Submitted as: methods for assessment of models
23 May 2022
Submitted as: methods for assessment of models | 23 May 2022
Status: this preprint is currently under review for the journal GMD.

Global Sensitivity Analysis of the distributed hydrologic model ParFlow-CLM (V3.6.0)

Wei Qu1, Heye Bogena2, Christoph Schüth1, Harry Vereecken2, Zongmei Li3, and Stephan Schulz1 Wei Qu et al.
  • 1Institute of Applied Geosciences, Technische Universität Darmstadt, 64287 Darmstadt, Germany
  • 2Agrosphere (IBG-3), Forschungszentrum Jülich GmbH, Jülich, 52425, Germany
  • 3Department of Computer and Information Engineering, Xiamen University of Technology, China

Abstract. The integrated distributed hydrological model ParFlow-CLM was used to predict water and energy transport between subsurface, land surface, and atmosphere for the Stettbach headwater catchment, Germany. Based on this model, a global sensitivity analysis was performed using the Latin-Hypercube (LH) sampling strategy followed by the One-factor-At-a-Time (OAT) method to identify the most influential and interactive parameters affecting the main hydrologic processes. In total 12 parameters were evaluated including soil hydraulic properties, storage, Manning coefficient, leaf area index, stem area index, and aerodynamic resistance that characterize water and energy fluxes in soil and vegetation. In addition, the sensitivity analysis was also carried out for different slopes and meteorological conditions to test the transferability of the results to regions with other topographies and climates. Our results show that the simulated energy fluxes, i.e. latent heat flux and sensible heat flux are sensitive to the parameters such as wilting point, leaf area index, and stem area index, especially for steep slope and subarctic climate conditions. The simulated soil evaporation, plant transpiration, infiltration, and runoff, are most sensitive to soil porosity, the van Genuchten parameter n representing the soil pore size distribution, soil wilting point, and leaf area index. The subsurface soil water storage and groundwater storage are most sensitive to soil porosity, while the surface water storage was most sensitive to the soil roughness parameter. For the different slope and climate conditions, the rank order of input parameter sensitivity is consistent, but the magnitude of parameter sensitivity is very different. The strongest deviation in parameter sensitivity occurred for sensible heat flux under the different slope conditions as well as for transpiration under different climate conditions. Overall, this study provides an insight into the most important input parameters that control hydrological fluxes and how the simulated variables vary with the change in parameter values, which can improve our understanding of the key processes in the model and help us to reduce the computational demands of completing multiple simulations of expensive domains.

Wei Qu et al.

Status: open (until 18 Jul 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2022-131', Anonymous Referee #1, 21 Jun 2022 reply

Wei Qu et al.

Data sets

SA analysis data and input files Wei, Qu

Model code and software

ParFlow-CLM model Smith, Steve; Maxwell, Reed; Condon, Laura et al.

Wei Qu et al.


Total article views: 291 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
240 45 6 291 2 0
  • HTML: 240
  • PDF: 45
  • XML: 6
  • Total: 291
  • BibTeX: 2
  • EndNote: 0
Views and downloads (calculated since 23 May 2022)
Cumulative views and downloads (calculated since 23 May 2022)

Viewed (geographical distribution)

Total article views: 267 (including HTML, PDF, and XML) Thereof 267 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
Latest update: 26 Jun 2022
Short summary
We applied the global sensitivity analysis LH-OAT to the integrated hydrology model ParFlow-CLM to investigate the sensitivity of the 12 parameters for different scenarios. And we found that the general patterns of the parameter sensitivities were consistent, however, for some parameters a significantly larger span of the sensitivities was observed, especially for the higher slope and in subarctic climatic scenarios.