The Great 2011 Thailand flood disaster revisited: Could it have been mitigated by different dam operations based on better weather forecasts?

This paper revisits the 2011 Great Flood in central Thailand to answer one of the hotly debated questions at the time "Could the operation decisions of the flood control structures substantially mitigate the flood impacts in the downstream areas?". Using a numerical modeling approach, we develop a hypothesis such that the two upstream dam reservoirs: Bhumibol and Sirikit had more accurately forecasted the typhoon-triggered abnormal rainfall volumes and released more water earlier to save the storage capacity via 17 different scenarios or alternative operation schemes. We subsequently quantify the potential improvements, or reduced flood impacts in the downstream catchments, solely by changing the operation schemes of these two dam reservoirs, with all other conditions remaining unchanged. We observed that changing the operation schemes could have reduced only the flood depth while offering very limited improvements in terms of inundated areas for the lower Chao Phraya River Basin. Among 17 scenarios simulated, the inundated areas could have been reduced at most by 3.68%. This result justifies the limited role of these mega structures in the upstream during the disaster on one hand, while pointing to the necessity of handling local rainfall differently on the other. The paper expands the discussion into how the government of Thailand has drawn the lessons from the 2011 flood to better prepare themselves against the lurking flood risk in 2021, also triggered by tropical cyclones. The highlighted initiatives, both technical and institutional, could have provided important references for the large river catchment managers in Southeast Asia and with implications of our method beyond the present application region.

Inferring floodplain bathymetry using inundation frequency.

This study proposes a new method to retrieve the bathymetry of turbid-water floodplains from the inundation frequency (IF) data derived from over 32 years of composite optical remote sensing data. The new method was tested and validated over the Curuai floodplain in the lower Amazon River, where the entire bathymetry was surveyed in 2004, and water level gauge data has been available since 1960. The depth was estimated based on the relationship derived from IF and surveyed depth data, and the results were compared to those retrieved from bare-Earth DEM. We further assessed the sensitivity of the approach by analyzing the deepest part of the lake (i.e., permanent water body ~ 8m) with high IF, as well as the effect of gradual sedimentation in the lake over time. The results showed that the model is highly accurate and sensitive to IF changes even in the permanent water body areas, suggesting that this model can be used in other seasonal lakes worldwide with turbid-waters, where large-scale bathymetry surveys are not feasible due to high operation costs.