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This book provides a comprehensive examination of the various aspects of SDSS evolution, components, architecture, and implementation. Integrating research from a variety of disciplines, it supplies a complete overview of SDSS technologies and their application. This groundbreaking reference provides thorough coverage of the roots of SDSS. It explains the core principles of SDSS, how to use them in various decision making contexts, and how to design and develop them using readily available enabling technologies and commercial tools.
Published by the American Geophysical Union as part of the Geophysical Monograph Series, Volume 108. Non-point source (NPS) pollution in the vadose zone (simply defined as the layer of soil extending from the soil surface to the groundwater table) is a global environmental problem. Characteristically, NPS pollutants are widespread and occasionally ubiquitous in extent, thus making remediation efforts difficult and complex; have the potential for maintaining a relatively long active presence in the global ecosystem; and may result in long?]term, chronic health effects in humans and other life forms. Similar to other global environmental issues, the knowledge and information required to address the problem of NPS pollutants in the vadose zone cross several technological and subdisciplinary lines: spatial statistics, geographic information systems (GIS), hydrology, soil science, and remote sensing. Cooperation between disciplines and scientific societies is essential to address the problem. Evidence of such cooperation was the jointly sponsored American Geophysical Union Chapman/Soil Science Society of America (SSSA) Outreach Conference that occurred in October 1997, entitled “Applications of GIS, Remote Sensing, Geostatistics, and Solute Transport Modeling to the Assessment of Non-Point Source Pollution in the Vadose Zone.” The objective of the conference and this book, which was developed from the conference, was to explore current multidisciplinary research for assessing NPS pollution in soil and groundwater resources.
Soil degradation has serious global impacts on agronomic, economic, and sociopolitical conditions, however, statistics regarding the degree of these impacts has been largely unreliable. This book aims to standardize the methodology for obtaining reliable and objective data on soil degradation. It will also identify and develop criteria for assessing the severity of soil degradation, providing a realistic scenario of the problem.
New York City's municipal water supply system provides about 1 billion gallons of drinking water a day to over 8.5 million people in New York City and about 1 million people living in nearby Westchester, Putnam, Ulster, and Orange counties. The combined water supply system includes 19 reservoirs and three controlled lakes with a total storage capacity of approximately 580 billion gallons. The city's Watershed Protection Program is intended to maintain and enhance the high quality of these surface water sources. Review of the New York City Watershed Protection Program assesses the efficacy and future of New York City's watershed management activities. The report identifies program areas that may require future change or action, including continued efforts to address turbidity and responding to changes in reservoir water quality as a result of climate change.
The book provides comprehensive information on possible applications of remote sensing data for hydrological monitoring and modelling as well as for water management decisions. Mathematical theory is provided only as far as it is necessary for understanding the underlying principles. The book is especially timely because of new programs and sensors that are or will be realised. ESA, NASA, NASDA as well as the Indian and the Brazilian Space Agency have recently launched satellites or developed plans for new sensor systems that will be especially pertinent to hydrology and water management. New techniques are presented whose structure differ from conventional hydrological models due to the nature of remotely sensed data.
Most environmental studies are based upon data collected at fine spatial scales plots, sediments, cores, etc.. Furthermore, temporal scales of these studies have been relatively short days, weeks, months and few studies have exceeded three years duration the typical funding cycle.; Despite this history, environmental scientists are now being called upon to extrapolate findings from "plot-level" studies to broader spatial scales and from short-term studies to longer temporal scales, up to decades for questions related to long-term processes such as global warming and the rise in sea level.; The complex questions being addressed internationally require that scientists take advantage of new technologies including remote sensing, geographic information systems GIS, and powerful climatic and environmental simulation models. As more environmental scientists begin to work at these broader spatial and temporal scales, and to utilize many of the newer technologies, they are recognising a whole new class of problems.; This book aims to address the most pertinent issues, and includes a comprehensive review of selected topics, case studies, and theoretical discussions, divided into seven sections each preceded by a brief introduction.
The Encyclopedia of GIS provides a comprehensive and authoritative guide, contributed by experts and peer-reviewed for accuracy, and alphabetically arranged for convenient access. The entries explain key software and processes used by geographers and computational scientists. Major overviews are provided for nearly 200 topics: Geoinformatics, Spatial Cognition, and Location-Based Services and more. Shorter entries define specific terms and concepts. The reference will be published as a print volume with abundant black and white art, and simultaneously as an XML online reference with hyperlinked citations, cross-references, four-color art, links to web-based maps, and other interactive features.
Decision support systems (DSS) have evolved over the past four decades from theoretical concepts into real world computerized applications. DSS architecture contains three key components: knowledge base, computerized model, and user interface. DSS simulate cognitive decision-making functions of humans based on artificial intelligence methodologies (including expert systems, data mining, machine learning, connectionism, logistical reasoning, etc.) in order to perform decision support functions. The applications of DSS cover many domains, ranging from aviation monitoring, transportation safety, clinical diagnosis, weather forecast, business management to internet search strategy. By combining knowledge bases with inference rules, DSS are able to provide suggestions to end users to improve decisions and outcomes. This book is written as a textbook so that it can be used in formal courses examining decision support systems. It may be used by both undergraduate and graduate students from diverse computer-related fields. It will also be of value to established professionals as a text for self-study or for reference.