Event-based probabilistic risk assessment of livestock snow disasters in the Qinghai–Tibetan Plateau

Abstract

Abstract. Understanding risk using quantitative risk assessment offers critical information for risk-informed reduction actions, investing in building resilience, and planning for adaptation. This study develops an event-based probabilistic risk assessment (PRA) model for livestock snow disasters in the Qinghai–Tibetan Plateau (QTP) region and derives risk assessment results based on historical climate conditions (1980–2015) and present-day prevention capacity. In the model, a hazard module was developed to identify and simulate individual snow disaster events based on boosted regression trees. By combining a fitted quantitative vulnerability function and exposure derived from vegetation type and grassland carrying capacity, we estimated risk metrics based on livestock mortality and mortality rate. In our results, high-risk regions include the Nyainqêntanglha Range, Tanggula Range, Bayankhar Mountains and the region between the Kailas Range and the neighbouring Himalayas. In these regions, annual livestock mortality rates were estimated as >2 % and mortality was estimated as >2 sheep unit km−1 at a return period of 20 years. Prefectures identified with extremely high risk include Guoluo in Qinghai Province and Naqu, and Shigatse in the Tibet Autonomous Region. In these prefectures, a snow disaster event with a return period of 20 years or higher can easily claim total losses of more than 500 000 sheep units. Our event-based PRA results provide a quantitative reference for preparedness and insurance solutions in reducing mortality risk. The methodology developed here can be further adapted to future climate change risk analyses and provide important information for planning climate change adaption in the QTP region.

Snow Disaster Hazard Assessment on the Tibetan Plateau Based on Copula Function

“…However, the interannual variation of snowfall in the TP region is also regulated by the ocean-atmosphere coupling system, such as El Niño-Southern Oscillation (ENSO) and sea-surface temperature (SST), which have an impact on the occurrence of snow disasters [57][58][59]. Furthermore, research has found that as the pure income of herders' families increased and infrastructure such as shelters improved, continuous socioeconomic development led to a decrease in annual livestock losses caused by snow disasters during the period from 1981 to 2015, at the rate of −7% year −1 [17]. Undoubtedly, socioeconomic development will have an impact on the results of snow disaster risk assessment [15].…”

“…With the instability of the climate system intensifying due to global climate change [13], the frequency and intensity of snow disasters on the Tibetan Plateau may further increase, exacerbating the region's already fragile ecological system and socio-economic development [14]. Table 1 presents a list of significant historical snow disaster events and their respective losses in the Tibetan Plateau, lending strong support to the critical importance and value of snow disaster hazard assessment [15][16][17][18][19][20]. [11] Snow disasters on the Tibetan Plateau are the result of a complex interplay of multiple factors, such as temperature, snowfall, snow depth, snow duration, and affected area, among others.…”

“…Bai used snow depth to represent the hazard of snow disasters and evaluated the risk of snow disaster loss in different return periods in Qinghai Province, combined with vulnerability [29]. Ye constructed a snow disaster event identifier-simulator to calculate the frequency and duration of snow damage based on historical event data to characterize snow hazard on the Tibetan Plateau [17]. While these studies quantitatively analyze snow hazards, most of them are characterized by single disaster factors or historical information, which cannot comprehensively reflect snow hazards.…”