Tradeoffs Between Temporal and Spatial Pattern Calibration and Their Impacts on Robustness and Transferability of Hydrologic Model Parameters to Ungauged Basins

M. C. Demirel, J. Koch, O. Rakovec, R. Kumar, J. Mai, S. Müller, S. Thober, L. Samaniego, S. Stisen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Optimization of spatially consistent parameter fields is believed to increase the robustness of parameter estimation and its transferability to ungauged basins. The current paper extends previous multi-objective and transferability studies by exploring the value of both multi-basin and spatial pattern calibration of distributed hydrologic models as compared to single-basin and single-objective model calibrations, with respect to tradeoffs, performance and transferability. The mesoscale Hydrological Model (mHM) is used across six large central European basins. Model simulations are evaluated against streamflow observations at the basin outlets and remotely sensed evapotranspiration patterns. Several model validation experiments are performed through combinations of single- (temporal evaluation through discharge) and multi-objective (temporal and spatial evaluation through discharge and spatial evapotranspiration patterns) calibrations with holdout experiments saving alternating basins for model evaluation. The study shows that there are very minimal tradeoffs between spatial and temporal performance objectives and that a joint calibration of multiple basins using multiple objective functions provides the most robust estimations of parameter fields that perform better when transferred to ungauged basins. The study indicates that particularly the multi-basin calibration approach is key for robust parametrizations, and that the addition of an objective function tailored for matching spatial patterns of ET fields alters the spatial parameter fields while significantly improving the spatial pattern performance without any tradeoffs with discharge performance. In light of model equifinality, the minimal tradeoff between spatial and temporal performance shows that adding spatial pattern evaluation to the traditional temporal evaluation of hydrological models can assist in identifying optimal parameter sets.

Original languageEnglish
Article numbere2022WR034193
JournalWater Resources Research
Volume60
Issue number1
DOIs
Publication statusPublished - Jan 2024

Bibliographical note

Publisher Copyright:
© 2024. The Authors.

Funding

We acknowledge the financial support for the SPACE project by the Villum Foundation ( http://villumfonden.dk/ ) through their Young Investigator Program (Grant VKR023443). The first author is supported by the Scientific Research Projects Department of Istanbul Technical University (ITU‐BAP) under Grant MDA‐2022‐43762 and by the National Center for High Performance Computing of Turkey (UHeM) under Grant 1007292019 and by NASA program that is, NNH22ZDA001N‐RRNES: A.24 Rapid Response and Novel Research in Earth Science under the Grant 22‐RRNES22‐0010. We acknowledge the financial support for the SPACE project by the Villum Foundation (http://villumfonden.dk/) through their Young Investigator Program (Grant VKR023443). The first author is supported by the Scientific Research Projects Department of Istanbul Technical University (ITU-BAP) under Grant MDA-2022-43762 and by the National Center for High Performance Computing of Turkey (UHeM) under Grant 1007292019 and by NASA program that is, NNH22ZDA001N-RRNES: A.24 Rapid Response and Novel Research in Earth Science under the Grant 22-RRNES22-0010.

FundersFunder number
ITU‐BAP
National Center for High Performance Computing of Turkey
National Aeronautics and Space Administration22‐RRNES22‐0010, NNH22ZDA001N-RRNES
Villum FondenVKR023443
Ulusal Yüksek Başarımlı Hesaplama Merkezi, Istanbul Teknik Üniversitesi1007292019
Istanbul Teknik Üniversitesi
Bilimsel Araştırma Projeleri Birimi, İstanbul Teknik ÜniversitesiMDA‐2022‐43762

    Keywords

    • parameter transferability
    • spatial pattern optimization
    • ungauged basins

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