Numerous applications of hydrologic models have shown their capability to simulate hydrologic processes up to a reasonable degree of certainty. In terms of flood modeling, the hereby required quality of the key input parameter precipitation is of vast importance but often remains questionable. This Ph.D. thesis presents a critical review of experiences made in the EU-funded RAPHAEL project. Different meteorological data sources are evaluated to assess their applicability for flood modeling and forecasting in the Bavarian pre-alpine watershed of the Ammer river (709 km²), for which the manifold hydrologic aspects of runoff production as well as the complex nature of floods are described. Apart from conventional rain gauge data, forecasts of several Numerical Weather Prediction Models (NWP) as well as rain radar data and precipitation derived from METEOSAT are examined, scaled and applied within the framework of a GIS-structured and physically based hydrologic model. Multi-scenario results are quantitatively compared and analysed. The synergetic approach leads to promising results under certain meteorological conditions, but also emphasizes a variety of drawbacks. At present, NWPs are the only data source to provide placed rainfall forecasts (up to 96 hours) with large spatial coverage and high temporal resolution. On the other hand, the coarse spatial resolution of NWP grids cannot as yet image the heterogeneous structures of orographic rainfields in complex convective situations and hence introduces a major downscaling problem for mountain catchment applications. As shown for two selected Ammer flood events, a high variability in prediction accuracy still has to be accepted at present. Sensitivity analysis of both meteo-data input and hydrological model performance in terms of process description are discussed, drawing positive conclusions for future applications of an advanced meteo-hydro model synergy.