Articles | Volume 11, issue 5
Methods for assessment of models
15 May 2018
Methods for assessment of models |  | 15 May 2018

The SPAtial EFficiency metric (SPAEF): multiple-component evaluation of spatial patterns for optimization of hydrological models

Julian Koch, Mehmet Cüneyd Demirel, and Simon Stisen

Related authors

The precision of satellite-based net irrigation quantification in the Indus and Ganges basins
Søren J. Kragh, Rasmus Fensholt, Simon Stisen, and Julian Koch
Hydrol. Earth Syst. Sci., 27, 2463–2478,,, 2023
Short summary
Water-table-driven greenhouse gas emission estimates guide peatland restoration at national scale
Julian Koch, Lars Elsgaard, Mogens H. Greve, Steen Gyldenkærne, Cecilie Hermansen, Gregor Levin, Shubiao Wu, and Simon Stisen
Biogeosciences, 20, 2387–2403,,, 2023
Short summary
An inter-comparison of approaches and frameworks to quantify irrigation from satellite data
Søren Julsgaard Kragh, Jacopo Dari, Sara Modanesi, Christian Massari, Luca Brocca, Rasmus Fensholt, Simon Stisen, and Julian Koch
Hydrol. Earth Syst. Sci. Discuss.,,, 2023
Preprint under review for HESS
Short summary
Assessing the impact of climate change to landslides using public data, a case study from Vejle, Denmark
Kristian Svennevig, Julian Koch, Marie Keiding, and Gregor Luetzenburg
Nat. Hazards Earth Syst. Sci. Discuss.,,, 2023
Preprint under review for NHESS
Short summary
Machine-learning-based downscaling of modelled climate change impacts on groundwater table depth
Raphael Schneider, Julian Koch, Lars Troldborg, Hans Jørgen Henriksen, and Simon Stisen
Hydrol. Earth Syst. Sci., 26, 5859–5877,,, 2022
Short summary

Related subject area

Enhancing the representation of water management in global hydrological models
Guta Wakbulcho Abeshu, Fuqiang Tian, Thomas Wild, Mengqi Zhao, Sean Turner, A. F. M. Kamal Chowdhury, Chris R. Vernon, Hongchang Hu, Yuan Zhuang, Mohamad Hejazi, and Hong-Yi Li
Geosci. Model Dev., 16, 5449–5472,,, 2023
Short summary
NEOPRENE v1.0.1: a Python library for generating spatial rainfall based on the Neyman–Scott process
Javier Diez-Sierra, Salvador Navas, and Manuel del Jesus
Geosci. Model Dev., 16, 5035–5048,,, 2023
Short summary
Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations
Adam Pasik, Alexander Gruber, Wolfgang Preimesberger, Domenico De Santis, and Wouter Dorigo
Geosci. Model Dev., 16, 4957–4976,,, 2023
Short summary
Validating the Nernst–Planck transport model under reaction-driven flow conditions using RetroPy v1.0
Po-Wei Huang, Bernd Flemisch, Chao-Zhong Qin, Martin O. Saar, and Anozie Ebigbo
Geosci. Model Dev., 16, 4767–4791,,, 2023
Short summary
DynQual v1.0: a high-resolution global surface water quality model
Edward R. Jones, Marc F. P. Bierkens, Niko Wanders, Edwin H. Sutanudjaja, Ludovicus P. H. van Beek, and Michelle T. H. van Vliet
Geosci. Model Dev., 16, 4481–4500,,, 2023
Short summary

Cited articles

Alexandrov, G. A., Ames, D., Bellocchi, G., Bruen, M., Crout, N., Erechtchoukova, M., Hildebrandt, A., Hoffman, F., Jackisch, C., Khaiter, P., Mannina, G., Matsunaga, T., Purucker, S. T., Rivington, M., and Samaniego, L.: Technical assessment and evaluation of environmental models and software: Letter to the Editor, Environ. Model. Softw., 26, 328–336,, 2011. 
Brown, B. G., Gotway, J. H., Bullock, R., Gilleland, E., Fowler, T., Ahijevych, D., and Jensen, T.: The Model Evaluation Tools (MET): Community tools for forecast evaluation, in: Preprints, 25th Conf. on International Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, Phoenix, AZ, Amer. Meteor. Soc. A, Vol. 9, 2009. 
Clark, M. P., Kavetski, D., and Fenicia, F.: Pursuing the method of multiple working hypotheses for hydrological modeling, Water Resour. Res., 47, W09301,, 2011. 
Cloke, H. L. and Pappenberger, F.: Evaluating forecasts of extreme events for hydrological applications: An approach for screening unfamiliar performance measures, Meteorol. Appl., 15, 181–197, 2008. 
Short summary
Our work addresses a key challenge in earth system modelling: how to optimally exploit the information contained in satellite remote sensing observations in the calibration of such models. For this we thoroughly test a number of measures that quantify the fit between an observed and a simulated spatial pattern. We acknowledge the difficulties associated with such a comparison and suggest using measures that regard multiple aspects of spatial information, i.e. magnitude and variability.