Quantifying the Uncertainty of the Future Hydrological Impacts of
Climate Change: an Advanced Hierarchical Sensitivity Analysis in a Humid
Subtropical Basin, China
Abstract
The comparison and quantification of different uncertainties of future
climate change involved in the modeling of a hydrological system are
highly important for both hydrological modelers and policy-makers.
However, few studies have accurately estimated the relative importance
of different sources of uncertainty involved in climate change
predictions. In this study, an advanced hierarchical uncertainty
analysis framework incorporated with a variance-based global sensitivity
analysis, was developed to quantify different sources of uncertainty in
hydrological projections under climate change. The uncertainties
considered in this research are from greenhouse gas emission scenarios
(GGES), global climate models (GCMs), hydrological models (Xinanjiang
and variable infiltration capacity (VIC) models) and hydrological
parameters, and this new methodology was implemented in a humid
subtropical basin in southern China. The results indicated that the GCMs
and hydrological parameters (GGESs) are the main (least) contributor of
uncertainty in the discharge projections at the interannual scale. At
the intra-annual scale, GCMs contribute the largest uncertainty of the
discharge predictions during summer season, whereas the uncertainty due
to GGESs, hydrological model and parameters is generally larger in
winter. It was also found that although there is a strong temporal and
spatial variability of general sources of uncertainty, this
heterogeneity does not affect the importance of uncertainty sources.
This study provides a better understanding of the uncertainty sources in
hydrological predictions in the context of climate change. And the
uncertainty analysis framework used is mathematically rigorous and can
be applied to a wide range of climate and hydrological models with
different uncertainty sources.