The Use of Computer-Assisted Mapping Techniques to Delineate Potential Areas of Salinity Development in soils: I. A Conceptual Introduction
Authors
D. L. CorwinJ. W. Werle
J. D. Rhoades
Authors Affiliations
D. L. Corwin was a Soil Scientist with the U.S. Salinity Laboratory, USDA-ARS, Riverside, California; J. W. Werle was an Automated Mapping Consultant with James W. Werle &; Associates, Crestline, California; J. D. Rhoades was a Supervisory Soil Scientist with the U.S. Salinity Laboratory and an Adjunct Professor in the Department of Soil and Environmental Sciences, University of California, Riverside.Publication Information
Hilgardia 56(2):18-17. DOI:10.3733/hilg.v56n02p017. May 1988.
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Abstract
Several interacting factors are generally associated with the development of soil salinity on irrigated lands of the arid Southwest. Notable examples include physical edaphology (clay content and soil permeability), depth to the perched water table, salinity of the perched groundwater, and irrigation efficiency. By creating map overlays of these properties and noting the areas of intersection of specific levels or thresholds of these properties, areas can be delineated that demonstrate varying propensities for salt accumulation in the soil profile.
Utilizing an automated geographic information system (GIS), a conceptual approach to delineating areas with similar propensities for the development of soil salinity on irrigated arid-zone soils is presented. The computer mapping strategies provide an efficient and accurate means of organizing, compiling, analyzing, and displaying complex interrelated data bases that are associated with soil salinization. A map can easily be made from the data to aid in land and irrigation management decision making. The automated GIS operates on a microcomputer with enhanced graphics capabilities and requires only 32K of usable memory. The automated GIS is capable of performing mapping tasks generally reserved for larger and more expensive computer systems. The mapping system’s polygonal spatial data base maximizes spatial accuracy and produces maps that are aesthetically pleasing and easy to interpret.
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