Error Propagation of Radar Rainfall Nowcasting Fields through a Fully Distributed Flood Forecasting Model

Abstract

This study presents a first attempt to address the propagation of radar rainfall nowcasting errors to flood forecasts in the context of distributed hydrological simulations over a range of catchment sizes or scales. Rainfall forecasts with high spatiotemporal resolution generated from observed radar fields are used as forcing to a fully distributed hydrologic model to issue flood forecasts in a set of nested subbasins. Radar nowcasting introduces errors into the rainfall field evolution that result from spatial and temporal changes of storm features that are not captured in the forecast algorithm. The accuracy of radar rainfall and flood forecasts relative to observed radar precipitation fields and calibrated flood simulations is assessed. The study quantifies how increases in nowcasting errors with lead time result in higher flood forecast errors at the basin outlet. For small, interior basins, rainfall forecast errors can be simultaneously amplified or dampened in different flood forecast locations depending on the forecast lead time and storm characteristics. Interior differences in error propagation are shown to be effectively averaged out for larger catchment scales.

Statistical analysis of error propagation from radar rainfall to hydrological models

“…Borga (2002) selected different elevation scan angles to evaluate the impact of VPR on the catchment stream flow through a lumped hydrological model. Vivoni et al (2007) presented the propagation of radar rainfall nowcasting error to flood forecasts in the context of distributed hydrological simulations over a range of catchment size or scales.…”

Operational verification of a framework for the probabilistic nowcasting of river discharge in small and medium size basins

“…The generated hydrograph shows the flow forecasted by the system with a certain lead time. In Vivoni et al (2006Vivoni et al ( , 2007, other techniques are used to verify the benefits of using rainfall forecasts with different lead times as input in a hydrological model.…”

“…Other authors have tried to couple nowcasting techniques and hydrological models with the objective of extending the lead time of hydrological forecast by improving the knowledge of future rainfall (Berenguer et al, 2005;Vivoni et al, 2006;Vivoni et al, 2007;Salek et al, 2006). Berenguer et al (2005) presented a detailed study of the improvements and the limits of using a nowcasting algorithm to predict rainfall in respect to the application of eulerian or lagrangian persistence to the most recent observations.…”

Physical controls on the scale-dependence of ensemble streamflow forecast dispersion

“…The first is related to the spatiotemporal attenuation of a QPF as it is transformed into streamflow by the physical processes in a basin (e.g., Vivoni et al, 2007a): analyses by Mascaro et al (2010) indicated that the basin smoothing effect is higher for larger areas, implying a greater need for accurate ensemble QPFs for smaller basins.…”