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United States Department of Agriculture

Agricultural Research Service

Title: Using the NRCS National Soils Information System (NASIS) to provide soil hydraulic properties for engineering applications)

item Rawls, Walter
item Nemes, Attila
item Pachepsky, Yakov
item Saxton, Keith

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/1/2007
Publication Date: 9/1/2007
Citation: Rawls, W.J., Nemes, A., Pachepsky, Y.A., Saxton, K.E. 2007. Using the NRCS National Soils Information System (NASIS) to provide soil hydraulic properties for engineering applications. Transactions of the ASABE. 50(5):1715-1718.

Interpretive Summary: The ability of soils to retain and to transmit water is not usually measured by soil survey agencies in most countries. This impedes the use of predictive and diagnostic models with soil survey data, and requires separate soil hydraulic measurements for specific projects in soil hydrology, agronomy, meteorology, ecology, and other areas dealing with soil and water. Such measurements are not possible for large-scale projects because of labor costs and time limitations; therefore, soil hydraulic properties have to be estimated from soil survey data for such projects. To make such estimates, soil hydraulic properties have to be empirically related to soil basic properties that are measures by soil surveys. These empirical relations, however, cannot be widely applied if soil hydraulic properties and soil basic properties are measured haphazardly, are measured only in some specific project-related areas, or are measured with different methods and frequencies. The soil survey program of USDA-NRCS is unique in that it requires measurements of soil hydraulic properties along with soil basic properties. The objective of this work was to demonstrate the advantages of such soil survey and show the added value of the soil hydraulic information. The NRCS National Soils Information System (NASIS) includes 50,000 pedons. Presented results show that the hydraulic property estimates can be improved by including additional important predictors such as soil structure descriptors and topography-related indices. Having this incredibly rich database allowed us to test modern data-mining methods to radically improve soil hydraulic estimation technology and to suggest avenues of further research.

Technical Abstract: Modern agricultural, biological, and environmental engineers have a multitude of uses for soil hydraulic parameters that quantify the ability of soils and sediments to retain and transmit water. These parameters are difficult and costly to obtain, especially if large areas of land need to be characterized. An active search for the relationships of soil hydraulic parameters with readily available soil properties began in the 1970's based on compilations of data from various sources. Although substantial progress was made, further developments were hampered by the non-homogeneity of the data compendiums in terms of soil variables included, methods of their measurements, ranges of parameters, regional representation, and uncertain data quality. New opportunities to supply soil hydraulic parameters to the end users have been created by the public domain availability of soils information provided in the USDA- NRCS National Soils Information System (NASIS) (Soil Survey Staff, 2007). These data coupled with analytical advances have enhanced the development of new relationships describing soil hydraulic properties. The database currently contains analytical data for more than 50,000 pedons describing U. S. soil. The data set has provided the opportunity to study the effects of qualitative information such as soil structure and topography properties which improve our ability to estimate hydraulic soil properties. The size of the database also allowed experimentation with new data analyses methods that were not previously usable. A summary of methods which have used the NASIS dataset to predict the soil hydraulic properties for a range of scales is presented along with examples of engineering applications that use such estimates. Opportunities for future research based on the NASIS dataset are given.

Last Modified: 05/26/2017
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