Flood Simulations in Mid-Latitude Agricultural Land Using Regional Current and Future Extreme Weathers

Abstract

Recent extreme weather events like the August 2016 flood disaster have significantly affected farmland in mid-latitude regions like the Tokachi River (TR) watershed, the most productive farmland in Japan. The August 2016 flood disaster was caused by multiple typhoons that occurred in the span of two weeks and dealt catastrophic damage to agricultural land. This disaster was the focus of our flood model simulations. For the hydrological model input, the rainfall data with 0.04° grid space and an hourly interval were provided by a regional climate model (RCM) during the period of multiple typhoon occurrences. The high-resolution data can take account of the geographic effects, hardly reproduced by ordinary RCMs. The rainfall data drove a conceptual, distributed rainfall–runoff model, embedded in the integrated flood analysis system. The rainfall–runoff model provided discharges along rivers over the TR watershed. The RCM also provided future rainfall data with pseudo-global warming climate, assuming that the August 2016 disaster could reoccur again in the late 21st century. The future rainfall data were used to conduct a future flood simulation. With bias corrections, current and future flood simulations showed the potential inundated areas along riverbanks based on flood risk levels. The crop field-based agricultural losses in both simulations were estimated. The future cost may be two to three times higher as indicated by slightly higher simulated future discharge peaks in tributaries.

Assessment of climate change impact on probable maximum floods in a tropical catchment

“…The relationship between rainfall and runoff is always very di cult to be structured because of the immense spatial and temporal variability of rainfall and the physical characteristics of the watershed, as well as a few hydrological features of the watershed that should be included in the model process (Choi, Shin, & Kim, 2020;Gan, He, & Qin, 2020;Ling et al, 2019). Therefore, many R-R models have been developed over time based on a different concept (Kimura et al, 2019). The existing R-R models could be categorized into three main classes, empirical, conceptual and physical.…”