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Title: Using available soil data to populate models to address public concerns

Author
item NEMES, ATTILA - UNIVERSITY OF MARYLAND
item Timlin, Dennis
item Pachepsky, Yakov
item Rawls, Walter

Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 6/15/2007
Publication Date: 11/4/2007
Citation: Nemes, A., Timlin, D.J., Pachepsky, Y.A., Rawls, W.J. 2007. Using available soil data to populate models to address public concerns [abstract]. ASA-CSSA-SSSA International Annual Meeting, November 4-8, 2007, New Orleans, LA. Abstract 37-7. 2007 CDROM.

Interpretive Summary:

Technical Abstract: Field and watershed scale simulation models allow different agencies worldwide to examine the impact of policies and practices on different environmental aspects. Such models usually require a large amount and variety of data as input. The hydraulic characteristics of the soil largely define the fate of nutrients and pollutants, and therefore constitute an important input to such models. However, collection of measured soil hydraulic data is often not feasible - especially if large areas of (heterogeneous) land need to be characterized. Estimation of soil hydraulic properties has been a subject of research for over 25 years. Numerous approaches have been introduced and a significant number of national and/or international scale data collections have been used for this purpose. While a significant number of studies are being conducted that estimate soil hydraulic properties, the functional testing of such estimates is a lot less explored area of research. As an example, very little is known on how, say, 5 vol. % error of field capacity estimates or 3 vol. % error in wilting point estimates will propagate in a process-based simulation model in terms of e.g. water balance, sediment yield estimates, nutrient loss estimates, etc. We highlight some typical pitfalls in the estimation of soil hydraulic properties, report a case study, and provide further ideas for advancement in functional evaluation of such estimated properties.