Published In
Water Resources Research
Document Type
Article
Publication Date
8-1-2006
Subjects
Error analysis (Mathematics) -- Applications to hydrology, Streamflow -- Mathematical models
Abstract
The aim of this paper is to foster the development of an end-to-end uncertainty analysis framework that can quantify satellite-based precipitation estimation error characteristics and to assess the influence of the error propagation into hydrological simulation. First, the error associated with the satellite-based precipitation estimates is assumed as a nonlinear function of rainfall space-time integration scale, rain intensity, and sampling frequency. Parameters of this function are determined by using high-resolution satellite-based precipitation estimates and gauge-corrected radar rainfall data over the southwestern United States. Parameter sensitivity analysis at 16 selected 5ø ? 5ø latitude-longitude grids shows about 12?16% of variance of each parameter with respect to its mean value. Afterward, the influence of precipitation estimation error on the uncertainty of hydrological response is further examined with Monte Carlo simulation. By this approach, 100 ensemble members of precipitation data are generated, as forcing input to a conceptual rainfall-runoff hydrologic model, and the resulting uncertainty in the streamflow prediction is quantified. Case studies are demonstrated over the Leaf River basin in Mississippi. Compared with conventional procedure, i.e., precipitation estimation error as fixed ratio of rain rates, the proposed framework provides more realistic quantification of precipitation estimation error and offers improved uncertainty assessment of the error propagation into hydrologic simulation. Further study shows that the radar rainfall-generated streamflow sequences are consistently contained by the uncertainty bound of satellite rainfall generated streamflow at the 95% confidence interval.
DOI
10.1029/2005WR004398
Persistent Identifier
http://archives.pdx.edu/ds/psu/8324
Citation Details
Hong, Y., K. Hsu, H. Moradkhani, and S. Sorooshian (2006), Uncertainty quantification of satellite precipitation estimation and Monte Carlo assessment of the error propagation into hydrologic response, Water Resour. Res., 42, W08421.
Description
This is the publisher's final pdf. Originally published in Water Resources Research (http://www.agu.org/journals/wr/) and is copyrighted by American Geophysical Union (http://www.agu.org/)