Early warning of snow-caused disasters in pastoral areas on the Tibetan Plateau

Abstract

This study develops a model for early warning of snow-caused livestock disasters on a county basis and proposes a method of qualitative risk assessment of snow disasters at 500 m resolution for pastoral areas on the Tibetan Plateau (TP). Data used for the model development include remote sensing data, statistical data of weather, livestock, and social economy, and 45 typical snow disaster cases from 2000 to 2010. The principal component analysis (PCA) approach is used to choose 7 crucial factors that contribute over 85% of information for early warning snow disasters on the TP. They are mean annual probability of snow disaster, number of snow-covered days, livestock stocking rate, continual days of mean daily temperature below −10 °C, grassland burial index, rate of snow-covered grassland, and per livestock gross domestic product. The chosen 411 cases from 2008 to 2010 are used to validate the prediction results from the developed early warning model, with an overall accuracy of 85.64% in predicting snow disasters and no disasters. This suggests that the early warning approach developed in the study has operational potential for predicting snow disasters on the TP

Variability in snow cover phenology in China from 1952 to 2010

“…Simulation exper-iments using climate models indicated that, with continuing global warming, the snow cover in China would show more variations in space and time than ever before (Shi et al, 2011;Ji and Kang, 2013). Spatiotemporal variations of snow cover are also manifested as snowstorms or blizzards, particularly excessive snowfall over a short time duration (Bolsenga and Norton, 1992;Liang et al, 2008;Gao, 2009;Wang et al, 2013;Llasat et al, 2014).…”

Spatio-Temporal Change of Snow Cover and Its Response to Climate over the Tibetan Plateau Based on an Improved Daily Cloud-Free Snow Cover Product

“…Global warming has accelerated the rate of glacier melt and has increased precipitation and caused a redistribution of precipitation [39]. This increased rate of melting and precipitation has caused more frequent flooding and snow disasters [31,40]. The results also demonstrate that the snow-cover dynamics on the TP influence the atmospheric circulation and the weather system in East Asia, which further influence the climate of China [34,41,42].…”

Snow Disaster Early Warning in Pastoral Areas of Qinghai Province, China

“…The studies mainly focused on snow disaster monitoring methods [8][9][10], spatiotemporal analyses of the disaster-causing factors [7,11,12], snow disaster risk zoning and evaluation [12][13][14][15][16][17][18], and snow disaster early warning modeling and hazard assessment [1,3,[18][19][20][21][22]. Many of these studies are both qualitative and quantitative and span from hazard evaluations of snow disasters to spatiotemporal early warning systems for snow disasters, as well as from single-factor models to multi-factor models.…”

“…Snow disaster early warning includes the probabilistic prediction of the hazard area and intensity of a snow disaster that is most likely to occur in the near future. Some studies only focused on assessing prior snow-caused disasters for the factors that caused the disasters and the associated damages [2,7,18,23], the vulnerability and resilience of a hazard-bearing body [17,24] and multi-factor, comprehensive early warning models [3,21,25]. However, only a few studies intended to combine potential risk assessments of a certain area into an early warning model for snow-caused disasters.…”

“…The existing results of modeling a snow disaster for early warning purposes have some inherent weaknesses. For instance, some models do not consider the effects of factors outside the grassland animal husbandry system on snow disasters [26] and the effects of human intervention on the degree of damage of snow disasters [21]. They also ignored the effects of herding, meteorological factors, and other factors on snow disaster hazards [3].…”