Regional runoff prediction through aggregation of first-order hydrological process knowledge: a case study

Abstract

The dominant processes concept was used to develop a regionally applicable rainfall—runoff model. The first-order runoff processes are identified through a combination of field investigations, physico-geographical analysis of the research area, the Alzette River basin in the Grand-Duchy of Luxembourg, and discharge data series analysis. Lithology appeared to be the major source of discrepancy in hydrological behaviour over the total area. As a result, the hydrological behaviour of each lithological substratum was characterized and conceptualized into a parsimonious model structure. The runoff signals were calibrated against the hourly-recorded discharge series of eight sub-basins, with parameter sensitivity and correlation analysis outlining the need for minor corrections to the model structure. Validation against another set of 10 sub-basins showed good results for the regional parameter set, with an average loss in efficiency (Reff) of 0.04, compared to the reference model, with a mean Reff of 0.79. Due to an up-scaling effect, inducing variations in the dominance of particular runoff processes, some anomalies were found in the performance of individual runoff characteristics. In this respect, limiting the application of the model to a certain spatial scale gives a high reliability of the prediction of the dynamics of hourly runoff in ungauged basins within the study area.