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ARS Home » Plains Area » Bushland, Texas » Conservation and Production Research Laboratory » Soil and Water Management Research » Research » Publications at this Location » Publication #237170
Title: Application of remote sensing based tillage mapping technique to evaluate water quality impacts of tillage management decisions in Upper White River Basin.

Author
item SHASHANK, SINGH - PURDUE UNIVERSITY
item CHAUBEY, INDRAJEET - PURDUE UNIVERSITY
item Gowda, Prasanna

Submitted to: Environmental and Water Resources Institute World Congress Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 4/15/2009
Publication Date: 5/1/2009
Citation: Shashank, S., Chaubey, I., Gowda, P. 2009. Application of remote sensing based tillage mapping technique to evaluate water quality impacts of tillage management decisions in Upper White River Basin. Environmental and Water Resources Institute World Congress Proceedings.May 17-21, 2009, Kansas City, Missouri. p.4392-4399. 2009 CDROM

Interpretive Summary: Tillage information is crucial in environmental and watershed modeling as it has a direct impact on soil and water quality. In this study, a set of remote sensing based tillage mapping models were evaluated for their ability to identify contrasting tillage practices in an agricultural watershed in Indiana. Results indicated that tillage information derived from remote sensing data may be useful as input to water quality simulation models for estimating nonpoint source pollution.

Technical Abstract: Tillage practices directly impact runoff processes, soil erosion, and water quality in agricultural watersheds. Consequently, environment models require tillage information for water quality modeling; but often this information is not available at required spatial and temporal scales. A remote sensing approach facilitates tillage mapping at a larger scale than conventional surveying methods. Models based on remote sensing can classify contrasting tillage practices with accuracy of 80% to 92%. The objective of this study was to use reflectance based logistic regression models to classify contrasting tillage practices in agricultural watersheds using a Landsat Thematic Mapper imagery. This study was conducted in the Upper White River Basin (7,000 km**2) located in central Indiana, an agricultural watershed with corn-soybean rotation. A single tillage practice can have different levels of impact at different slope classes within the watershed. Therefore, the tillage system information is coupled with the slope classes within a watershed using geographic information system (GIS). This can identify the optimum slope class for a tillage system for minimum sediment loss. The tillage data derived will be used as input in the Soil and Water Assessment Tool (SWAT) model to evaluate the distribution of tillage practices and their impacts on runoff, sediment, and pollutant losses.