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Soil Biology Primer
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Soil Conservation Service Curve Number (SCS-CN) Methodology
The Soil Conservation Service (SCS) curve number (CN) method is one of the most popular methods for computing the runoff volume from a rainstorm. It is popular because it is simple, easy to understand and apply, and stable, and accounts for most of the runoff producing watershed characteristics, such as soil type, land use, hydrologic condition, and antecedent moisture condition. The SCS-CN method was originally developed for its use on small agricultural watersheds and has since been extended and applied to rural, forest and urban watersheds. Since the inception of the method, it has been applied to a wide range of environments. In recent years, the method has received much attention in the...
Guidelines for Soil Description
Soils are affected by human activities, such as industrial, municipal and agriculture, that often result in soil degradation and loss. In order to prevent soil degradation and to rehabilitate the potentials of degraded soils, reliable soil data are the most important prerequisites for the design of appropriate land-use systems and soil management practices as well as for a better understanding of the environment. The availability of reliable information on soil morphology and other characteristics obtained through examination and description of the soil in the field is essential, and the use of a common language is of prime importance. These guidelines, based on the latest internationally accepted systems and classifications, provide a complete procedure for soil description and for collecting field data. To help beginners, some explanatory notes are included as well as keys based on simple test and observations.--Publisher's description.
Digital Soil Mapping
Digital Soil Mapping is the creation and the population of a geographically referenced soil database. It is generated at a given resolution by using field and laboratory observation methods coupled with environmental data through quantitative relationships. Digital soil mapping is advancing on different fronts at different rates all across the world. This book presents the state-of-the art and explores strategies for bridging research, production, and environmental application of digital soil mapping.It includes examples from North America, South America, Europe, Asia, and Australia. The chapters address the following topics: - evaluating and using legacy soil data - exploring new environmental covariates and sampling schemes - using integrated sensors to infer soil properties or status - innovative inference systems predicting soil classes, properties, and estimating their uncertainties - using digital soil mapping and techniques for soil assessment and environmental application - protocol and capacity building for making digital soil mapping operational around the globe.
Predicting Soil Erosion by Water
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.
