Assessing the Snow Disaster and Disaster Resistance Capability for Spring 2019 in China’s Three-River Headwaters Region

Quanqin Shao, Guobo Liu, Xiaodong Li, Haibo Huang, Jiangwen Fan, Liya Wang, Jiyuan Liu and Xingjian Guo
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Quanqin Shao: Key Laboratory of Land Surface Pattern and Simulation, The Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Guobo Liu: Key Laboratory of Land Surface Pattern and Simulation, The Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Xiaodong Li: Alpine Ecological Meteorological Laboratory, Qinghai Provincial Institute of Meteorological Sciences, Xining 810001, China
Haibo Huang: Key Laboratory of Land Surface Pattern and Simulation, The Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Jiangwen Fan: Key Laboratory of Land Surface Pattern and Simulation, The Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Liya Wang: Grassland Survey Planning and Design Section, Qinghai Provincial Station of Grassland, Xining 810008, China
Jiyuan Liu: Key Laboratory of Land Surface Pattern and Simulation, The Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Xingjian Guo: Key Laboratory of Land Surface Pattern and Simulation, The Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

Sustainability, 2019, vol. 11, issue 22, 1-14

Abstract: Frequent snowfall and low temperatures led to a considerable snow disaster in some areas of China’s Three-River Headwaters Region (TRHR) in Qinghai province in the spring of 2019, exerting a considerably negative influence on animal husbandry production in local grasslands. Based on a model of snow disaster classification and quantitative estimations of disaster-stricken animal husbandry, we propose a comprehensive disaster resistance capability index (CDRCI) using remote sensing, ground monitoring, and statistical investigations. With a comprehensive assessment of the space distribution and the magnitude of snow disasters, combined with a quantitative determination of disaster-stricken animal husbandry, the proposed CDRCI calculates how grassland animal husbandry is affected by snow disasters in different counties of the TRHR. The results indicate that approximately 2.31 million sheep and yaks were affected by moderate to severe snow disasters in the TRHR, accounting for 78.3% of the total livestock in the affected region. Of these affected livestock, approximately 1.54 million sheep and yaks were specifically affected by severe snow disasters, accounting for 52.1% of the total number of livestock. The CDRCIs for grassland animal husbandry in both Yushu and were moderate, being higher for the former than for the latter. We confirmed that the proposed CDRCI can accurately evaluate the magnitude of snow disasters in terms of how they affect grassland animal husbandry. The CDRCI is a way of relating the number of animal deaths to spatial disaster prevention and resistance. We expect that this research will provide important theoretical support for formulating snow disaster resistance policy, for example for increasing the construction of grassland animal husbandry infrastructure as well as providing greater stored forage material.

Keywords: Three-River Headwaters Region; snow disaster; grassland animal husbandry production; comprehensive snow disaster resistance capability; policy suggestions (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
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