Abstract
Watersheds are complex systems due to their internal spatial connections and their coupled hydrological and biochemical processes. Understanding their responses to a particular stressor requires a holistic approach that quantifies the complex spatial and temporal linkages between them. Anthropogenic stressors are of main importance in highly altered watersheds where their main processes are determined by the implementation of Watershed Management Practices (WMP). The objective of this study was to simulate the impacts of WMP on the stream water quality in the Upper Sangamon Watershed (USW), an agricultural watershed in Central Illinois that is greatly impacted by non-point source pollution and high sediment load. A physically-based hydrologic model, MIKE SHE, was used to simulate the response of the watershed to different WMP. Preliminary results study suggested that reduction in Nitrogen-Nitrate load was not controlled by the location of the WMP in the watershed but rather by the amount of area they cover. Nitrogen-Nitrate load contribution from tile drains was found to be significantly greater than that from the overland one. Furthermore, WMP that are structural in nature such as bioreactors, wetlands, and drainage water management might be necessary to remove Nitrogen load from tile drainage. Considering the spatial and temporal aspects in WMP evaluation can lead to a cost-effective analysis of their tradeoffs and can provide environmental managers the necessary guidelines for focus implementation of conservation and managerial schemes.
Original language | English (US) |
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DOIs | |
State | Published - 2017 |
Event | 2017 ASABE Annual International Meeting - Spokane, United States Duration: Jul 16 2017 → Jul 19 2017 |
Other
Other | 2017 ASABE Annual International Meeting |
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Country/Territory | United States |
City | Spokane |
Period | 7/16/17 → 7/19/17 |
Keywords
- Hydrology
- Mike-she
- Water management practices
- Water quality
- Watershed model
ASJC Scopus subject areas
- Bioengineering
- Agronomy and Crop Science