Impact of missing precipitation values on hydrological model output: a case study from the Eddleston Water catchment, Scotland

A hydrological model was applied to select the best infilling method of missing precipitation (1) and to assess the impact of the length of deleted and filled precipitation data (2). The model was calibrated and validated using the hourly observed discharges from two gauges located in the outlet of the catchment (62.34 km²) and in the inner sub-catchment (2.05 km²). Precipitation from four gauges was spatially interpolated over the overall catchment, while the sub-catchment used the precipitation from one gauge. Four scenarios of different lengths of deletion within three high-intensity events were established in the data of this gauge. Three infilling methods were applied and compared: substitution, linear regression and inverse distance weighting (IDW). Substitution showed the best results, followed by linear regression and IDW in both scales. Differences between methods were significant only in 8.3% and 19.4% of all cases (sub-catchment and catchment, respectively). The impact of length was assessed using the substitution only and by comparing differences in discharges and performance statistics caused by four scenarios. Higher differences in discharges were found on the catchment scale compared to the inner sub-catchment and were insignificant for all events and scenarios. The hypothesis that a longer length of deleted and filled data would lead to a greater error in discharges was wrong for 11.1% and 16.7% of all cases (sub-catchment and catchment, respectively). In several cases (33.4% sub-catchment, 27.1% catchment), the model produced better results using the time series with filled gaps compared to the configuration with observed data.