Uncertainty is prevalent in the result of any hydrological modeling studies. The uncertainty in a
hydrological model is a function of uncertainty in input data, model parameters and the structure
of the model. As precipitation is the driving variable of hydrological models, the uncertainty in
precipitation input data is considered as the most dominant cause of hydrological model
uncertainty. Precipitation uncertainty occurs due to two reasons: measurement error and error in
representing spatial and temporal variability due to limited sampling. The aim of this study is to
develop a general framework for analyzing the uncertainty in precipitation measurement and to
apply it as a case study to the Bagmati River basin in Nepal. To analyze the accuracy in
precipitation measurement, a qualitative approach is proposed at first. This approach includes
preparation of enquiry lists, field survey of the precipitation gauging stations and the assessment
of dominant errors in precipitation measurement based on the field study. Finally, the dominant
sources of errors are evaluated in a quantitative way using error correction approach. From the
analysis of qualitative study, wind error is identified as a major source of error, followed by
wetting error and evaporation error. The result of the quantitative analysis shows that the total
error in precipitation for the basin is less than 15%. However, the contribution of error due to
human (both observation and data handling error) can not be given any specific value and this
error should not be neglected. The only way to reduce this error is to implement strict quality
control measures.