You are here:
REGIONAL VULNERABILITY ASSESSMENT: CREATING A CONTEXT FOR EVALUATING STREAM ACIDIFICATION
Citation:
Flum, T, B H. Hill, AND A. T. Herlihy. REGIONAL VULNERABILITY ASSESSMENT: CREATING A CONTEXT FOR EVALUATING STREAM ACIDIFICATION. Presented at International Congress on Ecosystem Health: Managing for Ecosystem Health, Sacramento, CA, August 15-20, 1999.
Description:
USEPA's Regional Vulnerability Assessment (ReVA) program is designed to identify ecosystems that are likely to vary beyond the range of natural variability and thereby experience reduced ecological integrity as a result of natural and human-induced stressors. ReVA makes use of remotely sensed and other data suitable for analysis using GIS to locate particular areas where ecosystems may be exposed to the impact of single and multiple stressors. The immediate focus for ReVA is the mid-Atlantic region where several biological assessments have recently been performed including the USEPA's Environmental Monitoring and Assessment Program (EMAP). EMAP results from the Mid-Atlantic Highland Area (MAHA) expressed as a percentage of total stream miles include: 1) <1% of steams were acidic due to mine drainage; 2) <4% were acidic due to acid deposition; 3) 14% were impacted by mine drainage; 4) 24% had poor riparian habitat quality; and 5) 17% had poor in-stream habitat quality. Applying the EMAP data for the purposes of ReVA requires identifying which of the steam miles with poor riparian habitat and in-stream habitat quality were related to mining activity. This is accomplished by overlaying the EMAP sampling locations on mine sites identified using Thematic Mapper (TM) satellite imagery taken from 1989-1993 as well as mine sites identified in other projects and relating the riparian and in-stream condition to the presence or absence of mines. A framework is then presented that demonstrates how to identify factors potentially interacting with mining including acid deposition, issues related to agricultural land use, and hydrologic alterations. This framework is used to develop a model that accounts for the interactions among the identified factors. The model is then applied to projected locations of future mining activity to serve as a case study for ReVA.