Author
Lerch, Robert | |
Sadler, Edward | |
Alberts, Edward | |
Sudduth, Kenneth - Ken |
Submitted to: ASAE Annual International Meeting
Publication Type: Abstract Only Publication Acceptance Date: 5/16/2005 Publication Date: 7/18/2005 Citation: Lerch, R.N., Sadler, E.J., Alberts, E.E., Sudduth, K.A. 2005. Overview of the Missouri Conservation Effects Assessment Project [abstract] [CDROM]. American Society of Agricultural Engineers Annual International Meeting. Abstract No.052134. Interpretive Summary: Technical Abstract: The Conservation Effects Assessment Project (CEAP) will study the environmental benefits of conservation practices implemented through the 2002 Farm Bill programs. The watershed assessments component of CEAP will provide an in-depth study of environmental effects and benefits and provide additional research on conservation practices and their expected effects at the watershed scale. The Salt River/Mark Twain Lake basin is one of twelve ARS benchmark watersheds that will conduct these watershed-scale assessments. The Salt River Basin in northeastern Missouri is the source of water to the Mark Twain Lake, a 7,530-ha Army Corp of Engineers reservoir that is the major public water supplier for approximately 42,000 people. Land use is predominately agraicultural within this 6,520 sq km basin. The basin has a known and well documented history of herbicide and sediment contamination problems. Previous ARS research has shown that the naturally formed claypan soils that predominate within the basin create a barrier to percolation and promote surface runoff. This results in a high degree of vulnerability to surface transport of sediment, herbicides, and nutrients. The Missouri CEAP entails a three-fold approach to meet the goals of CEAP: 1) establish a stream water quality monitoring network ranging in scale from 73 sq km to 6,520 sq km; 2) plot and field scale studies to assess the effectiveness of existing and newly developed management practices at mitigating contaminant transport; and 3) simulation modeling to predict water quality at multiple scales, determine contaminant source areas within watersheds, and serve as a decision support aid for BMP implementation. |