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An integrated framework was employed to develop probabilistic floodplain maps, taking into account hydrologic and hydraulic uncertainties under climate change impacts. To develop the maps, several scenarios representing the individual and compounding effects of the models’ input and parameters uncertainty were defined. Hydrologic model calibration and validation were performed using a Dynamically Dimensioned Search algorithm. A generalized likelihood uncertainty estimation method was used for quantifying uncertainty. To draw on the potential benefits of the proposed methodology, a flash-flood-prone urban watershed in the Greater Toronto Area, Canada, was selected. The developed floodplain maps were updated considering climate change impacts on the input uncertainty with rainfall Intensity–Duration–Frequency (IDF) projections of RCP8.5. The results indicated that the hydrologic model input poses the most uncertainty to floodplain delineation. Incorporating climate change impacts resulted in the expansion of the potential flood area and an increase in water depth. Comparison between stationary and non-stationary IDFs showed that the flood probability is higher when a non-stationary approach is used. The large inevitable uncertainty associated with floodplain mapping and increased future flood risk under climate change imply a great need for enhanced flood modeling techniques and tools. The probabilistic floodplain maps are beneficial for implementing risk management strategies and land-use planning.
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The avulsion time scale of channels on the Yellow River delta (YRD) is about a decade due to the large sediment load, and rapid channel aggradation and progradation. Nevertheless, the Qingshuigou channel has been maintained for about four decades since 1976. This channel provides an ideal opportunity to study channel evolution following avulsion and to examine different avulsion criteria. In this study, we analyzed the geomorphic adjustment of the lower Qingshuigou channel during 1976–2015, and calculated normalized gradient advantage and superelevation at the channel to estimate how close the channel was to avulsion. Results showed that channel evolution processes may be divided into four phases: I (1976–1980) rapid aggradation, II (1980–1985) channel widening and enlargement, III (1985–1996) main channel aggradation and shrinkage, and IV (1996–2015) main channel incision and deepening. Evolution phases I, II and III are similar to the avulsion cycle observed in natural and experimental fluvial systems. The calculated values of normalized gradient advantage and superelevation in early 1990s exceeded the critical values suggested by previous studies, implying that the channel was prone to avulsion. Nevertheless, avulsion was prevented mainly due to limited overbank flows, constriction from artificial dikes, and slowed channel extension as a result of reduced sediment load. The evolution of the Qingshuigou channel confirms previous arguments that superelevation and gradient advantage are not sufficient for avulsion, and multiple factors should be considered, including flood frequency, lateral mobility, sediment diameter, and human interruptions.