Trade-offs between parameter constraints and model realism: a case study.

Area of Science:

• Hydrology
• Environmental Modeling
• Geoscience

Background:

• Constraining hydrological model parameters is crucial but challenging, especially for complex models.
• Complex hydrological models often excel at simulating river behavior.
• A trade-off exists between parameter constraint and predictive accuracy of hydrological signatures.

Purpose of the Study:

• To explore the trade-offs between tightly constrained parameters and the prediction of hydrological signatures.
• To evaluate model complexity's impact on parameter uncertainty and hydrological behavior simulation.
• To assess the influence of different evapotranspiration methods on model parameters.

Main Methods:

• Developed five hydrological models of varying complexity (lumped to semi-lumped with 8 subdivisions).
• Utilized a consistent modeling framework, data, and calibration algorithm across all models.
• Investigated two distinct methods for calculating potential evapotranspiration.

Main Results:

• A clear trade-off between model complexity, parameter constraint, and hydrological signature prediction was observed.
• Simpler models achieved well-constrained parameters but poorly predicted hydrological signatures.
• More complex models accurately captured hydrological signatures but exhibited less constrained parameters.

Conclusions:

• Focusing solely on parameter uncertainty can be misleading in hydrological modeling.
• Tightly constrained parameters may lend false credibility to oversimplified hydrological model structures.
• Model complexity is a critical factor influencing the balance between parameter identifiability and predictive performance.