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Article

The Application of Remote Sensing Technology in Post-Disaster Emergency Investigations of Debris Flows: A Case Study of the Shuimo Catchment in the Bailong River, China

by
Feibiao Huo
1,
Fuyun Guo
2,
Pengqing Shi
2,
Ziyan Gao
2,
Yan Zhao
3,
Yongbin Wang
1,
Xingmin Meng
3 and
Dongxia Yue
1,*
1
Key Laboratory of Western China’s Environmental Systems, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
2
Geological Environment Monitoring Institute of Gansu Province, Lanzhou 730050, China
3
Gansu Technology & Innovation Center for Environmental Geology and Geohazards Prevention, Gansu Geohazards Field Observation and Research Station, School of Earth Sciences, Lanzhou University, Lanzhou 730000, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2024, 16(15), 2817; https://doi.org/10.3390/rs16152817
Submission received: 25 June 2024 / Revised: 26 July 2024 / Accepted: 29 July 2024 / Published: 31 July 2024
(This article belongs to the Special Issue Remote Sensing Makes it Possible: Prediction and Evaluation of Natural Hazards)
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Abstract

:
The Bailongjiang River Basin is a high-risk area for debris flow in China. On 17 August 2020, a debris flow occurred in the Shuimo catchment, Wen County, which blocked the Baishui River, forming a barrier lake and causing significant casualties and property damage. In this study, remote sensing, InSAR, field surveys, and unmanned aerial vehicle (UAV) techniques were used to analyze the causal characteristics, material source characteristics, dynamic processes, and disaster characteristics after the debris flow. The results showed that the Shuimo catchment belongs to low-frequency debris flows, with a recurrence cycle of more than 100 years and concealed features. High vegetation coverage (72%) and a long main channel (11.49 km) increase the rainfall-triggering conditions for debris flow occurrence, making it more hidden and less noticed. The Shuimo catchment has a large drainage area of 31.26 km2, 15 tributaries, significant elevation differences of 2017 m, and favorable hydraulic conditions for debris flow. The main sources of debris flow material supply are channel erosion and slope erosion, which account for 84.4% of the total material. The collapse of landslides blocking both sides of the main channel resulted in an amplification of the debris flow scale, leading to the blockage of the Baishui River. The scale of the accumulation fan is 28 × 104 m3, and the barrier lake area is 37.4 × 104 m2. The formation mechanism can be summarized as follows: rainfall triggering → shallow landslides → slope debris flow → channel erosion → landslide damming → dam failure and increased discharge → deposition and river blockage. The results of this study provide references for remote sensing emergency investigation and analysis of similar low-frequency and concealed debris flows, as well as a scientific basis for local disaster prevention and reduction.

1. Introduction

Debris flows have received widespread attention due to their high suddenness and destructive power [1]. The occurrence frequency of debris flows can vary from several times a year to once every 50 years or even longer [2,3]. Among them, low-frequency debris flows are easily overlooked due to their strong concealment and lack of adequate preventive measures. Once a debris flow occurs, it often leads to severe disasters, causing significant casualties and property damage [4,5].
In the Bailong River Basin in China, low-frequency debris flow disasters often occur. For example, on 8 August 2010, a 200-year recurrence period of debris flows from Sanyanyu and Luojiayu struck Zhouqu County, resulting in 1765 deaths and direct economic losses of approximately 3.3 billion yuan [6]. On 7 August 2017, Wen County was hit by an exceptionally heavy rainstorm, causing an 80-year recurrence period of debris flows in the Yangtang catchment and resulting in five deaths. The Liping Village at the mouth of the catchment was destroyed, and the Longba River was blocked, forming a barrier lake that submerged roads and vast farmland, with direct economic losses exceeding 30 million yuan [7]. From 14–17 August 2020, the Bailong River Basin experienced once-in-50-to-100-years heavy rainfall, triggering widespread landslides and debris flows. In particular, a debris flow in the Tieba River Basin in Zhouqu destroyed Monuo Village. Thanks to timely warnings, 440 people were evacuated, resulting in no casualties, but the economic loss was nearly 100 million yuan. In Wen County, 66 debris flows caused disasters, with the Shuimo catchment being one of them. According to preliminary investigation data, there are currently 1,148 potential debris flow hazard points in the Bailong River Basin, 349 of which are low-frequency debris flows with significant potential harm. It is necessary to conduct research on the development characteristics and dynamic mechanisms of such debris flows.
The frequency of debris flow occurrences is controlled by the coupling effect of rainfall and the catchment’s bedrock features [8,9,10]. The characteristics of rainfall and the availability of loose materials play significant roles in the activity of debris flows [11]. High rainfall conditions required to trigger debris flows or the long time needed for the supply of loose materials in the basin to recover after a debris flow event are the main reasons for low-frequency debris flows. Many studies suggest that lithology is an important controlling factor for the movement of materials, such as debris flows [12,13]. Some research emphasizes the impact of lithology and tectonic fractures on the occurrence of debris flows [4,14,15,16]. Some studies highlight the influence of surface and vegetation cover on hydrological responses, which in turn affect the occurrence of debris flows [17,18,19,20]. Some research stresses the impact of land use on debris flow occurrences [21], while others emphasize the influence of landslides on debris flow formation [22,23]. Additionally, some studies highlight the impact of geomorphic factors on debris flow occurrences [24,25,26,27,28].
Many studies have conducted research on low-frequency debris flows. Ref. [29] proposed an identification system for low-frequency debris flows based on the identification and stability calculation of colluvium deposits in a hollow region and the quantitative roundness analysis of the stones in a deposit fan. Ref. [30] analyzed the influence of extreme climate and tectonic control on large-scale, low-frequency debris flows. Ref. [31] analyzed the formation causes of large-scale, low-frequency debris flow disasters. Ref. [32] analyzed low-frequency, large-scale debris flows triggered by extreme climate and human. Therefore, many studies have focused on the formation characteristics and causes of low-frequency debris flows. The investigation methods primarily include field surveys and remote sensing techniques. However, from the perspective of post-disaster emergency investigations, there is still a lack of research on the analysis of the concealed causes, driving conditions, and material supply characteristics of low-frequency debris flows.
In recent years, thanks to the continuous improvement in spatial and temporal resolution of satellite remote sensing images, the use of high-resolution remote sensing data and Interferometric Synthetic Aperture Radar (InSAR) for detailed investigation and analysis of landslides, debris flows, and their development environment has become increasingly mature [33,34,35,36,37]. Taking the debris flow disaster that occurred in the Shuimo catchment, Bailong River Basin, in 2020 as an example, this study comprehensively used remote sensing, InSAR, field survey, and UAV techniques to analyze the causal characteristics, sediment source characteristics, dynamic processes, and disaster characteristics after this debris flow.

2. Study Area

The Shuimo catchment is located in Shijiaba Town, Wen County, Longnan City, Gansu Province. It is a first-order tributary on the right bank of the Baishui River, and Shijiaba Town is located on its alluvial fan. The Shuimo catchment has an area of 31.26 km2, a main channel length of 11.49 km, and a relative elevation difference of 2017 m. The Shuimo catchment is located in the controlled area of the Wen County–Kang County Fault Zone, with regional structural distribution trending in the NEE direction, including the Zhongzhai–Zhongping anticline and the Shijiaba–Guanyinba fault [38]. In the adjacent area, there have been 15 earthquakes above magnitude 7 in history, including the 1879 Wen County earthquake with a magnitude of 8.0, which covered the entire basin and had a significant impact on the regional geological environment, exacerbating the damage to mountain and soil structures [39]. The exposed strata in the upstream area of the catchment mainly consist of Permian shale, interbedded thick layers of dolomite, and Triassic sandstone and shale exposed in the middle and lower catchments. The distribution of Quaternary loose deposits is extensive, with various types of formation and significant variations in thickness, including alluvial fans, floodplain deposits, slope deposits, residual slope deposits, and gravity erosion deposits (Figure 1).
The vegetation in the Shuimo catchment is mainly composed of shrubs and trees. The vegetation coverage in the upstream area reaches more than 70%, while it is 30–70% in the middle and lower reaches (Figure 2). Sloping cultivated land is widely distributed. The regional climate belongs to the transition zone from the northern subtropics to the temperate zone of North Asia. It has two distinct characteristics: vertical climatic zones and distinct dry and wet seasons. The period from November to April of the following year is the dry season, while the period from May to October is the rainy season. According to data from the Wen County Meteorological Station, the average annual precipitation is 454.1 mm, with the maximum precipitation reaching 671.9 mm and the minimum precipitation only 310.1 mm [40]. The precipitation from July to September accounts for 76.2% of the annual precipitation, reaching 337.6 mm. The longest consecutive rainy days recorded were 12 days (from 20 August to 30 August 1976), with an average of 7.6 consecutive rainy days, mostly from July to September. The rainfall intensity during heavy rain is high, with a maximum daily rainfall of 142.6 mm, a maximum hourly rainfall of 93.3 mm (on 17 August 2020), and a maximum rainfall in 10 min of 30 mm. High-intensity heavy rain is the main triggering condition for geological disasters such as debris flows and landslides [41].

3. Data and Methods

3.1. Data

The data used in this study include high-resolution images from the Gaofen-1 and Gaofen-2 satellites, as well as Pleiades satellite images. The DEM data are from ALOS with a resolution of 12.5 m. SAR data are obtained from the European Space Agency’s Sentinel-1A satellite and covers the study area with 62 ascending and descending track data. To analyze the deformation of the landslide from January 2020 to May 2022, both ascending and descending track data are selected for time-series interferometric processing. Pre-disaster optical remote sensing data mainly consist of historical satellite images from the Gaofen series, Pleiades, Worldview, and other satellites. Post-disaster data mainly include unmanned aerial vehicle (UAV) aerial images and high-resolution satellite images. In addition, regional geological information was referenced. Please refer to the Table 1 for specific data and features.

3.2. Methods

The terrain features, main channel morphology, channel gradient, fan characteristics, and sediment source characteristics of the Shuimo catchment were measured and analyzed through field surveys. Using SBAS-InSAR technology and high-resolution remote sensing images, detailed investigations of the catchment’s characteristics and disaster-causing features were conducted post-disaster. The overall process framework is shown in Figure 3.
Satellite remote sensing, mainly images of pre- and post-disaster, is used to obtain features of land cover changes in the target area. SBAS-InSAR utilizes the phase value changes from multiple SAR images acquired during different passes to obtain time-series deformation information of the target area.
The main process of SBAS-InSAR is shown in Figure 4. First, M interferograms are obtained based on the interferometric combination conditions. High-coherence points with stable backscatter characteristics are selected. After removing the topographic and flat-earth phases, the interferograms are unwrapped. Elevation errors and linear deformation phases are estimated using baseline conditions and interferometric phase information. The residual phase, which mainly includes nonlinear deformation and the atmospheric phase, is obtained by subtracting these estimates from the original interferometric phase. The unwrapped residual phase undergoes spatial low-pass filtering and temporal high-pass filtering to separate the atmospheric phase. By removing the atmospheric phase from the residual phase and compensating for the linear deformation component, the complete deformation phase is obtained, resulting in the total deformation rate.

4. Results

4.1. Topographic Characteristics of the Debris Flow

Based on the DEM and slope map (Figure 5), an analysis of the topographic characteristics of the Shuimo catchment is conducted. It can be observed that the basin has a fan-shaped planform with an area of 31.26 km2. The total length of the main channel is 11.49 km, with a maximum relative elevation difference of 2017 m. The average longitudinal slope of the main channel is 167.1‰. The downstream section of the main channel exhibits a “V” shape, while the middle and upper sections have a “U” shape.
The average longitudinal slope of the middle and upper sections is 238‰, with channel slopes ranging from 20° to 65°. The middle section of the channel is relatively open and has a wide and gentle “U” shape, with a channel width ranging from 220 to 350 m. The average longitudinal slope of the middle section is 147.2‰. The downstream section of the channel has a width of 250 m and an average longitudinal slope of 13.18‰. In the alluvial fan deposit area, the average longitudinal slope is 52.6‰. The catchment has a total of 15 developed tributary valleys, including 8 tributaries with a length greater than 1 km. The total length of the tributary valleys is 18.5 km, with an average channel density of 0.59 km−1. The majority of the tributary valleys exhibit a “V” shape, with average slopes ranging from 28.2% to 78.0%.
The Melton index [42] of the Shuimo catchment was calculated to be 0.36, and the hypsometric integral value [43] was 0.56, indicating that the Shuimo catchment has favorable energy conditions [44].
Therefore, the Shuimo catchment is a typical valley-type debris flow catchment. Its watershed morphology is conducive to the collection of precipitation. The entire watershed has a significant relative elevation difference, with an area of 26.78 km² having a slope greater than 25°, accounting for 78% of the total area. This relatively steep terrain favors runoff and the convergence of rainwater. The formation area of the catchment is 30.12 kmc, making up 96.14% of the total area; the transport area is 0.25 km², accounting for 0.80% of the total area; and the deposition area is 0.55 km2, accounting for 1.76% of the total area. Overall, the Shuimo catchment has a large catchment area with significant longitudinal slopes in the main and tributary channels, providing relatively advantageous hydrodynamic conditions.

4.2. Characteristics of Debris Flow Material Sources

After the Wenchuan earthquake, the supply of material sources exhibited new characteristics: an increase in the total amount of material, a growing convertible amount, and a progressive increase in material sources with elevation [35]. According to field investigations, the material sources for the Shuimo catchment are mainly divided into three types: gravity erosion supply, surface erosion supply, and channel erosion supply. Gravity erosion is further categorized into landslides, collapses, and slope debris flows. This study employs optical remote sensing and InSAR technology to interpret and quantitatively calculate the gravity erosion and channel erosion material sources of the Shuimo catchment (Figure 6 and Figure 7).

4.2.1. Gravity Erosion Supply

Gravity erosion material sources mainly include landslides, collapses, and slope debris flows. According to remote sensing interpretation combined with field surveys, there are a total of 44 landslides distributed in the watershed, mainly concentrated in the middle and lower reaches of the main and tributary channels. The total area of landslides is 2.26 km2, with a total volume of about 1560 × 104 m3 based on experience during the field survey. The landslides are primarily composed of shallow and superficial accumulation layer slides, as well as a small number of large-scale bedrock slides. For example, Figure 8 shows a typical landslide where its toe is eroded by water flow, causing the landslide to slowly move downward and compress the channel, continuously supplying material for debris flows.
Collapses are mainly distributed upstream, where the gray limestone is located, and are also widely developed along the channel in the middle and lower reaches of the catchment. The area of collapses is 0.33 km2, with an estimated volume of 150 × 104 m3. The collapses are primarily rock collapses, with a small number of gravel and soil collapses in the middle and lower reaches. Collapses often form debris piles and bury the slope vegetation.
Slope debris flows mainly occur on steep slopes with gradients of more than 40° in the middle and lower reaches of the catchment. The weathered and fragmented gravel soil on these steep slopes becomes shallow, saturated soil that slides under the influence of rainfall. These shallow slides then transform into debris flows in a flowing form, causing erosion on the slopes along the way, ultimately entering the main channel as material sources. There are a total of 13 slope debris flows, covering an area of 0.26 km2, with an estimated overall volume of approximately 78 × 104 m³.

4.2.2. Channel Erosion Supply

The channel sediment source comprises the following: debris flow deposits accumulated within the channel; the loose surface layer of alluvial and proluvial deposits due to erosion by flowing water; and alluvial and proluvial deposits accumulated on the channel bed, mainly distributed within the wider and slower-flowing channel area. These channel bed deposits have a large thickness; e.g., the maximum thickness within the Daya valley is ~20 m (Figure 9). In the rainy season, when debris flows tend to occur, the large volumes of flowing water erode the channel sides and bed, facilitating the movement of this layer. Based on a comprehensive investigation and calculations, the total reserve of loose materials in the channel is 1877.5 × 104 m3 (Table 2).

4.2.3. Surface Erosion Supply

Surface erosion material sources are composed of alluvial and colluvial deposits. On both sides of the Shuimo catchment, the mountains are covered with a large amount of loose material. The tops of the mountains are covered with loess, while the middle and lower slopes are covered with weathered and fragmented gravel soil. This colluvial gravel soil consists of highly weathered phyllite, slate, and carbonaceous slate, with a typical thickness of 0.2 to 5 m and particle sizes ranging from 2 to 10 cm. The gaps between the particles are filled with fine particles and clay, which makes the soil highly permeable. This loose material structure is easily mobilized by heavy rainfall, flowing into the channel in the form of sheet and dispersed flows, making it a significant component of debris flow material sources.
According to previous research, sheet erosion occurs on slopes less than 45°, especially in the range of 25–32°. In areas without vegetation cover, soil erosion intensity can reach 19,745 t/km²·a. With 90% vegetation cover, the erosion modulus decreases to 7086 t/km²·a. Both steeper and flatter slopes exhibit relatively lower erosion rates. From the generated watershed slope map (Figure 10), it is evident that areas with slopes less than 45° cover 28.78 km2, accounting for 88.44% of the entire catchment. These areas are prone to erosion and are key zones for sediment production. Field surveys estimate that the sheet erosion material supply amounts to 942 × 104 m3.
To determine the transformable amount of various loose sediment sources, InSAR technology was used to evaluate the landslide deformation characteristics in the basin. Active landslides, which are small to medium-sized shallow landslides, are distributed throughout the basin. The transformation of landslide material typically occurs when the front edge is eroded by floods, with only 10% of the total landslide accumulation being transformable.
In the case of gravity erosion, collapse, and slope debris flow, materials are generally transformed into debris flow sediment sources, with a high transformation rate of 75%. Channel erosion is identified as the primary sediment source for debris flow. Field investigations clearly indicated the significant impact of debris flow material on the erosion of channel sides and bases within the main channel.
The statistics of loose materials in the debris flow catchment (Table 3) show that the convertible amounts of channel erosion and slope erosion are 1277 × 104 m³ and 518 × 104 m³, respectively, which account for 84.4% of the total material. Therefore, channel erosion and slope erosion are the main sources of debris flow material supply.
In summary, the total amount of loose sediment in the basin is 4608 × 104 m³, with a transformable amount of 2126 × 104 m3. In the upstream area, there are large groups of limestone collapse and rockfall deposits, with many developed landslides in tributary gullies, making gravity-induced sediment sources very abundant. The thickness of loose deposits within the main tributary valley ranges from 5 to 24 m, with a total channel length of 28 km. The area of slopes with an inclination below 45 degrees in the basin reaches 28.78 km2, accounting for 88.44% of the entire basin. Among these, there are 9.04 km2 of sloped farmland, which is highly prone to slope erosion, generating a significant amount of loose sediment that supplies debris flow.
During the recent debris flow event, a different sediment supply type from short-term concentrated rainfall-induced debris flows was observed. In the mid to lower basin, steep slopes with inclinations above 45° experienced numerous shallow landslides in saturated soils. These shallow landslides transformed into slope debris flows, providing direct sediment sources for the debris flow.
On the other hand, due to the large basin area, the mid and upper reaches are densely covered with vegetation, primarily collecting clear water. Most of the solid loose materials are stabilized on the slopes and at the slope bases, making them less likely to be directly eroded and transported by debris flows, with only a small portion being transformable into debris flow material. In the lower reaches, the rock and soil bodies are nearly exposed, and phyllite and calcareous slate are prone to weathering and peeling. The banks are continuously eroded and expanded by collapse and landslides. The loose soil bodies formed under these conditions are almost entirely transformable into debris flow material due to the geomorphological constraints of the valleys. Therefore, in the lower reaches, the abundance of solid loose material, coupled with a high accumulation rate, facilitates the frequent development and further evolution of slope debris flows.

4.3. Dynamic Process of the Debris Flow

4.3.1. Rainfall Process

Heavy rainfall is the primary triggering factor for debris flows. In the Bailong River Basin, there are two types of rainfall patterns that trigger debris flows. One type is short-term concentrated heavy rainfall, such as the catastrophic debris flow in Zhouqu County on 8 August 2010, and the debris flow in Wen County on 7 August 2017 [7]. The other type is a combination of previous precipitation and intense rainfall during the current period, with a typical example being the debris flow cn Wudu on 3 August 1984 [33]. The debris flow in the Shuimo Catchment belongs to the latter type.
According to meteorological data, from 14:00 on 14 August to 23:00 on 17 August, Wen County experienced large-scale continuous heavy rainfall (Figure 11). The number of heavy rain events, their intensity, range, duration, and cumulative precipitation within a short period all broke historical records for Wen County. The cumulative rainfall in the upper reaches of the Shuimo catchment reached 250 mm, while the rainfall in the downstream Shijiba Town was relatively small. This rainfall event mainly occurred in two stages (Figure 12 and Figure 13). The initial rainfall was primarily concentrated from 11 to 13 August, with the upstream Zuojiaba Rainfall Station recording a cumulative rainfall of 74 mm and the downstream Shijiba Rainfall Station recording 30.4 mm. Due to the sustained rainfall, the shallow layers of loose deposits in the basin were saturated.
On the 16th, from 15:00 to 15:00 on the 17th, another rainfall event occurred, lasting 24 h. The Zuojiaba Rainfall Station recorded a cumulative rainfall of 67.7 mm, reaching the heavy rain level, while the Shijiba Rainfall Station recorded only 8.1 mm, categorized as light rain. There was a significant difference in rainfall between the upstream and downstream areas during this period. The rainfall at the Zuojiaba Rainfall Station was mainly concentrated in two periods: the first peak lasted from 15:00 to 24:00 on the 16th, with a cumulative rainfall of 20.1 mm over 11 h and the maximum rainfall intensity of 4.3 mm/h occurring at 20:00 on the 16th; the second peak lasted from 1:00 to 15:00 on the 17th, with a cumulative rainfall of 47.6 mm over 13 h and the maximum rainfall intensity of 11.8 mm/h occurring at 5:00 on the 17th.
Actual rainfall monitoring data show that the hourly rainfall amount for triggering the debris flow in this event was not very large. Compared to the concentrated rainfall of 77.6 mm in 1 h for the Zhouqu debris flow on 8 August and 67 mm in 2 h for the Yangtang debris flow in Wen County, the significant characteristic of this rainfall event was that the hourly rainfall intensity was not high. However, there was a large accumulation of precipitation in the basin prior to the event, and the intensity of the daily rainfall during the event was high. This type of rainfall pattern can also trigger large-scale debris flows.
Regarding the characteristics of the triggering rainfall, Dangchang had a return period of 50 years, Liangdang had a return period of 70 years, and Wudu, Kang County, Hui County, and Wen County all reached or exceeded a return period of 100 years. Among them, the rainfall in the Bailong River, Baishui River, and Jialing River basins was 2.3 times, 3.0 times, and 1.7 times the historical extreme values, respectively.
From Figure 11, it can be seen that although the Shuimo catchment was not the center of the rainfall in this event, the total rainfall in its upstream area reached 147 mm. The cumulative rainfall prior to the occurrence of the debris flow reached as high as 74 mm, and the rainfall triggering the debris flow reached 67.5 mm.

4.3.2. Debris Flow Process

Based on the interpretation of images and DEM before and after the disaster, it is evident that the initiation point of the debris flow is located 8.5 km from the catchment mouth. Therefore, the main channel has a long transportation distance, making it prone to blockages from landslides on both sides. Combined with field investigations, a total of 8 blockage points were found in the main channel, and they have not completely failed yet (Figure 14). The channel has been widened to varying degrees, increasing 5–12 m upstream and 7–30 m downstream, indicating that the main channel has suffered severe erosion and widening.
The rainfall was mainly concentrated from 5:00 to 8:00 on the 17th, while the debris flow emerged from the outlet at 14:30 on the 17th, with a long interval of 7.5 h. The occurrence of this phenomenon is mainly related to blockages in the channel. On the other hand, the high vegetation coverage in the catchment delayed the gathering of rainfall. The area with vegetation coverage greater than 75% in the watershed was 23.26 square kilometers, accounting for 72% of the entire watershed. On the other hand, it is related to the fact that heavy rainfall mainly occurs in the upper reaches. The main channel has a length of 11.49 km and requires about 50 min for the convergence of water flow.
According to the field investigation, the debris flow disaster in the Shuimo catchment was triggered around 14:30 in the afternoon and gradually subsided around 17:30, lasting for about 3 h. At 14:30, the debris flow, carrying large boulders and mud, surged out of the channel and quickly entered the Bailong River. By 14:50, it started to block the river, and subsequently, more mud and sand continued to flow in, forming a barrier lake about 800 m long and up to 300 m wide, causing the water level of the Baishui River to rise rapidly. At 15:20, the barrier lake formed on the left bank of the Shuimo catchment outlet, raising the upstream water level by about 10 m and submerging the Xianya Dam Village. Villagers reported that the water level rose rapidly within a short period, and 20 min later, only the tops of the three-story buildings in the downstream Xianya Dam Village were visible.

4.4. Characteristics of the Debris Flow Disaster

According to the post-disaster investigation, this debris flow resulted in three deaths and direct economic losses of approximately 230 million. Based on the analysis of pre-disaster (17 July 2020) and post-disaster (19 August 2020) domestic high-resolution satellite data, post-disaster UAV aerial photography, and feedback from field surveys, an analysis of the distribution of the submerged area of the post-disaster lake, the barrier body, and the disaster damage distribution was conducted for the debris flow and barrier lake disaster. This analysis provided a macro-level assessment of the disaster situation (Figure 15) and obtained the macro-scale distribution of the disaster damage.
Utilizing the post-disaster high-resolution satellite imagery data from 19 August 2020, the interpretation of the debris flow barrier lake (Figure 15) was completed. The debris from the Shuimo catchment completely blocked the Baishui River, causing the water level in the upstream area to rise and submerging Zhuyuanba New Village, Shuimo New Village, and others. The initial surface area of the barrier lake was approximately 1.06 km2. Remote sensing imagery data from August 19 showed that the barrier lake area increased by 0.76 km2 compared to the original river channel, resulting in a submerged area of approximately 37.4 × 104 m2 relative to the pre-disaster imagery. This submerged area was mainly distributed in the Bai Shui River basin area around Zhuyuanba New Village, Shuimo New Village, and Xinguan Village. The G247 road from Shuimo New Village to Shijiba Town was submerged and covered with silt in that direction.
Based on this, the 59 people trapped on rooftops within the inundated area of the barrier lake were quickly identified, and helicopters were urgently dispatched to evacuate them to a safe area.
The debris flow accumulation fan in the Shuimo catchment had an area of 7.91 × 104 m2. The thickness of the debris flow accumulation at the mouth of the catchment was raised by 3.5 m on the original base, and the scale of the accumulation fan was 28 × 104 m3. It was distributed within a range of 40–120 m on both sides of the catchment. The barrier lake had an area of approximately 1.06 km2 and a submerged area of approximately 37.4 × 104 m2. It was mainly distributed in the Bai Shui River basin area around Zhuyuanba New Village, Shuimo New Village, and Xinguan Village (Figure 16).
The severely affected areas of the Shuimo catchment debris flow mainly include the mid-to-lower reaches of the main valley (Figure 17) and the alluvial fan area at the catchment mouth. These areas primarily consist of village and community residential points, farmland, orchards, roads, and bridges. Some sections have a high population density with concentrated residents. West of the downstream Lishu Dixia Village, the frequency of slope-type and valley-type debris flow disasters will gradually increase, resulting in significant losses.

5. Discussion

According to the investigation, the Shuimo catchment experienced a large-scale debris flow over 120 years ago, occurring after the earthquake in 1879, and no large-scale debris flows have occurred since then. Therefore, the Shuimo catchment is classified as a typical low-frequency debris flow. Additionally, due to the high vegetation coverage within the basin, it has generally been perceived as an area where debris flows are unlikely to occur. In this sense, this debris flow has a hidden characteristic.
Compared to more active debris flow catchments, the occurrence frequency of this type of debris flow channel is very low, which indicates that its rainfall threshold is quite high. Debris flows will only occur during rare extreme rainfall events [45]. Several factors contribute to its higher rainfall threshold, such as topographic characteristics determining the potential energy condition [4], the quantity and difficulty of materials within the watershed that can be converted into debris flows [46,47], which affect the rainfall threshold and formation process of debris flows [11,48], as well as conditions like lithology, landslides, land use, and vegetation cover [13,19,21,22,23].
Specifically, the reasons for the high rainfall triggering threshold of the Shuimo catchment are primarily attributed to topography and material supply. In terms of topography, although the Shuimo catchment has a significant elevation difference, its main channel is relatively long, leading to poorer confluence conditions. Regarding material supply, while investigations have found a large amount of material storage within the catchment, channel erosion and slope erosion are the main sources of material supply for debris flows. This presents greater difficulty in mobilizing materials compared to more active debris flows that rely on landslides and other means for replenishment. Additionally, the high vegetation cover in the Shuimo catchment enhances the stability of loose materials, resulting in a higher discharge required to mobilize these materials. Considering these factors, the Shuimo catchment has become a typical example of a large-scale, low-frequency debris flow catchment. The rainfall characteristics triggering this debris flow were influenced by both early rainfall and concurrent intense rainfall. The early rainfall increased the soil moisture content in the surface layers, which enhanced the runoff conversion rate during the subsequent rainfall and reduced the strength of the soil.
The hazard of debris flows is not only related to their activity but also to the location of engineering structures, the flood control capacity of flood control projects, and the economic and social conditions within the affected area. From the perspective of disaster characteristics, this event caused part of the houses in Qingtuya and Shuimo New Village at the village entrance along the main valley to be destroyed. The debris flow caused a large-scale blockage of the Baishui River, resulting in backflow that flooded Xiayaba Village and Zhuyuanba Village, forming a typical chain disaster. On one hand, after the Wenchuan earthquake, some hidden debris flows in the strong earthquake zone have acquired the conditions for becoming disasters. On the other hand, in recent years, with continuous population growth, a large amount of hillside land in the basin has been reclaimed as farmland. The increasing scarcity of construction land for towns and villages has led to the development of relatively low-lying areas along rivers and valley terraces as construction land for villages and towns, laying the groundwork for geological disasters.
For the application of remote sensing in emergency investigations of debris flow disasters, this study mainly used UAV images to quickly determine the situation of debris flow blockages and dammed lakes, providing support for emergency rescue. On the other hand, it also identified multiple situations of landslides blocking the channels and unstable slopes in the catchment, providing support for the analysis of the formation mechanism of debris flow.
Although this study provides an emergency investigation framework for debris flow disasters, the key to debris flow risk management is how to early identify and prevent the occurrence of such hidden debris flow disasters. It is evident that this study cannot achieve that. To achieve early identification of similar disasters, it is necessary to build on this study and incorporate related technologies such as remote sensing and geographic information science to quantify the characteristics of hidden debris flows and search for similar watershed units in the region. This will be the direction of our next efforts.

6. Conclusions

After the occurrence of the debris flow in the Shuimo catchment, this study conducted an emergency investigation of the triggering mechanisms and disaster characteristics of the debris flow using technologies such as remote sensing, InSAR, UAV, and field surveys. The main conclusions are as follows:
  • The Shuimo catchment is a typical low-frequency debris flow catchment, characterized by its hidden nature. Shuimo catchment has a large area and a significant elevation difference, with a relatively long main channel that provides sufficient potential energy conditions; however, the confluence conditions are inadequate. The debris flow was influenced by previous rainfall and triggered by the subsequent intense rainfall. The initiation mechanism of the debris flow is channel blockage and failure amplification.
  • Based on the interpretation of remote sensing images, it is known that the initiation point of the debris flow is located 8.5 km from the outlet, resulting in a long transportation distance. A total of 8 blockage points were identified. The channel has experienced severe erosion and widening. Using drone imagery, the area of the debris flow accumulation fan was determined to be 79,100 m². The area of the dammed lake is approximately 1.06 km², with the submerged area around 374,000 m², providing support for the rescue of trapped individuals.
  • Based on InSAR technology, the number and distribution of unstable slopes within the catchment were determined. Combined with field investigations, it was found that channel erosion and slope erosion are the primary sources of material supply for the debris flow.
  • The formation mechanism and dynamic characteristics of the Shuimo catchment debris flow can be summarized as follows: rainfall triggering → shallow landslides → slope debris flows → channel erosion → landslide damming → dam failure and increased discharge → deposition and river blockage.

Author Contributions

Conceptualization, methodology, software, writing—original draft preparation, F.H. and F.G.; supervision, validation, resources, D.Y. and X.M.; visualization, investigation, data curation, P.S. and Z.G.; writing—reviewing and editing, Y.Z. and Y.W. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Key Research and Development Program of China (2023YFC3007101); the Major Scientific and Technological Projects of Gansu Province (22ZD6FA051); the National Natural Science Foundation of China (42130709, 42077230); the Second Tibetan Plateau Scientific Expedition and Research Program (STEP) (2021QZKK0204); the Construction Project of Gansu Technological Innovation Center (18JR2JA006).

Data Availability Statement

For relevant data, please contact the corresponding author.

Acknowledgments

The DEM data were provided by the International Scientific and Technical Data Mirror Site, Computer Network Information Center, Chinese Academy of Sciences.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Geology of the Shuimo catchment. (1. talus deposit; 2. landslide deposit; 3. debris flow transportation zone and deposit; 4. upper Pleistocene Malan Loess; 5. Triassic sandy slate and sandstone; 6. lower Permian limestone and slate; 7. landslide; 8. debris flow; 9. collapse; 10. river system; 11. stratigraphic boundary; 12. catchment boundary).
Figure 1. Geology of the Shuimo catchment. (1. talus deposit; 2. landslide deposit; 3. debris flow transportation zone and deposit; 4. upper Pleistocene Malan Loess; 5. Triassic sandy slate and sandstone; 6. lower Permian limestone and slate; 7. landslide; 8. debris flow; 9. collapse; 10. river system; 11. stratigraphic boundary; 12. catchment boundary).
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Figure 2. Vegetation coverage of the Shuimo catchment.
Figure 2. Vegetation coverage of the Shuimo catchment.
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Figure 3. The overall process framework.
Figure 3. The overall process framework.
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Figure 4. Flow chart of SBAS-InSAR.
Figure 4. Flow chart of SBAS-InSAR.
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Figure 5. DEM (left) and slope map (right) of the Shuimo catchment.
Figure 5. DEM (left) and slope map (right) of the Shuimo catchment.
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Figure 6. InSAR interpretation of the material sources in the Shuimo catchment.
Figure 6. InSAR interpretation of the material sources in the Shuimo catchment.
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Figure 7. Interpretation of the material sources in the Shuimo catchment.
Figure 7. Interpretation of the material sources in the Shuimo catchment.
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Figure 8. Typical landslides in the Shuimo catchment.
Figure 8. Typical landslides in the Shuimo catchment.
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Figure 9. Channel deposits and erosion phenomena in the Shuimo catchment.
Figure 9. Channel deposits and erosion phenomena in the Shuimo catchment.
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Figure 10. Distribution of slope angles within the Shuimo catchment.
Figure 10. Distribution of slope angles within the Shuimo catchment.
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Figure 11. Spatial distribution of heavy rainfall in Wenxian County on 17 August 2020.
Figure 11. Spatial distribution of heavy rainfall in Wenxian County on 17 August 2020.
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Figure 12. Temporal distribution of rainfall in the Shuimo catchment from 1 August to 19 August 2020.
Figure 12. Temporal distribution of rainfall in the Shuimo catchment from 1 August to 19 August 2020.
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Figure 13. Temporal distribution of 24 h rainfall in the Shuimo catchment (from 15:00 on 16 August, to 15:00 on 17 August 2020).
Figure 13. Temporal distribution of 24 h rainfall in the Shuimo catchment (from 15:00 on 16 August, to 15:00 on 17 August 2020).
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Figure 14. Blockage points in the Shuimo catchment.
Figure 14. Blockage points in the Shuimo catchment.
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Figure 15. Images taken before and after the 2020 “17.8” debris flow in the Shuimo catchment.
Figure 15. Images taken before and after the 2020 “17.8” debris flow in the Shuimo catchment.
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Figure 16. Interpretation of the area of the alluvial fan of the Shuimo catchment debris flow.
Figure 16. Interpretation of the area of the alluvial fan of the Shuimo catchment debris flow.
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Figure 17. Pre- and post-disaster images of Shuimo New Village in the middle part of the Shuimo catchment.
Figure 17. Pre- and post-disaster images of Shuimo New Village in the middle part of the Shuimo catchment.
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Table 1. Details about the satellite remote sensing images used in this study.
Table 1. Details about the satellite remote sensing images used in this study.
Data TypeSpectral FeaturesSpatial ResolutionAcquisition Time
PleiadesVisible light: 4 near-infrared bands, 1 panchromatic band2 m multispectral, 0.5 m panchromatic spectrum24 August 2020
Gaofen-1Visible light: 4 near-infrared bands, 1 panchromatic band8 m multispectral, 2.0 m panchromatic spectrum20 August 2020
Gaofen-2Visible light: 4 near-infrared bands, 1 panchromatic band4 m multispectral, 0.8 m panchromatic spectrum24 August 2020
UAV imageTrue colorBetter than 0.2 m17 August 2020
Table 2. Estimated inventory of loose materials in the channel.
Table 2. Estimated inventory of loose materials in the channel.
Branch Channel NameAccumulation Thickness (m)Length along Path (m)Volume (104 m3)
Middle and upper reaches of the main channel
(above Lishuxia Village)		3–85880352.8
Middle reaches of the main channel
(Lishuxia Village–Wenjiagou Village)		5–103980477.6
Lower reaches of the main channel
(below Wenjiagou Village)		5–1546541047.1
Total 1877.5
Table 3. Statistical analysis of the loose materials in the Shuimo catchment available for transformation into debris flows.
Table 3. Statistical analysis of the loose materials in the Shuimo catchment available for transformation into debris flows.
Gravity ErosionChannel
Erosion		Slope ErosionTotal
Volume
(104 m3)		Area
(km2)		Supplementary Amount per
Unit Area
104 m3/km2
Landslide Collapse Slope Debris Flow Channel
Deposits		Residual Slope
Deposits
Material
reserves
(104 m3)		1560150781878942460831.26147.4
Transformation rate (%)107090685546.14
Available
supplementary amount
(104 m3)		156105701277518212631.2668.2
Proportion (%)7.344.943.2960.0724.36100
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Huo, F.; Guo, F.; Shi, P.; Gao, Z.; Zhao, Y.; Wang, Y.; Meng, X.; Yue, D. The Application of Remote Sensing Technology in Post-Disaster Emergency Investigations of Debris Flows: A Case Study of the Shuimo Catchment in the Bailong River, China. Remote Sens. 2024, 16, 2817. https://doi.org/10.3390/rs16152817

AMA Style

Huo F, Guo F, Shi P, Gao Z, Zhao Y, Wang Y, Meng X, Yue D. The Application of Remote Sensing Technology in Post-Disaster Emergency Investigations of Debris Flows: A Case Study of the Shuimo Catchment in the Bailong River, China. Remote Sensing. 2024; 16(15):2817. https://doi.org/10.3390/rs16152817

Chicago/Turabian Style

Huo, Feibiao, Fuyun Guo, Pengqing Shi, Ziyan Gao, Yan Zhao, Yongbin Wang, Xingmin Meng, and Dongxia Yue. 2024. "The Application of Remote Sensing Technology in Post-Disaster Emergency Investigations of Debris Flows: A Case Study of the Shuimo Catchment in the Bailong River, China" Remote Sensing 16, no. 15: 2817. https://doi.org/10.3390/rs16152817

APA Style

Huo, F., Guo, F., Shi, P., Gao, Z., Zhao, Y., Wang, Y., Meng, X., & Yue, D. (2024). The Application of Remote Sensing Technology in Post-Disaster Emergency Investigations of Debris Flows: A Case Study of the Shuimo Catchment in the Bailong River, China. Remote Sensing, 16(15), 2817. https://doi.org/10.3390/rs16152817

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