Demasking the integrated information of discharge: Advancing sensitivity analysis to consider different hydrological components and their rates of change
AffiliationUniv Arizona, Dept Hydrol & Atmospher Sci
MetadataShow full item record
PublisherAMER GEOPHYSICAL UNION
CitationDemasking the integrated information of discharge: Advancing sensitivity analysis to consider different hydrological components and their rates of change 2016, 52 (11):8724 Water Resources Research
JournalWater Resources Research
Rights© 2016. American Geophysical Union. All Rights Reserved.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at email@example.com.
AbstractDischarge as an integrated representation of all hydrological processes is the most common response variable used in sensitivity analyses. However, due to overlaying effects of all hydrological processes, the sensitivity signal of certain parameters to discharge can be masked. A more informative form of sensitivity analysis can be achieved by investigating how parameter sensitivities are related to individual modeled hydrological components. In our study, the TEDPAS (TEmporal Dynamics of PArameter Sensitivity) methodology is used to calculate daily sensitivities to modeled hydrological components and to detect temporal variations in dominant parameters. As a further enhancement to consider both magnitude and dynamics, temporal variations in parameter dominance are analyzed, both for magnitudes and rates of change of hydrological components. For this purpose, regime curves for parameter sensitivities are constructed. The results demonstrate that sensitivities of parameters increase when using the corresponding hydrological component instead of discharge as response variable. For each hydrological component, seasonal patterns of parameter dominance are detected using both magnitude and rate of change as response variable. Major differences are detected for certain capacity parameters, which are less pronounced using rates of change. Overall, we show that disentangling the diagnostic information hidden in the integrated signal of discharge can lead to a more informative signal regarding the sensitivity of hydrological components. Such advancements in sensitivity analysis can lead to a better understanding of how model parameters control the individual hydrological components in time.
Note6 month embargo; First published: 17 November 2016
VersionFinal published version
SponsorsDeutsche Forschungsgemeinschaft (DFG) [GU 1466/1-1]; CAWa (Central Asian Water) project [AA7090002]; German Federal Foreign Office, German Water Initiative for Central Asia ("Berlin Process"); Australian Research Council through the Centre of Excellence for Climate System Science [CE110001028]; EU [INCO-20011-7.6, 294947]