Publications

Developing a GIS-based geospatial decision support tool for assessing climate change impacts on flood risks in Northern Cascadia road networks.

Citation

Strauch, R. L., E. Istanbulluoglu, R. Rochefort, Z. Duran, and K. Purnell. 2018. Developing a GIS-based geospatial decision support tool for assessing climate change impacts on flood risks in Northern Cascadia road networks. Natural Resource Report NPS/NOCA/NRR—2018/1808. National Park Service, Fort Collins, Colorado.


Abstract

Changes in temperature and precipitation patterns associated with changing climate have direct effects on the hydrologic system that impact transportation systems. Peak flows are particularly challenging to the integrity of road segments that intersect streams. This report evaluates four possible approaches for estimating peak flows in the future to assess impacts and manage culvert stream-crossing structures within North Cascades National Park (NOCA).Thus, hydrologic modeling provides an approach to estimating streamflows in the future at small scales appropriate for culverts.

This study found that information on NOCA culvert locations and conditions is insufficient to inform NPS managers interested in adapting transportation systems to changing climates. Thus, this report describes tools developed to inventory culverts and document culvert conditions. A data sheet, geospatial database, and mobile app were developed to help increase the culvert information retained by the park. This study also explored several methods to estimate future peak streamflow based on hydrologic modeling using the Variable Infiltration Capacity (VIC) macro-scale hydrology model, which was previously run for the study area. A potential limitation of the VIC model is the daily scale data used to derive peak flows estimates, which results in lower peak flows estimates than when using observations based on instantaneous (i.e., 15 minute) data. However, this limitation can be accounted for with a correction factor that scales the daily-based estimate with the instantaneousbased estimate. The major value of the VIC model lies in its ability to capture hydrologic processes, such as evapotranspiration and snowmelt, that will change in the future as temperatures warm. Therefore, peak flow estimates derived from the VIC model provide a mechanism to understand how these changing processes will alter peak flows in the future, which is important for designing and operating transportation infrastructure over the long term.

The VIC model can be used in combination with existing streamflow estimation tools that are based on historical climatology. StreamStats, a USGS online tool, is currently used by managers to estimate peak flows on ungauged streams. However, it does not take into account future change in climate and its effect on stream flow. An approach was developed to use the changes in peak flow estimated by VIC, represented as a ratio of future to historic peak flows, to adjust the estimated peak flows provided by StreamStats. Throughout the park, the future-to-historic streamflow ratio is increasing for higher peak flows (e.g., 100-year flows or Q100), with greater increases later in the century. This indicates expected increases in peak flows in the future. At lower peak flows, some areas on the eastside of the park may see declines in mean annual flows (Q2) in the future, primarily because of reduced snowpack. A simple Excel spreadsheet tool was developed to quickly adjust estimates of peak flows from StreamStats using the VIC model future projections of streamflow. The tool provides five different peak flow return periods between 2 and 100 years (i.e. Q2, Q10, Q25, Q50, and Q100) based on climatology from ten different future climate scenarios modeled by Global Climate Models for both the 2040s and 2080s, thus disclosing future flow uncertainty. This tool can be used in the design of culvert sizes to accommodate future channel flows, to assess areas with viii higher risk of damage from greater changes in peak flows, and in prioritizing culvert inventories and maintenance.