Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 4.936 IF 4.936
  • IF 5-year value: 5.615 IF 5-year
    5.615
  • CiteScore value: 4.94 CiteScore
    4.94
  • SNIP value: 1.612 SNIP 1.612
  • IPP value: 4.70 IPP 4.70
  • SJR value: 2.134 SJR 2.134
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 107 Scimago H
    index 107
  • h5-index value: 63 h5-index 63
Discussion papers
https://doi.org/10.5194/hess-2019-305
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2019-305
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 10 Jul 2019

Submitted as: research article | 10 Jul 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).

Weak sensitivity of the terrestrial water budget to global soil texture maps in the ORCHIDEE land surface model

Salma Tafasca1, Agnès Ducharne1, and Christian Valentin2 Salma Tafasca et al.
  • 1METIS (Milieux Environnementaux, Transferts et Interactions dans les Hydrosystèmes et les Sols), Institut Pierre Simon Laplace (IPSL), Sorbonne Université, CNRS, EPHE, Paris, France
  • 2iEES-Paris (Institut d'Ecologie et des Sciences de l'Environnement de Paris), Sorbonne Université, CNRS, INRA, IRD, Paris, France

Abstract. Soil physical properties play an important role for estimating soil water and energy fluxes. Many hydrological and land surface models (LSMs) use soil texture maps to infer these properties. Here, we investigate the impact of soil texture on soil water fluxes and storage at global scale using the ORCHIDEE LSM, forced by several complex or globally-uniform soil texture maps. The model shows a realistic sensitivity of runoff processes and soil moisture to soil texture, and reveals that medium textures give the highest evapotranspiration and lowest total runoff rates. The three tested complex soil texture maps being rather similar by construction, especially when upscaled at the 0.5° resolution used here, they result in similar water budgets at all scales, compared to the uncertainties of observation-based products and meteorological forcing datasets. A useful outcome is that the choice of the input soil texture map is not crucial for large-scale modelling. The added-value of more detailed soil information (horizontal and vertical resolution, soil composition) deserves further studies.

Salma Tafasca et al.
Interactive discussion
Status: open (extended)
Status: open (extended)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement
Salma Tafasca et al.
Salma Tafasca et al.
Viewed  
Total article views: 395 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
320 72 3 395 15 1 5
  • HTML: 320
  • PDF: 72
  • XML: 3
  • Total: 395
  • Supplement: 15
  • BibTeX: 1
  • EndNote: 5
Views and downloads (calculated since 10 Jul 2019)
Cumulative views and downloads (calculated since 10 Jul 2019)
Viewed (geographical distribution)  
Total article views: 322 (including HTML, PDF, and XML) Thereof 320 with geography defined and 2 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Cited  
Saved  
No saved metrics found.
Discussed  
No discussed metrics found.
Latest update: 13 Oct 2019
Publications Copernicus
Download
Short summary
In land surface models (LSMs), soil properties are inferred from soil texture. In this study, we use different input global soil texture maps from the literature to investigate the impact of soil texture on the simulated water budget in an LSM. The medium loamy textures give the highest evapotranspiration and lowest total runoff rates. However, the different soil texture maps result in similar water budgets because of their inherent similarities, especially when upscaled at the 0.5° resolution.
In land surface models (LSMs), soil properties are inferred from soil texture. In this study, we...
Citation