Integrated assessment: Missing link in the acid rain debate?

The United States is finding it difficult to develop a coherent policy on acid rain. Despite more than a decade of scientific research and policy initiatives, no clear course of action has been identified. This article argues that what is missing is an integrated assessment of the scientific knowledge that will guide the political process. The role of the integrated assessment is described, and a conceptual framework presented that would accomplish the desired goal. Currently available acid rain assessment models are compared against this framework and found to be less than satisfactory. The article concludes by stressing the opportunity now available to the National Acid Precipitation Assessment Program to perform such an assessment and break the logjam.     

ANALYSIS AND MODELING OF LONG-TERM STREAM TEMPERATURES ON THE STEAMBOAT CREEK BASIN,OREGON: IMPLICATIONS FOR LAND USE AND FISH HABITAT1

ABSTRACT: Steamboat Creek basin is an important source of timber and provides crucial spawning and rearing habitat for anadromous steelhead trout (Oncorhynchus mykiss). Because stream temperatures are near the upper limit of tolerance for the survival of juvenile steelhead, the possible long-term effect of clear-cut logging on stream temperatures was assessed. Twenty-year (1969–1989) records of summer stream temperature and flow from four tributaries and two reaches of Steamboat Creek and Boulder Creek (a nearby unlogged watershed) were analyzed. Logging records for the Steamboat Creek basin and air temperature records also were used in the analysis. A time-series model of the components of stream temperature (seasonal cycle of solar radiation, air temperature, streamflow, an autoregressive term of order 1, and a linear trend variable) was fitted to the water-temperature data. The linear trend variable was significant in all the fitted models except Bend Creek (a tributary fed by cool ground-water discharge) and Boulder Creek. Because no trends in either climate (i.e., air temperature) or streamflow were found in the data, the trend variable was associated with the pre-1969 loss and subsequent regrowth of riparian vegetation and shading canopies.     

EXPOSURE ASSESSMENT OF POPULATIONS USING ENVIRONMENTAL MODELING,DEMOGRAPHIC ANALYSIS,AND GIS1

ABSTRACT: Simulation of ground-water flow and fate of contaminants in the subsurface environment constitutes a major phase of most environmental assessment and site remediation studies. These simulation studies yield information on spatial and temporal distributions of contaminants in the subsurface media. An important use of this information is to conduct exposure assessment studies. Spatial and temporal distributions of both chemical concentrations and exposed populations render this integrated exposure analysis task rather difficult. Geographic Information Systems (GIS), on the other hand, provide a platform in which layered, spatially distributed databases can be manipulated with ease, thereby simplifying exposure analysis tasks significantly. In this paper, we describe procedures that combine the simulation models and demographic databases under a GIS platform to automate the exposure assessment phase of a typical health assessment study. Procedures developed herein significantly simplify the post-processing phase of the analysis, and render the overall task more ‘user friendly.’ A site-specific application is included as a demonstration of the proposed process.     

CONFLICTING PERSPECTWES ABOUT DETECTION LIMITS AND ABOUT THE CENSORING OF ENVIRONMENTAL DATA1

ABSTRACT: Current conventions for reporting analytical results from environmental samples brings the objectives of laboratory scientists into conflict with those of environmental scientists. The objective of chemical analyses is to provide estimates of the true composition of samples. Reported results must reflect the analytical uncertainty. Current conventions require left-censoring of those results below the Limit of Detection. The objective of statistical interpretation of environmental data is to provide estimates of the characteristics of ecosystems. Such statistical analyses are often confounded by left-censoring of analytical results. We review the different points of view and propose a compromise which recognizes these conflicting perspectives.     

Initial decision analysis (IDA): a participatory approach for developing resource policies

Initial decision analysis (IDA) is a microcomputer based decision-making technique that is organized so that a rational, step-by-step, procedure can be followed to use existing knowledge to develop resource policies. The IDA process provides a systematic way for participants to define their own problem and to explore jointly alternative solutions. IDA is particularly suited to resolving complex problems involving many groups with conflicting interests. IDA is illustrated with data from the US Forest Service's Draft Environmental Impact Statement for the 1985 to 2030 Resource Planning Act Program for the United States. Four policy options are evaluated: maximization of timber production, of grazing, and of wilderness, and a dominant use policy that concentrates timber management on productive sites. Policies were evaluated using a new mathematical satisficing procedure. Mathematical satisficing of simulated policy consequences showed that, for selected performance standards, current RPA policies are superior to the four alternative policies examined.     

IDENTIFICATION OF AQUIFER DISPERSIVITIES: METHODS OF ANALYSIS AND PARAMETER UNCERTAINTY1

ABSTRACT: This paper presents a method for estimating aquifer dispersivities in solute transport models. Sensitivity equations are derived for the calculation of sensitivity coefficients. A modified Gauss-Newton algorithm is used to perform the least-squares minimization. A statistical procedure is outlined to assess reliability of the estimated parameters. The solute transport model is solved by the upstream weighted, multiple cell balance method which combines the concepts of local mass balance and finite element approximations. A one-dimensional solute transport problem in a vertical column system is first used to illustrate the inverse technique. A second example considers the parameter identification problem for three-dimensional solute transport with a unidirectional steady and uniform flow field. The third example solves the parameter identification problem in a three-dimensional, stream-aquifer, solute transport system with steady state flow. Numerical experiments are conducted to study data requirements for parameter identification.     

REAL-TIME SNOW SIMULATION MODEL FOR THE MONONGAHELA RIVER BASIN1

ABSTRACT: The Pittsburgh District, U.S. Army Corps of Engineers, is responsible for operating two multipurpose reservoirs in the 7384 square mile (19198 square kilometer) Monongahela Basin. A third reservoir, presently under construction, will soon be operating. The real-time forecasting of runoff for operational purposes requires simulation of snow accumulation and snowmelt throughout the Basin during the winter season. This article describes capabilities of SNOSIM, a model being developed for performing such simulation. The application of this model as part of a comprehensive system of water control software, and some initial simulation results are presented.     

BASIN WATER MONITORING: HYDROLOGIC IMPACT OR LEGAL COMPLIANCE1

ABSTRACT: The Surface Mining Control and Reclamation Act of 1977 (PL 95–87) requires data collection prior to mining which will allow a determination to be made of the probable hydrologic consequences. Modeling strategies exist which allow for such determination, but selection of a specific model form will dictate the length of data record needed. The absence of a sound management strategy by the regulatory authority in‘Maryland does not result in valid data collection and suggests that the agency is concerned more with legal compliance than with integrated resource management.     

SHORT-TERM FORECASTING OF SNOWMELT RUNOFF USING ARMAX MODELS1

ABSTRACT: Time series models of the ARMAX class were investigated for use in forecasting daily riverflow resulting from combined snowmelt/rainfall. The Snowmelt Runoff Model (Martinec-Rango Model) is shown to have a form similar to the ARMAX model. The advantage of the ARMAX approach is that analytical model identification and parameter estimation techniques are available. In addition, previous forecast errors can be included to improve forecasts and confidence limits can be estimated for the forecasts. Diagnostic checks are available to determine if the model is performing properly. Finally, Kalman filtering can be used to allow the model parameters to vary continuously to reflect changing basin runoff conditions. The above advantages result in improved flow forecasts with fewer model parameters.     

A hierarchical approach to fisheries planning and modeling in the Columbia River Basin

The Columbia River Basin is the scene of a massive effort to restore populations of Pacific salmon (Oncorhynchus spp.) and steelhead (O. mykiss). Efficient restoration is confounded by a high level of complexity, competing sociopolitical goals and values, and uncertainty about key system properties. Simulation models and other tools of systems analysis are important to development of a comprehensive, regionally acceptable strategy. Hierarchy theory provides a useful paradigm for organized complexity within the Columbia Basin and the basis for a trilevel hierarchical structure for organizing and integrating models. Life-stage models compose the most basic simulation units at the lowest level in the proposed hierarchical modeling structure. Each life-stage model simulates a distinct period in the life cycle of anadromous salmonids. Population models at the intermediate level simulate the complete life cycles of salmon and steelhead populations. At the highest level in the hierarchy, interpopulation models simulate extensive, long-term processes that affect multiple species and stocks. A hierarchical system of models is preferable to a single model or to a group of models lacking formal structure. A principal advantage is that models have the correct spatial and temporal resolution for analyzing questions at different scales. A hierarchical structure also facilitates the flow of information among models, and aids in understanding the impacts of uncertainty. Constructing a hierarchy of models should involve both bottom-up and top-down perspectives that maintain logical consistency among models, while allowing unique model structures appropriate for each level in the hierarchy.