Stormwater Runoff in Coastal Watersheds: Predicting Impacts of Development and Climate Change
Project Status: This project began in January 2007 and is Ongoing
We developed a stormwater runoff modeling system to predict the impacts of development and climate change on stormwater runoff in small coastal watersheds. The model quantifies runoff using climate change projections and urban development scenarios and can be used for different regions by substituting local characteristics. Also, we are building a tool that will enable research scientists, resource managers, decision makers, and others to use the model.
Why We Care
Stormwater runoff pollutes and erodes waterways, and the related flooding directly exposes people to harmful contaminants. Across the nation, but especially in coastal areas, population growth and development have increased the amount of runoff and, in tandem, its impact on water quality, public health, and marine life. The increasing rates of urban development, as well as projected increases in the occurrence of intense storms, will generate even more runoff in the future and at faster rates.
To enact water management, environmental research, and community resource strategies this forecast demands, the ability to quantify runoff at local scales has become critical. However, few methods to do so are available.
What We Are Doing
NCCOS developed a stormwater runoff modeling system (SWARM) that quantifies runoff volumes and rates using climate change and development scenarios. We based SWARM on the runoff curve number method and unit hydrograph algorithms of the U.S. Department of Agriculture's Natural Resources Conservation Service. We validated SWARM using U.S. Geological Survey discharge and rain data, and validation results support the appropriateness of our modeling system for southeastern coastal watersheds. We are building a user-friendly tool for use by research scientists, resource managers, decision makers, and others. SWARM also can be applied to other regions by recalibrating parameters and modifying calculation templates.
Key applications of SWARM are:
comparing runoff among watersheds representing different environmental settings (e.g., levels of development, soil types, a range of sizes, topography);
evaluating and illustrating (singularly or in combination) effects of primary drivers of runoff amount and flashiness including development level, soil type, antecedent runoff conditions, rainfall amount;
predict runoff under a range of development scenarios within a watershed;
integrate effects of urbanization and projected climate change scenarios.
What We Are Finding
SWARM output consistently shows higher runoff volume, higher peak rate, and shorter runoff duration with increasing urbanization in three of our study sites representing undeveloped, residential, and urban watersheds. For modeling runoff from a two-year storm event (4.5 inches over a period of 24 hours), peak runoff rate is three to five times greater in the developed watersheds than in the undeveloped watershed, runoff volume is twice as great in the developed watersheds, and total runoff time in the developed watersheds is less than half that of the undeveloped watershed. Integrating climate change into the modeled 2-year storm event shows dramatic impacts in all three watersheds by doubling peak runoff rates and increasing runoff volume by more than 25 percent.
Benefits of our Work
The modeling system is flexible and robust, and that combined with user-friendly templates makes it a powerful tool for scientific research and coastal resource management. We will be finalizing the SWARM tool which comprises calculation and graphic templates to:
calculate volume and impervious cover percent and determine curve numbers for antecedent runoff conditions;
calculate predicted volumes with increased (or decreased) development;
calculate annual runoff volume.
Related Regions of Study: Alabama, Florida, Georgia, Mississippi, North Carolina, South Carolina
Primary Contact: Anne Blair
Climate Impacts ( Impacts of Changing Temperature and Hydrology, Climate Adaptation, Vulnerability Assessments)
Related NCCOS Center: HML