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
Volume 22, issue 2
Hydrol. Earth Syst. Sci., 22, 1299–1315, 2018
https://doi.org/10.5194/hess-22-1299-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Hydrol. Earth Syst. Sci., 22, 1299–1315, 2018
https://doi.org/10.5194/hess-22-1299-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 20 Feb 2018

Research article | 20 Feb 2018

Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

Mehmet C. Demirel et al.
Related authors  
Selection of multi-model ensemble of general circulation models for the simulation of precipitation and maximum and minimum temperature based on spatial assessment metrics
Kamal Ahmed, Dhanapala A. Sachindra, Shamsuddin Shahid, Mehmet C. Demirel, and Eun-Sung Chung
Hydrol. Earth Syst. Sci., 23, 4803–4824, https://doi.org/10.5194/hess-23-4803-2019,https://doi.org/10.5194/hess-23-4803-2019, 2019
Short summary
The SPAtial EFficiency metric (SPAEF): multiple-component evaluation of spatial patterns for optimization of hydrological models
Julian Koch, Mehmet Cüneyd Demirel, and Simon Stisen
Geosci. Model Dev., 11, 1873–1886, https://doi.org/10.5194/gmd-11-1873-2018,https://doi.org/10.5194/gmd-11-1873-2018, 2018
Short summary
The skill of seasonal ensemble low-flow forecasts in the Moselle River for three different hydrological models
M. C. Demirel, M. J. Booij, and A. Y. Hoekstra
Hydrol. Earth Syst. Sci., 19, 275–291, https://doi.org/10.5194/hess-19-275-2015,https://doi.org/10.5194/hess-19-275-2015, 2015
Short summary
Related subject area  
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
A virtual hydrological framework for evaluation of stochastic rainfall models
Bree Bennett, Mark Thyer, Michael Leonard, Martin Lambert, and Bryson Bates
Hydrol. Earth Syst. Sci., 23, 4783–4801, https://doi.org/10.5194/hess-23-4783-2019,https://doi.org/10.5194/hess-23-4783-2019, 2019
Short summary
Assessing the impacts of hydrologic and land use alterations on water temperature in the Farmington River basin in Connecticut
John R. Yearsley, Ning Sun, Marisa Baptiste, and Bart Nijssen
Hydrol. Earth Syst. Sci., 23, 4491–4508, https://doi.org/10.5194/hess-23-4491-2019,https://doi.org/10.5194/hess-23-4491-2019, 2019
Short summary
Future shifts in extreme flow regimes in Alpine regions
Manuela I. Brunner, Daniel Farinotti, Harry Zekollari, Matthias Huss, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 23, 4471–4489, https://doi.org/10.5194/hess-23-4471-2019,https://doi.org/10.5194/hess-23-4471-2019, 2019
Short summary
Time variability and uncertainty in the fraction of young water in a small headwater catchment
Michael Paul Stockinger, Heye Reemt Bogena, Andreas Lücke, Christine Stumpp, and Harry Vereecken
Hydrol. Earth Syst. Sci., 23, 4333–4347, https://doi.org/10.5194/hess-23-4333-2019,https://doi.org/10.5194/hess-23-4333-2019, 2019
Short summary
Hydrodynamic simulation of the effects of stable in-channel large wood on the flood hydrographs of a low mountain range creek, Ore Mountains, Germany
Daniel Rasche, Christian Reinhardt-Imjela, Achim Schulte, and Robert Wenzel
Hydrol. Earth Syst. Sci., 23, 4349–4365, https://doi.org/10.5194/hess-23-4349-2019,https://doi.org/10.5194/hess-23-4349-2019, 2019
Short summary
Cited articles  
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop Evapotranspiration – Guidelines for Computing Crop Water Requirements, FAO Irrigation and drainage paper 56, http://www.fao.org/docrep/x0490e/x0490e00.htm (last access: 16 February 2018), 1998.
Berezowski, T., Nossent, J., Chormański, J., and Batelaan, O.: Spatial sensitivity analysis of snow cover data in a distributed rainfall-runoff model, Hydrol. Earth Syst. Sci., 19, 1887–1904, https://doi.org/10.5194/hess-19-1887-2015, 2015.
Beven, K. and Freer, J.: Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology, J. Hydrol., 249, 11–29, https://doi.org/10.1016/S0022-1694(01)00421-8, 2001.
Campolongo, F., Cariboni, J., and Saltelli, A.: An effective screening design for sensitivity analysis of large models, Environ. Model. Softw., 22, 1509–1518, https://doi.org/10.1016/j.envsoft.2006.10.004, 2007.
Chen, J. M., Chen, X., Ju, W., and Geng, X.: Distributed hydrological model for mapping evapotranspiration using remote sensing inputs, J. Hydrol., 305, 15–39, https://doi.org/10.1016/j.jhydrol.2004.08.029, 2005.
Publications Copernicus
Download
Short summary
Satellite data offer great opportunities to improve spatial model predictions by means of spatially oriented model evaluations. In this study, satellite images are used to observe spatial patterns of evapotranspiration at the land surface. These spatial patterns are utilized in combination with streamflow observations in a model calibration framework including a novel spatial performance metric tailored to target the spatial pattern performance of a catchment-scale hydrological model.
Satellite data offer great opportunities to improve spatial model predictions by means of...
Citation