1,2,3,2,3,4- 1Tongji University, College of Surveying and Geo-informatics, China
- 2Hohai University, Key Laboratory of Water Disaster Prevention, China
- 3Hohai University, College of Hydrology and Water Resources, China
- 4Chair of Hydrology and River Basin Management, TUM School of Engineering and Design, Technical University of Munich, Munich, Germany
The complex orography of the Tibetan plateau (TP) and the scarcity and uneven spatial distribution of meteorological stations
present significant challenges in accurately estimating meteorological variables for hydrological simulations. This study aims
to enhance the accuracy of daily precipitation and temperature interpolation for hydrological simulations in the Lhasa River
Basin (LRB), particularly during flood events. We evaluate and compare the performance of deterministic Inverse Distance
Weighting—IDW and geostatistical (Ordinary Kriging—OK and Kriging with External Drift—KED) interpolation methods for
estimating precipitation and temperature patterns. Subsequently, we investigate the influence of different interpolation meth
ods on hydrological simulations by using the interpolated meteorological data as input for the Water Balance Simulation Model
(WaSiM) to simulate daily discharge in the LRB. Our results revealed that geostatistical methods, specifically OK and KED, are
more effective in capturing the spatial variability and anisotropy inherent in precipitation patterns influenced by the Indian
summer monsoons. In addition, the KED method effectively captured the daily variation of the temperature lapse rate, indicating
the inadequacy of using a constant lapse rate for hydrological modelling in high- elevation regions like the TP. The geostatistical
technique outperformed the Deterministic method, with KED realising the best temperature and precipitation interpolation
performance based on cross- validation results. However, although KED provides superior results based on cross- validation per
formance, applying its precipitation interpolation as input into WaSiM led to the poorest discharge simulation. The combination
of OK for precipitation and KED for temperature produced the most accurate discharge simulations in the LRB, highlighting
the importance of not solely relying on cross- validation results but also considering the practical implications of interpolation
methods on hydrological model outputs. Our study offers a robust framework for improving flood simulations and water resource
management in a data- scarce, high- elevation region like the TP.
How to cite: guede, K. G., Yu, Z., and Hofmeister, F.: Geostatistical Interpolation Approach for Improving Flood Simulation Within a Data- Scarce Region in the Tibetan Plateau, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4141, https://doi.org/10.5194/egusphere-egu26-4141, 2026.
