Articles | Volume 11, issue 5
https://doi.org/10.5194/gmd-11-1873-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-1873-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The SPAtial EFficiency metric (SPAEF): multiple-component evaluation of spatial patterns for optimization of hydrological models
Department of Hydrology, Geological Survey of Denmark and Greenland,
Copenhagen, 1350, Denmark
Mehmet Cüneyd Demirel
Department of Hydrology, Geological Survey of Denmark and Greenland,
Copenhagen, 1350, Denmark
Department of Civil Engineering, Istanbul Technical University, 34469
Maslak, Istanbul, Turkey
Simon Stisen
Department of Hydrology, Geological Survey of Denmark and Greenland,
Copenhagen, 1350, Denmark
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- OSARIS, the “Open Source SAR Investigation System” for Automatized Parallel InSAR Processing of Sentinel-1 Time Series Data With Special Emphasis on Cryosphere Applications D. Loibl et al. 10.3389/feart.2019.00172
- Diagnosis of GCM-RCM-driven rainfall patterns under changing climate through the robust selection of multi-model ensemble and sub-ensembles S. Gaur et al. 10.1007/s10584-022-03475-z
- Challenges in modeling and predicting floods and droughts: A review M. Brunner et al. 10.1002/wat2.1520
- Learning from satellite observations: increased understanding of catchment processes through stepwise model improvement P. Hulsman et al. 10.5194/hess-25-957-2021
- Additional Value of Using Satellite-Based Soil Moisture and Two Sources of Groundwater Data for Hydrological Model Calibration . Demirel et al. 10.3390/w11102083
- Synergistic Calibration of a Hydrological Model Using Discharge and Remotely Sensed Soil Moisture in the Paraná River Basin A. Fleischmann et al. 10.3390/rs13163256
- Novel measures for summarizing high-resolution forecast performance E. Gilleland 10.5194/ascmo-7-13-2021
- Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa M. Dembélé et al. 10.5194/hess-24-5379-2020
- Distributed Hydrological Model Based on Machine Learning Algorithm: Assessment of Climate Change Impact on Floods Z. Iqbal et al. 10.3390/su14116620
- A novel framework for selecting general circulation models based on the spatial patterns of climate M. Nashwan & S. Shahid 10.1002/joc.6465
- Downscaling of AMSR-E Soil Moisture over North China Using Random Forest Regression H. Zhang et al. 10.3390/ijgi11020101
- From simple to complex – Comparing four modelling tools for quantifying hydrologic ecosystem services B. Decsi et al. 10.1016/j.ecolind.2022.109143
- Learning and inferring the diurnal variability of cyanobacterial blooms from high-frequency time-series satellite-based observations H. Li et al. 10.1016/j.hal.2023.102383
- Effect of Dynamic PET Scaling with LAI and Aspect on the Spatial Performance of a Distributed Hydrologic Model U. Demirci & M. Demirel 10.3390/agronomy13020534
Latest update: 30 Sep 2023
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.
Our work addresses a key challenge in earth system modelling: how to optimally exploit the...