Addressing Uncertainty in TMDLS: Short Course at Arkansas Water Resources Center 2001 Annual Conference

Management of a critical natural resource like water requires information on the status of that resource. The US Environmental Protection Agency (EPA) reported in the 1998 National Water Quality Inventory that more than 291,000 miles of assessed rivers and streams and 5 million acres of lakes do not meet State water quality standards. This inventory represents a compilation of State assessments of 840,000 miles of rivers and 17.4 million acres of lakes; a 22 percent increase in river miles and 4 percent increase in lake acres over their 1996 reports. Siltation, bacteria, nutrients and metals were the leading pollutants of impaired waters, according to EPA. The sources of these pollutants were presumed to be runoff from agricultural lands and urban areas. EPA suggests that the majority of Americans-over 218 million-live within ten miles of a polluted waterbody. This seems to contradict the recent proclamations of the success of the Clean Water Act, the Nation\u27s water pollution control law. EPA also claims that, while water quality is still threatened in the US, the amount of water safe for fishing and swimming has doubled since 1972, and that the number of people served by sewage treatment plants has more than doubled

Risk Regulation and the Faces of Uncertainty

Dr. Walker addresses the difficulty of regulators\u27 working with potentially inaccurate information and clarifies related aspects of decision making by presenting a taxonomy for the kinds of uncertainty inherent in necessarily incomplete data

The role of learning on industrial simulation design and analysis

The capability of modeling real-world system operations has turned simulation into an indispensable problemsolving methodology for business system design and analysis. Today, simulation supports decisions ranging from sourcing to operations to finance, starting at the strategic level and proceeding towards tactical and operational levels of decision-making. In such a dynamic setting, the practice of simulation goes beyond being a static problem-solving exercise and requires integration with learning. This article discusses the role of learning in simulation design and analysis motivated by the needs of industrial problems and describes how selected tools of statistical learning can be utilized for this purpose

Modeling the Structure and Complexity of Engineering Routine Design Problems

This paper proposes a model to structure routine design problems as well as a model of its design complexity. The idea is that having a proper model of the structure of such problems enables understanding its complexity, and likewise, a proper understanding of its complexity enables the development of systematic approaches to solve them. The end goal is to develop computer systems capable of taking over routine design tasks based on generic and systematic solving approaches. It is proposed to structure routine design in three main states: problem class, problem instance, and problem solution. Design complexity is related to the degree of uncertainty in knowing how to move a design problem from one state to another. Axiomatic Design Theory is used as reference for understanding complexity in routine design

Water Quality Trading and Agricultural Nonpoint Source Pollution: An Analysis of the Effectiveness and Fairness of EPA's Policy on Water Quality Trading

Water quality problems continue to plague our nation, even though Congress passed the Clean Water Act (CWA) to "restore and maintain the chemical, physical, and biological integrity of the Nation's waters"1 more than three decades ago. During the past thirty years, the dominant sources of water pollution have changed, requiring us to seek new approaches for cleaning up our waters. Water quality trading has been heralded as an approach that can integrate market mechanisms into the effort of cleaning up our water. This Article examines the Environmental Protection Agency's (EPA) policy on water quality trading and the prospects for water quality trading to help improve water quality.Part II briefly describes our water quality problems and causes. Part III examines the theoretical basis for trading and the EPA's Water Quality Trading Policy. Part IV discusses the potential impact of total maximum daily loads (TMDLs) on water quality trading, and Part V analyzes potential problems that water quality trading programs confront. Part VI addresses distributional and efficiency concerns that arise when considering trading and agricultural nonpoint source pollution. Part VII then examines issues relating to water quality trading and state laws before reaching conclusions and recommendations in Part VIII