thumbnail

Sensitivity analysis, calibration, and testing of a distributed hydrological model using error-based weighting and one objective function

Water Resources Research

By:
, , ,
DOI: 10.1029/2008WR007255

Links

Abstract

We evaluate the utility of three interrelated means of using data to calibrate the fully distributed rainfall-runoff model TOPKAPI as applied to the Maggia Valley drainage area in Switzerland. The use of error-based weighting of observation and prior information data, local sensitivity analysis, and single-objective function nonlinear regression provides quantitative evaluation of sensitivity of the 35 model parameters to the data, identification of data types most important to the calibration, and identification of correlations among parameters that contribute to nonuniqueness. Sensitivity analysis required only 71 model runs, and regression required about 50 model runs. The approach presented appears to be ideal for evaluation of models with long run times or as a preliminary step to more computationally demanding methods. The statistics used include composite scaled sensitivities, parameter correlation coefficients, leverage, Cook's D, and DFBETAS. Tests suggest predictive ability of the calibrated model typical of hydrologic models. Copyright 2009 by the American Geophysical Union.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Sensitivity analysis, calibration, and testing of a distributed hydrological model using error-based weighting and one objective function
Series title:
Water Resources Research
DOI:
10.1029/2008WR007255
Volume
45
Issue:
6
Year Published:
2009
Language:
English
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Water Resources Research