Articles | Volume 17, issue 10
Nat. Hazards Earth Syst. Sci., 17, 1741–1761, 2017
Nat. Hazards Earth Syst. Sci., 17, 1741–1761, 2017

Research article 09 Oct 2017

Research article | 09 Oct 2017

A meteo-hydrological modelling system for the reconstruction of river runoff: the case of the Ofanto river catchment

Giorgia Verri1, Nadia Pinardi1,2, David Gochis3, Joseph Tribbia3, Antonio Navarra1, Giovanni Coppini1, and Tomislava Vukicevic1,a Giorgia Verri et al.
  • 1Centro Euro-Mediterraneo sui Cambiamenti Climatici, CMCC, Italy
  • 2Department of Physics and Astronomy, University of Bologna, Bologna, Italy
  • 3National Centre for Atmospheric Research, Boulder, USA
  • anow at: Interdisciplinary Science and Engineering Division, National Water Center, Tuscaloosa, Alabama, USA

Abstract. A meteo-hydrological modelling system has been designed for the reconstruction of long time series of rainfall and river runoff events. The modelling chain consists of the mesoscale meteorological model of the Weather Research and Forecasting (WRF), the land surface model NOAH-MP and the hydrology–hydraulics model WRF-Hydro. Two 3-month periods are reconstructed for winter 2011 and autumn 2013, containing heavy rainfall and river flooding events. Several sensitivity tests were performed along with an assessment of which tunable parameters, numerical choices and forcing data most impacted on the modelling performance.

The calibration of the experiments highlighted that the infiltration and aquifer coefficients should be considered as seasonally dependent.

The WRF precipitation was validated by a comparison with rain gauges in the Ofanto basin. The WRF model was demonstrated to be sensitive to the initialization time and a spin-up of about 1.5 days was needed before the start of the major rainfall events in order to improve the accuracy of the reconstruction. However, this was not sufficient and an optimal interpolation method was developed to correct the precipitation simulation. It is based on an objective analysis (OA) and a least square (LS) melding scheme, collectively named OA+LS. We demonstrated that the OA+LS method is a powerful tool to reduce the precipitation uncertainties and produce a lower error precipitation reconstruction that itself generates a better river discharge time series. The validation of the river streamflow showed promising statistical indices.

The final set-up of our meteo-hydrological modelling system was able to realistically reconstruct the local rainfall and the Ofanto hydrograph.

Final-revised paper