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Global assessment of storm disaster-prone areas
Damaging hydrological events are extreme phenomena, the source of multiple hazardous events with potentially serious impacts on human societies . Among these, floods and events causing flooding are identified as hydrological disasters, which also include meteorological disasters like thunderstorms. Like other extreme phenomena, hydrological disasters typically leave behind socio-economic damage, the severity of which depends on the resilience of the affected population and the available infrastructures . Potentially severe natural events are typically not classified as natural disasters if they occur in areas without a vulnerable population, e.g. deserts.
Advances in climate change research contribute to improved forecasts of hydrological extremes with potentially severe impacts on human societies and natural landscapes. Rainfall erosivity density (RED), i.e. rainfall erosivity (MJ mm hm-2 h-1 yr-1) per rainfall unit (mm), is a measure of rainstorm aggressiveness and a proxy indicator of damaging hydrological events. By using measured Ranfall Erosivity Density (RED) for 3,625 raingauges worldwide and applying kriging methodologies, we identify the damaging hydrological hazard-prone areas that exceed warning and alert thresholds (1.5 and 3.0 hm-2 h-1 yr-1, respectively).
We have analysed for the first time the spatial pattern of hydrological hazard associated with rainfall erosivity in a global-scale visualisation. The results indicated that about 31% and 19% of the world’s land area have a greater than 50% probability of exceeding the warning and alert thresholds of 1.5 and 3.0 hm-2 h-1 yr-1, respectively, with the most affected regions being tropical Latin America, South Africa, India and the Indian Archipelago.
Fig. 1. Global spatial patterns of kriged-probability map over the period 2002–2011. Exceedance of the rainfall erosivity density (RED) threshold-value at a) warning state: RED > 1.5 MJ hm-2 h-1 yr-1, and b) alert state: RED > 3.0 MJ hm-2 h-1 yr-1.
Quantifying the probability of exceeding threshold values of erosivity density in a way that enables meaningful comparisons with hydrological records is an important topic of study, and our article is a step forward towards this goal. Future studies should assess the results in diverse physical geographic conditions and socio-economic situations, taking into account that population density, infrastructures, plant density and other factors also influence the occurrence of damage. In addition, probability calculations have also to take into account particularly long periods of low rainfall intensity, which are not erosive but can lead to deadly flooding and landslides.
Reference:
Diodato N, Borrelli P, Panagos P, Bellocchi G (2022) Global assessment of storm disaster-prone areas. PLoS ONE 17(8): e0272161. https://doi.org/10.1371/journal.pone.0272161
Data: The data showing the probability of exceedance rainfall erosivity density threasholds are available. The point measured data for 3,625 stations can be requested from contact author (for scientific developments).