Keywords

1 Introduction

Slope instability is a natural hazard that exerts a profound influence on the operation and reliability of infrastructure. Unlike engineered structures, natural slopes are not designed for safe performance. As a consequence of natural processes, slopes have heterogeneous material properties. Moreover, slopes are prone to erosion, and their gradient changes with time. Underground hydrology is hardly captured in practical engineering. Therefore, quantitatively assessing the extent of slope stability is very difficult in practical situations. Although the movement of landslide masses, which has been slow in conventional studies, is already a major threat to human activities, rapid and unpredictable slope failure triggered by gravity or heavy rain is more hazardous because it may instantaneously result in an enormous loss of human life and the destruction of infrastructure. However, predicting the abrupt failure of slopes to avoid damage is still difficult. Communities in mountain regions are particularly prone to this type of damage. The situation is more serious for transportation infrastructure because its function can be entirely disrupted by a single slope failure (Lee et al. 2013; Sartori et al. 2003). Ongoing global climate change increases the likelihood of heavy and concentrated rainfall, which results in more rainfall-induced slope failures.

As stated above, the mitigation of landslide disasters is difficult and the available funding for conducting elaborate site investigations is far too little. Practitioners have been trying to improve safety by developing slope monitoring and early warning system (EWS) technologies with the objective of predicting slope failure in advance based on the observed slope behavior and mitigating the extent of damage (Medina-Cetina and Nadim 2008). The United Nations International Strategy for Disaster Reduction (UN-ISDR 2006) advocates that EWS should “empower individuals and communities threatened by hazards to act within sufficient time and in an appropriate manner to reduce the possibility of personal injury, loss of life, and damage to property and the environment” (from the UN-ISDR web site).

There is a long history of prevention and mitigation of rainfall and/or scouring-induced landslides. Mechanical countermeasures to prevent slope failure have been widely used, including retaining walls and ground anchors. However, these methods can be expensive and are not always realistically applicable to all slopes of varying scales and potential risk factors. Therefore, careful monitoring of slope behavior and consequent early warning of failure provides a reasonable and slope-specific alternative.

In this paper, an early warning system for slope failure is proposed and its development is described (Fig. 1) (Wang et al. 2017). The system consists of a minimum number of low-cost sensors strategically placed on a slope, with monitoring data that are collected being transmitted via a wireless network. It is anticipated that this low-cost and simple system will provide at residents risk with access to accurate and timely precautions or warnings of slope failure.

Fig. 1
a. 2 photos of the tilt meter sensor, and the sensor is placed into the ground. b. 2 photos of the miniature tilt sensor that is inserted into the ground. c. A diagram of the 2-axis M E M S tilt sensor inserted into the intact base layer and the volumetric sensor inserted into the unstable layer.

Schematic illustration of MEMS tiltometer sensor for early warning (Wang et al. 2017)

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Uchimura et al. (2015) summarized case studies of slope tilting rates during pre-failure stages obtained on several natural slope sites under natural or artificial heavy rainfall. Figure 2 presents an example of the typical monitoring data obtained, in which the tilting rate (X-axis) can be related with the time elapsed until slope failure or slope stabilization (Y-axis). Figure 3 shows the definition of the tilting rate and the time in Fig. 2, in which Ti is the time until failure or stabilization, and Ri is tilting rate.

Fig. 2
A graph plots time until failure or stabilization versus tilting rate. The values are graphed for deformation and failure. 10 lines follow a decreasing trend with some fluctuations between 0.01 and 1000. Slopes tend to fail finally as the titling rate develops to more than 0.1 degrees per hour.

Graphic illustration of the tilting rate as a function of time before slope failure (or stabilization) for several case studies (Uchimura et al. 2015)

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Fig. 3
A profile plots tilt angle versus time. A stabilization curve begins along the x axis, remains stable, and follows an increasing trend. 3 tangent dotted lines for tilting rates R 1, R 2, R 3, and R 4 are drawn from the curve. 4 vertical lines for T 1, T 2, T 3, and T 4 are drawn from the curve.

Definition of the tilting rate and the durations (Uchimura et al. 2015)

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In cases where the slope failed at the position of the tilt sensor, the elapsed time is measured from the time when tilting accelerated to the time of failure. In cases where the slope did not fail but instead stabilized, the time is measured from when tilting decelerated to the time when the slope stabilized.

According to Fig. 2, the order of tilting rate observed with slope deformation varied widely, from 0.0001°/h to 10°/h depending on several factors. The tilting rate tends to increase towards failure with a relatively short time until failure, when a higher tilting rate is observed. The observed tilting rate was >0.01°/h for all the cases in which the slope failed or nearly hour was observed before failure for a tilting rate of 0.1°/h.

Based on the past case studies, it is proposed that when the tilting rate exceeds 0.1°/h a warning of slope failure should be issued, and a precaution issued at a tilting rate of 0.01°/h, taking safety into account. Additionally, this paper explores efforts by the current authors to improve the applicability of the monitoring and early warning system. The miniature tilt sensors are modified from that currently available to be more cost-effective, smaller in size and weight, and simpler to install, maintain and operate. As a result, it is possible to install a larger number of sensors on a given slope, thereby providing greater coverage and higher data density.

Figure 4 illustrates the typical arrangement of two types of proposed sensors, with data transfer pathways also shown. Despite the advantages described above, the new type of miniature tilt sensors has relatively short radio transmission distances (~30 m in non-ideal conditions). They are arranged densely on high-risk areas of a slope, with one conventional tilt sensor unit collecting all the data of each area. The data are transmitted over greater distances (300–600 m) and uploaded to an internet server.

Fig. 4
A diagram for the installation of a tilt sensor with the transfer distance F S K mode less than or equal to 600 meters and LoRa mode greater than 1 kilometer. Data base is transmitted from the data logger and transfer base station, and a warning is sent from the wireless radio wave transfer route.

An early warning system of slope failure by multi-point tilt and volumetric water content (Wang et al. 2017)

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2 Field Validation of Tilt Sensor for Slope Monitoring

Previously, MEMS tilt sensors have been used at more than 100 sites with slope instability in worldwide. Most of these slopes did not fail, but several of these slopes have failed with and without rainfall and provided important data. Based on these data, the warning threshold has been determined as 0.1°/h. In this section, various cases that have not been reported are discussed.

2.1 Prevention of Secondary Disaster During Restoration of Failed Slope–Fukuoka Pref., Japan

An EWS was successfully used in 2015 in Fukuoka Prefecture, Japan. When this region received heavy rainfall during typhoon No. 11 “Nangka” on July 17 and 18, the slope collapsed and the local road was closed for traffic (Fig. 5). This slope comprises Funi volcanic rock of andesite karst, tuff breccia, and tuff. To safely keep one lane open for traffic during slope restoration, the slope movement was monitored by a set of tilt sensors as shown in Fig. 6. The traffic was intended to stop if the tilt sensor detected an excessive tilting rate during the slope restoration works.

Fig. 5
a. A schematic diagram exhibits the 2 D plan view and four sensor locations on the slope. b. An aerial view of the slope in Fukuoka with the installation of the monitoring sensors.

Monitored slope in Fukuoka

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Fig. 6
A graph plots inclination angle and cumulative rainfall versus duration time. 3 lines for X Y composite, X, and Y directions at (15.2, 0), remain stable, in which 2 follow an increasing trend and 1 follows a decreasing trend. A cumulative rainfall line follows an increasing trend.

Time histories of monitored data at Fukuoka site

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Figure 6 shows the plot of the tilt angle and the rainfall data on July 21st and 22nd, shortly after the main slope collapse. The slope was considered to be prone to further failures during the restoration works. From 4 PM to 8 PM on July 21st, that is, immediately after the tilt sensor installation, the tilting rate of 0.083°/h was recorded and continued until 8 AM on July 22nd. Thereafter, the tilting rate accelerated to 0.89°/h, possibly owing to rainfall amounting to approximately 10 mm from 8 AM to 9 AM. Furthermore, owing to further rainfall after 11 AM, the tilting rate sharply increased to 12°/h after 12 PM and the slope finally collapsed at 12:30 PM. Thus, the field monitoring helped control the traffic during the critical period and ensured the safety of human life.

Based on practical experiences at many sites with and without failure, the authors (2015) recommend that a warning and evacuation order should be issued at this tilting rate. Moreover, precautions may be issued at a tilting rate of 0.01°/h to ensure safety, because the time left until failure will be several hours or longer.

In the typical case wherein the surface soil thickness is 150 cm (Fig. 1) in Japan, the 0.01°/h and 0.1°/h tilting rates correspond to the displacement rates of 150 × tan (0.01°) or 150 × tan (0.1°), that is, 0.026 cm/h or 0.26 cm/h, respectively. Hence, it is extremely difficult for GPS, LIDAR, and InSAR to continuously monitor this small movement during heavy rainfall. Therefore, the authors prefer using tilt sensors. The following sections discuss the practical experience acquired at other slope-monitoring sites and used to validate the warning principle described above.

2.2 Practical Tilt Sensor Monitoring in Tokyo

Because of the heavy rain associated with Typhoon No. 21 “Jebi” on October 23, 2018, a part of industrial waste landfill collapsed in Tokyo. Consequently, a part of the collapsed sediment flowed and reached the prefectural road below the slope (Fig. 7).

Fig. 7
a. A schematic diagram exhibits the 2 D plan view and four sensor locations on the collapsed landslide in Tokyo. b. An aerial view of the land slide at the monitoring site with the installation of the sensors.

Monitoring at landfill slope in Tokyo. (a) Plan view and tilt sensor locations. (b) Appearance of slope failure

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Accordingly, a temporary protective fence and large sandbags were placed along the road, but drastic measures against the landfill collapse were not implemented. However, it was highly likely that slope failure would reoccur during the rainy season in 2019. Hence, the Environment Bureau of the Tokyo Metropolitan Government installed three extensometers at the edge of the landfill for monitoring. Moreover, three tilt sensors were installed for research purposes.

Figure 8 shows the monitored time history of the cumulative rainfall and the tilt angles. When the rainfall, which cumulatively amounted to 38 mm, occurred before 8 PM on June 15, there was no significant change in the records of tilt sensors K-1 and K-2. Thus, the situation remained relatively stable. A few hours later, in the early morning of June 16, the tilt angles started to increase toward infinity at 5:10 AM (slope collapse). The tilting rate of sensor K-1 reached 0.58°/h (X axis of slope direction) at 4 AM on June 16, and sensor K-2 reached 0.20°/h (X axis of slope direction) at 3:30 AM on the same day. Because the record of the tiltmeters accumulated in the negative direction of the X axis (toward the top of the slope), it is believed that the slope failure mechanism was associated with a circular slip (rotation).

Fig. 8
a. A graph plots cumulative rainfall versus time and data. A curve begins at 0, remains stable, follows an increasing trend until 38, drops down, and again remains stable. b and c plot tilt angle versus time. 2 lines for K 1 and K 2 begin at 0, remain stable, and follow a decreasing trend.

Recorded cumulative rainfall and tilt angles at sensor K-1 and K-2 at the site shown in Fig. 7 (June 15th and 16th)

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2.3 Monitoring Slope Failure at Manzawa, Yamanashi, Japan

The Manzawa area in the Yamanashi Prefecture of Japan contains a large-scale reactivation of old slope failures featuring rockfalls that involve the detachment and rapid downward movement of rock.

Because most traditional slope monitoring methods are expensive, difficult to control and may not be suitable for application in this civilian area, the simple and low-cost monitoring system was deployed on a test slope to validate field performance. It should be noted that the research is supported by the Japanese Government during 2014–2017, and the following result that is reported in this paper.

Figure 9 shows the scale of Manzawa slope failure site, and Fig. 10 shows the arrangement of the multi-point tilt sensors and locations, where two types of tilt sensor were used. The arrangement interval of the sensor is designed to 5 m. A total of 66 sets of sensors were deployed.

Fig. 9
An aerial view of the area of the slope failure and monitoring area in Japan, which are highlighted by elliptical and polygonal. The scale measures from 0 to 150 meters.

Area of slope failure at Manzawa site, Japan

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Fig. 10
A diagram exhibits the 2 D plan view of the monitoring site with the installation of the multi-point tilt sensors. The locations of tilt, new type, miniature type, receiver of miniature type tilt sensors, and data logger and transfer base station are marked in the left, middle, and right zones.

Arrangement of the multi-point tilt sensors

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The 66 sensor units are divided into three groups, left/middle/right zone, and one data receiver unit and one logger/gateway unit for internet to collect all the data from respective group as shown in Fig. 10. There were eight heavy rainfall events during summer of 2015 shown in Fig. 11, and the tilting rate averaged during each rainfall event is shown in Fig. 12. Distribution of tilting behaviors of two tears result was figured out by multi-point monitoring in Fig. 13 during 2015–2017.

Fig. 11
5 spectra plot daily rainfall versus data. The first spectra plot several vertical strips with varying peaks. The second and fourth spectra plot a slight decreasing trend for daily volumetric water content and X titling rate. The third and fifth spectra plot an increasing trend with some variations.

Time histories of movements in rainy days during summer of 2015

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Fig. 12
A set of 8 3 D bar graphs plots the tilting rate during rainy days versus dates from October 2015 to September 2015. The observed distribution rates are 0.006893, 0.000324, 0.001041, 0.000482, 0.000855, 0.001136, 0.000723, and 0.000208.

Distribution of tilting rates during each rain day during summer of 2015

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Fig. 13
A 3 D surface graph plots inclination angle versus tilt angle and events. A plane is graphed with several peaks, and the distribution of the accumulated inclination angle ranges from 0.000 to 8.000.

Distribution of accumulated inclination angle during 2015–2017

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2.4 Early Warning by Using Multi-point Monitoring

Wang et al. (2017) proposed an early warning method based on single-sensor monitoring. Recently, the authors have extended the scope of slope monitoring to multi-point monitoring, which can capture both the spatial and temporal behavior of the entire slope. Additionally, multi-point monitoring can avoid erroneous warnings caused by very local slope movement and animal contact, among other causes of error. Thus, the reliability of early warning is improved.

The spacing between multiple sensors must be kept within a reasonable limit (a few meters to a few tens of meters, as in the practical cases discussed in this paper), and a new index of slope movement must be proposed in place of a single sensor’s tilting rate, as in past practical cases.

Certainly, the new index must handle data at all monitoring points. Presently, the new index is assumed to be expressed as follows:

$$ {\mathrm{V}}_{\mathrm{alarm}}=\sum \limits_{\mathrm{n}=1}^{\mathrm{n}}\left(|\mathrm{Vn}|\ast {\frac{\mathrm{A}\mathrm{n}}{\mathrm{A}0}}^{\ast}\mathrm{\partial n}\right) $$
(1)

where n is the total number of tilt sensors; Vi is the tilting rate (otherwise denoted as dα/dt) in the slope direction of the ith sensor (°/h); Ai is the area covered by the ith sensor; A0 is the area covered by the entire sensor array; ∂i is the coefficient determined by the geology, geography, soil type, and vegetation conditions at the installation points. Moreover, the ∂i coefficients regard the field conditions, and their values are determined based on the results of geomaterial experiments and the assessment of geologists. Although this issue requires further investigation, ∂i = 1 is currently used in practical situations.

3 Conclusion

The authors have been developing slope failure monitoring and early warning technology. This technology is characterized using MEMS tilt sensors. In earlier versions, monitoring was conducted using a single sensor. However, a multi-sensor approach was implemented in recent development. This paper introduces the most recent development of the authors’ EWS based on data obtained from several sites and their interpretation. The following conclusions were drawn from this study:

  1. (1)

    In the previous version of the technology, a caution alert was issued when the tilting rate exceeded 0.01°/h, while a warning associated with an evacuation order was issued when the rate exceeded 0.1°/h. These threshold values are based on practical experience and have been validated by recently obtained monitoring results.

  2. (2)

    In this paper, various monitoring cases are summarized. The linear relationship between the logarithm of the rate of the tilting angle of the sensors and the logarithm of the time remaining until slope failure was demonstrated. This relationship has an interesting similarity to the relationships suggested by the Monkman-Grant model (Monkman and Grant 1956) and Saito’s rheological interpretation of laboratory soil tests (Saito and Uezawa 1961; Saito 1965).

  3. (3)

    The recent extension of monitoring to multi-point practice enables a more detailed interpretation of slope behavior in the transient stage and up to the final failure.

As the actual plans, the authors are currently undertaking the National key R&D project of Sino-Japan “Development and demonstration of monitoring and warning technology for the rainstorm induced mountain torrent disaster chain”, which takes the rainstorm-flood-landslide-debris flow disaster chain as the research object and is carrying out through international cooperation and joint research. By using the strength of the Japanese participating units in the field of disaster mechanism research and sensing technology and bring into play the advanced level of the Chinese participating units in communication technology and platform development, the results such as deeply exploring the occurrence and evolution mechanism and developing the key technologies for precise monitoring and dynamic warning of the rainstorm-induced mountain flood disaster chain are expected to be obtained. The project aims to provide scientific and technological support for the mountain flood disaster chain prevention and control, and effectively improve the theoretical and technological level of disaster prevention and reduction research between China and Japan.