Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model
Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target the patt...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2018-02-01
|
| Series: | Hydrology and Earth System Sciences |
| Online Access: | https://www.hydrol-earth-syst-sci.net/22/1299/2018/hess-22-1299-2018.pdf |
| _version_ | 1811193385234464768 |
|---|---|
| author | M. C. Demirel M. C. Demirel J. Mai J. Mai G. Mendiguren G. Mendiguren J. Koch J. Koch L. Samaniego S. Stisen |
| author_facet | M. C. Demirel M. C. Demirel J. Mai J. Mai G. Mendiguren G. Mendiguren J. Koch J. Koch L. Samaniego S. Stisen |
| author_sort | M. C. Demirel |
| collection | DOAJ |
| description | Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM) is used to simulate streamflow and AET and has been selected due to its soil
parameter distribution approach based on pedo-transfer functions and the
build in multi-scale parameter regionalisation. In addition two new spatial
parameter distribution options have been incorporated in the model in order
to increase the flexibility of root fraction coefficient and potential
evapotranspiration correction parameterisations, based on soil type and
vegetation density. These parameterisations are utilised as they are most
relevant for simulated AET patterns from the hydrologic model. Due to the
fundamental challenges encountered when evaluating spatial pattern
performance using standard metrics, we developed a simple but highly
discriminative spatial metric, i.e. one comprised of three easily interpretable
components measuring co-location, variation and distribution of the spatial data.
<br><br>
The study shows that with flexible spatial model parameterisation used in
combination with the appropriate objective functions, the simulated spatial
patterns of actual evapotranspiration become substantially more similar to
the satellite-based estimates. Overall 26 parameters are identified for
calibration through a sequential screening approach based on a combination
of streamflow and spatial pattern metrics. The robustness of the
calibrations is tested using an ensemble of nine calibrations based on
different seed numbers using the shuffled complex evolution optimiser. The
calibration results reveal a limited trade-off between streamflow dynamics
and spatial patterns illustrating the benefit of combining separate
observation types and objective functions. At the same time, the simulated
spatial patterns of AET significantly improved when an objective
function based on observed AET patterns and a novel spatial performance
metric compared to traditional streamflow-only calibration were included. Since the overall water balance is usually a crucial goal in hydrologic modelling,
spatial-pattern-oriented optimisation should always be accompanied by
traditional discharge measurements. In such a multi-objective framework, the
current study promotes the use of a novel bias-insensitive spatial pattern
metric, which exploits the key information contained in the observed
patterns while allowing the water balance to be informed by discharge observations. |
| first_indexed | 2024-04-12T00:07:28Z |
| format | Article |
| id | doaj.art-abe844ef29d8456c9eecc856ab6830c3 |
| institution | Directory Open Access Journal |
| issn | 1027-5606 1607-7938 |
| language | English |
| last_indexed | 2024-04-12T00:07:28Z |
| publishDate | 2018-02-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Hydrology and Earth System Sciences |
| spelling | doaj.art-abe844ef29d8456c9eecc856ab6830c32022-12-22T03:56:03ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382018-02-01221299131510.5194/hess-22-1299-2018Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic modelM. C. Demirel0M. C. Demirel1J. Mai2J. Mai3G. Mendiguren4G. Mendiguren5J. Koch6J. Koch7L. Samaniego8S. Stisen9Geological Survey of Denmark and Greenland, Øster Voldgade 10, 1350 Copenhagen, DenmarkDepartment of Civil Engineering, Istanbul Technical University, 34469 Maslak, Istanbul, TurkeyDepartment Computational Hydrosystems, UFZ – Helmholtz Centre for Environmental Research, Leipzig, GermanyDepartment of Civil and Environmental Engineering, University of Waterloo, Waterloo, CanadaGeological Survey of Denmark and Greenland, Øster Voldgade 10, 1350 Copenhagen, DenmarkDepartment of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, DenmarkGeological Survey of Denmark and Greenland, Øster Voldgade 10, 1350 Copenhagen, DenmarkDepartment of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, DenmarkDepartment Computational Hydrosystems, UFZ – Helmholtz Centre for Environmental Research, Leipzig, GermanyGeological Survey of Denmark and Greenland, Øster Voldgade 10, 1350 Copenhagen, DenmarkSatellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM) is used to simulate streamflow and AET and has been selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance using standard metrics, we developed a simple but highly discriminative spatial metric, i.e. one comprised of three easily interpretable components measuring co-location, variation and distribution of the spatial data. <br><br> The study shows that with flexible spatial model parameterisation used in combination with the appropriate objective functions, the simulated spatial patterns of actual evapotranspiration become substantially more similar to the satellite-based estimates. Overall 26 parameters are identified for calibration through a sequential screening approach based on a combination of streamflow and spatial pattern metrics. The robustness of the calibrations is tested using an ensemble of nine calibrations based on different seed numbers using the shuffled complex evolution optimiser. The calibration results reveal a limited trade-off between streamflow dynamics and spatial patterns illustrating the benefit of combining separate observation types and objective functions. At the same time, the simulated spatial patterns of AET significantly improved when an objective function based on observed AET patterns and a novel spatial performance metric compared to traditional streamflow-only calibration were included. Since the overall water balance is usually a crucial goal in hydrologic modelling, spatial-pattern-oriented optimisation should always be accompanied by traditional discharge measurements. In such a multi-objective framework, the current study promotes the use of a novel bias-insensitive spatial pattern metric, which exploits the key information contained in the observed patterns while allowing the water balance to be informed by discharge observations.https://www.hydrol-earth-syst-sci.net/22/1299/2018/hess-22-1299-2018.pdf |
| spellingShingle | M. C. Demirel M. C. Demirel J. Mai J. Mai G. Mendiguren G. Mendiguren J. Koch J. Koch L. Samaniego S. Stisen Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model Hydrology and Earth System Sciences |
| title | Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model |
| title_full | Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model |
| title_fullStr | Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model |
| title_full_unstemmed | Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model |
| title_short | Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model |
| title_sort | combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model |
| url | https://www.hydrol-earth-syst-sci.net/22/1299/2018/hess-22-1299-2018.pdf |
| work_keys_str_mv | AT mcdemirel combiningsatellitedataandappropriateobjectivefunctionsforimprovedspatialpatternperformanceofadistributedhydrologicmodel AT mcdemirel combiningsatellitedataandappropriateobjectivefunctionsforimprovedspatialpatternperformanceofadistributedhydrologicmodel AT jmai combiningsatellitedataandappropriateobjectivefunctionsforimprovedspatialpatternperformanceofadistributedhydrologicmodel AT jmai combiningsatellitedataandappropriateobjectivefunctionsforimprovedspatialpatternperformanceofadistributedhydrologicmodel AT gmendiguren combiningsatellitedataandappropriateobjectivefunctionsforimprovedspatialpatternperformanceofadistributedhydrologicmodel AT gmendiguren combiningsatellitedataandappropriateobjectivefunctionsforimprovedspatialpatternperformanceofadistributedhydrologicmodel AT jkoch combiningsatellitedataandappropriateobjectivefunctionsforimprovedspatialpatternperformanceofadistributedhydrologicmodel AT jkoch combiningsatellitedataandappropriateobjectivefunctionsforimprovedspatialpatternperformanceofadistributedhydrologicmodel AT lsamaniego combiningsatellitedataandappropriateobjectivefunctionsforimprovedspatialpatternperformanceofadistributedhydrologicmodel AT sstisen combiningsatellitedataandappropriateobjectivefunctionsforimprovedspatialpatternperformanceofadistributedhydrologicmodel |