Attribution of regional flood changes based on scaling fingerprints.

Changes in the river flood regime may be due to atmospheric processes (e.g., increasing precipitation), catchment processes (e.g., soil compaction associated with land use change), and river system processes (e.g., loss of retention volume in the floodplains). This paper proposes a new framework for attributing flood changes to these drivers based on a regional analysis. We exploit the scaling characteristics (i.e., fingerprints) with catchment area of the effects of the drivers on flood changes. The estimation of their relative contributions is framed in Bayesian terms. Analysis of a synthetic, controlled case suggests that the accuracy of the regional attribution increases with increasing number of sites and record lengths, decreases with increasing regional heterogeneity, increases with increasing difference of the scaling fingerprints, and decreases with an increase of their prior uncertainty. The applicability of the framework is illustrated for a case study set in Austria, where positive flood trends have been observed at many sites in the past decades. The individual scaling fingerprints related to the atmospheric, catchment, and river system processes are estimated from rainfall data and simple hydrological modeling. Although the distributions of the contributions are rather wide, the attribution identifies precipitation change as the main driver of flood change in the study region. Overall, it is suggested that the extension from local attribution to a regional framework, including multiple drivers and explicit estimation of uncertainty, could constitute a similar shift in flood change attribution as the extension from local to regional flood frequency analysis.

Identifying changes in flood characteristics and their causes from an event-based perspective in the Central Taihu Basin.

Increasing rainstorms induced by climate change and modification in the land surface due to urbanization have greatly altered floods at different spatio-temporal scales. However, investigating flood events in urbanized plains is challenging as anthropogenic behaviors can change river flow without rainfall. In addition, while the frequency and magnitude of floods have been well examined, knowledge about variations in the rate of flood change is still limited. To fill these gaps, we proposed a scheme that focused on flood responses to rainfall to detect changes in flood characteristics in the Central Taihu Basin, a highly urbanized region in the Yangtze River Delta of China. Four characteristic metrics were adopted to summarize the flood hydrograph, including the peak, increment, rising rate, and falling rate. We then examined trends of these metrics based on the selected rainfall-flood events from ten hydrological stations during 1970-2020. Subsequently, the reduction method was used to separate the impacts of regional climate change and human activities on flood characteristics alterations. Furthermore, the importance of fifteen factors was quantified by the random forest model. We found that there is a significant upward trend in the evolution of flood characteristics, except for the increment of floods. Flood characteristics exhibit higher values when rainfall accumulates, indicating stronger responses of floods to a large amount of rainfall. The results also show that human activities dominate and impact the peak, rising rate, and falling rate of floods more than climate change. Meanwhile, although cumulative precipitation is the most important factor, flood characteristics are also susceptible to anthropogenic factors, such as land use change and hydraulic engineering construction. Our findings, which provide insights into flood event identification and enhance the understanding of regional flood changes, will serve as a reference for water resource management and flood mitigation in urbanized areas.