Hydrological extremes across scales

Flooding is one of the leading natural disasters in terms of human fatalities and economic loss globally. The rising trends in global and regional economic losses due to floods have raised concerns about floods becoming more severe in a warming climate. Interestingly, there is still limited evidence of changes in floods across space and time, arguably due to fragmented (and even conflicting) scientific findings of local-scale studies, limited spatiotemporal coverage of streamflow observations, and the complexity of flood generating processes.

Hong's research program explores how floods have changed and what are the driving factors of these changes across scales from the regional (e.g. the Great Lakes) to the global, using a combination of streamflow observations and hydrological models. Hong's research interests are centered around three main themes.

Improving the accessibility of streamflow observations for hydrological research

In-situ streamflow observation is an important asset for obtaining insights into many aspects of large-scale hydrology, including the characteristics of global flood hazards. The Global Streamflow Indices and Metadata archive (GSIM) project was initiated for this purpose, and has successfully compiled an unprecedented daily streamflow dataset of more than 30,000 stations worldwide. During GSIM development, significant efforts have been invested to develop a comprehensive set of metadata (e.g. catchment boundary and landscape attributes) and process streamflow indices (e.g. time series of annual maximum) that freely accessible online.

Evaluating hydrological models performance using large-sample of streamflow observations

Although streamflow observation is crucial to advance hydrology, this asset alone cannot provide a holistic perspective of changes in river flows across scales, due to limited coverage of observational networks. Large-scale hydrology studies have increasingly used global hydrological models to provide an alternate line of evidence. The downside of this approach is that models tend to find contradict results to what observed in streamflow measurements. The credibility of model-based conclusions is difficult to determine, as model evaluation is still under-represented in the literature.

Exploring the usefulness of hydrological models is one of Hong's research interest. The focus is on the performance of model ensembles (e.g., Inter-Sectoral Impact Model Intercomparison Project, and Global Earth Observation for Integrated Water Resource Assessment ) or state-of-the-art modeling platform (e.g., North American Land Data Assimilation System).

Improving the understanding of changes in flood hazards and the underlying mechanism

Many mechanisms can influence flood generation such as extreme rainfall events, snowmelt processes, and catchment wetness build-up. Hong's research showed that it is feasible to identify regional patterns of important flood generation mechanisms using observational data.

Nevertheless, identifying the factors driving changes in flood hazards is challenging, as both hydro-climatic processes and anthropogenic impacts across the drainage basins can play a substantial role. Hong's research aims to attribute changes in flood hazards across scale to possible mechanisms such as land use changes or intensified short-duration rainfall extremes.