Effects of pore water pressure on the slope profile of a laboratory simulated rainfall-induced landslides

doi:10.21203/rs.3.rs-2441683/v1

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Effects of pore water pressure on the slope profile of a laboratory simulated rainfall-induced landslides

https://doi.org/10.21203/rs.3.rs-2441683/v1

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This paper presents a methodology to identify the controlling parameters of rainfall-induced landslides. Two laboratory scale model of a typical slope has been created with the help of a tilting flume setup incorporated with rainfall simulators to understand the landslide fluidization process using various sensors and cameras. The results obtained with this study will help determine the most efficient monitoring parameters to be considered for developing a landslide early warning system (LEWS). The tilting flume setup was created with 45-degree and 60-degree slopes. The pore water pressure parameters were measured, and instantaneous photographs were taken continuously after simulating artificial rainfall using rainfall simulators. The landslide mechanics that cause the initiation of soil movement have been closely monitored. The summary of this study will help develop an early warning system for landslide-prone regions. The findings of this study emphasize that pore water pressure monitoring is not the best method to develop an early warning system as the pressure values are unpredictable in a massive heterogeneous soil body and sloping angle. However, there is a sudden release of pore pressure right after the failure of the mass, which is evident from the results obtained.

Rainfall

Landslide

Tilting flume

Landslide early warning system (LEWS)

Pore pressure

Landslides are initiated when instability occurs in the existing ground profile. A landslide can be classified into rockfall and mudflow. A significant share of rainfall-induced landslides occurs on the soil slopes (Froude and Petley 2018). A rainfall-induced landslide can be easily monitored, and a predictive model can be established to develop a landslide early warning system (LEWS), unlike earthquake-induced landslides. Studies recommend understanding rainfall thresholds to identify the critical rainfall at which the landslides trigger using various mathematical techniques (Starkel 1979; Caine 1980; Abraham et al. 2020b; Piciullo et al. 2020; Menon and Kolathayar 2022). The factors such as soil characteristics, slope profile, natural and artificial disturbances, and antecedent rainfall are site-specific properties for analyzing any landslide. Hence it is evident that every landslide is unique, and their controlling parameters can vary from site to site and can also be a combination of many parameters.

The LEWS is more than just a device. It is a system that integrates the conceptual process of soil instability on slopes due to triggering parameters. Hence there is no single method of predicting and monitoring landslides. Various parameters affect landslides during a rainfall event. The current site condition is one such critical parameter. Hence the LEWS are supposed to be site-specific. The first stage of LEWS development will be to study the present site conditions from site inspections and digital elevation models (DEM) (Intrieri et al. 2012, 2017). Geographic information systems and remote sensing techniques have a massive scope in the future for a better understanding of landslide mechanics (Dai et al. 2003). But only with laboratory experimentation, the soil can be further studied to identify its behavior against rainfall.

The rate at which the soil loses its structural integrity is essential for understanding the landslide phenomenon. The LEWS is still under a transition stage of recognition because of its novelty and complex design (Intrieri et al. 2013). The government and authorities are still working on implementing the LEWS in a more practical scenario. This is due to the lack of field databases available and the requirement of multi-domain knowledge for its development. LEWS is a handy tool and must be looked into for a better sustainable, and safe future. The present study discusses the possibility for a LEWS based on rainfall threshold. The laboratory parametric studies will further help identify the best parameters to be chosen as the controlling parameter.

Landslide flume study can represent the real-world conditions that arise from the complex mechanics of landslides to a more scaled model. Henceforth the study can be much simpler, and geotechnical parameters can be controlled. The mechanism can be studied based on the change in slope angle, rainfall intensity and duration, and variation of soil properties. The data obtained using the sensors can be used to conduct a parametric study involved in the mechanism of landslides. The critical parameters monitored in this work are Rainfall intensity, Excess pore water pressure, and Structural Integrity of the slope. The primary study revolves around the parameters affecting most soils’ landslide mechanics under heavy rainfall. A landslide flume study incorporated with a rainfall simulator is proposed to find these parameters. These parameters are found with standard sensors like pore water pressure, flow meter, and cameras. The work discussed in this paper consists of a tilting landslide flume incorporated with rainfall simulators capable of change in slope and rainfall intensity-duration. This study will also help to identify the most critical soil sections and their economic impact (Pereira et al. 2017).

Rainfall thresholds

Meteorological and morphological parameters govern an extreme event like a landslide. The most extreme events were observed in the mountain areas that experienced deforestation (Starkel 1979). Rainfall indirectly causes slope instability through the change in pore water pressure and soil shear strength loss. Critical rainfall is a function of intensity and duration for every particular soil characteristic (Starkel 1979; Caine 1980; Wasowski 1998; Eichenberger et al. 2013; Gariano et al. 2015; Hong et al. 2017). Studies have shown that the rise of average annual rainfall is almost directly proportional to the number of landslide occurrences (Wang et al. 2013). Out of all the parameters, the rainfall can be easily measured, even from a remote location. Many empirical relations are established using the intensity and duration of rainfall to identify the rainfall threshold (Aleotti 2004; Hong et al. 2006; Guzzetti et al. 2008; Dikshit and Satyam 2018). A study by Rosso et al. on a physical model of shallow landslides in the USA shows that the soil’s initial moisture content, specific gravity, and void ratio also play a crucial part in slope stability during landslide events (Rosso et al. 2006). With continuous real-time data monitoring, it is possible to get a more refined threshold relationship for detecting rainfall-induced landslides (Bhandari 1988; KUBOTA 2011). Much literature supports that prolonged rainfall is the primary cause of landslides (Kuriakose et al., 2009).

After every transformation to the state of the soil, the rainfall-landslide relation may also vary, and the slope will be severely affected. Hence, the rainfall-landslide relationships must be re-established for the exact location, depending on the geomorphological changes. In addition, the study has to be repeated even after a landslide event because the soil must have reached a new normal condition. The soil slope stability could either increase or decrease after a landslide event because the change in bulk density after a rainfall event might contribute to the disturbing forces or the resisting force (Zhao et al. 2010). High pore water pressure development was observed at the time of failure in the previous studies of laboratory simulated rainfall-induced landslides (Wang and Sassa 2001). Wang and Sassa also observed a pore water pressure development after the slope failure and at the time of failure, depending on the initial density index. The threshold value also depends on the grain size parameters of the soil, as the finer particles will have lesser mobility against slope stability during rainfall (Wang and Sassa 2003). This is due to the pore pressure generation in the soil mass due to finer particles. Thus, the pore water pressure generation indicates the impending disaster. The vertical permeability of soil plays a significant part in the landslide proneness of soil. This study will show whether excess pore water pressure (EPWP) in the soil can be used to identify an impending catastrophe.

Eckersley used a glass tank in the form of a stationary flume to analyze a laboratory-simulated landslide. This pioneering work has simulated a real-world condition of a stockpile slope failure in the laboratory (Eckersley 1985, 1991). Hence, in the following years, many researchers took inspiration, and different types of flume experiments were conducted to study the landslide mechanics (Eckersley 1991; Spence and Guymer 1997; Wang and Sassa 2003, 2001; Okura et al. 2002; Acharya et al. 2009; Aksoy et al. 2012; Chae and Kim 2012; Ooi et al. 2014; Cogan and Gratchev 2019; Li et al. 2021). The essential points to be considered while conducting such experiments are the flume size and instrumentations. The size should be according to the model used; hence, for every specialized test, different tanks are required. In work conducted by Okura et al., even the slope of the flume setup has been predetermined. Hence, a tilting flume is used in the present study to avoid such discrepancies. Instrumentation for basic slope stability studies may include hydraulic piezometers, pore pressure transducers, accelerometers, cameras, temperature probes, and total stress cells. Eckersley concluded that flume experiments are giving almost similar results to that in the field. Hence, rapid pore pressure developments cause the model profile to be flat from the initial slope profile. From the literature, it is evident that the selection of the most appropriate type of monitoring is based on the variables to be considered for quantifying the slope displacement characteristics. In other studies, MEMS (microelectromechanical system) accelerometer sensors were used to identify slope movement and rotational characteristics. The field applications and reliability of MEMS sensors are widely studied in previous literature (Ooi et al. 2014; Uchimura et al. 2015; Cina et al. 2019; Abraham et al. 2020a).

A tilting-type flume has been constructed using mild steel (Fig. 1). Laboratory model experiments were conducted in this tilting flume constructed in a way that it can change the slope of the soil bed (Fig. 1). With this feature, it is possible to run tests for various slope angles. The data can be collected and stored in an external device for further analysis. The setup is 5 feet long and 2 feet wide, which can take around 1.5 tons of soil, and the tilting part’s slope can vary from 10^o to 50^o. The test tank was incorporated with adequate sensors and a camera to study the changes happening in the soil for different slopes. The rainfall simulator can regulate rain intensity, and the relationship between rainfall intensity and pore pressure variations in the soil can be studied. The soil was tested with different rain intensities at different slope angles, and the pressure variation was recorded. The threshold values were found to change with each parameter, which indicates that the landslide prediction is achievable only with a proper understanding of landslide mechanics with the changes in various parameters such as moisture content in the soil, rainfall intensity, duration of rainfall, slope of the soil surface, and pore pressure parameters. As reported in the previous studies (Okura et al. 2002; Aleotti 2004; Gian et al. 2017; Senthilkumar et al. 2018; Li et al. 2021), a significant reduction in shear strength can be observed due to the pore water pressure development. Figure 2 shows the picture taken with the camera before starting the test. To understand the mechanism, it is crucial to understand the reason triggering the failure. The laboratory flume experiment provides us with the flexibility to determine the influence of different parameters on slope failure.

According to the open-source digital elevation model (DEM) data, GIS software was used to identify the location of the samples collected for the flume study. According to Fig. 3, the in-situ slope ranges between 20–30 degrees, and the slope seems stable under rainfall conditions. As a further investigation, the slope profile was interpolated from the DEM data, analyzed in a limit equilibrium software, and found that the slope is safe, with a Factor of Safety of more than 1.5. The present study attempted to experimentally study the effect of varying slope angles for a given soil type under varying rainfall intensities.

According to the laboratory parametric studies (IS:2720 (Part 4) 1985), the soil was in a boundary classification with high sand and silt contents. 50.6% sand, 46.6% Silt, and 2.8% clay content was present in the soil. Table 1 shows the parameters obtained from the laboratory experimentations (Bureau of Indian Standards (BIS) 1987).

Table 1

Soil parameters obtained
Parameters	Description
Specific gravity (G)	2.6
Natural bulk unit weight (γ)	13.54 KN/m³
Sand	46.6%
Silt	50.6%
Clay	2.8%
Liquid limit	48.3%
Plastic limit	34%
Friction angle of undisturbed sample (ϕ)	23.6^o
The cohesion of undisturbed sample (C)	32 KPa

The model landslides were conducted for two different slope profiles. The slope model was set with the parameters given in Table 2. The significant results obtained from the experimentations are EPWP from the 6 locations of pore pressure sensors, as per Fig. 1. Each location of the sensors is marked from S1 to S6. The slope failure profile observed at the end of each test is shown in Fig. 4. The amount of soil displaced is higher in the 60-degree slope profile than in the 45-degree slope. The time taken for failure in the 60-degree slope almost doubled from the 45-degree slope. This was due to the lesser rainfall intensity and higher unit weight of the model slope. Hence, the slope and rainfall intensity is not the only controlling parameters. Still, geotechnics also plays a vital role as the failure time was different for the same soil with varying field densities. The EPWP values are taken as moving averages to understand the increasing and decreasing pattern of the EPWP values more clearly. The density also affects the infiltration of the water into the soil, which later affects the critical slip circle formation of a landslide.

Table 2

Summary of the laboratory experiments
Name	Slope	Initial Moisture content (%)	Average simulated rainfall (cm/h)	Unit Weight (KN/m³)	Before Rainfall		24 hrs after rainfall
Name	Slope	Initial Moisture content (%)	Average simulated rainfall (cm/h)	Unit Weight (KN/m³)	Cohesion (C) (KPa)	The angle of internal friction (ϕ)	Cohesion (C) (KPa)	The angle of internal friction (ϕ)
Test 1	45^o	34.8	21.3	12.56	6.3	25.6^o	3.4	26.3^o
Test 2	60^o	34.9	16.9	13.15	6.7	24^o	11.5	26.2^o

Figure 5 shows the few images taken from the first test with the cameras used to capture the landslide event. The pictures shown here are at a time interval of two minutes and somewhere between 520 seconds and 640 seconds when the first surface cracks were formed. According to the data obtained, an average rainfall intensity of 21.3 cm/hour was provided. The rainfall intensity is relatively higher, so the failure happened much faster. In addition, the unit weight of the slope model is lesser; hence, it only took less time for water to percolate into the slope model, causing the EPWP generation much faster.

According to the EPWP values obtained for the 45-degree slope profile, a sudden decrease in the values was observed between 600 and 700 seconds from the start of the experiment. These result from cracks in the soil surface, causing the pore water pressure to dissipate. The apparent surface failure was observed between 760 and 880 seconds. Hence, in some locations, EPWP increases once the slope profile is reformed into the next possible shape. Here minor variations were observed in the S2, S4, and S5 locations. These are due to the crack formation in the soil. The formation of the cracks can be in any location. Hence it is critical to identify such locations and use pore pressure sensors in those locations in case of field monitoring of EPWP variations.

The failure was prolonged in the 60-degree slope profile because of the higher unit weight and lesser rainfall intensity. The general knowledge is that the increase in slope value will decrease its mobility against failure. Here it is evident that the slope value and general soil properties are not the only parameters to be considered while predicting a slope failure. Figure 7 shows a significant surface movement initiated between 1180 and 1240 seconds. In the EPWP values, the pore pressure decreased after crack formation and started rising after the failure. Also, the peak EPWP values are lesser for 60-degree slopes considering 45-degree slopes. This indicates that the pore water pressure development could be higher for lower slope values.

The landslide flume technique is one of the most useful methods to identify soil’s behavioral characteristics to identify an impending disaster. Such studies can be further elaborated to identify the most suitable parameters to be considered while developing a landslide early warning system. The EPWP in the soil seems to be one of the dependent parameters of the rainfall intensity and slope of the soil profile. Hence there cannot be a unified approach to predicting the landslide based on EPWP values alone. Thus, the prediction parameters for any LEWS shall be multi-dimensional. Also, most parameters will be site-specific; for every location, site-specific early warning systems are recommended for better results.

The rainfall intensity-duration relationship was used to identify the threshold for rainfall-induced landslides in most of the previous literature. But here, laboratory model tests gave a site-specific detailed study on a probable landslide. The laboratory flume experiments are one of the most effective methods to identify the site-specific parameters of soil against landslides. Hence a detailed laboratory flume study is recommended before deploying any early warning system to landslide-prone sites. The significant findings from the laboratory flume experiments conducted in the present study are listed below,

The increase in slope will decrease the peak EPWP generation inside the soil during rainfall. But EPWP is not only the controlling parameter in a landslide event, but also the physical characteristics like specific gravity, void ratio, and initial water content of the soil have to be taken into account to come up with a generalized relationship to consider while developing a LEWS.
The strength reduction and regaining rate of the landslide-prone soil have to be studied to understand the importance of the critical duration of rainfall that might cause a landslide.
The EPWP generation is localized in specific locations in a soil mass. Like in the 45-degree slope, most variations have been located near the surface, and the EPWP variations deep in the soil mass are not significant, considering the failure.
EPWP generation after the failure is evident near the toe and face of the slope in case of steeper soil slopes like in 60-degree slope failure.
A site-specific study is recommended to develop a LEWS for a particular site, and the soil characteristics change after every landslide. It is evident from the rapid growth of EPWP after the failure in the laboratory tests conducted. Hence EPWP may not be a perfect candidate to be considered for developing a LEWS.

Further studies are required to distinguish whether the soil parameters are hugely affected before and after the rainfall event and to understand whether the soil regains its strength in intermittent rains. The time required for the soil to regain its strength properties can be further exploited by conducting model tests with intermittent rainfall events to quantify the soil’s ability to regain its strength over time.

Funding.

The authors would like to express sincere gratitude to the Science and Engineering Research Board (SERB) of the Government of India for the funding provided (IMPRINT-2 program of DST/SERB with MHRD titled: “Impounding of River floodwaters along Dakshina Kannada Coast: A sustainable strategy for water resource development in water resources” (IMP/2018/001298)).

Acknowledgment.

The authors would like to acknowledge the funding agencies for the financial support.

Conflict of Interest.

The authors declare no conflict of interest.

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No competing interests reported.

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Effects of pore water pressure on the slope profile of a laboratory simulated rainfall-induced landslides

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Rainfall thresholds

Experimental setup

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