Spatiotemporal Hotspots and Decadal Evolution of Extreme Rainfall-Induced Landslides: Case Studies in Southern Taiwan

The 2009 Typhoon Morakot triggered numerous landslides in southern Taiwan, and the landslide ratios in the Ailiao and Tamali river watershed were 7.6% and 10.7%, respectively. The sediment yields from the numerous landslides that were deposited in the gullies and narrow reaches upstream of Ailiao and Tamali river watersheds dominated the landslide recovery and evolution from 2010 to 2015. Rainfall records and annual landslide inventories from 2005 to 2015 were used to analyze the landslide evolution and identify the landslide hotspots. The landslide recovery time in the Ailiao and Tamali river watershed after 2009 Typhoon Morakot was estimated as 5 years after 2009 Typhoon Morakot. The landslide was easily induced, enlarged, or difficult to recover during the oscillating period, particularly in the sub-watersheds, with a landslide ratio > 4.4%. The return period threshold of rainfall-induced landslides during the landslide recovery period was <2 years, and the landslide types of the new or enlarged landslide were the bank-erosion landslide, headwater landslide, and the reoccurrence of old landslide. The landslide hotspot areas in the Ailiao and Tamali river watershed were 2.67–2.88 times larger after the 2009 Typhoon Morakot using the emerging hot spot analysis, and most of the new or enlarged landslide cases were identified into the oscillating or sporadic or consecutive landslide hotspots. The results can contribute to developing strategies of watershed management in watersheds with a dense landslide.

Application of High-Resolution Radar Rain Data to the Predictive Analysis of Landslide Susceptibility under Climate Change in the Laonong Watershed, Taiwan

Extreme rainfall has caused severe road damage and landslide disasters in mountainous areas. Rainfall forecasting derived from remote sensing data has been widely adopted for disaster prevention and early warning as a trend in recent years. By integrating high-resolution radar rain data, for example, the QPESUMS (quantitative precipitation estimation and segregation using multiple sensors) system provides a great opportunity to establish the extreme climate-based landslide susceptibility model, which would be helpful in the prevention of hillslope disasters under climate change. QPESUMS was adopted to obtain spatio-temporal rainfall patterns, and further, multi-temporal landslide inventories (2003–2018) would integrate with other explanatory factors and therefore, we can establish the logistic regression method for prediction of landslide susceptibility sites in the Laonong River watershed, which was devastated by Typhoon Morakot in 2009. Simulations of landslide susceptibility under the critical rainfall (300, 600, and 900 mm) were designed to verify the model’s sensitivity. Due to the orographic effect, rainfall was concentrated at the low mountainous and middle elevation areas in the southern Laonong River watershed. Landslide change analysis indicates that the landslide ratio increased from 1.5% to 7.0% after Typhoon Morakot in 2009. Subsequently, the landslide ratio fluctuated between 3.5% and 4.5% after 2012, which indicates that the recovery of landslide areas is still in progress. The validation results showed that the calibrated model of 2005 is preferred in the general period, with an accuracy of 78%. For extreme rainfall typhoons, the calibrated model of 2009 would perform better (72%). This study presented that the integration of multi-temporal landslide inventories in a logistic regression model is capable of predicting rainfall-triggered landslide risk under climate change.

Drawing the landslide susceptibility maps based on long term evolution of extreme rainfall-induced landslide

&lt;p&gt;This research is concerned with the prediction accuracy and applicability of statistical landslide susceptibility model to the areas with dense landslide distribution caused by extreme rainfall events and how to draw the annual landslide susceptibility maps after the extreme rainfall events. The landslide induced by 2009 Typhoon Morakot, i.e. an extreme rainfall event, in the Chishan river watershed is dense distributed. We compare the annual landslide inventories in the following 5 years after 2009 Typhoon Morakot and finds the similarity of landslide distribution.&lt;/p&gt;&lt;p&gt;The landslide distributions from 2008 to 2014 are concentrated in the midstream and upstream watersheds. The landslide counts and area in 2009 are 3.4 times and 7.4 times larger than those in 2008 due to 2009 Typhoon Morakot. The landslide counts and area in 2014 are only 69.8% and 53.4 % of those in 2009. The landslide area from 2010 to 2014 shows that the landslide area in the following years after 2009 Typhoon Morakot gradually decreases if without any heavy rainfall event with more accumulated rainfall than that during 2009 Typhoon Morakot.&lt;/p&gt;&lt;p&gt;The landslide ratio in the upstream watershed in 2008 is 1.37%, and that from 2009 to 2014 are over 3.51%. The landslide ratio in the upstream watershed in 2014 is 1.17 times larger than that in 2009. On average, the landslide inventory from 2010 to 2014 in the upstream watershed is composed of 60.1 % old landslide originated from 2009 Typhoon Morakot and 39.9 % new landslide.&lt;/p&gt;&lt;p&gt;The landslide ratio in the midstream watershed reaches peak (9.19%) in 2009 and decreases gradually to 2.56 % in 2014. The landslide ratio in 2014 in the midstream watershed is only 27.9% of that in 2009, and that means around 72.1 % of landslide area in 2009 in the midstream watershed has recovered. On average, the landslide inventory from 2010 to 2014 in the midstream watershed is composed of 76.1 % old landslide originated from 2009 Typhoon Morakot and 23.9 % new landslide.&lt;/p&gt;&lt;p&gt;The research uses the landslide area in 2009 and 2014 in the same subareas to calculate the expanding or contracting ratio of landslide area. The contracting ratio of riverbank and non-riverbank landslide area in the midstream watershed are 0.760 and 0.788, while that in the downstream watershed are 0.732 and 0.789. The expanding ratio of riverbank and non-riverbank landslide area in the upstream watershed are 1.04 and 1.02.&lt;/p&gt;&lt;p&gt;The annual landslide susceptibility in each subarea in the Chishan river watershed in a specific year from 2010 to 2014 is the production of landslide susceptibility in 2009 and the contraction or expanding ratio to the Nth power, and the N number is how many years between 2009 and the specific year. We adopt the above-mentioned equation and the landslide susceptibility model based on the landslide inventory after 2009 Typhoon Morakot to draw the annual landslide susceptibility maps in 2010 to 2014. The mean correct ratio value of landslide susceptibility model in 2009 is 70.9%, and that from 2010 to 2014 are 62.5% to 73.8%.&lt;/p&gt;