Winter Baseflow Calibration's Critical Role in Hydrological Modeling for the Pamir Region
DOKPE
- Huang, J. ORCID University of Fribourg
- Barandun, M. ORCID University of Fribourg
- Richard‐Cerda, J. ORCID Technische Universität Darmstadt, Germany
- Hoelzle, M. University of Fribourg
- Pohl, E. ORCID University of Fribourg
- 2026
Published in:
- Water Resources Research. - Wiley. - 2026, vol. 62, no. 1
English
The Pamir Mountains, a critical water source for Central Asia, require accurate quantification of runoff components for water resource management under climate change. Uncertainties in precipitation data are known to greatly affect hydrological model accuracy, leading to the widespread use of multi-data calibration methods to avoid internal error compensation effects between snow and glacier accumulation and melt processes. Traditional approaches incorporating runoff, snow cover fraction, and glacier mass balance are frequently employed in the region's hydrological model calibration; yet we find this calibration approach to still result in significant uncertainties in the quantification of baseflow, snowmelt, and glacier runoff. Here we show winter baseflow calibration to provide a previously overlooked yet powerful constraint on model parameters, not only constraining baseflow but also enhancing the estimation of snowmelt and glacier runoff through groundwater parameters' control on hydrograph characteristics. Even with low-quality forcing data, winter baseflow calibration guides parameters toward more realistic values of runoff estimates, improving model reliability. Using five different forcing data sets, we show that incorporating winter baseflow alongside traditional calibration variables (runoff, snow cover, and glacier mass balance) reduces uncertainty ranges from 34%–61% to 8%–21% for snowmelt, 5%–17% to 3%–11% for glacier runoff, and 33%–50% to 7%–21% for baseflow estimates. Though parameter equifinality remains a challenge, winter baseflow calibration consistently enhances model accuracy, emphasizing its vital role in refining hydrological predictions in alpine, data-scarce, and climate-sensitive regions.
- Faculty
- Faculté des sciences et de médecine
- Department
- Département de Géosciences
- Language
-
- English
- Classification
- Meteorology, climatology
- Other electronic version
- License
-
CC BY
- Open access status
- gold
- Identifiers
-
- DOI 10.1029/2025WR040043
- ISSN 0043-1397
- Persistent URL
- https://folia.unifr.ch/unifr/documents/336245
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