Paper No. JAWRA-07-0137-P of the Journal of the American Water Resources Association (JAWRA). Discussions are open until April 1, 2009.
Evaluation of the MIKE SHE Model for Application in the Loess Plateau, China1
Article first published online: 8 OCT 2008
© 2008 American Water Resources Association. No claim to original U.S. government works
JAWRA Journal of the American Water Resources Association
Volume 44, Issue 5, pages 1108–1120, October 2008
How to Cite
Zhang, Z., Wang, S., Sun, G., McNulty, S. G., Zhang, H., Li, J., Zhang, M., Klaghofer, E. and Strauss, P. (2008), Evaluation of the MIKE SHE Model for Application in the Loess Plateau, China. JAWRA Journal of the American Water Resources Association, 44: 1108–1120. doi: 10.1111/j.1752-1688.2008.00244.x
- Issue published online: 8 OCT 2008
- Article first published online: 8 OCT 2008
- Received September 26, 2007; accepted May 13, 2008.
- Loess Plateau;
- MIKE SHE;
- model calibration and validation;
Abstract: Quantifying the hydrologic responses to land use/land cover change and climate variability is essential for integrated sustainable watershed management in water limited regions such as the Loess Plateau in Northwestern China where an adaptive watershed management approach is being implemented. Traditional empirical modeling approach to quantifying the accumulated hydrologic effects of watershed management is limited due to its complex nature of soil and water conservation practices (e.g., biological, structural, and agricultural measures) in the region. Therefore, the objective of this study was to evaluate the ability of the distributed hydrologic model, MIKE SHE to simulate basin runoff. Streamflow data measured from an overland flow-dominant watershed (12 km2) in northwestern China were used for model evaluation. Model calibration and validation suggested that the model could capture the dominant runoff process of the small watershed. We found that the physically based model required calibration at appropriate scales and estimated model parameters were influenced by both temporal and spatial scales of input data. We concluded that the model was useful for understanding the rainfall-runoff mechanisms. However, more measured data with higher temporal resolution are needed to further test the model for regional applications.