Advanced Tools for Studying Soil Erosion Processes: Erosion Modelling, Soil Redistribution Rates, Advanced Analysis, and Artificial Intelligence presents the most recent technologies and methods in quantifying soil erosion, focusing on quantitative geomorphological assessment, soil erosion interaction with natural and man-made hazards using new methods, and technologies that employ GIS, remote sensing (RS), spatial modeling, and machine learning tools as an effective plan for decision-makers and land users.Organized into three parts: 1) Erosion processes and impacts, 2) Advanced computing techniques to quantify soil erosion, and 3) Methods of Soil Erosion, this book will be an invaluable source material for researchers, academicians, graduate and undergraduate students, and professionals in the field of geology, specifically focused on geographic information systems and remote sensing. - Provides an overview of soil erosion and its interaction with natural hazards (i.e., geological, hydrological, meteorological, and biological) - Introduces advanced tools and technologies in soil erosion management - Presents future soil erosion opportunities and challenges

- Problem der Bodenerosion wird hier mit ganzheitlichem Ansatz besprochen - Ursachen und Auswirkungen der Erosion werden in sozialökonomischen Kontext gebracht - ausführliche Angaben über Methoden der Verfolgung von Bodenerosion (GPS, GIS, Erdfernerkundung) - mit einer gut verständlichen allgemeinen Einführung in Bodenkunde und Hydrologie

Provides a unique and comprehensive assessment of soil erosion throughout Europe, an important aspect to control and manage if landscapes are to be sustained for the future. Written in two parts, Soil Erosion in Europe primarily focuses on current issues, area specific soil erosion rates, on and off-site impacts, government responses, soil conservation measures, and soil erosion risk maps. The first part overviews the erosion processes and the problems encountered within each European country, whilst the second section takes a cross-cutting theme approach. Based on an EU-funded project that has been running for four years with erosion scientists from 19 countries Reviews contemporary erosion processes and rates on arable and rangeland in Europe Looks at current issues, such as socio-economic drivers, controlling factors specific to the country and changes in land use

The movement of sediment and associated pollutants over thelandscape and into water bodies is of increasing concern withrespect to pollution control, prevention of muddy floods andenvironmental protection. In addition, the loss of soil on site hasimplications for declining agricultural productivity, loss ofbiodiversity and decreased amenity and landscape value. The fate ofsediment and the conservation of soil are important issues for landmanagers and decision-makers. In developing appropriate policiesand solutions, managers and researchers are making greater use oferosion models to characterise the processes of erosion and theirinteraction with the landscape. A study of erosion requires one to think in terms ofmicroseconds to understand the mechanics of impact of a singleraindrop on a soil surface, while landscapes form over periods ofthousands of years. These processes operate on scales ofmillimetres for single raindrops to mega-metres for continents.Erosion modelling thus covers quite a lot of ground. This bookintroduces the conceptual and mathematical frameworks used toformulate models of soil erosion and uses case studies to show howmodels are applied to a variety of purposes at a range of spatialand temporal scales. The aim is to provide land managers and otherswith the tools required to select a model appropriate to the typeand scale of erosion problem, to show what users can expect interms of accuracy of model predictions and to provide anappreciation of both the advantages and limitations of models.Problems covered include those arising from agriculture, theconstruction industry, pollution and climatic change and range inscale from farms to small and large catchments. The book will alsobe useful to students and research scientists as an up-to-datereview of the state-of-art of erosion modelling and, through aknowledge of how models are used in practice, in highlighting thegaps in knowledge that need to be filled in order to develop evenbetter models.

Introduction and history; Rainfall-runoff erosivity factor (R); Soil erodibility factor (K); Slope length and steepness factors (LS); Cover-management factor (C); Support practice factor (P); RUSLE user guide; Coversion to SI metric system; Calculation of EI from recording-raingage records; Estimating random roughness in the field; Parameter values for major agricultural crops and tillage operations.

For nearly a century, scientific advances have fueled progress in U.S. agriculture to enable American producers to deliver safe and abundant food domestically and provide a trade surplus in bulk and high-value agricultural commodities and foods. Today, the U.S. food and agricultural enterprise faces formidable challenges that will test its long-term sustainability, competitiveness, and resilience. On its current path, future productivity in the U.S. agricultural system is likely to come with trade-offs. The success of agriculture is tied to natural systems, and these systems are showing signs of stress, even more so with the change in climate. More than a third of the food produced is unconsumed, an unacceptable loss of food and nutrients at a time of heightened global food demand. Increased food animal production to meet greater demand will generate more greenhouse gas emissions and excess animal waste. The U.S. food supply is generally secure, but is not immune to the costly and deadly shocks of continuing outbreaks of food-borne illness or to the constant threat of pests and pathogens to crops, livestock, and poultry. U.S. farmers and producers are at the front lines and will need more tools to manage the pressures they face. Science Breakthroughs to Advance Food and Agricultural Research by 2030 identifies innovative, emerging scientific advances for making the U.S. food and agricultural system more efficient, resilient, and sustainable. This report explores the availability of relatively new scientific developments across all disciplines that could accelerate progress toward these goals. It identifies the most promising scientific breakthroughs that could have the greatest positive impact on food and agriculture, and that are possible to achieve in the next decade (by 2030).

This new edition of Soil Erosion Research Methods retains the themes and layout of the first edition. However, most chapters have been revised and some additional chapters have been added. There are new chapters on modeling wind and water erosion. Extensive revisions and updating have been done in chapters dealing with assessment of erosivity and erodibility, erosion, crop productivity, measuring sediment yield from river basins and field plot techniques. There is extensive updating of current statistics on the global magnitude of soil erosion by water and wind and on denudation rates. Several new authors have made significant improvements in revising and updating available information.

Remote Sensing of Soil and Land Surface Processes: Monitoring, Mapping, and Modeling couples artificial intelligence and remote sensing for mapping and modeling natural resources, thus expanding the applicability of AI and machine learning for soils and landscape studies and providing a hybridized approach that also increases the accuracy of image analysis. The book covers topics including digital soil mapping, satellite land surface imagery, assessment of land degradation, and deep learning networks and their applicability to land surface processes and natural hazards, including case studies and real life examples where appropriate. This book offers postgraduates, researchers and academics the latest techniques in remote sensing and geoinformation technologies to monitor soil and surface processes. - Introduces object-based concepts and applications, enhancing monitoring capabilities and increasing the accuracy of mapping - Couples artificial intelligence and remote sensing for mapping and modeling natural resources, expanding the applicability of AI and machine learning for soils and sediment studies - Includes the use of new sensors and their applications to soils and sediment characterization - Includes case studies from a variety of geographical areas

Degradation of agricultural catchments due to water erosion is a major environmental threat at the global scale, with long-lasting destructive consequences valued at tens of billions of dollars per annum. Eroded soils lead to reduced crop yields and deprived agroecosystem’s functioning through, for example, decreased water holding capacity, poor aeration, scarce microbial activity, and loose soil structure. This can result in reduced carbon sequestration, limited nutrient cycling, contamination of water bodies due to eutrophication, low protection from floods and poor attention restoration—consequences that go far beyond the commonly modelled soil loss and deposition budgets. This book demonstrates, using data from the Harod catchment in northern Israel, how cutting-edge geoinformatics, data science methodologies and soil health indicators can be used to measure, predict, and regulate these major environmental hazards. It shows how these approaches are used to quantify—in time and space—the effect of water erosion not only on the soil layer, soil minerals, and soil loss, but also on the wide-range of services that agricultural ecosystems might supply for the benefit and well-being of humans. The algorithms described in this book play a major role in this paradigm shift and they include, for example, extraction of photogrammetric DEMs from drone's data, advanced drainage structure calculations, fuzzy process-based modelling and spatial topographic threshold computations, multicriteria analyses and expert-based systems development using analytic hierarchal processes, innovative data-mining and machine learning tools, autocorrelation and interpolation of soil health, physically-based soil evolution models, spatial decision support systems and many more.

The Universal Soil Loss Equation (USLE) enables planners to predict the average rate of soil erosion for each feasible alternative combination of crop system and management practices in association with a specified soil type, rainfall pattern, and topography. When these predicted losses are compared with given soil loss tolerances, they provide specific guidelines for effecting erosion control within specified limits. The equation groups the numerous interrelated physical and management parameters that influence erosion rate under six major factors whose site-specific values can be expressed numerically. A half century of erosion research in many States has supplied information from which at least approximate values of the USLE factors can be obtained for specified farm fields or other small erosion prone areas throughout the United States. Tables and charts presented in this handbook make this information readily available for field use. Significant limitations in the available data are identified.