Clean Water Act assessment processes in relation to changing US Environmental Protection Agency management strategies
Cooter, W. (2004). Clean Water Act assessment processes in relation to changing US Environmental Protection Agency management strategies. Environmental Science and Technology, 38(20), 5265-5273.
During the 1970s the U.S. Environmental Protection Agency (EPA) devised a multiscale system of basin planning and regional implementation that encouraged a balanced mixture of monitoring and modeling-based assessments. By the 1980s, this goal had not been achieved. Modeling and monitoring assessment approaches became largely decoupled. To a significant degree, modeling was viewed as too inaccurate to handle issues such as setting permit limits involving toxics. During the 1980s, EPA also encouraged the idea that monitoring approaches were adequate to document water quality problems, guide the development of management plans, and demonstrate the achievement of management goals. By the late 1990s, large numbers of waters listed under the Clean Water Act's Total Maximum Daily Load (TMDL) provisions showed the widespread nature of pollutant concerns, but the uneven nature of the listing information also revealed fundamental problems in the ability of state monitoring programs to achieve credible and comprehensive assessments. Statistics are presented from the 1998 and the most current publicly available 2000 baseline periods showing the limitations in the scope of state assessments. There are significant opportunities for the increased use of relatively simple modeling systems that can be flexibly implemented over a variety of spatial scales. In addition to conventional modeling frameworks, the value of bioassessment monitoring techniques is stressed. Bioassessment indicators can often be combined with landscape modeling methods, as well as analyses from conventional modeling outputs, to help target small area monitoring by use of tiered approaches. These findings underscore the value of integrated monitoring and modeling approaches to build properly balanced assessment systems