Soil loss as a measure of carrying capacity in recreation environments

This article describes three applications of the Universal Soil Loss Equation for further defining differences between natural environments in terms of their suitabilities for recreation use. Physical capacity limits based upon vulnerability to erosion and loss of soil productivity are discussed. Examples include: (a) applications to site planning and comparison of existing campsites; (b) use of the methodology for setting limits of acceptable change; and (c) characterization of third-order or larger watersheds that compare ecological land type interpretations with those based upon application of the equation.     

A land suitability model for the evaluation of land-use change

A land suitability model was developed to provide the planner with a quantitative tool for assessing the environmental limitations on proposed land-use changes in the area surrounding Lake Monroe in southern Indiana. The model incorporates a weighting procedure that allows the environmental evaluation of a decision to convert the present land use to another category. The data base for the model was assembled by a multidisciplinary team. A case study is included, which illustrates the advantages and limitations of the land suitability model as it is applied to the evaluation of a site for the Alumni Family Camp.     

Synergistic Techniques for Better Understanding and Classifying the Environmental Structure of Landscapes

The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC) for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions has become the search for the best classification that optimally trades off classification complexity for class homogeneity. In this study, three techniques are investigated for their ability to find the best classification of the physical environments of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network, and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure of the landscape and to use this knowledge to select the best ELC at the required scale of analysis.     

Evaluation of the National Land Cover Database for Hydrologic Applications in Urban and Suburban Baltimore,Maryland1

Smith, Monica Lipscomb, Weiqi Zhou, Mary Cadenasso, Morgan Grove, and Lawrence E. Band, 2010. Evaluation of the National Land Cover Database for Hydrologic Applications in Urban and Suburban Baltimore, Maryland. Journal of the American Water Resources Association (JAWRA) 46(2):429-442. DOI: 10.1111/j.1752-1688.2009.00412.x Abstract: We compared the National Land Cover Database (NLCD) 2001 land cover, impervious, and canopy data products to land cover data derived from 0.6-m resolution three-band digital imagery and ancillary data. We conducted this comparison at the 1 km², 9 km², and gauged watershed scales within the Baltimore Ecosystem Study to determine the usefulness and limitations of the NLCD in heterogeneous urban to exurban environments for the determination of land-cover information for hydrological applications. Although the NLCD canopy and impervious data are significantly correlated with the high-resolution land-cover dataset, both layers exhibit bias at <10 and >70% cover. The ratio of total impervious area and connected impervious area differs along the range of percent imperviousness – at low percent imperviousness, the NLCD is a better predictor of pavement alone, whereas at higher percent imperviousness, buildings and pavement together more resemble NLCD impervious estimates. The land-cover composition and range for each NLCD urban land category (developed open space, low-intensity, medium-intensity, and high-intensity developed) is more variable in areas of low-intensity development. Fine-vegetation land-cover/lawn area is incorporated in a large number of land use categories with no ability to extract this land cover from the NLCD. These findings reveal that the NLCD may yield important biases in urban, suburban, and exurban hydrologic analyses where land cover is characterized by fine-scale spatial heterogeneity.     

The integrated project AquaTerra of the EU sixth framework lays foundations for better understanding of river-sediment-soil-groundwater systems

The integrated project "AquaTerra" with the full title "integrated modeling of the river-sediment-soil-groundwater system; advanced tools for the management of catchment areas and river basins in the context of global change" is among the first environmental projects within the sixth Framework Program of the European Union. Commencing in June 2004, it brought together a multidisciplinary team of 45 partner organizations from 12 EU countries, Romania, Switzerland, Serbia and Montenegro. AquaTerra is an ambitious project with the primary objective of laying the foundations for a better understanding of the behavior of environmental pollutants and their fluxes in the soil-sediment-water system with respect to climate and land use changes. The project performs research as well as modeling on river-sediment-soil-groundwater systems through quantification of deposition, sorption and turnover rates and the development of numerical models to reveal fluxes and trends in soil and sediment functioning. Scales ranging from the laboratory to river basins are addressed with the potential to provide improved river basin management, enhanced soil and groundwater monitoring as well as the early identification and forecasting of impacts on water quantity and quality. Study areas are the catchments of the Ebro, Meuse, Elbe and Danube Rivers and the Brévilles Spring. Here we outline the general structure of the project and the activities conducted within eleven existing sub-projects of AquaTerra.