NHESSNatural Hazards and Earth System SciencesNHESSNat. Hazards Earth Syst. Sci.1684-9981Copernicus PublicationsGöttingen, Germany10.5194/nhess-19-93-2019Characteristics and influencing factors of rainfall-induced landslide and debris flow hazards in Shaanxi Province, ChinaCharacteristics and influencing factors of rainfall-induced landslideZhangKekzhang@hhu.edu.cnhttps://orcid.org/0000-0001-5288-9372WangShengBaoHongjunbaohongjun@cma.gov.cnZhaoXiaomengState Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, and College of Hydrology and Water Resources, Hohai University, Nanjing, Jiangsu, 210098, ChinaNational Meteorological Center, China Meteorological Administration, Beijing, 100081, ChinaShaanxi Climate Center, Xi'an, Shaanxi, 710014, ChinaKe Zhang (kzhang@hhu.edu.cn) and Hongjun Bao (baohongjun@cma.gov.cn)14January2019191931059September201812September201819December2018This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/This article is available from https://nhess.copernicus.org/articles/19/93/2019/nhess-19-93-2019.htmlThe full text article is available as a PDF file from https://nhess.copernicus.org/articles/19/93/2019/nhess-19-93-2019.pdf
Shaanxi Province, located in northwest China and spanning multiple
hydroclimatic and geological zones, has many areas largely suffering from
rainfall-induced landslide and debris flow. The objectives of this study are
to reveal the spatiotemporal characteristics of the two hazards and identify
their major controlling factors in this region based on a region-wide,
comprehensive ground-survey-based hazard inventory dataset from 2009 to 2012.
We investigated the spatiotemporal characteristics of the two hazards and
quantified the relationships between the occurrence rates of the two hazards
and their influencing factors, including antecedent rainfall amount, rainfall
duration, rainfall intensity, terrain slope, land cover type and soil type.
The results show that landslide has a higher occurrence rate and more
extensive distribution than debris flow in this region, while the two hazards
are both concentrated in the south with ample rainfall and steep terrains.
Both of the hazards show clear seasonalities: July–September for landslide
and July for debris flow. Rainfall characteristics (amount, duration and
intensity) and slope are the dominant factors controlling slope stability
across this region. Debris flow is more sensitive to these rainfall metrics
on the high-value ranges than landslide in this region. Land cover is another
influencing factor but soil type does not appear to impose consistent impacts
on the occurrence of the two hazards. This study not only provides
important inventory data for studying the landslide and debris flow hazards
but also adds valuable information for modeling and predicting the two
hazards to enhance resilience to these hazards in this region.
Introduction
Landslides and debris flows are two widespread and destructive natural
hazards around the world (Peruccacci et al., 2012; Huang et al.,
2017; Nicolussi et al., 2015; Blothe et al., 2015; Wooten et al., 2008; Hong et
al., 2007), which can cause large casualties and economic losses
(Jaboyedoff et al., 2012; Hong et al., 2017b; Zhang et al., 2016).
Globally, landslides are responsible for approximately 1000 deaths and
about USD 4 billion in property losses per year (Pradhan and Youssef, 2010).
Landslide-caused fatalities accounted for 17 % of fatalities due to
natural hazards (H. Y. Hong et al., 2015). For debris flows, it is more
difficult to quantify the resultant casualties and damages because it is
hard to distinguish debris-flow-induced losses from the losses caused by
concurrent flood or other hazards (Borga et al., 2014). China is
severely affected by geological disasters, including landslide and debris
flow (Petley, 2010; H. Y. Hong et al., 2015). Statistical reports by the Chinese
Institution of Geological Environmental Monitoring showed that unexpected
geological hazards lead to 1167 casualties and CNY 6.4 billion in property
losses per year (Zhang et al., 2017). Other research reported that
landslide disasters have caused about 1100 fatalities and USD 5–10 billion
in China since 2000 (Hong et al., 2017a).
Due to the massive casualties and property damages that landslide and
debris flow may cause, it is essential to have a profound comprehension of
the causes, e.g., heavy rainfall, earthquakes and human activities, of these
disasters (Chen et al., 2015b). Landslide occurrence is a
complex nonlinear process (Qin et al., 2001; Sorbino et al., 2010) that
is influenced by many different factors such as geological features and
hydrological conditions (Zhu et al., 2017). In many
regions, rainfall is the primary trigger (Milne et al., 2012)
of shallow landslides and debris flows that have posed significant threats
to human lives and properties (Gariano et al., 2015; Pradhan and Youssef,
2010). Hence, numerous studies have been conducted on understanding and
modeling the rainfall-induced landslides and debris flows.
The methods used to predict landslide occurrence can be divided into two
general categories, statistical methods and physically based models.
The representative statistical method is the rainfall threshold method
(Guzzetti et al., 2007; Peruccacci et al., 2012; Gariano et al.,
2015; Bogaard and Greco, 2018), which usually builds a simple statistical
model quantifying the relationship of landslide occurrence rate or
probability with cumulated rainfall (the total rainfall measured from the
beginning of the rainfall event to the time of slope failure), rainfall
intensity (the average rainfall intensity during the rainfall event) and/or
rainfall duration. Physically based models usually use rainfall time
series as input data to model the slope stability based on the physical
processes and mechanisms. There are many physically based landslide
forecasting models such as TRIGRS (Baum et al., 2010; Alvioli and Baum,
2016), SHALSTAB (Montgomery and Dietrich, 1994), SLIDE (Y. Hong et
al., 2015; Liao et al., 2012) and SLIP (Montrasio and Valentino,
2008). Recently, several studies were conducted to couple the landslide
models with distributed hydrological models to develop coupled
flood–landslide models (He et al., 2016; Zhang et al., 2016). Modeling
the movement and run-out extent of debris flow is a more complicated process
than modeling the slope failure or the landslide occurrence. Numerical
simulation of the debris flow process is usually based on shallow water
equations (Han et al., 2017) and numerical solutions of mass and
momentum conservation equations using finite-element and finite differential
methods (Naef et al., 2006; Zhang et al., 2015).
Despite that various advanced methods and models have been used for the
prediction of landslide and debris flow, it is still difficult to completely
explain the physical mechanisms controlling slope failure and to accurately
predict the occurrence of landslide and debris flow in most areas (Hong
et al., 2017a; Althuwaynee et al., 2014). In addition, there have been limited efforts
on landslide and debris flow prediction in Shaanxi Province, China, so far.
Additionally, most previous studies were mainly focused in
understanding and modeling landslides and/or debris flows in small and
medium-sized areas (Chen et al., 2016, 2017; Sun et al., 2016;
Zhuang and Peng, 2014). There is still limited knowledge on the
characteristics, distributions, and influencing factors of landslide and
debris flow hazards across this region.
Therefore, the objectives of this study are to reveal the spatiotemporal
characteristics of rainfall-triggered landslide and debris flow hazards in
Shaanxi Province and to identify the major controlling factors of the
occurrence of the two hazards. To this end, we firstly compiled an inventory
data of rainfall-induced landslide and debris flow events in Shaanxi
Province for the period 2009–2012 provided by the geological survey office
of the Department of Land and Resources of Shaanxi Province. Considering the
interannual and intra-annual differences in rainfall, we then analyzed the
characteristics of spatiotemporal distributions of landslide and debris flow
using statistical methods. Next, we derived the characteristics of rainfall
processes, terrain slope, land cover type and soil type for each grid cell.
Finally, we studied the relationships of landslide and debris flow
occurrence rates with rainfall level, terrain slope, land cover type and soil type.
Study area and dataDescription of study area
Shaanxi Province, situated in the middle of northwest China, is located
between 105∘29′ and 111∘15′ E longitude
and between 31∘42′ and 39∘35′ N latitude with a
total area of about 205 800 km2. Statistical data show that
more than 38 million people live in Shaanxi. Altitude mostly ranges from
350 to 3500 m with a regional average slope of 19.9∘ (Fig. 1a). In
Shaanxi, elevation is higher in the north and south and lower in the middle
(Fig. 1a). The average elevation of the Qinling Mountains is more than 2000 m
and they stretch from east to west, representing an important natural line
of demarcation between north and south China (Wu and Qian, 2017). The
high elevations and relatively steep terrains in many areas of this region
make them susceptible to both landslide and debris flow. The Bei Mountains
and the Qinling Mountains divide Shaanxi Province into three geographical
regions: Shaanbei Loess Plateau in the north, Guanzhong Plain (also known as
Wei River basin) in the central area and Qinling–Dabashan Mountains in the
south (Jiang et al., 2015). Because of this, land cover
shows a distinct regional distribution from north to south: grasslands,
cultivated lands and forests (Fig. 1b). The soil type in the study area is
mainly loam (Fig. 1c).
Spatial maps of (a) elevation, (b) land cover and
(c) soil type across the study region.
The hydrological conditions of Shaanxi Province are diverse due to the
diversity of its physiographic features and climate, which vary regionally
and seasonally. The study area consists of three main climatic zones,
the semiarid zone, semi-humid zone and humid zone, distributed from north to
south. Regional mean annual temperature is about 6.5–16.6 ∘C.
However, temperature decreases from south to north. Spatial average annual
rainfall is 400–600, 500–700 and
700–900 mm in the northern, central and southern areas,
respectively, while precipitation decreases from south to north and is
significantly influenced by the mountains. In addition, rainfall has a
strong seasonality in this region. Rainfall in summer is the greatest and
accounts for 40 %–60 % of annual rainfall. Rainfall of the remaining
seasons decreases in the order of autumn, spring and winter. As rainfall is
mostly concentrated in the monsoon season (May–October), rainfall-triggered
landslide and debris flow occur frequently during this season.
Datasets
Data used in this study include rainfall, inventory data of geological
hazards, digital elevation model (DEM), land cover and soil type. The
rainfall, DEM, land cover and soil type data are gridded data, while the
inventory data of landslide and debris flow hazards are a list of events with
recorded locations (latitudes and longitudes), hazard types, causes,
occurrence times and associated casualties.
The rainfall data are hourly observations from 756 stations provided by the
China Meteorological Administration (CMA). We interpolated the site data
into gridded data by using the inverse distance weighting method. The
spatial resolution of the grid is 90 m. The geological disaster data are
from the
geological survey office of Department of Land and Resources of Shaanxi
Province. The DEM data with a spatial resolution of 90 m × 90 m were
downloaded from the geospatial data cloud (http://www.gscloud.cn; DEM data, 2017). This
database covers land area from 60∘ N to 60∘ S and was
released to the public in 2003.
The GlobeLand30-2010 product is a product of global land cover at a spatial
resolution of 30 m derived from remote-sensing images in 2010 (Chen et
al., 2015a). The dataset covers land area from 80∘ N to
80∘ S and consists of 10 land cover types. These 30 m data were
aggregated to 90 m resolution to match with the DEM data.
The soil data are from the Harmonized World Soil Database (HWSD) v1.2
(https://daac.ornl.gov/SOILS/guides/HWSD.html; Soil data, 2017), which was compiled from
four source databases, the European Soil Database (ESDB), the 1:1000000
soil map of China, various regional SOTER databases (SOTWIS database) and
the FAO and FAO-UNESCO soil maps of the World. The soil database used in the research is
classified based on the USDA classification method of soil texture, which
includes 13 types. The soil data were also reprojected and resampled to the
90 m resolution.
Methodology
To reveal the spatiotemporal distributions of the rainfall-triggered
landslide and debris flow hazards, we analyzed the spatial, latitudinal,
interannual and seasonal distributions of these hazard events and the
relationship of the number of hazard events with the corresponding rainfall amount.
To investigate the impacts of rainfall characteristics, including antecedent
rainfall amount (Pa), rainfall duration (D) and rainfall intensity (I),
terrain slope (θ), land cover type (L), and soil type (S)
on the occurrence rates (R) of the landslide and debris flow, we first
projected the locations of these recorded hazard events onto the DEM grid with
a spatial resolution of 90 m. If multiple events of the same type of hazard
occurred on the same grid cell within 1 h, these events were treated as
one event; the earliest occurrence time of these events is treated as the
occurrence time of the combined event. From the 90 m DEM, we further
computed the slope angles for each grid cell. We then tabulated all of the
above gridded data with the following attributes: grid cell ID, rainfall
event ID, rainfall amount, rainfall duration, rainfall intensity, rain
intensity class, slope, land cover type, soil type and hazard type. We
defined a rainfall event as an event with continuous rainfall or a
combination of several discontinued rains with the non-rain intermittent
periods less than or equal to 2 h.
When we calculated the occurrence rate of one type of hazard, we excluded
all grid cells without any reported event of this type of hazard and all
rainless events from the analysis. The occurrence rate of a kth type of hazard
conditional on a given explanatory variable or its class J (Rj,k) is defined as
Rj,k=n(J==jandK==k)n[J==jand(K==korK==0)],
where K is the hazard type (0, 1 and 2 for rainfall event without causing
any geological hazard, rainfall-induced landslide and rainfall-induced debris
flow, respectively); J is the class of Pa, D, I, θ, land
cover type and soil type; n(J==j and K==k) is the number of events of a given hazard k when the
corresponding J belongs to the jth class; and n[J==i and (K==k or K==0)]
is the number of positive and negative events of a given
hazard k when the corresponding J belongs to the jth class. In this study,
we classified the rainfall amount, rainfall duration, rainfall intensity
and rain type into five (0–10, 10–30, 30–60, 60–100 and >100 mm), five
(0–3, 3–12, 12–24, 24–36 and >36 h), five (0–1,
1–2, 2–3, 3–5 and >5 mm h-1) and four classes (light rain,
moderate rain, heavy rain and violent rain), respectively. Following the
American Meteorology Society (Glickman and Walter, 2000), light rain, moderate
rain, heavy rain and violent rain are defined as rains when the
precipitation rate is <2.5, 2.5–7.6,
7.6–50 and >50 mm h-1, respectively. We
categorized the slope, land cover type and soil type into five
(0–2, 2–5, 5–10, 10–20 and >20∘), three (cultivated land, forest and
grassland) and three classes (loamy sand, loam and clay), respectively.
The other land cover types and soil types are not used in the computation of
the hazard occurrence rates because we did not find any reported landslide
or debris flow event under these types.
Locations of reported rainfall-triggered landslide and debris flow
events and the resultant casualties in Shaanxi Province from 2009 to 2012; the
inset shows the location of Shaanxi Province in China.
ResultsSpatiotemporal distributions of landslide and debris flow events
The locations of the recorded landslide and debris flow events and the
resultant casualties from 2009 to 2012 are shown in Fig. 2. It is clear that
all of these recorded landslide and debris flow events are located to the
south of 36∘ N (Fig. 2). In general, debris flow events are
distributed further south than landslides. Most of the landslide and debris
flow events are near the rivers and/or in the areas with steep slopes (see
Figs. 2 and 1a). In addition, the landslide events outnumber the debris
flow events (Fig. 2), indicating that landslide occurs more frequently than
debris flow in this region.
(a) Interannual distributions of reported landslide and debris
flow events and the associated casualties from 2009 to 2012 and (b) pie
charts of the disaster types and their corresponding casualties.
There were a total of 1177 reported rainfall-triggered landslide events in
Shaanxi Province from 2009 to 2012 with 69, 619, 332 and
157 events in the 4 years (Fig. 3a), while a total of 209 rainfall-triggered
debris flow events occurred in this province during the same period, with 6, 175, 13 and 15 events in the 4 years (Fig. 3a). More than
half of the two types of events occurred in 2010. The corresponding
casualties are clearly proportional to the number of hazards (Fig. 3a). In
particular, landslides and debris flows in 2010 killed 72 and 73 people,
respectively. During the 4-year period, the reported landslide and
debris flow hazards caused the deaths of 131 and 78 people, respectively
(Fig. 3a), indicating that the two types of hazards are destructive in this
region. Generally, debris flow is even more destructive than landslide.
Although the number of debris flow events accounts for only 15 % of the
total events of the two hazards, the debris-flow-caused fatalities are 37.32 %
of the total deaths caused by the two hazards (Fig. 3b). The above
results suggest that debris flow imposes a higher threat to people in this
province per event than landslide.
In terms of interannual distributions of the two hazards, total annual
numbers of landslide and debris flow hazards show a correlation with annual
rainfall amount (Fig. 4a). However, annual rainfall amount is not the only
factor influencing the occurrences of the two hazards. For example, there is
more annual rainfall in 2011 and 2012 than in 2010, but the total numbers of
landslide and debris flow events in 2011 and 2012 are actually lower than
these in 2010 (Fig. 4a). In terms of intra-annual distributions of the two
hazards, landslide events are mainly distributed between July and September,
which are the top 3 months in terms of both total rainfall amount
(Fig. 4b) and average rainfall intensity (Fig. 4c). Meanwhile, almost all
debris flow events occurred in July, the month having the largest rainfall
amount (Fig. 4b) and rainfall intensity (Fig. 4c) with multi-year mean
values of 117 mm month-1 and 0.96 mm h-1, respectively, during a
year. Statistical analysis shows that rainfall between July and September
accounts for 63.6 % of annual rainfall, while the proportions of
landslide and debris flow events during the 3 months are 98.6 % and
100 % of annual events, respectively. As can be seen, the landslide and debris
flow hazards are seasonal hazards in Shaanxi Province and mainly occur
during the rainy season. The above results show that the landslide season is
longer than the debris flow season.
(a) Yearly distributions and (b) monthly distributions
of rainfall amount, the number of landslide events, and the number of debris
flow events from 2009 to 2012 and (c) the distribution of multi-year
mean monthly rainfall intensity.
We further analyzed the latitudinal distribution of annual rainfall, the
number of landslides, the number of debris flows, the zonal average slope
and the percentages of dominant land cover by dividing the region into four
latitude bins (31–33, 33–34, 34–35 and 35–36∘ N). As there are no reported landslide and debris flow
events in the areas north to 36∘ N, we excluded these regions for
analyzing the distributions of these hazards and their relations to
rainfall, terrain slope and land cover in these areas. There are apparent
latitudinal gradients in annual rainfall and the numbers of reported landslide
and debris flow events, which all decrease from the south to the north
(Fig. 5). The regional average terrain slope generally decreases from the south to
the north with values of 23.4, 23.7,
10.7 and 11.4∘ in the four latitude bins (Fig. 5).
These results suggest that more rainfall and steeper slopes in the south can
explain the larger numbers of reported landslides and debris flows in the
south than in the north. In addition, the southern part of this province
(31–34∘ N) is mainly covered by forests (≥78 %),
while the regions between 34 and 35∘ N and between
35 and 36∘ N are dominated by cultivated lands (50 %)
and grasslands (47.1 %), respectively (Figs. 5 and 1a). Although the
southern region has a denser and better preserved land cover than the middle
and northern parts, the southern region still experiences more landslide and
debris flow hazards. This suggests that the meteorological and
geomorphological factors such as rainfall and terrain slope play more
important roles in controlling the landslide and debris flow occurrence than land cover.
Distributions of annual rainfall amount, landslide events, and debris
flow events along the latitude bands and spatial average slopes and percentages
of dominant land cover types in these latitude bands.
Impacts of rainfall amount, intensity and duration on the landslide and debris flow occurrence
To attribute the causes of the landslide and debris flow hazards, we further
analyzed the relationships between rainfall characteristics (antecedent
accumulated amount, duration and intensity) and the occurrence rates of the
two hazards. Both the number of landslide events and the number of debris
flow events are not the least in the smallest antecedent rainfall amount.
However, the number of landslide and debris flow events increases with an
increasing amount of antecedent rainfall in the other four classes (Fig. 6a).
Meanwhile, the occurrence rate of debris flow exponentially increases
with increasing antecedent rainfall amount (R=0.0022exp1.8127Pa;
R2=0.988) (Fig. 6a). A similar
relationship appears between the landslide occurrence rate and antecedent
rainfall amount (R=0.0034exp1.6681Pa; R2=0.977). However, the landslide occurrence rate
is higher than the debris flow occurrence rate when antecedent accumulated
rainfall is lower than 100 mm (Fig. 6a). Once antecedent accumulated
rainfall is above 100 mm, the debris flow occurrence rate becomes much
larger than the landslide occurrence rate (Fig. 6a). This suggests that
triggering a debris flow generally requires more rainfall than triggering a landslide.
Relationship of occurrence rates of landslide and debris flow events
with the corresponding (a) accumulated amount of antecedent continuous
rainfall, (b) rainfall duration and (c) average rainfall intensity.
The occurrence rates of the two hazards also show positive exponential
relationships with the rainfall duration (R=0.0002exp(1.7175D), R2=0.997 for landslide;
R=0.00009exp(1.9526D), R2=0.977 for
debris flow) (Fig. 6b). In addition, the occurrence rates of the two hazards
also show positive exponential relationships with the average rainfall
intensity (Fig. 6c). These results indicate that rainfall amount, duration
and intensity all play an important role in controlling the landslide and
debris flow occurrence in this region. In addition, the three rainfall
metrics usually correlate with each other to some extent. In other words,
the rainfall event that has the largest accumulated rainfall usually has a
long duration and high average rainfall intensity.
Regional average occurrence rates of landslide and debris flow events
under different rainfall intensity classes.
In terms of the rainfall intensity, rainfall events can be classified into
four classes, i.e., light rain, moderate rain, heavy rain and violent rain
according to the American Meteorology Society. Therefore, we also calculated the
regional average occurrence rates of landslide and debris flow under the
four rain classes. Similar to the relationships between the occurrence rates
and rainfall intensity (Fig. 6c), the regional average occurrence rates of
the two hazards increase largely with increasing rainfall class (Fig. 7).
Furthermore, Fig. 8 shows the spatial maps of landslide and debris
occurrence rates under different rain classes. As rain becomes severe, both
landslide and debris flow occur on more grid cells (Fig. 8a and h).
For example, light rains caused 163 landslide events and
26 debris flow events during the 4-year period with average occurrence
rates of 0.006 % and 0.005 %, respectively. In contrast, violent rains
have led to 273 landslide events and 60 debris flow events during the same
period with average occurrence rates of 2.70 % and 8.57 %,
respectively. Meanwhile, the landslide occurrence rates on the grid cells
that experience at least one landslide event during the 4-year period
increase with increased rainfall intensity as well (Fig. 8a–d). As shown in
Fig. 8e–h, the debris flow occurrence rates on the grid cells that
experience at least one debris flow event during the 4-year period show
a similar correlation with the rain classes (or rainfall intensity classes).
Spatial distributions of the occurrence rates of (a–d) landslide
and (e–h) debris flow under four rainfall intensity classes: light
rain, moderate rain, heavy rain and violent rain; only these grid cells with
recorded landslide or debris flow events were analyzed and plotted in this figure.
Relationship of the landslide and debris flow occurrence with slope, land cover type and soil type
Terrain, in particular terrain slope, is another important factor
determining slope stability. Therefore, we grouped the 90 m grid cells with
at least one reported landslide or debris flow event during the study period
into five slope bins, i.e., 0–2, 2–5, 5–10, 10–20 and >20∘, and
computed the respective landslide and debris flow occurrence rates. It is
obvious that there are strong positive correlations between the occurrence
rates of the two hazards and the slope angle (Fig. 9). Once again, the
landslide occurrence rate is clearly larger than the debris flow occurrence
rate under all five slope classes (Fig. 9). Relative to debris flow,
landslide occurrence is more sensitive to terrain slope (Fig. 9). With
increasing terrain slope, the landslide occurrence rate accelerates much
faster than the debris flow occurrence rate.
Occurrence rates of landslide and debris flow under different degrees
of terrain slopes.
Occurrence rates of landslide and debris flow under different
(a) land cover types and (b) soil types.
We further analyzed the relationships of the hazard occurrence rates with
land cover type and soil type. For debris flow, the occurrence rate is
higher on the cultivated lands, followed by forests and grasslands
(Fig. 10a). As shown in Fig. 1b, grasslands are mainly located in the north where there is less rainfall and much flatter terrain than in the south. Therefore, it
is not a surprise to observe a lower debris flow occurrence rate on grasslands
than on cultivated lands and forests. For landslide, the occurrence rate is
also the highest on cultivated lands, but the occurrence rates on forests
and grasslands are very similar (Fig. 10a). Higher occurrence rates for both
landslide and debris flow on cultivated lands than on forests and grassland
suggest that the destruction and conversion of natural dense land cover can
weaken slope stability, making these areas more susceptible to landslides.
In this region, our analysis based on the available data does not show that
soil type imposes apparent consistent effects on the occurrence rates of
landslide and debris flow. For example, landslide has the highest occurrence
rate in the clay soil among the tree-dominant soil types in this region,
while the landslide occurrence rates in the loam soil and the loamy sand
soil are comparable (Fig. 10b). In contrast, debris flow has the highest
occurrence rate in the loamy sand soil, while the debris flow occurrence
rates are similar in the loam and clay soils (Fig. 10b).
Discussions
Based on the survey of rainfall-induced landslide and debris flow hazards
from 2009 to 2012 in Shaanxi Province, China, our results show that both
landslide and debris flow occur frequently in this region and are mainly
distributed in the southern part of this province, which has more rainfall
and steeper terrain slopes than the other areas of this province. Landslide
happens more frequently than debris flow. Although the number of the
reported debris flow events is only one-sixth of the number of the recorded
landslide events in this region, the debris-flow-caused casualties are equal
to 60 % of the landslide-caused casualties. Clearly, debris flow is more
destructive than landslide in this region in terms of the casualty per
event. Like many areas in the world, debris flow usually occurs in areas
near stream networks, which usually have a higher population. Moreover,
debris flow usually carries more materials and travels a longer distance
than landslide, making it more harmful to people and
property (Ietto et al., 2016). In fact, most debris flow
events are initialized from landslide and cause more damage to the
environment and society (Peng et al., 2015; Zhou et al., 2013).
Our results show that rainfall characteristics including rainfall amount,
rainfall intensity and rainfall duration all play important roles in
controlling the occurrence of landslide and debris flow. Relatively
speaking, rainfall amount and rainfall duration have higher impacts on the
occurrence of landslide and debris flow than average rainfall intensity in
this region. This is because a rainstorm with higher average rainfall
intensity does not necessary last for a long duration and leads to a larger
accumulated rainfall amount. In addition, one has to note that the three
rainfall characteristics do not necessarily correlate with each other. Previous studies have pointed out that different types of landslides and
debris flows have different critical rainfall conditions for failure
considering the different geologic and geomorphologic conditions (Zezere
et al., 2015; Guzzetti et al., 2008). For example, rapid debris flows are
typically triggered by very intense showers concentrated in a few hours,
while shallow translational soil slips are usually triggered by intense
precipitation falling within a few days (Zezere et al., 2015). In
contrast, deep-seated landslides of rotational, translational and complex
types are related to long periods (weeks to months) of nearly constant
rainfall (Zezere et al., 2015; Chen et al., 2013). In general, rainfall
with a long duration and large amount is more likely to trigger
landslide and debris flow (Saito et al., 2014).
Terrain slope is another important factor influencing the slope stability
since gravity makes these slopes with higher slope angles more vulnerable
(Nourani et al., 2014; Dehnavi et al., 2015). In addition, terrains with
steep slopes make plants harder to establish and grow. Furthermore, it is
harder for
vegetation roots to reach the sliding surface if the slope is steep
(usually exceed 1.5 m) (Ocakoglu et al., 2002; Cammeraat et al., 2005). In
this case vegetation biomass may increase the weight of landslide body and
promote the occurrence of landslides (Nilaweera and Nutalaya,
1999; Collison and Anderson, 1996). The terrain and vegetation can interact
with each other to create complex hydrological and mechanical effects on the
slope stability. Benefits from vegetation are conditional on the geological
and geomorphological conditions (Nilaweera and Nutalaya, 1999; Collison and Anderson, 1996).
Land cover type is another factor that impacts the slope stability. As shown
in our results (Fig. 10), cultivated lands have higher landslide and debris
flow occurrence rates than forests in the same climatic zone. Similar
findings were also reported in previous research, showing that
conversion of natural vegetated lands, in particular forests, to cultivated
lands or the early-stage abandonment of cultivated lands can largely weaken
slope stability by increasing surface water runoff, intensifying erosion
processes and increasing soil instability (Begueria, 2006; Lopez-Saez et
al., 2016; Persichillo et al., 2017). In addition, the slopes with woody
vegetation are more stable than those with herbaceous vegetation because
woody vegetation has deeper roots than herbaceous vegetation and can draw
down soil moisture, making the slopes more stable (Kim et al.,
2017; Begueria, 2006). In addition, some studies also show that the stand
age, structure and composition of vegetation can influence the slope
stability (Turner et al., 2010).
In this region, soil type does not appear to impose apparent consistent
effects on the occurrence rates of landslide and debris flow based on the
available data. These results suggest that soil type is not the dominant
factor influencing the slope stability in this region. As shown in other
studies, soil types and their physical properties such as cohesion,
saturated hydraulic conductivity, porosity and friction angle have impacts
on the slope failure and stability (Antinoro et al., 2017; van Asch and
Malet, 2009; Zhang et al., 2016; Pasculli et al., 2017; Milne et al., 2012).
Conclusions
In this paper, we analyzed the spatiotemporal distributions, occurrence
rates and resultant casualties of rainfall-triggered landslide and debris
flow based on a survey from 2009 to 2012 in Shaanxi Province, China. Our
results show that landslide has a higher occurrence rate and more extensive
distribution than debris flow in Shaanxi Province, while both of the two
hazards are concentrated in the south of this region with ample rainfall and
relatively steep terrains. Debris flow is more destructive than landslide in
terms of the casualties per event. Both landslide and debris flow show a
clear seasonality corresponding to the rainy season in this region. Debris
flow mainly occurs in July, whereas landslide usually takes place between
July and September.
The characteristics of rainfall events including accumulated rainfall
amount, duration, and intensity and terrain slope show the strongest impacts
on the slope stability and the occurrence rates of landslide and debris
flow. The landslide and debris flow occurrences have exponential
relationships with all of the above four factors (P<0.1). When
accumulated rainfall amount and intensity are on the low and intermediate
levels, landslide has a higher occurrence rate than debris flow. Conversely, the debris flow occurrence rate is much higher than the landslide
occurrence rate when accumulated rainfall amount and intensity are at a
high level. Responses of the landslide and debris flow occurrence rates to
rainfall duration do not differ much between each other. The occurrence of
both landslide and debris flow also largely depends on the terrain slope,
but landslide has a higher sensitivity to terrain slope than debris flow
does. Our results also show that land cover also influences the occurrence
of the two hazards to some extent in this region. In particular, both
landslide and debris flow has lower occurrence rates on natural
vegetated land than on cultivated lands. However, the study does not
find an apparent relationship between the occurrence rates of the two
hazards and soil type. In summary, we compiled an important data inventory
of the rainfall-triggered landslide and debris flow hazards in Shaanxi
Province, China, based on a 4-year survey and revealed the spatiotemporal
distributions and characteristics of these events and the impacts of
rainfall characteristics, topography and soil type on the occurrence of
landslide and debris. This study not only provides an important inventory
data for understanding the formation mechanisms and characteristics of the
landslide and debris flow hazards but also adds valuable information for
modeling and predicting the rainfall-triggered landslide and debris flow
hazards to improve preparedness for and enhance resilience to these hazards
in this region and the other similar areas.
The DEM data used in this study were provided by the geospatial
data cloud (http://www.gscloud.cn, DEM data, 2017). The land cover data
were derived from GlobeLand30-2010, which is a product of global land cover at a
spatial resolution of 30 m derived from remote-sensing images in 2010 (Chen et
al., 2015a, http://www.globeland30.cn, last access: 2 January 2017). The
soil data are from the Harmonized World Soil Database (HWSD) v1.2
(https://daac.ornl.gov/SOILS/guides/HWSD.html, Soil data, 2017). Rainfall
data were provided by the National Meteorological Information Center of China
Meteorological Administration (http://data.cma.cn, last access: 9 January 2019).
The other data can be provided by the authors upon request.
KZ designed the study; SW and KZ conducted this study;
KZ and SW wrote this paper; HB and XZ provided the data and reviewed this paper.
The authors declare that they have no conflict of interest.
Acknowledgements
This study was supported by the National Key Research and Development Program
of China (2018YFC1508101 and 2016YFC0402701), National Natural Science Foundation of China (51879067,
41775111, 41875131), Natural Science Foundation of Jiangsu Province (BK20180022),
Six Talent Peaks Project in Jiangsu Province (NY-004), Key Research & Development
Program of Ningxia Hui Automonous Region, China (2018BEG02010), Fundamental Research Funds for the Central Universities of
China (2018B42914), Open Foundation of State Key Laboratory of Hydrology-Water
Resources and Hydraulic Engineering (2017490311), and Priority Academic Program
Development of Jiangsu Higher Education Institutions.
Edited by: Mario Parise
Reviewed by: two anonymous referees
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