GIS‐Based Predictive Models of Hillslope Runoff Generation Processes1

Abstract: Successful nonpoint source pollution control using best management practice placement is a complex process that requires in‐depth knowledge of the locations of runoff source areas in a watershed. Currently, very few simulation tools are capable of identifying critical runoff source areas on hillslopes and those available are not directly applicable under all runoff conditions. In this paper, a comparison of two geographic information system (GIS)‐based approaches: a topographic index model and a likelihood indicator model is presented, in predicting likely locations of saturation excess and infiltration excess runoff source areas in a hillslope of the Savoy Experimental Watershed located in northwest Arkansas. Based on intensive data collected from a two‐year field study, the spatial distributions of hydrologic variables were processed using GIS software to develop the models. The likelihood indicator model was used to produce probability surfaces that indicated the likelihood of location of both saturation and infiltration excess runoff mechanisms on the hillslope. Overall accuracies of the likelihood indicator model predictions varied between 81 and 87% for the infiltration excess and saturation excess runoff locations respectively. On the basis of accuracy of prediction, the likelihood indicator models were found to be superior (accuracy 81‐87%) to the predications made by the topographic index model (accuracy 69.5%). By combining statistics with GIS, runoff source areas on a hillslope can be identified by incorporating easily determined hydrologic measurements (such as bulk density, porosity, slope, depth to bed rock, depth to water table) and could serve as a watershed management tool for identifying critical runoff source areas in locations where the topographic index or other similar methods do not provide reliable results.     

Impact of alternative metrics on estimates of extent of occurrence for extinction risk assessment

In International Union for Conservation of Nature (IUCN) Red List assessments, extent of occurrence (EOO) is a key measure of extinction risk. However, the way assessors estimate EOO from maps of species’ distributions is inconsistent among assessments of different species and among major taxonomic groups. Assessors often estimate EOO from the area of mapped distribution, but these maps often exclude areas that are not habitat in idiosyncratic ways and are not created at the same spatial resolutions. We assessed the impact on extinction risk categories of applying different methods (minimum convex polygon, alpha hull) for estimating EOO for 21,763 species of mammals, birds, and amphibians. Overall, the percentage of threatened species requiring down listing to a lower category of threat (taking into account other Red List criteria under which they qualified) spanned 11–13% for all species combined (14–15% for mammals, 7–8% for birds, and 12–15% for amphibians). These down listings resulted from larger estimates of EOO and depended on the EOO calculation method. Using birds as an example, we found that 14% of threatened and near threatened species could require down listing based on the minimum convex polygon (MCP) approach, an approach that is now recommended by IUCN. Other metrics (such as alpha hull) had marginally smaller impacts. Our results suggest that uniformly applying the MCP approach may lead to a one‐time down listing of hundreds of species but ultimately ensure consistency across assessments and realign the calculation of EOO with the theoretical basis on which the metric was founded.     

Decision support tools for collaborative marine spatial planning: identifying potential sites for tidal energy devices around the Mull of Kintyre,Scotland

The expansion of offshore renewable energy production, such as wind, wave and tidal energy, is likely to lead to conflict between different users of the sea. Two types of spatial decision support tools were developed to support stakeholder workshops. A value mapping tool combines regional attributes with local knowledge. A negotiation support tool uses these value maps to support stakeholders in finding acceptable locations for tidal energy devices. Interactive value mapping proved useful to address deficiencies in data and to create credibility for these maps. The negotiation tool helped stakeholders in balancing objectives of the various stakeholders.     

Impact evaluation of agrotechnologies in watersheds

The special project RAISA (Advanced Researches for Innovation in Agricultural Systems) of the National Research Council of Italy concerns the development of new methodologies for the study and evaluation of the impact of agrotechnologies on the environment. In the project, several trans-disciplinary Units have worked together since 1990. The aim of the project is to define systems, using tools such as remote sensing and Geographical Information Systems, for decision making support in land planning and land use management, with particular attention to groudwater table pollution. The fundamental steps for evaluation of the impact of agrotechnologies on the Po river watershed, 75,000 km² in northern Italy, and Tevere (Tiber) river watershed, 17.169 km² in Central Italy are described here. The study concerns particular areas located in the western part of the Po River plain, where flooded rice is the main crop, and in the central plain of the Tevere basin where the risk of water pollution is considerable, due to small and medium sized swine breeding farms. The aspects considered were water pollution due to mineral nitrogen used to fertilize the rice crop and the nitrogen contained in the waste water from pig farms. For the Po river basin the methodology developed was based on the integration of satellite remote sensing images, and the available cartography, such as topographic and thematic maps, together with the hydrological and the toxicological data of the chemical fertilizers employed, summarized in maps of the groundwater table pollution hazard. A simpler evaluation was obtained in the Tevere river basin: the thematic layers were crossed in bi-directional matrices and the result merged with the map of the territorial distributionof the swine. In both cases the selected information was integrated and processed in Integrated sub-basin scale. The GISs led to the development of a user-friendly system for formalizing our knowledge of the degree of pollution hazard in simple and readable maps.Research supported by National Research Council of Italy, Special Project RAISA, sub-project N. 1 Paper N.     

充分发挥科技资料在防震减灾事业中的作用

为了充分发挥科技资料在防震减灾事业中的作用,就如何改进地震科技资料的管理方式、提高地震科技资料的管理水平、为防震减灾一线科研人员提供最满意的服务进行了论述.     

Appreciating Ecological Complexity: Habitat Contours as a Conceptual Landscape Model

Abstract:  Organisms respond to their surroundings at multiple spatial scales, and different organisms respond differently to the same environment. Existing landscape models, such as the "fragmentation model" (or patch-matrix-corridor model) and the "variegation model," can be limited in their ability to explain complex patterns for different species and across multiple scales. An alternative approach is to conceptualize landscapes as overlaid species-specific habitat contour maps. Key characteristics of this approach are that different species may respond differently to the same environmental conditions and at different spatial scales. Although similar approaches are being used in ecological modeling, there is much room for habitat contours as a useful conceptual tool. By providing an alternative view of landscapes, a contour model may stimulate more field investigations stratified on the basis of ecological variables other than human-defined patches and patch boundaries. A conceptual model of habitat contours may also help to communicate ecological complexity to land managers. Finally, by incorporating additional ecological complexity, a conceptual model based on habitat contours may help to bridge the perceived gap between pattern and process in landscape ecology. Habitat contours do not preclude the use of existing landscape models and should be seen as a complementary approach most suited to heterogeneous human-modified landscapes.     

GIS地形分析技术在小范围土地利用规划中的应用

地形特征通过对光、水、热三个基本要素的重新分配影响了农业生产条件。山区土地利用规划需要着重考虑地形因素的影响。本文研究了元阳县杨系河流域海拔、坡度、坡向与该地区农业生产条件的关系，并探讨在ＧＩＳ支持下，在流域土地利用规划中以地形为主导因子进行分析的应用方法。     

THE ENVIRONMENTAL DISPLAY MANAGER: A TOOL FOR WATER QUALITY DATA INTEGRATION1

ABSTRACT: The Environmental Display Manager, EDM, is a development system on an IBM 3090 mainframe at the U.S. EPA National Computer Center in Research Triangle Park, North Carolina. EDM provides mapping, display, analysis support, and information management capabilities to workstations located across the United States, and connected to EPA through federal, state, academic, and private communications networks. Through interactive software, EDM can quickly support analyses, create maps and graphics, and generate reports that integrate millions of pieces of environmental data. The concept of EDM is to provide easy access to environmental information, to provide automated environmental analyses and reports, and then to provide data, graphics, images, text, and documents that can be used by numerous output devices, software packages, and computers. The mapping cumponent works with an electronic version of the 54,000 7.5 minute quad sheets of the U.S. Geological Survey. The software also works with a hydrographic data base of the surface waters of the United States. With the maps, a user can look at the rivers in any state, can zoom in on a small pond, and can overlay and identify particular features such as industrial waste dischargers and factories. The hydrography allows routing for modeling programs, identification of upstream and downstream components, and linkage of environmental features associated with surface waters. Alternatively, users can query data based on latitude/longitude, city name, EPA permit number, state agency and station code, river name or number, and river cataloging unit. The maps can be overlaid with roads and environmental sites such as: municipal and industrial dischargers, Superfund sites, public drinking water supplies, water quality monitoring stations, stream gages, and city locations. Retrievals from related systems can be performed for selected sites creating graphics showing water quality trends, discharge monitoring reports, and permit discharge limits.     

Predicting the distributions of marine organisms at the global scale

We present and evaluate AquaMaps, a presence-only species distribution modelling system that allows the incorporation of expert knowledge about habitat usage and was designed for maximum output of standardized species range maps at the global scale. In the marine environment there is a significant challenge to the production of range maps due to large biases in the amount and location of occurrence data for most species. AquaMaps is compared with traditional presence-only species distribution modelling methods to determine the quality of outputs under equivalently automated conditions. The effect of the inclusion of expert knowledge to AquaMaps is also investigated. Model outputs were tested internally, through data partitioning, and externally against independent survey data to determine the ability of models to predict presence versus absence. Models were also tested externally by assessing correlation with independent survey estimates of relative species abundance. AquaMaps outputs compare well to the existing methods tested, and inclusion of expert knowledge results in a general improvement in model outputs. The transparency, speed and adaptability of the AquaMaps system, as well as the existing online framework which allows expert review to compensate for sampling biases and thus improve model predictions are proposed as additional benefits for public and research use alike.     

Assessment of groundwater quality by means of self-organizing maps: application in a semiarid area

The Kohonen neural network was applied to hydrochemical data from the Detritic Aquifer of the Lower Andarax, situated in a semiarid zone in the southeast of Spain. An activation map was obtained for each of the sampling points, in which the spatial distribution of the activated neurons indicated different water qualities. To extract the information contained in the activation maps, they were divided into nine quadrats. Cartesian coordinates were assigned to each quadrant (x, y), and for each sampling point, three derived variables were selected, which were assigned the values x and y of the corresponding quadrat. A classification was defined based on this simple matrix system which allows an easy and rapid means of evaluating the water quality. This assessment highlights the various processes that affect groundwater quality. The method generates output that is easier to interpret than from traditional statistical methods. The information is extracted from the activation maps without significant loss of information. The method is proposed for assessing water quality in hydrogeochemically complex areas, where large numbers of observations are made.