Integrating Real-Time Sensor Networks, Data Assimilation, and Predictive Modeling to Assess the Effects of Climate Variability on Water Resources in an Urbanizing Landscape

UMBC: C. Welty (PI), Andrew Miller, Michael P. McGuire
Princeton: James Smith
LLNL: Reed Maxwell
USGS: Robert Shedlock

Funding Source: NOAA (10/1/07 - 9/31/12)


The goal of this project is to establish a real-time observing system with wireless telemetry and advanced visualization tools for simultaneous display of the temporal and spatial patterns of all components of the hydrologic cycle at sites throughout a 171-km^2 urbanizing watershed in the Baltimore metropolitan area. This end-to-end system will be integrated with a fully coupled groundwater/surface water/land surface model and with a simpler flood forecasting system. Real-time and near real-time data, visualization products and modeling results will be broadcast through a web site that can be accessed and utilized by agency partners and managers, by educators and students, and by the public at large.

The study site, the Gwynns Falls watershed, is already one of the most heavily instrumented urban watersheds in the U.S. and is the primary study watershed for one of only two NSF-funded Urban Long-Term Ecological Research sites as well as one of a national network of 11 NSF-funded WATERS Test Bed sites. Additional monitoring programs in both Baltimore City and County are being implemented as a result of mandates under consent decrees from EPA. The research team members have access to all of the previously collected monitoring data as well as numerous high-resolution spatial databases characterizing the landscape at grid scales as small as 0.3-1.0 m. The proposed project will fill in gaps in our present system by completing the observational network and adding telemetry required for real-time date feeds to a central system located at UMBC, thus enabling us to conduct research to meet NOAA’s needs. The enhanced monitoring network will include 20 real-time stream gages and rain gages, 25 wells, 2 eddy covariance stations, and 10 soil moisture/soil tension clusters with 5 instruments per cluster. Additional instruments are expected to be added with support from other projects over the next several years.

This work will address NOAA’s Mission Goals #2 (Understand climate variability and change to enhance society’s ability to plan and respond) and #3 (Serve society’s needs for weather and water information). The project will advance the ability of decision makers in the climate-sensitive water resources sector to make more effective use of NOAA’s climate products. The research will improve our ability to assess the sensitivity of flood and drought probability and water availability to the combined effects of urban development and climate change. Because urbanization and climate change both cause progressive changes in the frequency distribution of hydrologic time series, future conditions cannot reliably be predicted based on statistics of past events. Therefore we need improved understanding of the dynamic processes that link the various components of the hydrologic cycle, so that modeling scenarios can be developed to account for a range of possible future conditions. This work has potential benefits in the form of better and more timely understanding of hazards and improved planning by managers. We anticipate that the integration of additional data sources will be useful in improving existing flood forecasting software. The availability of an enhanced real-time data collection network integrated with advanced visualization tools will also likely result in increased customer satisfaction with water information and services.