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

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2090
Author(s):  
Chunhung Wu ◽  
Chengyi Lin
Keyword(s):  
Hot Spot ◽  
Recovery Period ◽  
Extreme Rainfall ◽  
Bank Erosion ◽  
Typhoon Morakot ◽  
River Watershed ◽  
Sediment Yields ◽  
Landslide Evolution ◽  
Southern Taiwan ◽  
Landslide Ratio

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.

scholarly journals Landslide Susceptibility Based on Extreme Rainfall-Induced Landslide Inventories and the Following Landslide Evolution

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2609 ◽  
Author(s):  
Chunhung Wu
Keyword(s):  
Landslide Susceptibility ◽  
Extreme Rainfall ◽  
Susceptibility Map ◽  
Typhoon Morakot ◽  
Landslide Susceptibility Map ◽  
Related Factors ◽  
Extreme Rainfall Events ◽  
River Watershed ◽  
Correct Ratio ◽  
Landslide Evolution

Landslide susceptibility assessment is crucial for mitigating and preventing landslide disasters. Most landslide susceptibility studies have focused on creating landslide susceptibility models for specific rainfall or earthquake events, but landslide susceptibility in the years after specific events are also valuable for further discussion, especially after extreme rainfall events. This research provides a new method to draw an annual landslide susceptibility map in the 5 years after Typhoon Morakot (2009) in the Chishan River watershed in Taiwan. This research establishes four landslide susceptibility models by using four methods and 12 landslide-related factors and selects the model with the optimum performance. This research analyzes landslide evolution in the 5 years after Typhoon Morakot and estimates the average landslide area different ratio (LAD) in upstream, midstream, and downstream of the Chishan River watershed. We combine landslide susceptibility with the model with the highest performance and average annual LAD to draw an annual landslide susceptibility map, and its mean correct ratio ranges from 62.5% to 73.8%.

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

2020 ◽  
Author(s):  
Chunhung Wu
Keyword(s):  
Landslide Susceptibility ◽  
Extreme Rainfall ◽  
Landslide Inventory ◽  
Landslide Area ◽  
Typhoon Morakot ◽  
Extreme Rainfall Events ◽  
Susceptibility Maps ◽  
Susceptibility Model ◽  
Landslide Ratio ◽  
Landslide Susceptibility Maps

&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;

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

2020 ◽  
Vol 12 (23) ◽  
pp. 3855
Author(s):  
Chun-Wei Tseng ◽  
Cheng-En Song ◽  
Su-Fen Wang ◽  
Yi-Chin Chen ◽  
Jien-Yi Tu ◽  
...  
Keyword(s):  
Climate Change ◽  
Logistic Regression ◽  
High Resolution ◽  
Landslide Susceptibility ◽  
Extreme Rainfall ◽  
Typhoon Morakot ◽  
Multi Temporal ◽  
High Resolution Radar ◽  
Rain Data ◽  
Landslide Ratio

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.

scholarly journals Assessment of Rainfall-Induced Landslide Distribution Based on Land Disturbance in Southern Taiwan

2021 ◽  
Vol 10 (4) ◽  
pp. 209
Author(s):  
Chih-Ming Tseng ◽  
Yie-Ruey Chen ◽  
Chwen-Ming Chang ◽  
Yung-Sheng Chue ◽  
Shun-Chieh Hsieh
Keyword(s):  
Satellite Image ◽  
Extreme Rainfall ◽  
Land Area ◽  
Rainfall Events ◽  
Land Disturbance ◽  
Bare Land ◽  
Southern Taiwan ◽  
The Impact ◽  
Landslide Distribution ◽  
The Relationship

This study explores the impact of rainfall on the followed-up landslides after a severe typhoon and the relationship between various rainfall events and the occurrence, scale, and regional characteristics of the landslides, including second landslides. Moreover, the influence of land disturbance was evaluated. The genetic adaptive neural network was used in combination with the texture analysis of the geographic information system for satellite image classification and interpretation to analyze land-use change and retrieve disaster records and surface information after five rainfall events from Typhoon Morakot (2009) to Typhoon Nanmadol (2011). The results revealed that except for extreme Morakot rains, the greater the degree of slope disturbance after rain, the larger the exposed slope. Extreme rainfall similar to Morakot strikes may have a greater impact on the bare land area than on slope disturbance. Moreover, the relationship between the bare land area and the index of land disturbance condition (ILDC) is positive, and the ratio of the bare land area to the quantity of bare land after each rainfall increases with the ILDC. With higher effective accumulative rainfall on the slope in the study area or greater slope disturbance, the landslide area at the second landslide point tended to increase.

Recurrent landslides in Southern Western Ghats, India: A changing environmental perspective

2021 ◽  
Author(s):  
Asokan Laila Achu ◽  
Girish Gopinath
Keyword(s):  
Western Ghats ◽  
Hot Spot ◽  
Extreme Rainfall ◽  
Vital Role ◽  
Monsoon Period ◽  
Extreme Rainfall Events ◽  
South West ◽  
South West Monsoon ◽  
West Monsoon ◽  
The Western Ghats

&lt;p&gt;The Western Ghats (WG), an elevated passive continental margin along the southwestern coast of India, is the most widely populated biodiversity hot spot in the world. Monsoon climate is prevalent throughout the length of the Western Ghats. The WG region is prone to the occurrence of various hydro-climatic disasters such as extreme rainfall-driven floods and landslides. During the past 100 years, landslides and floods caused by extreme rainfall events in the WG have occurred in 1924 and 1979; but the most disastrous event, in terms of area of impact, loss of life and economic impact, occurred in August 2018. Generally, the south-west monsoon (Indian summer monsoon) occurs in the first week of June and extends up to September and the Indian Meteorological Department (IMD) predicted above-normal rainfall of 13% during the month of August 2018. But the State received an excess of 96% during the period from 1st to 30th August 2018, and 33% during the entire monsoon period till the end of August. The unprecedented heavy rains, storms, floods and associated thousands of landslides have caused exorbitant losses including 400 life losses, over 2.20 lakh people were displaced, and 20000 homes and 80 dams were damaged or destructed. This study aimed to elucidate the reasons behind the thousands of landslides caused in WG using observed and field evidences. Changes in south-west monsoon pattern and rainfall intensity played a vital role in the occurrence of landslides in WG. Further, the extensive causalities are the result of anthropogenic disturbances including landscape alterations and improper landuse practices in the hilly tracks of WG. The major causative factors for series of landslides in various segments of WG is due to hindrance of lower order streams/springs, vertical cutting, intensive quarrying, unscientific rain pits &amp; man-made structures together with erratic rainfall triggered major and minor landslides in various segments of WG. The present investigation concludes that a scientific landuse policy and geoscientific awareness is essential to mitigate the environment.&lt;/p&gt;

scholarly journals Post-disaster assessment of landslides in southern Taiwan after 2009 Typhoon Morakot using remote sensing and spatial analysis

2010 ◽  
Vol 10 (10) ◽  
pp. 2179-2190 ◽  
Author(s):  
F. Tsai ◽  
J.-H. Hwang ◽  
L.-C. Chen ◽  
T.-H. Lin
Keyword(s):  
Spatial Analysis ◽  
Change Detection ◽  
Satellite Images ◽  
Regional Scale ◽  
Typhoon Morakot ◽  
Change Detection Analysis ◽  
Detection Analysis ◽  
Disaster Assessment ◽  
Southern Taiwan ◽  
Post Disaster

Abstract. On 8 August 2009, the extreme rainfall of Typhoon Morakot triggered enormous landslides in mountainous regions of southern Taiwan, causing catastrophic infrastructure and property damages and human casualties. A comprehensive evaluation of the landslides is essential for the post-disaster reconstruction and should be helpful for future hazard mitigation. This paper presents a systematic approach to utilize multi-temporal satellite images and other geo-spatial data for the post-disaster assessment of landslides on a regional scale. Rigorous orthorectification and radiometric correction procedures were applied to the satellite images. Landslides were identified with NDVI filtering, change detection analysis and interactive post-analysis editing to produce an accurate landslide map. Spatial analysis was performed to obtain statistical characteristics of the identified landslides and their relationship with topographical factors. A total of 9333 landslides (22 590 ha) was detected from change detection analysis of satellite images. Most of the detected landslides are smaller than 10 ha. Less than 5% of them are larger than 10 ha but together they constitute more than 45% of the total landslide area. Spatial analysis of the detected landslides indicates that most of them have average elevations between 500 m to 2000 m and with average slope gradients between 20° and 40°. In addition, a particularly devastating landslide whose debris flow destroyed a riverside village was examined in depth for detailed investigation. The volume of this slide is estimated to be more than 2.6 million m3 with an average depth of 40 m.

scholarly journals A numerical study of convection in rainbands of Typhoon Morakot (2009) with extreme rainfall: roles of pressure perturbations with low-level wind maxima

2015 ◽  
Vol 15 (6) ◽  
pp. 8479-8523
Author(s):  
C.-C. Wang ◽  
H.-C. Kuo ◽  
R. H. Johnson ◽  
C.-Y. Lee ◽  
S.-Y. Huang ◽  
...  
Keyword(s):  
Wind Shear ◽  
Vertical Wind Shear ◽  
Extreme Rainfall ◽  
Vertical Wind ◽  
Cold Pool ◽  
Rear Side ◽  
Gradient Force ◽  
Typhoon Morakot ◽  
Low Level ◽  
Pressure Perturbations

Abstract. This paper investigates the formation and evolution of deep convection inside the east–west oriented rainbands associated with a low-level jet (LLJ) in Typhoon Morakot (2009). With typhoon center to the northwest of Taiwan, the westerly LLJ was resulted from the interaction of typhoon circulation with the southwest monsoon flow, which supplied the water vapor for the extreme rainfall (of ~1000 mm) over southwestern Taiwan. The Cloud-Resolving Storm Simulator with 1 km grid spacing was used to simulate the event, and it successfully reproduced the slow-moving rainbands, the embedded cells, and the dynamics of merger and back-building (BB) on 8 August as observed. Our model results suggest that the intense convection interacted strongly with the westerly LLJ that provided reversed vertical wind shear below and above the jet core. Inside mature cells, significant dynamical pressure perturbations (pd') are induced with positive (negative) pd' at the western (eastern) flank of the updraft near the surface and a reversed pattern aloft (>2 km). This configuration produced an upward directed pressure gradient force (PGF) to the rear side and favors new development to the west, which further leads to cell merger as the mature cells slowdown in eastward propagation. The strong updrafts also acted to elevate the jet and enhance the local vertical wind shear at the rear flank. Additional analysis reveals that the upward PGF there is resulted mainly by the shearing effect but also by the extension of upward acceleration at low levels. In the horizontal, the upstream-directed PGF induced by the rear-side positive pd' near the surface is much smaller, but can provide additional convergence for BB development upstream. Finally, the cold-pool mechanism for BB appears to be not important in the Morakot case, as the conditions for strong evaporation in downdrafts do not exist.

scholarly journals Discharge of landslide-induced debris flows: case studies of Typhoon Morakot in southern Taiwan

2014 ◽  
Vol 2 (1) ◽  
pp. 315-346
Author(s):  
J.-C. Chen ◽  
M.-R. Chuang
Keyword(s):  
Debris Flow ◽  
Case Studies ◽  
Debris Flows ◽  
Maximum Flow ◽  
Field Investigation ◽  
Typhoon Morakot ◽  
Flow Discharge ◽  
Modeling Software ◽  
Southern Taiwan ◽  
Deposition Depth

Abstract. Three debris-flow gullies, the Hong-Shui-Xian, Sha-Xin-Kai, and the Xin-Kai-Dafo gullies, located in the Shinfa area of southern Taiwan were selected as case studies of the discharge of landslide-induced debris flows caused by Typhoon Morakot in 2009. The inundation characteristics of the three debris flows, such as the debris-flow volume, the deposition area, maximum flow depth, and deposition depth, were collected by field investigations and simulated using the numerical modeling software FLO-2D. The discharge coefficient cb, defined as the ratio of the debris-flow discharge Qdp to the water-flow discharge Qwp, was proposed to determine Qdp, and Qwp was estimated by a rational equation. Then, cb was calibrated by a comparison between the field investigation and the numerical simulation of the inundation characteristics of debris flows. Our results showed that the values of cb range from 6 to 18, and their values are affected by the landslide ratio The empirical relationships between Qdp and Qwp were also presented.

Testing the impacts of wildfire on hydrological and sediment response using the OpenLISEM model

2021 ◽  
Author(s):  
Jinfeng Wu ◽  
João Pedro Nunes ◽  
Jantiene E. M. Baartman
Keyword(s):  
Water Discharge ◽  
Extreme Rainfall ◽  
Fire Occurrence ◽  
Return Periods ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Erosion Risk ◽  
Sediment Yields ◽  
Splash Erosion ◽  
Event Based

&lt;p&gt;Wildfires have become a major concern to society in recent decades because increases in the number and severity of wildfires have negative effects on soil and water resources, especially in headwater areas. Models are typically applied to estimate the potential adverse effects of fire. However, few modeling studies have been conducted for meso-scale catchments, and only a fraction of these studies include transport and deposition of eroded material within the catchment or represent spatial erosion patterns. In this study, we firstly designed the procedure of event-based automatic calibration using PEST, parameters ensemble, and jack-knife cross-validation that is suitable for event-based OpenLISEM calibration and validation, especially in data-scarce burned areas. The calibrated and validated OpenLISEM proved capable of providing reasonable accurate predictions of hydrological responses and sediment yields in this burned catchment. Then the model was applied with design storms of six different return periods (0.2, 0.5, 1, 2, 5, and 10 years) to simulate and evaluate pre- and post-wildfire hydrological and erosion responses at the catchment scale. Our results show rainfall amount and intensity play a more important role than fire occurrence in the catchment water discharge and sediment yields, while fire occurrence is regarded as an important factor for peak water discharge, indicating that high post-fire hydro-sedimentary responses are frequently related to extreme rainfall events. The results also suggest a partial shift from flow to splash erosion after fire, especially for higher return periods, explained by a combination of higher splash erosion in burnt upstream areas with a limited sediment transport capacity of surface runoff, preventing flow erosion in downstream areas. In consequence, the pre-fire erosion risk in the croplands of this catchment is partly shifted to a post-fire erosion risk in upper slope forest and natural areas, especially for storms with lower return periods, although erosion risks in croplands are important both before and after fires. This is relevant, as a shift of sediment sources to burnt areas might lead to downstream contamination even if sediment yields remain small. These findings have significant implications to identify areas for post-wildfire stabilization and rehabilitation, which is particularly important given the predicted increase in the occurrence of fires and extreme rainfall events with climate change.&lt;/p&gt;

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