Attribution of typhoon-induced torrential precipitation in Central Vietnam, October 2020

In October 2020, Central Vietnam was struck by heavy rain resulting from a sequence of 5 tropical depressions and typhoons. The immense amount of water led to extensive flooding and landslides that killed more than 200 people, injured more than 500 people, and caused direct damages valued at approximately 1.2 billion USD. Here, we quantify how the intensity of the precipitation leading to such exceptional impacts is attributable to anthropogenic climate change. First, we define the event as the regional maximum of annual maximum 15-day average rainfall (Rx15day). We then analyse the trend in Rx15day over Central Vietnam from the observations and simulations in the PRIMAVERA and CORDEX-CORE ensembles, which pass our evaluation tests, by applying the generalised extreme value (GEV) distribution in which location and scale parameters exponentially covary with increasing global temperatures. Combining these observations and model results, we find that the 2020 event, occurring about once every 80 years (at least 17 years), has not changed in either probability of occurrence (a factor 1.0, ranging from 0.4 to 2.4) or intensity (0%, ranging from −8 to +8%) in the present climate in comparison with early-industrial climate. This implies that the effect of human-induced climate change contributing to this persistent extreme rainfall event is small compared to natural variability. However, given the scale of damage of this hazard, our results underline that more investment in disaster risk reduction for this type of rainfall-induced flood hazard is of importance, even independent of the effect of anthropogenic climate change. Moreover, as both observations and model simulations will be extended with the passage of time, we encourage more climate change impact investigations on the extreme in the future that help adaptation and mitigation plans and raise awareness in the country.

Aquatic Biological Diversity Responses to Flood Disturbance and Forest Management in Small, Forested Watersheds

We examined riparian system responses to an extreme rainfall event on 1–4 December 2007, in eleven small watersheds (mean area—13.2 km2) from 2008–2016 at debris flow, high flood, and low flood reaches (all extended overbank flows). Macroinvertebrate responses followed expected outcomes after extreme disturbance including increasing chironomids and other multi-voltine species. A core assemblage of twenty abundant and common species-maintained populations even after debris flow (likely by recolonizing quickly) with total richness during project of 253 including 183 rare species (<0.01 total abundance) supporting an annual turnover of species from 22 to 33%. Primary disturbance changes to habitat were declines in shade and in-channel wood at all reaches, more strongly at debris flow reaches. Macroinvertebrate communities across disturbance intensities became increasingly similar after the storm. Combined effects of the flood reducing channel complexity and previous logging decreasing in-channel wood recruitment from riparian systems, limits habitat complexity. Until this feature of forested watershed streams returns, there appears to be a ceiling on reach scale aquatic biological diversity.

Landslides Triggered by the May 2017 Extreme Rainfall Event in the East Coast Northeast of Brazil

Given the increasing occurrence of landslides on the East Coast Northeast of Brazil (ECNEB), it is essential to understand its conditions and triggering factors because meteorological anomalies triggered by a landslide will threaten life and property in the region. In this sense, this research aimed to diagnose the meteorological conditions that triggered landslides in the ECNEB in May 2017, evaluate the terrain’s intrinsic conditions using elevation, slope, and susceptibility parameters and determine critical precipitation thresholds for the city with the highest number of landslide risk areas in the region. A dynamic downscaling experiment was carried out using the Regional Climate Model (RegCM) to verify the ability of this model to represent rainfall over the ECNEB. The results from the intrinsic factors showed that the ECNEB is highly susceptible to landslides with various high-risk sectors for landslides to the population. The extreme rainfall event was associated with the convergence of humidity at low levels over the ocean, which contributed to landslides in the ECNEB, mainly in the State of Pernambuco, where 67 landslides were registered. The RegCM numerical simulation underestimated the high daily rainfall signal seen on the Tropical Rainfall Measuring Mission satellite. It is suggested that sensitivity tests can be performed using other physical parameters to find the best model configuration for the ECNEB. This work recommends that exploring the relationship between precipitation and landslides will provide objective criteria for assessing risk areas by contributing to the predictability of disasters in this region.