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Developing an Adaptive Management Approach Using Offsets for Reducing Mercury
Loadings to the Sacramento River Watershed
Water quality trading and offsets are being developed to improve policy-
maker’s and regulator’s ability to assess non–point source
impacts in watersheds and to evaluate the efficacy of using market-incentive
programs for preserving environmental quality. Offset programs allow facilities
facing higher pollution control costs to meet their regulatory obligations by
making pollution reductions elsewhere at a lower cost. Research is being
conducted by the U.S. Geological Survey (USGS) Western Geographic Science
Center (WGSC) in collaboration with Stanford University developing an adaptive
management approach (AMA) to help wastewater treatments plants decide whether
offsets can meet their
discharge permit requirements for mercury (Hg) Total Maximum Daily Loads (TMDL)
cost-effectively in the Sacramento River Watershed. The intent of the AMA is to
use empirical data and subjective judgment from real-life environmental and
economic conditions to provide TMDL decision-makers with a strong scientific
and technical basis for making offset decisions. An efficient AMA requires both
a scientific basis and methods to translate that science into a regulatory
decision framework under a variety of political and economic conditions.
Physical, chemical, and biological processes for Hg in aquatic environments are
quite complex and contain uncertainties for identifying the ecosystem dynamics.
Although a number of various deterministic models and empirical models have
been developed for Hg, the uncertainty of these underlying scientific processes
may produce similarly large uncertainties in the decision-making process. USGS
research is focusing on using alternative econometric and statistical methods
to explicitly state and reduce these uncertainties so that they are better
incorporated in policy decision-making. The USGS WGSC approach consists of
applying probabilities using a Bayesian Probability Network (BPN) which
integrates information of varying rigor and detail into a simple model of a
complex system. The relationships are identified and quantified using
historical data, physical process-based models, conceptual models, and expert
judgment. Thus, they are conceptual rather than mechanistic models, intended to
represent a coherent set of beliefs and knowledge about a system rather than
the physical processes themselves. This network structure provides an
integrated approach to uncertainty analysis and allows easy updating of
prediction and inference when new observations of model variables are made.
Based upon this work, USGS WGSC will apply this framework in the Cache Creek
watershed (sub-basin of the Sacramento River Watershed) as a hypothetical case
to aid decision-making for wastewater treatment plants and industrial
facilities for meeting discharge permit requirements. The objective of the AMA
is for the decision-maker, for instance, a permitted discharger, to use the
alternative statistical methods based on probabilistic relationships between
mitigation decisions and load reductions, to predict the impacts of a
remediation (offset) project on Hg load at the point of compliance as well as
mitigation costs.
 This
research project seeks to critically analyze society’s use of science and
statistics within a stakeholder framework to produce an optimal methodology for
water quality analysis. The purpose of the research is not to prescribe
specific offset decisions for point sources or policy decisions for regulatory
bodies pronouncing offsets as a suitable water quality policy. The intent is to
develop a decision support framework using empirical data that incorporate
actual issues and environmental conditions to provide TMDL decision-makers
(regulators and permitted-facilities) with a strong scientific and technical
basis for making water quality decisions. The methods employed through this
research will provide local, regional, and federal decision-makers an
understanding of whether discharge permit requirements can be met through
offsets (environmentally, cost-effectively, and legally) for persistent,
bio–accumulative toxics like Hg. In addition, this research will provide
alternative statistical methods for TMDL and water quality analyses explicitly
stating the uncertainty of economic and scientific results
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