Using ArcGIS hydrologic modeling and LiDAR digital elevation data to evaluate surface runoff interception performance of riparian vegetative filter strip buffers in central Iowa

Autor: Manish Shrivastav, David F. Webber, Steven K. Mickelson
Rok vydání: 2019
Předmět:
Zdroj: Journal of Soil and Water Conservation. 75:123-129
ISSN: 1941-3300
0022-4561
DOI: 10.2489/jswc.75.1.123
Popis: The Midwest is well known for agriculture, and Iowa is a leader in corn (Zea mays L.) and soybean (Glycine max [L.] Merr.) production. Fertilizers and chemical pesticides used to increase crop production can adversely affect the soil and water health. Midwest farmers also produce livestock and graze cattle on pastureland that can lead to excessive surface runoff and soil erosion. Establishing vegetative filter strips (VFSs) along the edge of farmland is one of the best management practices (BMPs) to reduce nutrient and sediment loss. However, studies have revealed that the classic VFS design along the length of an agricultural field does not adequately address nonuniform flow through the buffer. New designs are being researched to increase the efficiency of the VFS. In order to accurately implement new design strategies, the runoff flowpaths into the VFS need to be accurately modeled. This research assesses the performance of existing established VFS buffers of selected sites by modeling and analyzing the flow accumulation from the field into the VFS using geographic information system (GIS) and light detection and ranging (LiDAR) derived digital elevation model (DEM) 5 × 5 m data. This study also employed the new coefficient of flow interception (CFI) approach that improves the process of identifying areas where flow is concentrated and designing more efficient filter strips to account for concentrated runoff. In this study, the performance of VFS in three sites was evaluated by developing and using the CFI. Among the three sites, site 1 had very poor efficiency and no flow passes through the VFS, site 2 had low efficiency, and site 3 had excellent efficiency.
Databáze: OpenAIRE