Assessment of soil moisture dynamics and storm-induced
landslides hazard in forest landscapes
YI WANG1 , KEIJI TAKASE2, SRIKANTHA HERATH1
1

Environment and Sustainable Development Programme, United Nations University (UNU Centre),
5-53-70, Jingumae, Shibuya-ku, Tokyo 150-8925, Japan, ywang@hq.unu.edu
2Faculty of Agriculture, Ehime University, Matsuyama 790-8566, Japan

ABSTRACT: This study aims to provide insights in the linkages between soil moisturedynamics and landslides occurrence. A hydrologic model was developed for assessing
storm-induced landslides in forest landscapes. For model validation, it was applied in aforest catchment in Japan, which was affected by typhoons in 2004. Through the model,hydrologic conditions such as rainfall intensity, rainwater storage and soil moisture in2004 were obtained and compared with other 19 years (1985~2003). The relationshipbetween landslide occurrence and hydrologic phenomena were then assessed. Results
indicated that soil moisture, excess rainfall storage combined with rainfall intensity, andits duration were the key elements for landslides occurrence. It was able to represent
hydrologic phenomena reasonably and used for assessment of discharge, soil moisture,
and water storage. The concept of this model can be applied in other areas and is
expected to provide important information on soil moisture behavior for forecasting andpreventing landslide disasters.
Keywords: landslide; soil moisture dynamics; forest landscape
1. INTRODUCTION
In 2004, a series of typhoon accompanying with heavy rainfall have lashed the Japan
Islands and caused many floods and landslide disasters across the country. Thosetyphoon events from June to September in 2004 have triggered more than 160
landslides in the forest of Ehime Prefecture, Japan. Most of the slides were shallow
landslides in nature. Shallow landslides usually occur during the heavy rainfall(Campbell, 1975). Normally, rainwater storage is considered as a very important
indicator to the landslide occurrence, water saturation in the field is a significant factor
that allows the force of gravity to overcome the resistance of earth material to landslide
movement (Grozier, 1999). The rapid infiltration of precipitation, causing soil saturation
and a temporary rise of pore-water pressure, is generally accepted to be the cause of1

Rainfall
Evapotranspiration

Interception
Scon

Sstem
Permeable area
INF
INFmaxF18
Fs0

Impermeable area

Fs
S2
G2
S3
G3
S4
G4
S5
G5
S6

t
Infiltration

Sn

Cn

S1

C1

Excess Rainfall

C2

Percolation

C3

Runoff

C4
C5
C6

Fig. 1 Schematic structure of the hydrologic model in this study
most shallow landslides during storm events (Wieczorek, 1996). Quantitative
information on soil moisture before and during a rainfall event is important to forecast
the time and location of shallow landslides (Crosta and Frattini, 2003,1998) and floods(Glade, 2000). However, surface soil moisture content is highly variable in both space
and time; for many regions, soil moisture conditions, such as rainfall infiltration and soil
water percolation, are not available (Wieczorek and Glade, 2005; Wieczoroek, 1996).
Hence, in this research, a conceptual hydrologic model was applied for the analysis of
rainwater storage and soil moisture behavior in heavy storms, which caused landslides
in a forest catchment. The relationships between them and landslide occurrences werethen discussed.
2. HYDROLOGIC MODEL TO EVALUATE RAINWATER STORAGE
The concept of the proposed model in this study is shown in Fig. 1. This model, which
includes infiltration curve, was proposed to analyze the hydrologic processes in acatchment by Takeshita (Takeshita, et al., 2001. Takeshita and Takase, 2003). It isconstructed by a series of reservoirs to represent hydrologic processes in a forest
catchment. It includes the interception by the canopy of trees, evapotranspiration,
infiltration, percolation, and surface flow in both permeable and impermeable areas,
subsurface and base flow in different soil layers. In Fig. 1, Scon, Sstem, Sn, S1~S6 arestorage in each reservoir, respectively. In the model, Horton’s infiltration theory was2

used to divide actual rainfall into excess rainfall and infiltration water. S1 represents
storage of excess rainfall. The Horton’s infiltration equation is represented as follows
INF (t ) = FS + ( INF max − FS ) exp(− B ⋅ t )(1)
Where, INF (t) is the infiltration rate at time t, Fs is the final infiltration rate, INFmax
is the maximum rate and corresponds to the infiltration rate when surface soil layer isperfectly dried.
In this research, the occurrences of storm-induced landslide in an experiment forest
catchment were analyzed by the proposed hydrologic model. The catchment is locatedin a mountain of OZU city, Ehime Prefecture, Japan. The total area of the catchment is
21.0 ha, the surface geology of the catchment is the mixture of sandy rock and clay slate(Takase, 1988, 2000). From late-June to September of 2004, this forest catchment
suffered from landslides caused by typhoons accompanying with heavy storms. In thisstudy, therefore, long-term hydrologic properties in this catchment were investigated bycomparing with the hydrologic condition in 2004, to identify the role of hydrologic
conditions for landslide initiation.
3. HYDROLOGIC ANALYSIS AND DISCUSSION
3.1 Analysis of hydrologic properties in the catchment
To manage the hazard associated with shallow landslides, accurate identification ofhydrologic properties including not only rainfall but also soil moisture conditions thattriggered slope failure is needed for landslides’ forecasts and warnings. Therefore, thehydrologic properties in our experimental forest catchment were investigated. Observed
maximum daily and hourly rainfall (Rdmax, Rhmax) of 1985~2004 were shown tocompare the difference of rainfall characteristics of 2004 with other years in Table 1. In
addition, maximum hourly discharge (Qpeak) and upper layer soil moisture(SM) withexcess rainfall storage (S1) and storage in the lower layers (S2 ~ S6) were calculated ineach year by using the proposed hydrologic model. It was found from the table that anextremely heavy and sustained storm occurred in 2004. Maximum daily and hourly
rainfall, peak discharge, sum of upper layer soil moisture (SM) and excess rainfall
storage (S1) in 2004 show the highest values among all years. This might be consideredas the reason that flood disaster occurred in the forest area in 2004.
3.2 Statistical Analysis
In order to compare the hydrologic properties, a detailed analysis has been carried out inthose years. The statistical properties of maximum hourly rainfall, up-layer storage thatmeans the sum of SM, and S1 events were evaluated by the Hasen Plot method. The
regression line of logarithm distribution was obtained as shown in Fig. 2 and Fig. 3.

3

Table 1 Comparison of hydrologic properties in different years
Year Rdmax(mm/d)Rhmax(mm/hr) Qpeak(mm/hr) SM～S1(mm) SM～S2(mm) SM～S3(mm) SM～S6(mm)
1985
79.5
20.5
3.31
336.4
351.9
397.4
753.4
1986
94.0
40.0
6.54
355.4
374.2
394.0
768.5
1987
111.0
32.0
5.11
355.8
379.4
396.0
751.4
1988
132.5
41.0
7.73
364.8
377.7
385.3
747.8
1989
117.5
31.5
8.98
371.2
390.7
404.8
796.8
1990
99.5
29.5
6.27
355.1
372.0
382.2
772.8
1991
70.0
33.0
3.94
340.5
354.6
377.7
768.8
1992
115.5
23.5
2.80
333.7
340.4
350.6
742.4
1993
160.0
40.0
10.38
382.3
401.6
442.4
799.2
1994
64.0
19.0
1.97
328.7
334.7
336.7
690.3
1995
171.0
27.0
9.77
375.4
410.4
423.1
775.0
1996
119.0
27.0
3.76
339.5
355.8
365.7
679.6
1997
159.5
40.0
6.93
360.0
366.0
368.1
714.1
1998
99.5
32.0
4.97
344.7
375.0
388.0
721.4
1999
76.5
30.0
4.34
343.2
361.7
369.8
724.2
2000
99.0
21.5
5.68
352.1
362.3
372.3
705.7
2001
69.0
25.0
3.85
338.5
356.7
370.4
705.1
2002
56.0
13.5
0.57
316.4
330.5
338.1
689.3
2003
79.3
28.0
5.66
351.7
356.2
370.3
762.7
2004
220.5
61.0
19.41
399.0
410.5
414.4
750.0

Rdmax:

Maximum daily rainfall;

Rhmax:

Maximum hourly rainfall

Fn(%)

Wn(%) T (Year)
T(年)

Fn(%)

Wn(%)

99.99

.01

10000

99.99

.01

10000

.1

1000

99.9

.1

1000

1

100
83

99

1

100
100

95
90
80
70

5
10
20
30

20
10
5

95
90
80
70

5
10
20
30

20
10

50
30
20
10
5

50
70
80
90
95

2

50
30
20
10
5

50

2

時間雨量(1985～2003年)
Hourly Rainfall (1985~2003)

99.9

Hourly Rainfall (2004)
時間雨量(2004年)

99

1.1

Up-layer storage
タンクNo.1の貯留量(1985~2003)＋表層土壌水分量(1985～2003年)
タンクNo.1の貯留量
Up-layer storage＋表層土壌水分量(2004)(2004年)

70
80
90
95

T (Year)
T(年)

5

1.1

1

99

1.01

1

99

1.01

.1

99.9

1.001

.1

99.9

1.001

.01

99.99
100

1.0001.01

99.99
435 450
Nihama1.000150 61

10
Rainfall(mm hr-1 )

399
400

300
Storage(mm)Fig. 2 Return period of maximum hourly Fig. 3 Return period of maximum up-layer
rainfall in 2004
storage in 2004
From the regressive relation, it is clear that the maximum hourly rainfall occurred in
2004 corresponds to a return period of 83 years and the up-layer storage in 2004
corresponds to a return period of 100 years. It can be supposed that the unusualhydrologic phenomenon may be the reason to produce heavy storm disasters that
included landslides in 2004.
3.3 Detailed analysis of each storm in the catchment
In 2004, two heavy shallow landslides occurred in the forest catchment by two typhoons

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Table 2 The hydrological properties in the catchment during typhoon events
DATE
2004/8/1
2004/8/30
2004/9/7
2004/9/29

STORM
EVENT
TYPHOON 10
TYPHOON 16
TYPHOON 18
TYPHOON 21

Rdmax

Rhmax

DT1.8-S(SM+S1)max

Raccum(mm/d)
126.5
220.5
59.5
128.5

(mm/hr)
59.5
39.5
10
28.5

(hr)
8
18
13
20

(mm)
339.1
394.3
314.2
355.7

(mm)
110.5
120
30
98

Rdmax, Rhmax:

Maximum daily and hourly rainfall(SM+S1)max:

Maximum of up-layer storage

DT1.8-S:

Duration time in which soil moisture is bigger than pF1.8 condition (which include
saturated condition)

Raccum:Accumulated rainfall before maximum rainfall which does not include max rainfall

on August 30 and September 29. To consider the phenomena of these storm-induced
landslide occurrences, hydrologic conditions during these two landslide events wereanalyzed in detail and compared with other heavy storms. The hydrologic properties ofeach storm which include rainfall characters were recorded and soil moisture conditions

98

20

96

40

94

60

92
2004/8/30 00:00

80
2004/8/30 24:00

100

0

98

20

96

40

94

60

92

80

2004/9/29 00:00

Rainfall(mm/hr)

0Soil Moisture (%)

100

Rainfall(mm/hr)

Soil Moisture (%)

were estimated by using the model as they are shown in Table 2. Judging from rainfall
properties, it might be expected that typhoon 10 which have the highest hourly rainfall
intensity was very dangerous for inducing landslides. However, in this storm, theduration time (DT1.8-S), in which the upper layer’s soil moisture was bigger than boththat in gravity drainage pF1.8 condition and saturated condition, which can represent
the wet condition of soil and has effect on soil loosing, was only 8 hours. Moreover, thevalue of maximum up-layer storage (SM+S1), which reflects the effects of cohesion andpore-water pressure of this storm, was smaller. This might be the reason why this heavy
storm has not caused landslide disaster in our catchment. In the case of September 7,
duration time of DT1.8-S was 13 hours; as well the rainfall intensity and up-layer storage
was the smallest among all storms, so that landslide was not produced. On August 30
and September 29 when serious landslide occurred, there were heavy rainfalls, upper
layer of the soil remained partly saturated and reach the saturated state which continued

2004/9/29 24:00

Fig. 4 Saturation of soil moisture in typhoon events5

Table 3 Relationship between hydrologic properties and frequency of landslides in Ehime
prefecture
DATE

2004/6/27
2004/7/31
2004/8/17
2004/8/30
2004/9/7
2004/9/29

STORM EVENT LANDSLIDE EVENTSTORMTYPHOON 10
TYPHOON 15
TYPHOON 16
TYPHOON 18
TYPHOON 21

6
8
14
49
8
75

(SM+S1)max (mm)DAILY RAINFALL (mm/d)

327
333
362
393
346
435

18
91
189
214
83
299

Table 4. Relationship between hydrologic properties and frequency of landslides in
Ehime prefecture in different year (1993~2004)
Year
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004

R≥10
40
8
23
14
20
25
18
18
23
5
21
39

R≥30
2
0
0
0
1
2
1
0
0
0
0
3

S1>0,SM18≥0
613
26
212
134
298
285
358
278
190
0
235
421

Frequency
S1>0,SM≥SM18,R≥10
16
1
10
5
7
7
10
7
4
0
5
18

Forest Disaster
81
2
22
12
33
56
73
31
52
2
3
160

for a long time as shown in Fig. 4. Furthermore, maximum of up-layer storage (SM+S1)of these two storms were bigger than other storms, that may be the reason why heavy
landslide occurred in our catchment during these days.
3.4 Landslide analysis in Ehime prefecture
In 2004, Ehime prefecture has suffered greatly from a series of landslides during thetyphoon events. It has caused a lot of death of peoples and serious economic damage.
Most of disasters were occurred in Nihama city. There was serious heavy rainfall in thiscity and it has been seriously damaged. Therefore, rainfall data in Nihama were applied
to estimate the hydrologic phenomena during the storm events in 2004 by our model.
Through it, the correlation tendency between frequencies of shallow landslide andhydrologic properties was examined.
Relationships among the calculated maximum up-layer storage (SM+S1) by themodel, observed maximum daily rainfall, and total number of landslides in Ehime
Prefecture during each storm event are shown in Table 3. In the table, the greatest

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values of up-layer storage and daily rainfall are found in the event of typhoon 21 on
September 29th. It is considered that this extremely great storage might induce thenumerous landslides. Moreover, the high correlation between landslides’ quantity andthe soil water storage was found in the table. Furthermore, according to the data from
Ehime prefecture disaster report, forest landslide disasters of the prefecture and thefrequency of rainfall intensity which was bigger than 10mm and 30mm in different year
can be obtained (Table 4). In addition, it shows the model calculated frequency of upper
layer soil moisture(SM) was bigger than SM18, which means the amount of soil moistureunder condition of gravity drainage pF1.8 of each year. From the Table 4, the highcorrelation between landslides frequency and soil water storage combined with rainfall
intensity can be found.
4. CONCLUSION
A hydrologic model including the infiltration curve was proposed to evaluate hydrologic
processes which include soil moisture and rainwater storage in a watershed in this study.
Based on available hydrologic data, the relationship between the hydrologic conditions
and landslide occurrence were analyzed. As the result of its application to an
experimental catchment, time distribution of infiltration, soil moisture, water storage aswell as discharge could be understood. Comparison of hydrologic conditions of storms
in different years showed the unusual presence in 2004, which included the highest
value of daily and hourly rainfall, peak discharge and upper layer soil moisture withexcess rainfall storage. It was thought to be reason of heavy flood disasters including
landslide that occurred in 2004. Furthermore, the detailed analysis was focused on twoserious landslide disasters in the catchment, the correlation between landslide
occurrence and hydrologic conditions were investigated. Result shows that rainfall
intensity and the level of up-layer storage, which reflects the cohesion and pore-waterpressure, are the critical factors to trigger a landslide disaster. We conclude that in thecondition of high antecedent soil moisture, when soil moisture reaches the gravity
drainage condition and saturates, the heavy storm with long duration can induce shallow
landslide. The proposed hydrologic model in this study was able to represent hydrologic
phenomena reasonably. In addition, it can be used for the estimation of discharge, soil
moisture content, and water storage in forest catchment. The concept of this model isavailable to be applied in other areas if the inherent parameters can be obtained for theareas. The model can be expected to provide important information on soil moisture
behavior for forecasting and preventing landslide disaster in the forest landscapes.

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Crosta GB, Frattini P, 2003. Distributed modeling of shallow landslides triggered byintense rainfall, Nat. Haz. Earth Sys. Sci., 3, 81-93.
Crozier MJ, 1999. Prediction of rainfall-triggered landslides: A test of the antecedentwater status model. Earth Surface Processes and Landforms 24, p825-833.
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