The Water Environment Research Foundation (WERF) and the National Corn Growers Association (NCGA) have initiated a collaborative effort to develop an agricultural BMP performance database similar to the well-established International Stormwater BMP Database for urban BMPs.
An improved understanding of agricultural BMP performance is expected to lead to more informed decision-making and more cost-effective solutions for managing agricultural runoff. For many watersheds, scientifically sound knowledge of agricultural BMP (AgBMP) performance is needed to develop watershed-based approaches to reduce pollutant loading to waterbodies. The WERF/NCGA Agricultural BMP Database (AgBMPDB) effort builds upon research already conducted by a variety of federal and state agencies, university researchers, and others to provide a highly organized and user friendly BMP database specific to agricultural environments. The overall objective of this project is to create a centralized location where consistently collected and reported on AgBMP design, performance and cost data may be collected, summarized and made accessible for others via the www.bmpdatabase.org web interface. The intent is for the AgBMPDB to be populated by a collection of BMP field test data that can be linked to environmental conditions, design parameter and performance data.
Geosyntec (in association with Wright Water Engineers) has been performing a comprehensive literature review of preexisting agricultural BMP water quality models along with existing agricultural BMP databases and studies, such that the design of the AgBMPDB could capture and include the type of information and design parameters common to agricultural studies. This effort will result in a comprehensive set of recommended AgBMP monitoring and reporting protocols. Additionally, a conceptual database design was developed with a hierarchical data structure, which allows database queries to be completed based on site characteristics and agricultural BMP design factors. The database structure organizes BMP studies into multiple relational tables including study location, study configuration, monitoring stations, monitoring costs, monitoring events, monitoring data, and the specific practices utilized within each study. The AgBMPDB structure is unique in that it highlights practices that are common within agriculture, like conservation tillage, cover crops, and irrigation water management, which do not necessarily provide discrete upstream and downstream points for performance assessment.
As part of this ongoing project we have: conducted literature review to compile studies appropriate for inclusion in the AgBMPDB; identified agricultural BMP types and design and monitoring parameters needed to evaluate performance; developed an Excel spreadsheet that summarizes the BMP types and reporting parameters that will enable standardized entry of agricultural BMP studies; and developed an AgBMPDB portal on the BMP Database website (www.bmpdatabase.org) to provide project progress updates, tools and findings for public use.