1 to run watershed models that simulate hydrologic, sediment, and nutrient processes using inputs of land-use, land cover, soil type, topography, weather, and point sources of nutrients. The HAWQS platform is an online tool developed by Texas A&M University and the United States Environmental Protection Agency to allow decision-makers and researchers to run large-scale watershed simulation models using the Soil & Water Assessment Tool (SWAT) model without the need to download/install software, gather input data, perform initialization steps, or use up local computer resources.

Exposure Indicators

The exposure category had 15 indicators of projected changes in climate with five indicators in each of three categories: hydrology, precipitation, and temperature (see table below). Where possible, we used metrics that have been previously defined in the literature (for example: ETCCDI/CRD Climate Change Indices). The indicators were selected by managers and researchers working for the US Fish & Wildlife Service in the Midwest United States. To capture as broad of a characterization of climate change as possible, we inspected annual and seasonal changes in temperature, precipitation, and hydrology patterns across the region in order to select seasonal indicators (e.g. fall mean temperature, decrease in summer precipitation, increase in spring discharge) that were projected to show the directional change and captured different periods of the year. If we were unable to produce a desired indicator or were concerned about the quality of an indicator we substituted an alternate indicator that captured a similar aspect of climate change or, if necessary, made a replacement.

The exposure indicator values were calculated as the percent change of each indicator from the baseline period to future period for each of the five climate models. When calculating percent change in temperature, the indicators (i.e. AMT and FMT) were converted from Celsius to Kelvin prior to performing percent change calculations so that the zero point was not arbitrary. To ensure that all the exposure indicators were positively correlated with vulnerability we changed the sign (multiplied values by -1) of two indicators: growing season start (GSS) and decrease in summer precipitation (SUP).

Adaptive Capacity Indicators

Five indicators were identified to incorporate adaptive capacity: density of dams, landscape diversity, local connectedness, percent cultivated cover, and change in developed land cover (see table below for links to data sources). We used two layers developed by The Nature Conservancy (TNC) for their Resilient Lands Mapping Project: landscape diversity and landscape connectedness. Landscape diversity combines landform variety, coastal lake effect, and wetland influence into a metric that represents the local variation in microclimates and microhabitats. Local connectedness is characterized by factors that restrict movement in the terrestrial landscape (e.g. roads, developed land, agriculture, etc). Density of dams within watersheds was included as an adaptive capacity indicator to incorporate connectedness within stream and river channels. To calculate density of dams we used the 2018 National Inventory of Dams from U.S. Army Corps of Engineers. We used the National Agricultural Statistics Service 2018 Cultivated Layer raster to calculate the percentage of each watershed that was categorized as cultivated. The 2018 Cultivated Layer uses the last five years (2014-2018) of NASS Cropland Data Layers and classifies each 30m pixel as cultivated if it was assigned to one of the categories considered cultivated in at least two years in the five year period or during the most recent year. Projections of changes in the amount of developed land and urban growth were obtained from a dataset with land use projections over the 21st century generated using the FORE-SCE model. We calculated the proportion of each watershed classified as developed during the historic (average of 1992-1999) and future (average of 2046-2053) period and then calculated the percent change of each watershed from the historic to future period.

Calculating Vulnerability

We used the model developed by Glick et al. (2011) pictured below to conceptualize vulnerability and used it as a basis for creating a method for calculating a vulnerability index score.

Model of vulnerability including components of exposure, sensitivity,
                                         and adaptive capacity contributing to vulnerability

Prior to performing vulnerability calculations each of the exposure indicators and adaptive capacity indicators were min-max normalized using this formulation: (x-min(x))/ (max(x)-min(x)). The normalized values are then multiplied by the weights selected (left panel) for each indicator and combined to create the potential impact, adaptive capacity, and vulnerability scores using the following equation:

an equation used to calculate vulnerability described in text below

Where Ei is an exposure indicator, Si is the weight of that exposure indicator, Aj is an adaptive capacity indicator and wj is the weight of that adaptive capacity indicator. Vulnerability was calculated for each of the five climate models and then the multi-model mean and standard deviation was calculated. The composites of exposures (potential impact), adaptive capacity, and vulnerability were min-max normalized in order to adjust the scale to 0 to 1 to make them easier to compare.

Limitations

The underlying data used in this tool is intended for regional comparisons among watersheds. The hydrology metrics were generated using a regionally calibrated watershed modeling tool. Additionally, the climate metrics were summarized at the watershed scale. We provide the percent change from the baseline to the future period values for each exposure indicator for regional comparisons. We caution against using these values for local planning. A study of a specific location would require a more robust investigation. Particularly, with watershed models that are calibrated and validated specific to that location.


Adaptation Planning

Adaptation Workbook

The Adaptation Workbook was created by the Northern Institute of Applied Climate Science as a resource for managers and landowners to assist in the development of management actions that address climate change. The workbook was initially designed for forest management but has since been adapted to include other resource types, with more in the works.

Federal Adaptation Resources

The Federal Adaptation Resources page contains a collection of resources that can aid in the process of climate change adaptation planning.

Additional Climate Change Projections and Metrics

NOAA's Climate at a Glance

The National Oceanic and Atmospheric Administration's Climate at a Glance tool allows users to investigate past climate variability and change at global, national, and more regional and local scales.

The Climate Explorer

The Climate explorer allows the user to create and explore maps and graphs of future and historic climate changes for counties in the contiguous United States.

Tools and Maps

Daily Erosion Project

The Daily Erosion Project map displays the results of an erosion precipitation model that updates daily based upon the current soil and crop conditions and rainfall amounts at the HUC-12 scale. Erosion estimates can be visualized by single day or over user selected time periods.

FishTail

FishTail is a decision support mapper that provides information to assist in support decision making to conserve stream fish habitats. Users can visualize various metrics on the current condition of fish habitats as well as future projected conditions at a variety of scales.

Floodplain Prioritization Tool

The Nature Conservancy’s Floodplain Prioritization Tool allows users to detect areas where floodplain protection and restoration opportunities exist in the Mississippi River Basin.

Resilient Land Mapping Tool

The Nature Conservancy’s Resilient Land Mapping Tool provides estimates of resilience to climate change. We used two components of the climate change resilience categorizations (Landscape Diversity and Local Connectedness) from The Nature Conservancy’s Resilient Land Mapping Project as metrics of Adaptive Capacity in our vulnerability assessment tool.

Seasonal Forecasting

United States Drought Monitor

The United States Drought Monitor provides weekly drought condition updates along with monthly and seasonal outlooks.

Climate Prediction Center Three-Month Outlooks

The National Weather Service’s Climate Prediction Center produces seasonal outlooks over the coming year. With general predictions of whether precipitation or temperature will be above or below normal at different periods of the coming year, these outlooks can be useful when planning certain management actions.