Debris Flow Warning Threshold Based on Antecedent Rainfall:a Case Study in Jiangjia Ravine,Yunnan,China

Debris flows in Jiangjia Ravine in Yunnan province, China are not only triggered by intense storms but also by short-duration and low-intensity rainfalls. This reflects the significance of antecedent rainfall. This paper tries to find the debris flow- triggering threshold by considering antecedent rainfall through a case study in Jiangjia Ravine. From 23 debris flow events, the I-D （Intensity-Duration） threshold was found, which is very dose to the line of 95th percentile regression line of rainfall events, representing that 95% of rainfalls can potentially induce debris flows and reflects the limitation of I-D threshold application in this area. Taking into account the effect of antecedent rainfall, the debris flowtriggering threshold for rainfall quantity and intensity is statistically and empirically derived. The relationships can be used in debris flow warning system as key thresholds. Coupling with the rainfall characteristics in this area, new thresholds are proposed as triggering and warning thresholds.

Genetic Mechanism of Water-Rich Landslide Considering Antecedent Rainfalls:A Case Study of Pingyikou Landslide in Three Gorges Reservoir Area

Water-rich slope,which could easily fail after prolonged or heavy rain,is very sensitive to rainfall.Pingyikou Landslide is a typical water-rich slope located in the Three Gorges Reservoir area of China.It was unstable because of the continuous rainfall that occurred from September to October 2017.To understand the deformation process and genetic mechanism of the landslide,the geomorphological features,geological characteristics,hydrological conditions,and rainfall characteristics were systematically studied by a detailed field investigation of the slope and monitoring of rainfall,water level,and displacement.In addition,the influence of different initial conditions on the stability of the slope was also studied through numerical simulation using measured rainfall data on the basis of which,the effect of antecedent rainfall on slope stability was studied by unsaturated seepage analysis method.The results show that the deformation of slope is strongly correlated with the rainfall and groundwater level,and this landslide is a typical rainfall-induced landslide.In the analysis of genetic mechanism of the same type of landslide,a maximum initial pore water pressure of -25 kPa as the initial condition is reasonable.And the antecedent rainfall has a greater effect on the stability of the slope,more than 10 days of antecedent rainfall should be considered when designing and controling the slope.

Evaluation of rainfall threshold models for debris flow initiation in the Jiangjia Gully,Yunnan Province,China

Systematically determining the discriminatory power of various rainfall properties and their combinations in identifying debris flow occurrence is crucial for early warning systems.In this study,we evaluated the discriminatory power of different univariate and multivariate rainfall threshold models in identifying triggering conditions of debris flow in the Jiangjia Gully,Yunnan Province,China.The univariate models used single rainfall properties as indicators,including total rainfall(R_(tot)),rainfall duration(D),mean intensity(I_(mean)),absolute energy(Eabs),storm kinetic energy(E_(s)),antecedent rainfall(R_(a)),and maximum rainfall intensity over various durations(I_(max_dur)).The evaluation reveals that the I_(max_dur)and Eabs models have the best performance,followed by the E_(s),R_(tot),and I_(mean)models,while the D and R_(a)models have poor performances.Specifically,the I_(max_dur)model has the highest performance metrics at a 40-min duration.We used logistic regression to combine at least two rainfall properties to establish multivariate threshold models.The results show that adding D or R_(a)to the models dominated by Eabs,E_(s),R_(tot),or I_(mean)generally improve their performances,specifically when D is combined with I_(mean)or when R_(a)is combined with Eabs or E_(s).Including R_(a)in the I_(max_dur)model,it performs better than the univariate I_(max_dur)model.A power-law relationship between I_(max_dur)and R_(a)or between Eabs and R_(a)has better performance than the traditional I_(mean)–D model,while the performance of the E_(s)–R_(a)model is moderate.Our evaluation reemphasizes the important role of the maximum intensity over short durations in debris flow occurrence.It also highlights the importance of systematically investigating the role of R_(a)in establishing rainfall thresholds for triggering debris flow.Given the regional variations in rainfall patterns worldwide,it is necessary to evaluate the findings of this study across diverse watersheds.

Climate Variability & Establishment of Rainfall Threshold Line for Landslide Hazards in Rangamati, Bangladesh

This study aims to evaluate the impact of extreme rainfall events on landslides under current and past climate scenarios. Rainfall-triggered landslides are analyzed by rainfall estimates, derived using statistics of events. It is established that recent climate changes, mainly temperature and rainfall patterns have significantly increased the rainfall-induced landslide hazards in the Rangamati district, Bangladesh. It is also observed that the temperature and rainfall of Rangamati had increased gradually during the last 40 years (1981-2021). On 13 June 2017, a series of landslides triggered by heavy monsoon rains (300 mm/24 h) occurred and killed more than 112 people in the Rangamati hill district, Bangladesh. The highest annual decade rainfall is 3816 mm, recorded in 2010-21. A relationship between causalities and the number of events has also been established. The analysis shows that both antecedent and single-day major rainfall patterns can influence sliding events. It is established that monsoonal rainfall (June-September) can significantly influence catastrophic landslide hazard events. Finally, two rainfall threshold lines for the researched area are constructed based on antecedent and single-day major rainfall occurrences, as well as the number of fatalities caused by landslides. Total rainfall of 100 mm (16.66 mm/day) during six days appears to define the minimum rainfall that has led to shallow landslides/slope failures, while 210 mm (35 mm/day) within six days appears to define the lowest rainfall that could be a cause of catastrophic landslide in Rangamati district.