Articles | Volume 15, issue 12
Hydrol. Earth Syst. Sci., 15, 3809–3827, 2011
Hydrol. Earth Syst. Sci., 15, 3809–3827, 2011

Research article 21 Dec 2011

Research article | 21 Dec 2011

Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

A. Atencia1,2,*, L. Mediero3, M. C. Llasat2, and L. Garrote3 A. Atencia et al.
  • 1Meteorological Service of Catalonia, Barcelona, Spain
  • 2Department of Astronomy and Meteorology, Faculty of Physics, University of Barcelona, Barcelona, Spain
  • 3Department of Hydraulic and Energy Engineering, Technical University of Madrid, Madrid, Spain
  • *now at: Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, Canada

Abstract. The performance of a hydrologic model depends on the rainfall input data, both spatially and temporally. As the spatial distribution of rainfall exerts a great influence on both runoff volumes and peak flows, the use of a distributed hydrologic model can improve the results in the case of convective rainfall in a basin where the storm area is smaller than the basin area. The aim of this study was to perform a sensitivity analysis of the rainfall time resolution on the results of a distributed hydrologic model in a flash-flood prone basin. Within such a catchment, floods are produced by heavy rainfall events with a large convective component. A second objective of the current paper is the proposal of a methodology that improves the radar rainfall estimation at a higher spatial and temporal resolution. Composite radar data from a network of three C-band radars with 6-min temporal and 2 × 2 km2 spatial resolution were used to feed the RIBS distributed hydrological model. A modification of the Window Probability Matching Method (gauge-adjustment method) was applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation by computing new Z/R relationships for both convective and stratiform reflectivities. An advection correction technique based on the cross-correlation between two consecutive images was introduced to obtain several time resolutions from 1 min to 30 min. The RIBS hydrologic model was calibrated using a probabilistic approach based on a multiobjective methodology for each time resolution. A sensitivity analysis of rainfall time resolution was conducted to find the resolution that best represents the hydrological basin behaviour.