The complexity of hydrological systems and the necessary simplification of models describing these systems remain major challenges in hydrological modeling. Kirchner's (2009) approach of inferring rainfall and evaporation from discharge fluctuations by “doing hydrology backward” is based on the assumption that catchment behavior can be conceptualized with a single storage-discharge relationship. Here we test Kirchner's approach using a densely instrumented hydrologic measurement network spanning 24 geologically diverse subbasins of the Alzette catchment in Luxembourg. We show that effective rainfall rates inferred from discharge fluctuations generally correlate well with catchment-averaged precipitation radar estimates in catchments ranging from less than 10 to more than 1000 km2in size. The correlation between predicted and observed effective precipitation was 0.8 or better in 23 of our 24 catchments, and prediction skill did not vary systematically with catchment size or with the complexity of the underlying geology. Model performance improves systematically at higher soil moisture levels, indicating that our study catchments behave more like simple dynamical systems with unambiguous storage-discharge relationships during wet conditions. The overall mean correlation coefficient for all subbasins for the entire data set increases from 0.80 to 0.95, and the mean bias for all basins decreases from –0.61 to –0.35 mm d−1. We propose an extension of Kirchner's approach that uses in situ soil moisture measurements to distinguish wet and dry catchment conditions.