Limitations of multimedia models for use in environmental decision making

The United States currently is engaged in a complex,multi-billion dollar effort to cleanup a legacy ofboth privately- and federally-owned hazardous wastesites. Decisions regarding the best approach forremediation of these sites often are based on theanalysis of potential risks to human health and theenvironment. A cornerstone of such analysis is thefrequent use of computerized multimedia environmentaltransport models, to evaluate the large quantities ofinformation necessary to understand the present andfuture implications of contamination at a site. Onebarrier to wide-spread use of this analyticalprocedure is the view that results obtained usingcomputer models are highly dependent on user input,and therefore, subject to manipulation. It is widelyrecognized that for decisions to be both credible andimplementable, the public must have confidence in boththe scientific basis for judgments involved and thedecision processes employed (NRC, 1983). Our purposein this article is to overview the difficultiesassociated with application of multimedia models toreal world problems and the contribution these modelscan make to technically sound estimates of exposure and risk.     

Interpretation and Discrimination of Marshy Wetlands by Soil Factors in the Kuan-Tu Natural Park, Taiwan

This work investigated soil samples collected from Kuan–Tu wetlands, Taiwan. Factor analysis was performed to explain the impact of various soil factors on this marshy wetlands located in suburban Taipei. The results indicated that the latent factors were heavy metals, salinity, and soil organic matter. Canonical discriminant analysis was used to improve an existing vegetation classi–fication scheme by identifying the physical-chemical properties of sediment in Kaun–Tu wetlands, Taiwan. Predictive discriminant analysis was used to examine the ability of the models to predict class membership for unknown soil sample. Multivariate analysis of the spatial patterns of soil quality and vegetation types showed that different properties of soil grew different types of vegetation and absorbed contaminants differently. We can feasibly conserve a suitable habitat for wetland biology by processing these unstable predictor variables. The methodology and results provide useful information concerning the Kuan–Tu wetlands and may be applicable to other wetlands with similar properties that are experiencing similar environmental issues.     

Numerical integration of chemical ODE problems arising in air pollution models

The numerical treatment of a regional air pollution model (such models are, as a rule, described mathematically by systems of partial differential equations) leads to the solution of very large computational problems. The chemical submodel of an air pollution model is normally the most timeconsuming part of the computational work. The application of appropriate discretization and splitting procedures reduces the chemical submodel to a large number of relatively small ODE systems (one such system per gridpoint). In the process of searching for efficient numerical algorithms for the chemical submodels one can carry out experiments by using only one such ODE system in order to facilitate the work. This approach has been used in connection with a particular chemical scheme, the condensed CBM IV scheme, which is used in several large air pollution models. Six integration algorithms have been tested on a set of typical scenarios (consisting of different starting concentrations and/or of different values of the emissions). The advantages and the disadvantages of the algorithms tested are discussed. The final decision about the most efficient algorithm, among the algorithms tested, should be made after a second series of experiments. The coupling of the chemical process with the transport of air pollution (on, at least, a twodimensional domain) together with the application of highspeed computers has to be studied in the second series of experiments, which will be performed in a subsequent paper.     

An evaluation of grid size uncertainty in empirical soil loss modeling with digital elevation models

This paper presents a study on the effect of topographic variability on grid-based empirical estimation of soil erosion and sediment transport with raster geographic information systems (GIS). An original digital elevation model (DEM) of 10 m resolution for a case watershed is resampled to six realizations of greater grid sizes for a comparative examination. The Universal Soil Loss Equation (USLE) and a distance-based sediment delivery equation are applied to the watershed to calculate soil loss from each cell and total sediment transport to streams, respectively. The results suggest that the selection of the DEM gird size has considerable influence on the soil loss estimation with the empirical models. The estimate of total soil loss from the watershed decreases significantly with the increasing DEM cell size as the spatial variability is reduced by the cell aggregation. The empirical modeling approach is a useful tool for qualitative assessment of soil erosion, provided that spatial variability can be adequately represented by applied DEMs. However, discretion is suggested for its applications to quantitative estimation of soil loss concerning the sensitivity to the grid size selection.     

Introduction of Relative Abundance Distribution (RAD) Indices, Estimated from the Rank-Frequency Diagrams (RFD), to Assess Changes in Community Diversity

Quantifying a relative abundance distribution based on thesampling of a set of species is a widespread problem in ecology.A number of diversity indices have been proposed and used in numerous works in spite of a lack of statistical characteristics and tests of comparison. The relative abundancedistribution can also be described using rank-frequency diagrams but fitting these diagrams to mathematical models such as the Zipf-Mandelbrot model remains problematic. Strong correlation between the Zipf-Mandelbrot model parameters prevent their estimation by optimization algorithm. In light of this, new indices of sampled communities are introduced here. These indices are two linear regression slopes estimated from rank-frequency diagrams. The numerous statistical studies that have been carried out on linear regression models are used to compare sampled communities. These new indices possesscharacteristic properties with an ecological meaning.Correlations between these indices, the Zipf-Mandelbrot modelparameters and an evenness diversity index are examined. Anecological application is made using entomological data as anexample. This example consists of a transect from the edge of apond to a dry forest along which 60,000 insects were sampledfrom six different sampling stations. Using the new indicesdescribed here, station C, located at the edge of that areasubject to influence from the pond, is differentiated from theother stations. This station would seem to present the lowestdegree of niche diversity and the lowest evenness, and recent observations confirm the deterioration of this station.