Effect of the Rainfall Infiltration Processes on the Landslide Hazard Assessment of Unsaturated Soils in Tropical Mountainous Regions

Abstract

Natural disasters caused by meteorological phenomena are affecting countries of the world with increasing frequency, and they are producing severe damage to population and its infrastructure, hampering the economic development of the countries. The rainfallinduced landslides occur almost every year in all mountainous regions, and globally, 14% of economic losses and 0.53% of deaths from disasters caused by natural phenomena are attributed to landslides. For this reason, landslide risk assessment has become more applied in recent years. We present an assessment of the effect of rainfall infiltration on unsaturated soils on slope stability. Initially, a theoretical approach of the problem is presented, and a model of probabilistic analysis is described. Subsequently, an application of the model is carried out in an eastern zone of Medellin, Colombia. The probability of saturation and the landslide hazard are determined and validated considering the effect of a rainfall event registered in November 2010 that caused severe damages in the studied zone. The influence of infiltration under static scenario is evaluated using two different approaches, and the soil parameters for these evaluations are determined by field and laboratory tests. Finally, the effect of the rainfall infiltration processes on the landslide hazard assessment of evaluated unsaturated soils is determined.

Biochar stability assessment by incubation and modelling: Methods, drawbacks and recommendations

“…Para evaluar la respuesta obtenida, se ha realizado una búsqueda bibliográfica, en esta se pudo encontrar que otros autores reportan datos de simulaciones y experimentales, en los cuales se evidencia la variación de la saturación del suelo en función de la profundidad, al igual que los resultados encontrados en la simulación se observa que a medida que aumenta la profundidad la saturación va disminuyendo, uno de los modelos encontrados en la revisión bibliográfica es el modelo de Fredlund y King el cual está relacionado con la presión del aire, la porosidad y distribución de poros, esta permite evaluar la infiltración y saturación del suelo en este se encuentra la probabilidad de saturación del suelo, la cual al disminuye con la profundidad; por otro lado, Ochsner presenta el movimiento del agua en el suelo por medio de un modelo dinámico en el software CHEMFLO, en el cual se identificó que al ingresar agua cerca del estado de saturación la velocidad del frente húmedo o el contenido volumétrico de agua va disminuyendo con el tiempo y la profundidad, es decir la saturación del suelo disminuye a medida que aumenta la profundidad del suelo; Oliveira, realizó un estudio experimental en un periodo de dos años estudiando cambios en la saturación del suelo con aplicación de cal, a medida que aumenta la profundidad se presenta una disminución en la saturación del suelo; por lo que la respuesta que se obtiene para la saturación es coherente con lo reportado en la literatura, cabe resaltar que este comportamiento puede variar en función de las propiedades del suelo, ya que condición de frontera a la salida depende de propiedades del suelo como la porosidad, potencial de succión, permeabilidad, entre otras (Guo 2020;Hidalgo, Vega, and Obando 2018;Ochsner 2019;Oliveira et al 2003).…”

Prediction of landslide induced debris’ severity using machine learning algorithms: a case of South Korea

“…Rainfall data were grouped into twelve variables: cumulative rainfall, continuous hourly rainfall, three hours, six hours, nine hours, twelve hours, one day, three days, seven days, two weeks, three weeks, and four weeks' rainfall. Different measures of rainfall were captured due to the time-dependent cumulative effect of rainfall on the slope stability, and prolonged rainfall has a more damaging effect in mountainous regions (Baum and Godt 2010;Hidalgo et al 2017;Meena et al 2022). The conditioning factors, i.e., soil type, topsoil depth, altitude, slope, slopelength, slope aspect, and vegetation (leafage, size of tree, age of trees, and fire history), were collected.…”

Experimental Study of Site-Specific Soil Water Content and Rainfall Inducing Shallow Landslides: Case of Gakenke District, Rwanda

“…Rainfall-induced shallow landslides are among the most natural disasters that causes deaths and substantial economic losses damaging infrastructure or plants in different mountainous regions around the world [1][2][3]. In Rwanda, about 1,000 landslide cases have been identified during the past decade [4], affecting a significant number of citizens, agriculture land, livelihoods, and infrastructure that are valued in billions of dollars.…”

“…Numerous studies have been undertaken broadly to reduce the impact of landslides on human lives and economic loss. They include various prediction models, susceptibility models, and landslide early warning systems (LEWS) [3,10]. Some of the models establish the relationship between landslide occurrence and rainfall intensity through the laboratory field test as well as numerical analysis [22,23]; others estimated the rainfall intensity and duration that could cause landslide incidences [10,[24][25][26][27][28].…”

“…Past studies have used the laboratory flume test to identify the correlation between soil water content and landslide occurrence where rainfall, soil type (particle size), and slope inclination have been taken into consideration [16,20,[36][37][38][39]. Others used empirical field tests [39,40] or numerical modelling [3,41], and various studies conducted on LEWS have generally used historical rainfall data together with landslide occurrence records to determine the rainfall threshold inducing landslides [34,[42][43][44][45][46][47][48]. The studies conducted in [22,[49][50][51][52][53][54][55][56] have shown that they have used antecedent rainfall as a key parameter that has a great impact on landslides' occurrence.…”