The Water Research Foundation, the National Corn Growers Association (NCGA), and the United Soybean Board (USB) are pleased to announce a collaborative effort to begin the expansion of the International Stormwater BMP Database to include agricultural BMPs. Improved understanding of agricultural BMP performance will lead to more informed decision making and more cost-effective solutions for managing agricultural runoff. For many watersheds, scientifically sound knowledge of both urban and agricultural BMP performance is needed to develop watershed-based approaches to reduce pollutant loading to waterbodies. The Agricultural BMP Database effort will build upon research already conducted by a variety of federal and state agencies, university researchers and others.
Development of the Agricultural BMP Database is a long-term effort. The Phase 1 effort (November 2011-August 2012) focused on gathering field performance studies from the literature, developing the agricultural BMP Database framework, identifying the initial list of BMPs, preparing the metadata fields, and developing a data entry spreadsheet.
During Phase 2 of the project (June 2013 – March 2014), an Expert Panel was convened and the recommended revisions to the draft database structure were implemented by the project team. Additional literature sources and historical databases (Virginia Tech and MANAGE) were identified and used to initially populate the database. Over 200 studies were added to the database with corn and soybeans being the most common primary crop. Conservation tillage, filter strips, nutrient management practices, drainage water management, and multiple-practice studies were the most commonly studied practices. Phase 2 was concluded with the development of a User’s Guide and preparing the final data entry spreadsheet.
The Phase 3 scope of work (2016-2017) built upon work completed during the first two project phases. The primary focus was on strengthening the initially populated database and preparing a summary report that summarizes technical findings from the database to date. The key tasks of Phase 3 included: