Title: Relating Herbicide Loadings to Satellite-Derived Land Use on Watersheds with Runoff-Prone Soils Authors
|Jang, Gab-Sue - CHUNGNAM DEV INST S KOREA|
|Wang, Cuizhen - UNIVERSITY OF MISSOURI|
Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: June 15, 2006
Publication Date: October 11, 2006
Citation: Jang, G., Sudduth, K.A., Lerch, R.N., Sadler, E.J., Wang, C. 2006. Relating Herbicide Loadings to Satellite-Derived Land Use on Watersheds with Runoff-Prone Soils [abstract]. Managing Agricultural Landscapes for Environmental Quality, SWCS Meeting, October 11-13, 2006, Kansas City, Missouri. p. 65. Technical Abstract: Water quality of a stream can be affected by the fraction and geographic placement of various land uses, including crop types, within its watershed boundary. Because different herbicides, and different application rates, are used on different crops, the distribution of crop types within a watershed may significantly impact herbicide loadings measured at the watershed outlet. The purpose of this study was to investigate the relationship of crop type and land use, as determined from satellite imagery, to herbicide loadings for several sub-basins of the Salt River, a CEAP watershed in northeast Missouri. Landsat images obtained multiple times during the 1997 growing season were used to estimate land cover and crop types in the watershed. NOAA AVHRR data and ground truth information were used as auxiliary data in the classification process. Water samples were collected at the outlets of seven sub-basins during the period of maximum herbicide transport, from April 15 through July 15. Samples were analyzed in the laboratory for six herbicides commonly used on corn, soybean, and grain sorghum. Regression analysis was used to relate the fraction of each sub-basin in each crop type and other land uses to the measured herbicide loading. Results were also interpreted with respect to the relative placement of the various land uses within each sub-basin. The results of this study show that land use information estimated from satellite imagery may help to interpret variations in stream water quality.