Demasking the integrated information of discharge: Advancing sensitivity analysis to consider different hydrological components and their rates of change

Björn Guse, Matthias Pfannerstill, Abror Gafurov, Nicola Fohrer, Hoshin Gupta

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

Discharge 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.

Original languageEnglish (US)
Pages (from-to)8724-8743
Number of pages20
JournalWater Resources Research
Volume52
Issue number11
DOIs
StatePublished - Nov 1 2016

Keywords

  • diagnostic model analysis
  • dominant modeled processes
  • model understanding
  • regime curves
  • sensitivity analysis
  • temporal dynamics in parameter sensitivity

ASJC Scopus subject areas

  • Water Science and Technology

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