Uncertainty of Temporal and Spatial δ2H Interpolation on Young Water Fraction Estimates Using the StorAge Selection Function in Subtropical Mountain Catchments
Year: 2026
Type: article
Abstract: Water age reflects water sources, storage, and pathways, and regulates the solute retention and dissolution associated with biogeochemical processes, highlighting its hydrological and ecological importance. However, accurate water age estimation in tracer-aided models depends heavily on the quality and spatio-temporal resolution of precipitation isotopic signals. This study investigates how distributed rainfall δ2H signals affect the simulation of young water fraction (Fyw) via the Storage Age Selection (SAS) model in topographically complex subtropical mountain catchments. Eight precipitation δ2H scenarios were generated using two temporal approaches (stepwise and sinewave) and four spatial interpolation methods: (1) raw data, (2) reversed effective recharge elevation method (rERE), (3) linear regression with elevation (ER), and (4) regression-kriging (RK). Later on, the time-variant SAS model was calibrated against observed stream water δ2H collected from the year 2022 to the year 2024. Results show that the SAS model consistently produced similar Fyw estimates for catchments (8%~40%) across all eight scenarios, demonstrating strong robustness to input uncertainty and validating the dominant role of catchment characteristics in regulating water age. The combined stepwise temporal and rERE spatial approach provided better agreement with observed stream δ2H, particularly in the eastern, steeper catchments, yielding superior model efficiency along with better constrained uncertainty. This study highlights the sensitivity of age-tracking models to precipitation isotopic inputs and provides practical guidance for selecting an interpolation strategy in data-limited mountainous environments.
Source: Water
DOI: 10.3390/w18080958
Language: English
Subfield: Geochemistry and Petrology
Field: Earth and Planetary Sciences
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
Funder: National Taiwan University
Award: G2684651880
OpenAlex ID: W7154701765
