15:30 〜 17:00
[HDS05-P03] Spatiotemporal Analysis of extreme rainfall-induced landslide evolution in Southern Taiwan
キーワード：Landslide evolution, spatiotemporal cluster analysis, landslide hotspots
The 2009 Typhoon Morakor caused numerous landslides and severe debris flow in southern Taiwan, and the landslide ratio in the Kaoping River watershed after the typhoon exceeded 6.5%. Over a decade since 2009, sediment-related disaster events still occurred in the Kaoping River watershed. The Ailiao river watershed (ARW) and Tamali river watershed (TRW) were the watersheds with the highest landslide ratio in southern Taiwan after 2009. The ARW and TRW were selected to observe the landslide evolution from 2005 to 2015 and identify the landslide hotspots and cold spots using the spatiotemporal cluster analysis.
Long-term geomorphologic landslide evolution in watersheds is strongly related to spatiotemporal landslide distribution which can be observed using the spatiotemporal cluster analysis with the digital elevation model and multi-annual landslide inventories. Landslide disaster studies using spatiotemporal cluster analysis have focused on discussing the long-term spatiotemporal distribution of disasters and analyzing the relationship between disaster occurrence and related factors. Spatiotemporal cluster analysis with multi-annual landslide inventories after extreme rainfall events can contribute to determining landslide hotspots and cold spots, identifying locations where the landslide recovery was difficult, and analyze the reasons behind these factors.
The ARW and TRW were selected to observe the landslide evolution from 2005 to 2015 and identify the landslide hotspots and cold spots using the spatiotemporal cluster analysis. The effective accumulated rainfall index (EAR) based on the daily rainfall records from 2005 to 2015 of the rainfall stations near the ARW and TRW was used to assess the landslide-induced strength of rainfall events. The EAR value and return periods of rainfall events from 2005 to 2008 in the two watersheds was larger than those from 2010 to 2015 based on the analysis result.
The annual landslide inventories from 2005 to 2015 in Taiwan were used in this study. The area and number of the landslide from 2010 to 2015 in the two watersheds were larger than those from 2005 to 2008. Most of the landslides induced by 2009 Typhoon Morakot gradually recovered, but some new landslides occurred in the two watersheds in 2013. The rainfall factor was possibly not the only landslide-inducing factor in the two watersheds after 2009.
The study used the landslide topographic position analysis to examine the landslide evolution before and after 2009 in the ARW and TRW. Most of the landslides in the subwatersheds with dense landslide in 2015 were centered in areas with a normalized distance to a ridge of >0.7, meaning that the inducing factors should be related to the bank-erosion landslide which was possibly induced by the sinuous rivers with huge deposited sediment.
We used the emerging hot spot analysis in the space-time cluster analysis tool in the ArcGIS Pro software to analyze the landslide evolution from 2005 to 2015. The emerging hot spot analysis tool can detect eight hotspot or coldspot trends. The landslide hotspots area from 2010 to 2015 in the ARW and TRW are 2.67–2.88 times larger than those from 2005 to 2008, and the landslide coldspots area is 1.73–1.93 times. This result means that the total time of areas identified as landslides from 2010 to 2015 is longer than that from 2005 to 2008. The landslide recovery was more difficult and the landslide was easier to be clustered after than before 2009 Typhoon Morakot.
The main pattern of landslide hotspot are oscillating, sporadic, and consecutive in each research period. The main hotspots from 2010 to 2015 in the sub-watershed with dense landslide were concentrated in the headwater landslides, bank-erosion landslides in sinuous reaches, and reoccurrence of older (from 2005 to 2008) landslides. The hotspot and coldspot distributions from 2005 to 2015, from 2005 to 2008, and from 2010 to 2015 in the ARW and TRW represent the long-term landslide evolution.
Long-term geomorphologic landslide evolution in watersheds is strongly related to spatiotemporal landslide distribution which can be observed using the spatiotemporal cluster analysis with the digital elevation model and multi-annual landslide inventories. Landslide disaster studies using spatiotemporal cluster analysis have focused on discussing the long-term spatiotemporal distribution of disasters and analyzing the relationship between disaster occurrence and related factors. Spatiotemporal cluster analysis with multi-annual landslide inventories after extreme rainfall events can contribute to determining landslide hotspots and cold spots, identifying locations where the landslide recovery was difficult, and analyze the reasons behind these factors.
The ARW and TRW were selected to observe the landslide evolution from 2005 to 2015 and identify the landslide hotspots and cold spots using the spatiotemporal cluster analysis. The effective accumulated rainfall index (EAR) based on the daily rainfall records from 2005 to 2015 of the rainfall stations near the ARW and TRW was used to assess the landslide-induced strength of rainfall events. The EAR value and return periods of rainfall events from 2005 to 2008 in the two watersheds was larger than those from 2010 to 2015 based on the analysis result.
The annual landslide inventories from 2005 to 2015 in Taiwan were used in this study. The area and number of the landslide from 2010 to 2015 in the two watersheds were larger than those from 2005 to 2008. Most of the landslides induced by 2009 Typhoon Morakot gradually recovered, but some new landslides occurred in the two watersheds in 2013. The rainfall factor was possibly not the only landslide-inducing factor in the two watersheds after 2009.
The study used the landslide topographic position analysis to examine the landslide evolution before and after 2009 in the ARW and TRW. Most of the landslides in the subwatersheds with dense landslide in 2015 were centered in areas with a normalized distance to a ridge of >0.7, meaning that the inducing factors should be related to the bank-erosion landslide which was possibly induced by the sinuous rivers with huge deposited sediment.
We used the emerging hot spot analysis in the space-time cluster analysis tool in the ArcGIS Pro software to analyze the landslide evolution from 2005 to 2015. The emerging hot spot analysis tool can detect eight hotspot or coldspot trends. The landslide hotspots area from 2010 to 2015 in the ARW and TRW are 2.67–2.88 times larger than those from 2005 to 2008, and the landslide coldspots area is 1.73–1.93 times. This result means that the total time of areas identified as landslides from 2010 to 2015 is longer than that from 2005 to 2008. The landslide recovery was more difficult and the landslide was easier to be clustered after than before 2009 Typhoon Morakot.
The main pattern of landslide hotspot are oscillating, sporadic, and consecutive in each research period. The main hotspots from 2010 to 2015 in the sub-watershed with dense landslide were concentrated in the headwater landslides, bank-erosion landslides in sinuous reaches, and reoccurrence of older (from 2005 to 2008) landslides. The hotspot and coldspot distributions from 2005 to 2015, from 2005 to 2008, and from 2010 to 2015 in the ARW and TRW represent the long-term landslide evolution.