Literature DB >> 21509516

Geospatial approaches to characterizing agriculture in the Chincoteague Bay subbasin.

Frederick W Kutz1, John M Morgan, Jeremy Monn, Chad P Petrey.   

Abstract

Most agricultural information is reported by government sources on a state or county basis. The purpose of this study was to demonstrate use of geospatial data, the 2002 Agricultural Cropland Data Layer (CDL) for the mid-Atlantic region, to characterize agricultural, environmental, and other scientific parameters for the Chincoteague Bay subbasin using geographic information systems. This study demonstrated that agriculture can be characterized accurately on subbasin and subwatershed bases, thus complimenting various assessment technologies. Approximately 28% of the dry land of the subbasin was cropland. Field corn was the largest crop. Soybeans, either singly or double-cropped with wheat, were the second most predominant crop. Although the subbasin is relatively small, cropping practices in the northern part were different from those in the southern portion. Other crops, such as fresh vegetables and vegetables grown for processing, were less than 10% of the total cropland. A conservative approximation of the total pesticide usage in the subbasin in 2002 was over 277,000 lbs of active ingredients. Herbicides represented the most frequently used pesticides in the subbasin, both in number (17) and in total active ingredients (over 261,000 lbs). Ten insecticides predominated in the watershed, while only small quantities of three fungicides were used. Total pesticide usage and intensity were estimated using the CDL. Nutrient inputs to cropland from animal manure, chemical fertilizer, and atmospheric deposition were modeled at over 30 million pounds of nitrogen and over 7 million pounds of phosphorous. Crops under conservation tillage had the largest input of both nutrients.

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Year:  2011        PMID: 21509516     DOI: 10.1007/s10661-011-1994-x

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


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