| Title: | A topography analysis incorporated optimization method for the selection and placement of best management practices |
| Authors: | Shen, Z., L. Chen and L. Xu |
| Year: | 2013 |
| Journal: | PLOS ONE |
| Volume (Issue): | 8(1) |
| Pages: | e54520 |
| Article ID: | |
| DOI: | 10.1371/journal.pone.0054520.t001 |
| URL (non-DOI journals): | |
| Model: | SWAT |
| Broad Application Category: | hydrologic and pollutant |
| Primary Application Category: | BMP assessment (genetic algorithm or similar optimization approach) |
| Secondary Application Category: | pollutant cycling/loss and transport |
| Watershed Description: | 47.24 km^2 sub watershed of the Yulin River, a tributary of the Yangtze River in central China |
| Calibration Summary: | |
| Validation Summary: | |
| General Comments: | |
| Abstract: | Best Management Practices (BMPs) are one of the most effective methods to control nonpoint source (NPS) pollution at a
watershed scale. In this paper, the use of a topography analysis incorporated optimization method (TAIOM) was proposed,
which integrates topography analysis with cost-effective optimization. The surface status, slope and the type of land usewere evaluated as inputs for the optimization engine. A genetic algorithm program was coded to obtain the final
optimization. The TAIOM was validated in conjunction with the Soil and Water Assessment Tool (SWAT) in the Yulin
watershed in Southwestern China. The results showed that the TAIOM was more cost-effective than traditional optimization
methods. The distribution of selected BMPs throughout landscapes comprising relatively flat plains and gentle slopes,
suggests the need for a more operationally effective scheme, such as the TAIOM, to determine the practicability of BMPs
before widespread adoption. The TAIOM developed in this study can easily be extended to other watersheds to help
decision makers control NPS pollution. |
| Language: | English |
| Keywords: | |