Urban Critical Zone Cluster (National Science Foundation)
Lead PI: C. Welty
Collaborative PIs: J. Moore, D. Bain, P. Groffman, J. Duncan, A. Berkowitz, K. Prestegaard, L. Toran
This project will advance knowledge of urban critical zone processes through a Critical Zone (CZ) Cluster spanning four cities on the U.S. East Coast: Philadelphia, Baltimore, Washington, DC, and Raleigh. These cities were developed along the Fall Zone, a region of steep rivers incised into crystalline Piedmont bedrock upstream of the Atlantic Coastal Plain. The north-south gradient of this urban cluster is associated with climatic trends and with a gradient in age from older and denser development in Philadelphia and Baltimore to newer and sparser development in Raleigh.
We aim to address the following questions: (1) How does urbanization in a temperate, Eastern seaboard landscape result in a shift from a supply-limited to a transport-limited regime governing solute export? (2) How does the underlying structure of the CZ along the Piedmont-Coastal Plain transition interact with urbanization to affect export fluxes? (3) How do chemical and hydrological dynamics associated with urbanization affect material export along the latitudinal gradient from Philadelphia to Raleigh?
Research methods include development of a watershed-scale geochemical-hydrological model as a framework for data collection, assimilation, and prediction; geophysics for subsurface mapping; land cover/land use data analysis; soil and rock core chemical analysis; soil gas sampling; stream and well sampling for solutes; and analysis of sediment concentrations and yields. We will construct a new conceptual model of solute movement from the land surface through the subsurface to streams, constrained by geologic and geomorphic architecture and the overprinting of urban development. This project will train 7 undergraduates per year, 7 graduate students, and 1 post-doctoral associate.
Project participants will work with high school science teachers to identify topics for a CZ instructional module and a teacher professional development program. A regional CZ Citizen Science Interest Group will be convened to identify opportunities to adopt CZ project protocols in local programs and to contribute to CZ project research. The project engagement plan includes hosting open quarterly science meetings and establishing a visiting scholar fund to support scientific exchange with other CZ cluster sites.
Evaluation of watershed-scale impacts of stormwater management facilities on thermal loads to a Maryland Class IV stream using a high-frequency sensor network (Chesapeake Bay Trust)
PI: C. Welty
co-PI: A.J. MIller
We are deploying a high-density, high-frequency network of blue-tooth enabled temperature sensors throughout 16 km of a Use Class IV stream (Dead Run) in suburban Baltimore to address CBT 2021 RFP Question 5(a) on emerging pollutants: What best management practice design and siting methods will reduce thermal impacts to Maryland’s Use III and IV streams? At the watershed scale, we are collecting high-frequency (5-minute) temperature data from sensors secured to the streambed every 100 m, over all flow regimes (base flow to storm flow), for 2.25 years. Based on watershed-scale observations, we plan to collect stream temperature data downstream of ~30 BMP outfalls (spanning at least four BMP types) at a finer spatial scale (2 m – 50 m), and a higher frequency (1 minute). We will use this data set to quantify thermal inputs to the stream system from (1) surface and subsurface stormwater management facilities; (2) direct connections to land cover including impervious surface area during runoff events; and (3) effects of air temperature and tree canopy on stream temperature throughout the drainage network. This work will advance scientific knowledge by separating impacts from stormwater BMPs vs. other environmental factors on stream temperature at the watershed scale; the results can be used to inform regulatory policy for setting Total Maximum Daily Loads (TMDLs) for stream temperature.
The Baltimore Social-Environmental Collaborative Integrated Field Laboratory
Lead PI: Ben Zaitchik, Johns Hopkins University
Collaborative co-PIs: C. Welty, UMBC; Ken Davis; Penn State; Michael Waring, Drexel University; James Hunter, Morgan State; Lawrence Band, University of Virginia; Jiazhen Ling, DOE NREL; Peter Groffman, CARY/CUNY; Morgan Grove, USFS
The Baltimore Social-Environmental Collaborative (BSEC) is a DOE Integrated Field Laboratory centered on the Baltimore, MD metropolitan area. BSEC’s goal is to develop a model for community-oriented urban climate science that can be applied in other metropolitan areas. We are working with community partners to establish measurement and modeling platforms that address environment, health, and development priorities of the city and its neighborhoods, and that provide accessible and flexible entry points to engage with scientific results. We are leveraging our vast existing modeling and observational resources to build the BSEC. Our approach will include (1) placing environmental justice at the center of IFL designs; (2) adopting a participatory, multi-objective framework to identify just and sustainable pathways under climate change; (3) addressing the complexities of the built environment, including indoor-outdoor environmental interactions, to connect the IFL to residents’ lived experience; and (4) recognizing that a city is a coupled natural-human ecosystem in which human well-being and ecosystem processes are intertwined.
Baltimore Ecosystem Study (National Science Foundation and USDA Forest Service)
PI/PD: Chris Swan
Field headquarters host: C. Welty
The Baltimore Ecosystem Study (BES) seeks to:
• Pursue excellence in social-ecological research in an urban system;
• Maintain positive engagement with communities, environmental institutions, and government agencies;
• Educate and inform the public, students, and organizations that have need of scientific knowledge; and,
• Assemble and nurture a diverse and inclusive community of researchers, educators, and participants.