Environmental quality research in the Beasley Lake watershed, 1995 to 2007: Succession from conventional to conservation practices

Abstract

The Beasley Lake watershed (BLW), established for the Mississippi Delta Management Systems Evaluation Area project, represents the US Mississippi Delta region in the national Conservation Effects Assessment Project. The 915-ha (2,260-ac) BLW drains into an oxbow lake that has been monitored since 1995 when row crops were grown on 79% of the area, and the remaining area included a 25-ha (62-ac) lake and a 135-ha (330-ac) riparian forest. Currently, row crops account for 66.5% of the area with 12.4% enrolled in the Conservation Reserve Program. Cotton (Gossypium hirsutum L.) acreage has decreased from 63.3% to 8.9%. Historical and current research in BLW focuses on monitoring lake limnology, evaluating conservation practice effects on edge-of-field runoff, quantifying changes associated with the Conservation Reserve Program, and modeling watershed responses. Applying combinations of conservation practices can significantly reduce nonpoint source pollution. For example, converting row crops to reduced tillage and transgenic herbicide-resistant crops in BLW reduced suspended sediment (70% reduction), total phosphorus (41% reduction), and pesticide concentrations in lake water. Corresponding increases in Secchi visibility (97%) and chlorophyll a (a primary productivity indicator) likely contributed to improved fish productivity (e.g., fish weight increase comparing 1998 and 2004: Micropterus salmoides 87%, Lepomis macrochirus, 65%) during this period. Additional studies should quantify effects of individual practices and improve modeling tools for making better management decisions. The utilization of the Annualized Agricultural Non-Point Source (AnnAGNPS) model and the Riparian Ecosystem Management Model (REMM) together provides additional information on the effectiveness of conservation practices within the watershed by combining technology that assesses riparian buffer effectiveness in filtering nutrients at the field scale with the watershed water quality transport capabilities of the AnnAGNPS model.