Forecasting Watershed Loading and Lagoon Response Along the Delmarva Peninsula Due to Changing Land Use and Climate
Principal Investigator:Lora Harris
Institution:Chesapeake Biological Laboratory, University of Maryland Center for Environmental Science
Co-Principal investigator:Walter Boynton, Chesapeake Biological Laboratory, University of Maryland Center for Environmental Science; Mark J. Brush, Iris C. Anderson, Virginia Institute of Marine Science
Strategic focus area:Regional effects of climate change and sea level rise
OBJECTIVES: We propose a multidisciplinary modeling and field program to calibrate and apply watershed and lagoon ecosystem models across the seaside of the Delmarva Peninsula. Watershed modeling will be accomplished through a simplified Nitrogen Loading Model (NLM) calibrated through existing estimates of loads and new measurements of groundwater nutrients and source tracking. The NLM will then be used to predict changes in nitrogen loads to the Delmarva lagoons as a function of changes in land use, population sizes, and agricultural activities across the landscape. Forecasted loads will feed into a novel lagoon ecosystem model at two scales: (1) a coarse-scale version applied across all Delmarva lagoons and (2) a fine-scale version applied within specific lagoons. These models will be used to predict lagoon response to changing watershed loads and climate with a focus on (1) water quality, (2) habitat and ecosystem services, (3) alternative stable states, and (4) non-linear recovery trajectories.
METHODOLOGY: This work leverages our Sea Grant regional demonstration project currently under completion which has resulted in initial application of the NLM across the Delmarva and both the coarse- and fine-scale lagoon models in selected systems. Research will focus on simulations to predict changes in watershed loads and lagoon response. Field studies will provide data to improve calibration in two areas: (1) tidal creek water quality in VA to complement MD and DE datasets, and (2) groundwater nutrient sampling and source tracking.
RATIONALE: Local and county-wide managers on the Delmarva are currently faced with decisions related to land use, development pressure, agricultural operations, and population growth, but presently there is limited information relating watershed activities to resulting nutrient loads and lagoon responses. Management targets for land use decisions and nutrient loading along with decision-support modeling tools are urgently needed in these systems.
This section describes how this project has advanced scientific knowledge and/or made a difference in the lives of coastal residents, communities, and environments. Maryland Sea Grant has reported these details to the National Oceanic and Atmospheric Administration (NOAA), one of our funding sponsors.
Summary: Researchers created and disseminated a public, online analytical tool to help land-use managers understand the effects of development on nutrient loading in coastal bays on the Delmarva Peninsula. Maryland Sea Grant cosponsored workshops at which scientists presented the model to state and local officials. The researchers used feedback they received from the officials to improve the model’s usefulness.
Relevance: Local and county land-use managers on the Delmarva Peninsula (containing portions of Delaware, Maryland, and Virginia) face decisions on land use, development pressure, agricultural operations, and population growth in watersheds. Presently, these officials have limited information allowing them to relate these decisions to resulting nutrient loads and ecosystem responses in the peninsula’s coastal bays. Decision-support management tools like the one developed in this project may also help officials meet Total Maximum Daily Load (TMDL) targets for water quality in the bays.
Response: In this multi-year project, researchers supported by the Sea Grant programs of Maryland, Delaware, and Virginia developed three coupled models and adapted them to make them easy to use by non-scientists. A Nutrient Loading Model (NLM) represents effects of changes in watershed land use, population sizes, and agricultural activities on nutrient loading in the Delmarva bays. A Lagoon Ecosystem Model (LEM) describes the coastal bay ecosystems at a coarse scale across all lagoons and at a finer scale within specific bays. A Virtual Eelgrass Model (VEM) describes eelgrass growth in the bays. The research team adapted the models to include a number of land uses and to include parameters for regionally important nitrogen inputs from chicken production byproducts, septic systems, and tomato production. Principal investigator Lora Harris of the University of Maryland Center for Environmental Science’s Chesapeake Biological Laboratory worked in collaboration with graduate student Jessica Foley, a Maryland Sea Grant fellow, to expand the VEM to include reproductive processes and a seedling-specific growth rate sub-model. This work underscores the importance of modeling the effects of increasing water temperatures and rising sea level that are predicted to result from future climate change.
Results: The researchers released the coupled models in August 2015 for use by local and county planners and other stakeholders. As of February 2016, the stand-alone NLM spreadsheet and user’s guide were downloaded 134 and 180 times, respectively, and the online NLM-LEM was accessed 146 times. In the spring of 2015, co-principal investigator Harris participated in a meeting of Maryland coastal bay managers who are constructing policy to guide potential commercial harvest of macroalgae from the northern bays of Maryland. The researchers used the coupled models to evaluate various scenarios and provide preliminary guidance on whether to harvest macroalgae. In addition, the researchers submitted a section on estuarine models that was published in the "Encyclopedia of Estuaries."
Ganju, NK; Brush, MJ; Rashleigh, B; Aretxabaleta, AL; del Barrio, P; Grear, JS; Harris, LA; Lake, SJ; McCardell, G; O’Donnell, J; Ralston, DK; Signell, RP;Testa, JM; Vaudrey, JMP. 2015. Progress and challenges in coupled hydrodynamic-ecological estuarine modeling. Estuaries and Coasts:1-22. doi:10.1007/s12237-015-0011-y. UM-SG-RS-2015-10.