Hydrology and Earth System Sciences
www.hydrol-earth-syst-sci.net
1027-5606
1607-7938
11
4
2007
10.5194/hess-11-1373-2007
http://www.hydrol-earth-syst-sci.net/11/1373/2007/
http://www.hydrol-earth-syst-sci.net/11/1373/2007/hess-11-1373-2007.html
http://www.hydrol-earth-syst-sci.net/11/1373/2007/hess-11-1373-2007.pdf
1373
1390
2007-06-20
Spatial disaggregation of bias-corrected GCM precipitation for improved hydrologic simulation: Ping River Basin, Thailand
D. Sharma
A. Das Gupta
adg@ait.ac.th
M. S. Babel
Water Engineering and Management, Asian Institute of Technology, Thailand
Global Climate Models (GCMs) precipitation scenarios are often characterized
by biases and coarse resolution that limit their direct application for
basin level hydrological modeling. Bias-correction and spatial
disaggregation methods are employed to improve the quality of ECHAM4/OPYC
SRES A2 and B2 precipitation for the Ping River Basin in Thailand.
Bias-correction method, based on gamma-gamma transformation, is applied to
improve the frequency and amount of raw GCM precipitation at the grid nodes.
Spatial disaggregation model parameters (β,σ<sup>2</sup>),
based on multiplicative random cascade theory, are estimated using
Mandelbrot-Kahane-Peyriere (MKP) function at <i>q</i>=1 for each month.
Bias-correction method exhibits ability of reducing biases from the
frequency and amount when compared with the computed frequency and amount at
grid nodes based on spatially interpolated observed rainfall data. Spatial
disaggregation model satisfactorily reproduces the observed trend and
variation of average rainfall amount except during heavy rainfall events
with certain degree of spatial and temporal variations. Finally, the
hydrologic model, HEC-HMS, is applied to simulate the observed runoff for
upper Ping River Basin based on the modified GCM precipitation scenarios and
the raw GCM precipitation. Precipitation scenario developed with
bias-correction and disaggregation provides an improved reproduction of
basin level runoff observations.
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