| Recently,the frequency of natural disaster events has increased significantly under the influence of global climate change and human activities.The occurrence of natural disasters not only poses a serious threat to the personal and property safety of the residents,but also causes great damage to the ecological environment.In particular,landslides and debris flow are most prominent in mountainous areas.Therefore,the assessment and identification of ecological risk distribution pattern of natural disasters has become an important part of disaster response decision-making and a research hotspot of related disciplines.Based on the"source—flow—sink"theory and the landscape pattern,process,the previous paper selects three small watersheds in Hani Rice Terraces Heritage Site as the research object,to take the landslide disaster area as the source/sink patch,and the sediment as the ecological flow/ecological process.Then,we applied spatial principal component analysis to obtain the sensitivity zoning map of landslide disaster.The improved index of connectivity and hot spot analysis tool were used to analyze and identify the spatial characteristics and hot spots of sediment connectivity in the watershed.And discussed the relationship between landslide susceptibility and sediment connectivity.Finally,we integrated the landslide susceptibility and sediment connectivity to evaluate the ecological risk source pattern of landslide disaster.The minimum cumulative resistance model is used to identify the pattern and network of ecological risk of landslide disaster.Finally,the key patches and corridors of the ecological risk of landslide disasters are identified by gravity model and network structure index.This study puts forward the research method of ecological risk assessment under the stress of mountain landslide disaster,complements the case of disaster ecological risk study,and provides scientific basis for the prediction and prevention of landslide disaster risk of terrace heritage.The main conclusions are as follows:(1)The spatial distribution and susceptibility analysis of landslides in three small watersheds showed that the recorded landslides in the Bibo river watershed,Bimeng river watershed and Gota river watershed were 500,104 and 120 locations respectively,with a landslide area of 727,303m~2,87,961m~2 and 395,520m~2 respectively,and the largest landslide area was 112,074m~2,6,914m~2 and 122,949m~2 respectively.The core density analysis showed that the core density of landslides is decreasing gradually in the three watersheds.The landslides susceptibility level suggested that the sensitivity grades of the three watersheds are in the order of Bibo river watershed,Gota river watershed and Bimeng river watershed.The overall disaster susceptibility level of Bibo river watershed is relatively high,and its high susceptibility area of 26.61%is mainly distributed on both sides of the road.Whereas the high susceptibility area of Bimeng river watershed accounts for 23.94%,mainly distributed near the water outlet and road of the basin.The area of highly susceptibility area in Gota river watershed accounts for26.49%,which is mainly distributed near the water system.(2)The assessment and analysis of sediment connectivity showed that the Bibo river watershed is the highest in terms of average value and changed range of sediment connectivity,which indicated the erosion in this area is easy to occur.In terms of spatial distribution,the sediment connectivity of three watersheds performed that the closer the distance to river and road,the greater the connectivity value is,the larger the valley area and the smaller the slope area.In terms of landscape composition,the sediment connectivity of Bibo river and Bimeng river watershed in dry land is higher than that of paddy field.For the Gota River watershed,the connectivity value of paddy field is higher than that of dry land.According to the results of hot spot analysis,the hot spot area of Bibo river watershed is largest,accounting for 9.22%of the total area,and it is mainly distributed in the middle of Mengpin village in the lower reaches of the watershed,which explains the causes of frequent landslides.The hot spot area of Bimeng River watershed accounts for 8.63%of the total area,mainly distributed in the East,and the hot spot area of Gota River watershed accounts for 9.53%of the total area,most concentrated in the northwest.(3)The comprehensive assessment of basin disaster risk based on landslide disaster sensitivity and sediment connectivity shows that the patches with extremely high ecological risk more than 1km~2 are used as the source of landslide disaster ecological risk,and the risk source areas of Bibo,Bimeng and Gota river watersheds are 14,027,779m~2,4,451,965m~2 and 10,308,337m~2,respectively,accounting for 1.15%,1.19%and 1.13%of the area of the patches with extremely high risk.The importance index of risk source patches shows that the area of the most important patches in Bibo river watershed is the largest.The disaster ecological risk corridors identified based on the Minimum cumulative resistance model have 269,131 and 252 paths in corresponding three watersheds,accounting for 26.70%,30.55%and 33.06%of the total area respectively.The results of gravity model show that there are 26 important corridors in the Bibo river watershed,and the ecological network is relatively complete and densely distributed in the whole watershed.There are 18 corridors in the Bimeng river watershed,which are mainly concentrated in the southwest of the watershed,with poor connectivity in the north,and the ecological network is not perfect.There are 14corridors in the Gota River watershed,which are mainly distributed in the south of the basin.The main landscape types of ecological risk corridor are mainly forest land in three basins,which shows that forest land plays a great role in the process of sediment transport.On the whole,the landslide risk networks of the three watersheds are basically linked into a ring,and the patches can basically connect with each other,which provides good conditions for regional disaster risk management. |
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