Long-Term Oxbow Lake Trophic State under Agricultural Best Management Practices

A key principle of agricultural best management practices (BMPs) is to improve water quality by reducing agricultural-sourced nutrients and associated eutrophication. Long-term (1998–2016) lake summer trophic state index (TSI) trends of an agricultural watershed with agricultural best management practices (BMPs) were assessed. Structural BMPs included vegetative buffers, conservation tillage, conservation reserve, a constructed wetland, and a sediment retention pond. TSI included Secchi visibility (SD), chlorophyll a (Chl), total phosphorus (TP), and total nitrogen (TN). Summer TSI 1977 was >80 in 1998–1999 (hypertrophic) and decreased over the first 10 years to TSI 1977 ≈ 75 (eutrophic). TSI 1977 decrease and changing TSI deviations coincided with vegetative buffers, conservation tillage, and conservation reserve. The TSI(SD) decrease (>90 to <70) coincided with vegetative buffers and TSI(TP) decrease (>90 to <75) coincided primarily with conservation tillage and the sediment retention pond. TSI(Chl) increase (<60 to >70) coincided with conservation tillage and vegetative buffer. Results indicate watershed-wide BMPs can modestly decrease summer trophic state through increased water transparency and decreased TP, but these changes are off-set by increases in chlorophyll a to reach a new stable state within a decade. Future research should assess algal nutrient thresholds, internal nutrient loading, and climate change effects.

Assessing Surface Flowpath Interception by Vegetative Buffers Using ArcGIS Hydrologic Modeling and Geospatial Analysis for Rock Creek Watershed in Central Iowa

Nonpoint-source (NPS) pollution is a major cause of surface water quality degradation due to the transport of chemicals, nutrients, and sediments into lakes and streams. Vegetative buffers comprise several effective landscape best management practices (BMPs) that include vegetative filter strips (VFS) and grassed waterways. However, some BMPs are less effective due to concentrated surface flow, improper cropland-to-VFS area ratios, and surface flowpaths that partially or completely bypass vegetative buffers. The overall objective of this study was to quantify the accuracy of simulated flowpaths relative to observed and global positioning system (GPS)-assisted ground-truthed surface flowpaths for improved placement of VFS and other vegetative buffers to effectively intercept surface runoff. This study was conducted on three research sites in Rock Creek watershed in central Iowa. Geographic information system (GIS) software was used for flowpath hydrologic modeling and geospatial map comparison analysis. Digital elevation model (DEM) datasets were used for flowpath simulation and included internet-available USGS 30 m × 30 m grid (typically used to design and site VFS buffers) and light detection and ranging (LiDAR) 5 m × 5 m grid DEMs. Results from this study indicate that the LiDAR 5 m × 5 m DEM generated significantly more accurate simulated flowpaths than the USGS 30 m × 30 m DEM. These results quantitatively underscore the efficacy of using high-resolution LiDAR DEM data to more accurately determine how well surface flowpaths are intercepted by VFS and other vegetative buffers. These results also demonstrate the benefits of coupling high-resolution aerial imagery with quantitative geospatial map comparison data to improve visualization and comparison of field-scale and watershed-scale hydrologic and terrestrial attributes. Ultimately, the results and procedures from this study will be applied to the development of a novel cloud-based, user-interactive, virtual-reality decision support (DS) tool that can be used to remotely assess hydrologic landscape conditions, prescribe improvements to existing BMPs, and determine new sites for enhanced BMP placement and functionality within a high-resolution 3-D imagery environment. Keywords: ArcGIS, Best management practices (BMPs), Decision support (DS) tool, Digital elevation model (DEM), Geospatial analysis, Light detection and ranging (LiDAR), Nonpoint-source (NPS) pollution, Surface runoff, Vegetative filter strip (VFS), Watershed hydrol