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Predicting the temporal transferability of model parameters through a hydrological signature analysis
- Source :
- Frontiers of Earth Science. 14:110-123
- Publication Year :
- 2019
- Publisher :
- Springer Science and Business Media LLC, 2019.
-
Abstract
- Attention has recently increased on the use of hydrological signatures as a potential tool for assessing the fidelity of model structures and providing insights into the transfer of model parameters. The utility of hydrological signatures as model performance/reliability indicators in a calibration-validation testing scenario (i.e., the temporal transfer of model parameters) is the focus of this study. The Probability Distributed Model, a flexible conceptual hydrological model, is used to test the approach across a number of catchments included in the MOPEX data set. We explore the change in model performance across calibration and validation time periods and contrast it to the corresponding change in several hydrological signatures to assess signature worth. Results are explored in finer detail by utilizing a moving window approach to calibration and validation time periods. The results of this study indicated that the most informative signature can vary, both spatially and temporally, based on physical and climatic characteristics and their interaction to the model parameterization. Thus, one signature could not adequately illustrate complex watershed behaviors nor predict model performance in new analysis periods.
- Subjects :
- Watershed
010504 meteorology & atmospheric sciences
Computer science
media_common.quotation_subject
Distributed element model
Fidelity
Contrast (statistics)
010502 geochemistry & geophysics
computer.software_genre
01 natural sciences
Signature (logic)
Data set
Streamflow
General Earth and Planetary Sciences
Data mining
computer
Reliability (statistics)
0105 earth and related environmental sciences
media_common
Subjects
Details
- ISSN :
- 20950209 and 20950195
- Volume :
- 14
- Database :
- OpenAIRE
- Journal :
- Frontiers of Earth Science
- Accession number :
- edsair.doi...........090f42b251657cfee56d42e03ce6225f
- Full Text :
- https://doi.org/10.1007/s11707-019-0755-y