Input data resolution-induced uncertainty in watershed modelling
Article first published online: 2 MAR 2011
Copyright © 2011 John Wiley & Sons, Ltd.
Volume 25, Issue 14, pages 2302–2312, 1 July 2011
How to Cite
Patil, A., Deng, Z.-Q. and Malone, R. F. (2011), Input data resolution-induced uncertainty in watershed modelling. Hydrol. Process., 25: 2302–2312. doi: 10.1002/hyp.8018
- Issue published online: 5 JUL 2011
- Article first published online: 2 MAR 2011
- Accepted manuscript online: 28 JAN 2011 05:09AM EST
- Manuscript Accepted: 20 JAN 2011
- Manuscript Received: 24 JUL 2009
- NASA (National Aeronautics and Space Administration)
- Louisiana Water Resources Research Institute
- spatial resolution;
- HSPF model
The temporal-spatial resolution of input data-induced uncertainty in a watershed-based water quality model, Hydrologic Simulation Program-FORTRAN (HSPF), is investigated in this study. The temporal resolution-induced uncertainty is described using the coefficient of variation (CV). The CV is found to decrease with decreasing temporal resolution and follow a log-normal relation with time interval for temperature data while it exhibits a power-law relation for rainfall data. The temporal-scale uncertainties in the temperature and rainfall data follow a general extreme value distribution and a Weibull distribution, respectively. The Nash-Sutcliffe coefficient (NSC) is employed to represent the spatial resolution induced uncertainty. The spatial resolution uncertainty in the dissolved oxygen and nitrate-nitrogen concentrations simulated using HSPF is observed to follow a general extreme value distribution and a log-normal distribution, respectively. The probability density functions (PDF) provide new insights into the effect of temporal-scale and spatial resolution of input data on uncertainties involved in watershed modelling and total maximum daily load calculations. This study exhibits non-symmetric distributions of uncertainty in water quality modelling, which simplify weather and water quality monitoring and reducing the cost involved in flow and water quality monitoring. Copyright © 2011 John Wiley & Sons, Ltd.