2023 Early Hearing Detection & Intervention Conference

March 5-7, 2023 • Cincinnati, OH

<< BACK TO AGENDA

5/21/2019 | 12:00 PM - 12:15 PM | ASSESSING CONDITION AND VULNERABILITY OF HEALTHY WATERSHEDS IN THE CHESAPEAKE BAY REGION | 150 DEF

ASSESSING CONDITION AND VULNERABILITY OF HEALTHY WATERSHEDS IN THE CHESAPEAKE BAY REGION

The Chesapeake Bay Program has a goal of maintaining the long-term health of watersheds identified as healthy by its seven partner jurisdictions. Quantitative indicators are important to assess current watershed condition, track future condition, and assess vulnerability of these watersheds to future degradation. Building upon EPA’s Preliminary Healthy Watershed Assessment (PHWA) framework, we assembled and evaluated a set of candidate metrics characterizing multiple aspects of landscape condition, hydrology, geomorphology, habitat, biological condition, and water quality, for integration into an overall watershed health index. Geospatial analyses were structured, where possible, to leverage data from EPA StreamCat, the National Fish Habitat Partnership, the Chesapeake Bay model for nutrient loads, and other regional sources. Vulnerability metrics were derived including future developed land use, forest loss, protected land status, and brook trout susceptibility to climate change. Metric values were compiled for nearly 84,000 NHDPlus catchments Bay-wide, particularly within catchments comprising the state-identified healthy watersheds. We will discuss the major concepts addressed by the Chesapeake PHWA, key findings, and next steps. The indicators will be available to federal, state, and local managers as a geospatial tool, providing critical information for maintaining watershed health.

Conservation
Landscape
Assessment

Presentation:
This presentation has not yet been uploaded.

Handouts:
Handout is not Available

Transcripts:
CART transcripts are NOT YET available, but will be posted shortly after the conference

Presenters/Authors

Nancy Roth (), Tetra Tech, nancy.roth@tetratech.com;