Integrating Extreme Weather, Hydrology, and Societal Impacts in GIS

National Center for Atmospheric Research

GIS Tools for Decision SupportUnderstanding societal risks and vulnerabilities to weather hazards requires integration of georeferenced information from physical and social sciences, including observational weather data and forecast models, information about natural and built environments, demographic characteristics, as well as social and behavioral processes. NCAR’s Geographic Information Systems (GIS) program develops analytical frameworks, spatial methods, and GIS-based decision support tools for extreme weather, hydrology, and societal impacts research and applications.

An interactive web mapping portal was developed as a prototype decision support system to demonstrate integration of the Hurricane Weather Research and Forecast (WRF) model with socio-economic and infrastructure data. Using ESRI ArcGIS Server technology and JAVA, the portal overlays WRF netCDF files with U.S. Census and critical infrastructure GIS data in a web mapping application (Fig. 1). Custom query tools (Fig. 2) were developed for the user to ask specific questions about potential impacts of a hurricane event to then visualize areas, population, and critical infrastructure at risk (Fig. 3). This prototype serves as a foundation for developing operational extreme weather impact forecasting decision support systems.

Linking with GISGIS methods and geoprocessing tools can effectively link weather models with hydrologic applications. The GIS Program has developed GIS processes to inform hydrologic models. GIS has a rich toolset for hydrological processing, and those tools are used to develop input and forcing datasets for land surface (LSM) and hydrological models. Working with hydrologists, the NCAR GIS Program has developed both stand-alone and server based tools for processing geographic data for input into the Noah-LSM (WRF), WRF-Hydro, and NCAR Distributed Hydrological Modeling System (NDHMS). These applications include vector- and grid-based routing routines which allow topologically correct stream networks to be identified at various scales (Fig. 4). Other

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Figure. 1 - Web-based portal overlays Hurricane WRFmodel output with infrastructure data.

Figure 2 - Custom query tool which identifies infrastructure and population that could be affected by strong winds.

Figure 3 - Results from query mapping: Population density in census block groups which could be affected by strong winds.

Figure 4 – Grid-based runoff routing at multiple scales.

tools include basin delineation from any point in a domain, sub grid-scale aggregation of model input parameters, and grid-to-basin correspondence for aggregating model results (Fig. 5). The output of these custom toolsets are often used as input parameters to land models, and help reduce the processing time and GIS overhead for modelers. Using both proprietary and open-source tools such as ArcGIS, GRASS, GDAL, and Python, the NCAR GIS Program is able to quickly build and deploy a variety of applications (Fig. 6).

Significant progress has been made in the past several years in linking GIS with atmospheric and related geosciences and their datasets. There is growing interest among practitioners in GIS-compatible weather and climate data.

Societal RisksExtreme precipitation and social vulnerability interact in complex ways that can result in a flash flood disaster. A recent study conducted at NCAR (Wilhelmi and Morss 2013) demonstrates an integration of meteorological and socio-economic data in a GIS-based analysis of societal vulnerability to extreme precipitation and urban flash flooding in Fort Collins, Colorado. This study used radar-derived rainfall data to assess population’s exposure to extreme precipitation (Fig. 7).

For More Information, Contact:Olga WilhelmiNational Center for Atmospheric Research (NCAR)Research Applications Laboratory (RAL)PO Box 3000 Boulder CO 80307-3000303-497-8126 303-497-8401 faxolgaw@ucar.edu http://gis.ucar.edu

GISPROGRAMG E O G R A P H I C I N F O R M A T I O N S Y S T E M S

GISG E O G R A P H I C I N F O R M A T I O N S Y S T E M S

PROGRAM

The GIS Program works to improve spatial accuracy and usability of atmospheric models for terrestrial and societal applications.

Patterns of human occupancy, demographic indicators, characteristics of urban drainage, and structural flood control measures played major roles in the outcomes of the Fort Collins flood disaster. Recent advances in interoperability between GIS, radar-derived rainfall measurements, mesoscale weather forecast models, hydrologic models, and observations can further improve spatially explicit analyses of populations’ vulnerability to extreme precipitation events and flash floods.

Figure 5 – Aggregation of high resolutioninformation to model scales.

Figure 6 – Python-based graphical geoprocessingmodel for processing WRF input data.

Figure 7 – (a) Spatial distribution of flash flood exposure across the watersheds in and around Fort Collins, Colorado. z-Scores

>0.5 depict watersheds with flash flood potential.(b) Locations of flood-related 911 calls and flooded buildings

(Source: Wilhelmi and Morss 2013).