Year: 2025
Type: preprint
Abstract: An integrated framework combining CRNS monitoring and PDI-based modeling was developed to enhance soil water estimation in alpine catchments. Field experiments in two small basins (10-12 km²) provided CRNS-derived root-zone soil moisture data, which were assimilated into a PDI-parameterized HYDRUS-1D model. Data assimilation reduced parameter uncertainty by 35% and improved identifiability of τ and ω parameters. Validation against gravimetric sampling (0-50 cm) showed that the fusion approach reduced RMSE from 0.048 to 0.029 cm³•cm⁻³, and improved predictions of infiltration rates by 23%. Seasonal simulations captured snowmelt infiltration peaks with high fidelity (correlation coefficient r > 0.87). This fusion methodology bridges sensing and modeling, offering a scalable pathway for regional water resources assessment on the Tibetan Plateau.
Authors: James R Miller¹, Hui Chen², Maria L Gonzalez¹, Daniel T Wong², Katherine A Roberts¹
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W7084031324
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