Hazard assessment of rainfall-induced landsliding in mexico

Geomorphology 61 (2004) 19 – 40 www.elsevier.com/locate/geomorph

Hazard assessment of rainfall-induced landsliding in Mexico I. Alcantara-Ayala* Circuito Exterior, Ciudad Universitaria, Department of Physical Geography, Institute of Geography, National Autonomous University of Mexico (UNAM), 04510, Coyoacan Mexico D.F., Mexico Received 20 May 2002; received in revised form 6 March 2003; accepted 17 November 2003 Available online 17 January 2004

Abstract Rainfall-induced landsliding represents a major hazard in Mexico. About 200 municipalities in the states of Puebla, Veracruz and Hidalgo were affected by flooding and mass movement processes that resulted from a tropical depression from the Atlantic Ocean in October 1999. Hundreds of slope failures were triggered by intense precipitation, which in some localities reached 420 mm during a 24-h period. According to official information, 263 people died and 1 475 654 inhabitants were affected by flooding and landsliding. Rainfall event and cycle coefficient defined and the ratios between event and antecedent rainfalls, respectively, and the mean annual rainfall are summed to give a total coefficient. For landslide-triggering rainfalls in the Sierra Norte, values for the total coefficient of 0.8 and 0.4 for beginning and end of the wet season, respectively, appear to be important. In addition, a hazard assessment was carried out through the development of a landslide susceptibility indicator. This was elaborated by using aerial photographs, integrating field observations and the coupling of slope instability analysis within a digital elevation model framework. Field validation indicated that this approach provides a good representation of shallow translational failures; 81% of the observed landslides were satisfactorily predicted as potential unstable zones. Results suggested that this type of DEM-based hazard assessment can be extremely valuable not only after, but also before any landslide-related event, so that disaster preparedness and planning could be adequately structured. D 2003 Elsevier B.V. All rights reserved. Keywords: Rainfall; Cycle and total coefficients; Landslides; Hazard; Assessment

1. Introduction Rainfall-induced landsliding takes place in different parts of the globe. However, in areas where meteorological events such as cyclones, hurricanes, typhoons, etc., are recurrent, the consequences are especially devastating. For example, in 1989, more * Tel.: +52-555-6224339x45466; fax: +52-555-6162145. E-mail address: [email protected] (I. Alcantara-Ayala). 0169-555X/$ - see front matter D 2003 Elsevier B.V. All rights reserved. doi:10.1016/j.geomorph.2003.11.004

than 400 landslides were triggered by Hurricane Hugo in Puerto Rico (Larsen and Simon, 1993), and in 1996 in Taiwan, Typhoon Herb produced 1300 landslides (Lin and Jeng, 2000). The significance of tragic consequences of landsliding due to intense rainfall was demonstrated throughout the aftermath of Hurricane Mitch in Central America (1998) and the 1999 storm in Venezuela. During Mitch, on a single event, a mudflow produced in Volcano Casita in Nicaragua (Kerle and de Vries, 2001) buried two towns causing a death toll of about 2000 people. On the other hand,

20

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

thousands of mass movements occurred in the north of Venezuela due to the extraordinary rainfall of 1999 producing devastation and a great volume of deposits. This episode has been considered as one of the largest episodes of rainfall-induced landsliding worldwide documented in history (Wieczorek et al., 2001). Investigations concerning precipitation as a triggering factor for slope instability have been undertaken taking into account different approaches. Many of these studies determine a rainfall intensity-duration threshold to limit stability, a constraint introduced by Caine (1980), who suggested a slope instability threshold based on published records of rainfall intensities and durations that triggered shallow landslides and debris flows. According to his results, such a limit can be broadly defined as I = 114.82D
0.39 and is best typified for rainfall durations between 10 min and 10 days. In a similar way, Finlay et al. (1997) analysed the relationship between rainfall and the probability of landsliding occurrence in Hong Kong and obtained a general threshold rainfall indicating

that 1– 12 h rainfall duration is significant to predict the number of landslides for that area. Thresholds are strongly related to the environmental conditions of the processes; hence, they can satisfy specific objectives, but the universal applicability of them is questioned. In addition, the extreme complexity of the landscape forming materials system, where every single diaclase or the different degree of weathering for instance contributes to the properties and ‘‘behavior’’ of each material, influences the response to the actual processes. For instance, by using an empirical antecedent daily rainfall model, Glade et al. (2000) obtained regional rainfall thresholds for different areas of the North Island in New Zealand. They observed that predicted landslide events resulted from the modelling are influenced by the landslide database itself and the physical environment of the susceptible areas. Most of the mass movement processes that have occurred in Mexico over the last several decades have been induced by rainfall. In 1991, in the town of Meztitlan, located in the Hidalgo province (north of

Fig. 1. Physiographic setting and location of the studied area.

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

Mexico City), a rotational landslide involving a volume of circa 900 000 m3 injured some inhabitants and caused considerable damage to a 16th century monastery (Lugo et al., 1996). After Hurricane Pauline in 1997, floods and landslides affected the Bay of Acapulco in the Pacific Coast. Likewise, during an extreme rainfall in 1998, the southeast part of Mexico was severely damaged; in particular, the state of Chiapas suffered the worst consequences associated with floods and mass movement processes. Furthermore, the worst landsliding episode occurred during 1999, in a period of intense precipitation mainly over the provinces of Hidalgo, Veracruz and Puebla. The latter was the area of major loss. The aim of this paper is to analyse the mass movement processes that took place in 1999 in the province of Puebla, in particular in the Sierra Norte, as a representative case of rainfall-induced landsliding in Mexico. Moreover, based on aerial photographs, field observations and the coupling of slope instability analysis with a digital elevation model, the develop-

21

ment of a susceptibility indicator is presented in terms of hazard assessment.

2. Study area The Sierra Norte de Puebla is located in the State of Puebla within the transition of the Sierra Madre Oriental and the Trans-Mexican Volcanic Belt Physiographic Provinces (Fig. 1). The Sierra Madre Oriental follows a NNW– SSE orientation and is formed by a series of parallel stepped mountains ranging between 2100 and 2200 masl and by high elevations up to 3300 masl. This unit comprises Mesozoic sedimentary rocks which in some places are covered by volcanic deposits. The Trans-Mexican Volcanic Belt (TMVB) is a 1000-km E – W strip that crosses central Mexico from the Pacific Coast to the Gulf of Mexico. The TMVB was formed in the late Miocene as a result of the subduction of the Cocos and Rivera Plates (Ferrari et al., 1999), and according to Alva-

Fig. 2. Municipalities affected by landsliding in the Sierra Norte, Puebla.

22

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

Valdivia et al. (2000), in its initial stage, the TMVB was characterised by extensive basaltic volcanism with plateau-like structures resulting from the coalescence of shield volcanoes and fissure lava flows. It comprises a series of Late Tertiary and Quaternary strato-volcanoes, cinder cones, calderas, domes and maars, mostly of calc-alkaline type. The Sierra Norte, located in the northeastern part of the Puebla province (Fig. 2), comprises the sierras of Zacapoaxtla, Huauchinango, Teziutla´n, Tetela de Ocampo, Chignahuapan and Zacatla´n. In these sierras, altitudes of 4282 masl are reached, and the highest elevations are located in Apulco, Chichatl, Chignahuapan, Soltepec and Tlatlauquitepec. The area is characterised by intense erosion and gully development, mainly on sedimentary rocks that are overlain by volcanic rocks. Sedimentary layers of variable thickness outcrop in block folds where erosion has been controlled to a great extent by a system of faults and fractures. Volcanic structures are represented by a series of volcanoes, domes, calderas and a big extension of ignimbrites from the Upper Tertiary and Quaternary. Metamorphic rocks including lutites, schists and other types cover a much smaller area. Mass movement processes are common in this mountainous zone due to the fragile materials and the tectonism of the area.

The regional climate is warm temperate. In the northern part of the Sierra Norte, mean temperatures fluctuate between 22 and 26 jC, whereas in the southern area, they vary from 14 to 18 jC. In most of the region, rainfall takes place all year long, and in some cases, it is abundant during the summer.

3. The significance of landslides in Mexico Although there is not a complete landslide database in Mexico, preliminary statistics show that most catastrophic landsliding events have been associated with rainfall (Fig. 3). The first big event occurred in 1997 as a result of Hurricane Pauline, when 411 mm of rain fell in a 24-h period. Oaxaca and Guerrero provinces were severely affected by floods and landslides. Official figures indicated that 200,000 inhabitants were left homeless, whereas 228 people were killed and hundreds injured. A second important event took place a year later in the province of Chiapas; flooding and mass failures caused huge damage in 39 municipalities, with high level of disruption in the highway network and the destruction of almost 50% of the rural roads. The most critical incident occurred in October, 1999 in the provinces of Puebla, Veracruz and Hidalgo (Bitra´n, 2000). As a result of the inter-

Fig. 3. Temporal distribution of landslides and associated human losses in Mexico (1980 – 2000).

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

action between a tropical depression and a cold front, intense precipitation affected the area triggering hundreds of landslides and flooding principally in the province of Puebla. The aftermath of this event was extended to 81 municipalities, which correspond to about 37% of the total communities. Affected population was as high as 1 475 654 inhabitants, the equivalent to 30% of the whole population of Puebla (Bitra´n and Reyes, 2000).

4. Landsliding in Puebla The Sierra Norte in Puebla was the site most affected by rainfall-induced landsliding and flooding during October of 1999. The consequences were so bad that this event was catalogued as the worst Mexican disaster of the decade. According to Bitra´n and Reyes (2000), 263 people lost their lives and 1.5 million inhabitants were affected (30% of the entire population of Puebla).The total associated damage exceeded US$450 million. Communications and transport systems accounted for major losses, followed by the severe impairment of housing and the disruption of the energy sector (Table 1). The affected areas were vulnerable municipalities with high levels of marginality located in unfavorable Table 1 Damage caused by the extreme rainfall event of 1999 in the province of Puebla (Bitra´n and Reyes, 2000) Sectors

Millions of USD Direct damage

Social sector Housing Education Health Services and infrastructure Water Energy Communications and transport Productive sector Agriculture Cattle Forestal Fishing Total

Indirect damage

Total damage

50.5 48.61 1.64 0.25 154

1.5 0 1.5 – 0.1

52 48.61 3.14 0.25 154.1

8.46 48.11 97.43

0.18 – –

8.64 48.11 97.43

19.07 13.25 1.54 3.5 0.78 447.14

3.5 3.5 – – – 10.28

22.57 16.7 1.54 3.5 0.78 457.37

23

Table 2 Soil properties indexes of the Aurora landslide, Teziutla´n, Puebla (Mendoza et al., 2000) Properties

La Aurora landslide

Liquid Plastic Plastic Liquid

97.0% 59.1% 37.9% 1.02

limit limit index index

terrain, along unstable valleys formed by ancient landslide deposits, on structurally controlled terraces, on the divides and on the nonresistant ignimbrite piedmonts. The extent of landsliding was of few hundreds of failures over more than 5000 km2 (Va´zquez-Conde et al., 2001). Although rock-falls, slides, debris flows, mudflows and complex landslides took place in the area, translational slides occupied a bigger area. The most affected communities were Apulco, Chignahuapan, Cuetzalan, Huauchinango, Necaxa, Pahuatla´n, Tetela, Teziutla´n, Tlatlauquitepec, Zacapoaxtla, Zacatla´n, Zapotitla´n and Zaragoza. In Teziutla´n, on a single event, 109 people died buried by a slide that evolved into a mudflow. A slope formed of poorly consolidated ignimbrite deposits with a high sand content was destabilised by 2 days of intense rainfall. Whereas the mean rainfall at Teziutla´n meteorological station for October is 270 mm, 300.5 and 360 mm fell on the 4th and 5th. It means that during a 48-h period, 245% of the monthly mean, which is also the equivalent to 42% of the annual mean, fell and caused severe damages. According to Mendoza et al. (2000), the water content of the slope, as measured immediately after the failure, was slightly higher than the liquid limit (Table 2); in other words, the soil was in a semiliquid state. The failed mass had a maximum length of 100.5 m with a mean depth to the slide surface of 4.4 m. Even though the movement involved a relative small volume of material of 7350 m3, the impact was much bigger. One of the most peculiar types of landslides occurred in Totomoxtla, a town of 1100 people located on a slope mainly formed by lutites. Two kinds of movement took place. First of all, a rock slide of circa 350 m long, 80 m wide and 10 –20 m thick (Lugo et al., 2001), and secondly, a mudflow that was initiated at the top of the slope (Fig. 4). According to the inhabitants, the mass moved down slope very

24

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

Fig. 4. Remains of a mudflow at Totomoxtla, Sierra Norte, Puebla.

slowly, transporting heterogeneous clasts up to 1.5-m diameter. Fortunately, these mass movements did not cause human losses given the fact that the material moved along the main streets of the village. The low mobility was given by a high clay content derived from the lutites. In Zapotitla´n de Me´ndez, several landslides took place. This a community situated on a valley floor very

susceptible to flooding and mass movement. The instability of the slopes is determined to some extent by the intercalations of alluvial fans and ancient landslide deposits. The main lithologic units of the slopes are sedimentary rocks, also of the lutite type; however, in some areas, volcanic materials overlie the former units. There were two principal movements. A complex failure on sedimentary lithologies took place along the

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

main road obstructing communications for several days (Fig. 5). The movement was structurally influenced by the rock layers dipping out of the slope. On the other hand, the contact between the ignimbrite deposit and a unit of highly weathered lutites was the template of the occurrence of a flow slide that covered several houses of the town (Fig. 6). Luckily, a nonsophisticated local alarm system was set up in the town and at the time of the failure, as the bell of the main Catholic Church was

25

ringing, all the residents were evacuated. The landslide started with a rock slide in the upper part of a scarp, followed by a translational movement that evolved into a flow. The displaced mass involved a mixture of volcanic and sedimentary materials embedded into a clayed matrix. Smaller debris flows occurred elsewhere, but with no major consequences. Zacapoaxtla is a village located on a drainage divide. A high percentage of the housing was built

Fig. 5. Complex slide that blocked the main road of Zapotitla´n de Me´ndez, Puebla.

26

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

Fig. 6. Flow slide and buried houses in Zapotitla´n de Me´ndez, Puebla.

on gullies developed on pyroclastic materials, which in a few areas are underlaid by a small lava flow of basaltic composition. There are two types of pyroclastic materials: one composed of clays and the other of sands and loams. The contact between these two types determines the instability of the slopes, which is worsened by the intense erosion of gullies and anthropic activity. It is quite common to observe susceptible buildings situated along the gullies in this

town, where the inappropriate drainage conditions make the slopes more unstable.

5. Historical records and the rainfall event of October, 1999 The Sierra Norte has been historically affected by rainfall of high magnitude (Bitra´n and Reyes, 2000).

Table 3 Meterological events that have affected the Sierra Norte since 1950 (data from Zacapoaxtla rain gauge)

Characteristics

Total precipitation (mm) Maximum 24-h rainfall (mm) 3 days antecedent rainfall (mm) 5 days antecedent rainfall (mm) 10 days antecedent rainfall (mm) 15 days antecedent rainfall (mm) Cumulative rainfall Average monthly rainfall

Perturbation

Tropical storm

Hilda

Janet

Beulah

Fifi

Diana

Gert

Tropical depression

11 – 12 Sept., 1954 Hurricane Cat. 1

6 – 9 Oct., 1954 Tropical perturbation

23 – 30 Aug., 1955 Tropical storm

10 – 20 Sept., 1955 Hurricane Cat. 3

21 – 30 Sept., 1955 Hurricane Cat. 5

15 – 18 June., 1959 Tropical storm

14 – 22 Sept., 1974 Hurricane Cat. 2

4 – 9 Aug., 1990 Hurricane Cat. 2

14 – 21 Sept., 1993 Hurricane Cat. 2

481

602

299

72

379

3

331

168.6

204.1

3 – 7 Oct., 1999 Tropical depression and cold front 844

332

335

285

24

330

2.5

250

85.7

72.7

343

125

4

22

14

26

2

0

11.2

0

27.8

137

4

31

48

29

8.5

2.5

11.2

18.8

27.8

174.5

44.5

77

328

72

65

97.5

11.2

30.8

28.4

202

125.5

83

627

103

67.5

141.5

11.2

38.7

41.5

683 359.1

727.5 219.7

382 130.5

699 359.1

482 359.1

70.5 168

472.5 359.1

179.8 130.5

242.8 359.1

885.5 219.7

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

Date

Florence

27

28

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

Meteorological events such as tropical perturbations and hurricanes have influenced the landscape dynamic of the area causing extreme precipitation and floods (Table 3). In particular, the influence of hurricanes has been well demonstrated by the impact of Hurricanes Hilda (1955), Janet (1955), Beulah (1957), Fifi (1974), Diana (1990) and Gert (1993). Florence was the hurricane that generated the highest precipitation within the region (481 mm at Zacapoaxtla), whereas Hilda produced only 72 mm at the same rain gauge. Temporal precipitation distribution in the meteorological stations shown in Fig. 7 illustrate that before the 1960s (prior to tropical storm Beulah), rainfall records varied considerably in the same region, while from the 1970s, they followed similar patterns. Furthermore, it is quite significant to observe that highest precipitation records have not been produced by hurricanes but by tropical perturbations or the combination of different events such as the case of 1954 and 1999. The province of Puebla is located in a context where diverse meteorological events take place due to its closeness to the Gulf of Mexico, as well as to the influence of cold fronts developed further north. The episode of 1999 was an exceptional phenomenon initiated by a tropical wave originated in the Gulf of Mexico (1 –4 October) that evolved into a

tropical depression (4 – 7 October) and soon after interacted with a cold front, where the contact with humid air fluxes generated a large quantity of rain. The unusual amount of precipitation resulted from the stationary stage both phenomena experienced, so that consequences overpassed those triggered by actual hurricanes. Data from three regional meteorological stations (Table 4) illustrate the significance of this rainfall event by comparing the precipitation of October with other mean records. For example, mean annual precipitation in Zacapoaxtla amounts 1421.2 mm, whereas the cumulative value of the four most intense days of rain from October 3rd to 6th was 844 mm. In other words, the storm corresponded to 60% of the yearly average. In the case of Teziutla´n, where the biggest tragedy in terms of fatalities occurred, 743 mm were registered during the four critical rainy days, the equivalent to half of the annual mean. In contrast, 554.5 mm of rain fell in Huauchinango during the same period of time, a quarter of the yearly precipitation. Analyses from the same rain gauges revealed that the maximum 24-h rainfall registered during the October 1999 event accounted, in all cases, for more than the corresponding monthly average; it means that in Teziutla´n and Huauchinango, it totalled 133% of

Fig. 7. Precipitation of the major meteorological events that have affected the Sierra Norte.

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

29

Table 4 Rainfall data of some meteorological stations from Sierra Norte, Puebla (data provided by National Meteorological Service, SMN) Rain gauge

Mean annual rainfall (mm)

Event rainfall (mm)

Cumulative rainfall (mm)

Maximum 24-h rainfall

Average monthly rainfall (mm)

Teziutla´n Zacapoaxtla Huauchinango

1593 1421.2 2277.1

743 844 554.5

1041 885.5 586

360 343 285

270 219.7 214.9

the October mean, whereas in Zacapoaxtla, it was equivalent to 1.5 fold. In terms of cumulative rainfall, which included the 15 preceding days, Teziutla´n (1041 mm) and Zacapoaxtla (885.5 mm) records were higher than 60% of the annual mean, while Huauchinango only reached 25%. Five histograms were elaborated in order to illustrate the significance of the October 1999 rainfall event in the whole state of Puebla, in such a way that in Fig. 8, a general abrupt increase of rainfall on October 4th, and a sharp peak on the cumulative rain of the day after, can be observed. In the case of Tenango station, 1239.9 mm was recorded from the last day of September to October 13th; such amount is the equivalent to 85.68% of the mean annual precipitation. Although in the different graphs there is a common tendency to show the importance of the cumulative rainfall within the same region, it is not possible to define a unique rainfall threshold that could have triggered all the landslides.

Current meteorological records as well as few historical data have been used to determine the applicability of rainfall thresholds to understand landsliding on regional basis. A simple comparative approach through the analysis of the Teziutla´n and Zacapoaxtla histograms, two of the most affected sites, suggested that the role of rainfall as a triggering mechanism of mass movement is strongly influenced by the landscape dynamic and conditions developed by society through time. In this case, the main lithological units of both places comprise ignimbrite volcanic deposits derived from the activity of a caldera located nearby. Hillslopes on such areas are highly dissected by gully erosion and affected to some extent by deforestation and other kinds of anthropic disturbances. Although they are similar scenarios, the amount of rainfall needed to cause instability in Zacapoaxtla was much higher than the precipitation that triggered landslides in Teziutla´n, where the most catastrophic consequences of the event took place.

Fig. 8. Comparison of the maximum daily and cumulative rainfall records (September 30th to October 12th, 1999). Rain gauges located in diverse regions of the state of Puebla and in Tenango (province of Hidalgo, NW of Puebla).

30

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

Fig. 9. Rainfall intensity vs. return period for the available rain gauges information of the Sierra Norte.

According to historical archives, diverse mass movements were triggered in Zacapoaxtla and Tlatlauquitepec by a hurricane (with no name) in October 1954. Ten months later, similar events occurred in Teziutla´n and Huauchinango due to a tropical storm. During Hurricanes Hilda (Sept 10 –20, 1955), Janet (Sept 21 – 30, 1955) and Fifi (September 14 – 22, 1974), several movements were produced in Teziutla´n, Huauchinango and Zacapoaxtla. In particular, Hurricane Janet caused enormous devastation coun-

trywide; severe floods affected the neighboring provinces of San Luis Potosı´, Guanajuanto, Tamaulipas and Hidalgo, whereas the Sierra Norte suffered from landsliding in Chignahuapan, Huauchinango, Pahuatla´n, Teziutla´n, Zacapoaxtla, Zaragoza and Zautla. Furthermore, in 1993, rainfall derived from Hurricane Gert caused instability in Teziutla´n and Huauchinango. Intensity of rainfall is generally introduced when investigating the role of precipitation on landsliding.

Table 5 Cycle and event rainfall coefficients for the most critical events that have affected the Sierra Norte Rain gauge

Met. event H. Florence 1954

October 1954

T. Storm 1955

H. Hilda 1955

H. Janet 1955

H. Beulah 1959

H. Fifi 1974

H. Diana 1990

H. Gert 1993

October 1999

Coefficient type

Teziutla´n

N.A.

N.A.

N.A.

N.A.

N.A.

N.A.

N.A.

N.A.

N.A.

Zacapoaxtla

0.3384 0.8615 1.2000 N.A.

0.4235 1.3558 1.7794 N.A.

0.2666 0.8978 1.1645 0.0880 0.9153 1.0033 0.0463 0.3901 0.4364

N.A.

N.A.

N.A.

0.1478 0.6853 0.8331

0.0506 1.1064 1.1571 0.0577 1.0178 1.0755 0.0277 0.5600 0.5878

N.A.

0.0786 0.4886 0.5672

0.2103 0.5850 0.7954 0.1175 0.7245 0.8420 0.0218 0.3058 0.3277

0.2840 0.7361 1.0202 0.2329 0.8369 1.0698 0.2059 0.6500 0.8560 0.1908 0.6255 0.8164

0.0798 0.9668 1.0467 N.A.

0.5938 1.2217 1.8155 0.2443 1.0151 1.2595 N.A.

Event coef. Cycle coef. Total coef. Event coef. Cycle coef. Total coef. Event coef. Cycle coef. Total coef. Event coef. Cycle coef. Total coef.

Huauchinango

Tlatlauquitepec

Landsliding

N.A.

0.0052 0.4361 0.4414

N.A.

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

Representative results are in many cases derived not only from daily records, but also from hourly ones. In the case of Mexico, only a small number of rain gauges provide continuous hourly information; consequently, it is rather difficult analysing to a full extent such parameter. For the particular case of the Sierra Norte, 24-h precipitation is the best type of record available. In some cases, this value relates correctly to the actual rain; however, during events, when precipitation was concentrated in few hours, the calculated rainfall intensity becomes meaningless. According to the available information, during the event of October 1999, the highest maximum rainfall intensity of 15.83 mm/h was recorded at Zacapoaxtla, whereas 14.19, 12.58 and 11.87 mm/h were registered at Teziutla´n, Tlatlauquitepec and Huauchinango, respectively. Given the fact that rainfall duration for landsliding occurrence has only been observed for 24 h, a graph plotting rainfall intensity vs. return period has been elaborated (Fig. 9). This graph gives a general idea of the intensities associated to the main registered events. Maximum return periods have been calculated as 23, 39, 51 and 68 years. Unfortunately, rainfall records are not as complete as needed, and consequently, analysis accuracy to this respect would vary in space and time. Based on the work by Guidicini and Iwasa (1977) and Garland and Olivier (1993), cycle and event coefficients were developed for four rain gauge stations covering data from the most critical meteorological events that have affected the area up to now (Table 5). The scarcity of records did not allow the calculation of such coefficients for all cases. Nevertheless, results provided a general view of the correlation between rainfall and landsliding. The cycle coefficient has been defined in terms of the cumulative rainfall preceding the event divided by mean annual precipitation and the event coefficient as the rainfall of the event divided by mean annual precipitation; both coefficients can be summed to generate a total coefficient (Guidicini and Iwasa, 1977; Garland and Olivier, 1993). Event coefficients vary considerably through time and space. Rainfall-induced landsliding has been generated with values as high as 0.5 and as low as 0.05. By analyzing the case of Hurricane Hilda at Zacapoaxtla, the importance of antecedent rainfall can be exemplified. The event rainfall itself was only

31

Fig. 10. Determination of stability periods based on total and cycle rainfall coefficients.

32

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

72 mm (see Tables 3 and 5), with an event coefficient of 0.05; however, it was preceded by 9 days of rainfall that amounted 328 mm, along with 299 mm produced by a tropical storm during August 23rd – 30th, and therefore, the cycle coefficient went up 1.1. On the other hand, immediately after the influence of Hilda, Hurricane Janet affected the Sierra Norte producing 379 mm of rainfall and registering a 24-h maximum of 330 mm; the cycle coefficient was lower than Hilda’s, but total coefficients for both were similar. Instability periods can be broadly defined based on the relation among total and cycle coefficients vs. months of the rainy season. For the Sierra Norte case, a total coefficient higher than 0.8 would be needed to trigger landsliding at the beginning of the wet season, whereas at the end of it, values superior to 0.4 would cause instability (Fig. 10). The analysis elaborated for this region shows that there is not a particular correlation among event coefficients and mass movement. Instability is determined by intense precipitation, when maximum 24-h rainfall exceeds 200 mm and when soil moisture conditions derived from antecedent rainfall are high.

6. Landslide modelling and DEM’s One of the aims of this work was to produce a landslide susceptibility indicator by using slope instability analyses within a geographical information system framework (GIS). Geographical information systems have been frequently recognised as significant tools in the development of databases, topological attributes, overlays and spatial queries. In the case of landsliding, different works have attempted to construct maps or indexes reflecting susceptible landslide areas based on various approaches. In earlier works, the construction of landslide site inventories comprising attributes like slope, elevation, geological units, types of soil, vegetation, etc., was widespread (Amaral, 1993; Chaco´n et al., 1993; Ferna´ndez et al., 1994; Irigaray et al., 1994; among others). Later on, methodologies included the use of multivariate analysis based on discriminating factors (Carrara et al., 1991) and statistical analysis (Dhakal et al., 2000). For instance, results presented by Dai and Lee (2002) documented that slope stability

modelling can be effectively done by using GIS and logistic regression analysis. In addition, the use of remote sensing techniques combined with GIS can be illustrated by the construction of landslide hazard indicators. Based on the integration and weighting of various data layers such as land use, thrusts, photolineaments, lithology, drainage, slope angle and relative relief, Saha et al. (2002) built up a landslide hazard index for the Himalayas. Recently, efforts have been concentrated on the integration of dynamic elements. Van Westen and Terlien (1996) used an infinite slope model to calculate factors of safety and failure probabilities related to seismic acceleration from a deterministic GIS landslide hazard point of view. Montgomery et al. (1998) tested a regional model for shallow landslides taking into account values of critical rainfall derived from a theoretical model. In terms of computer simulation, Dymond et al. (1999) developed a model for shallow landslides within a GIS framework, which later on was applied to shallow failures in New Zealand. Furthermore, the spatial distribution of shallow debris slides has been modelled by using a GIS-based approach developed by Pack et al. (1999), which implied the coupling of slope stability and steadystate hydrological models. The landslide susceptibility indicator developed for the research area in the Sierra Norte integrated a gridbased spatial hydrological and slope stability modelling. The inclusion of a digital elevation model played a significant role given the importance of topography on landsliding, from which a wetness index was derived. Examples of this approach can be found in Beven and Kirkby (1979), O’Loughlin (1986), Moore et al. (1988), Montgomery and Dietrich (1994) and Alca´ntara-Ayala and Thornes (1996), to mention some. For the case of Sierra Norte, a data set of the area including a digital elevation model (DEM), an inventory of the rainfall-induced landslides occurred in October 1999, as well as topographic, geological and material properties information were prepared. The digital elevation model of the studied area was built at 100-m resolution using the geographic information system ARC/INFO (Fig. 11). Such coarse resolution was used due to the lack of detailed scale cartography at regional level. To this respect, it is important to consider that several investigations have

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

33

Fig. 11. Digital elevation model of the studied area.

addressed the effects of digital elevation resolution on terrain attribute calculation and therefore on the resulting modelling. Accuracy of DEM is determined by the source of the elevation data, the methods involved in creating the actual DEM, the structure of the elevation data, the vertical accuracy and horizontal resolution of the elevation data, the algorithms developed to calculate attributes and indeed by the complexity of the landscape surface (Theobald, 1989; Chang and Tsai, 1991; Florinsky, 1998; Thompson et al., 2001). For the specific case of landsliding, the most important factors to take into account are horizontal and vertical resolution and derived attributes. According to Thompson et al. (2001), analyses of terrain attributes derived from DEMs at different horizontal resolution have demonstrated that as resolution decreased, slope gradients also decreased, being more critical in areas of steeper slopes. Additionally,

the compound topographic index (index related to zones of surface saturation) as well as the specific catchment area increased as resolution decreased; major errors were found in areas of small catchments, for example, hillslope peaks or headwaters (Chang and Tsai, 1991; Quinn et al., 1991; Wolock and Price, 1994; Zhang and Montgomery, 1994; Thieken et al., 1999). In terms of vertical precision, Thompson et al. (2001) also suggested that when such accuracy decreases, a less continuous landscape is produced with more abrupt changes in slope gradient and slope curvature. DEM accuracy plays a very significant role in modelling results, and indeed, a high-resolution elevation model would be the optimum resource to be integrated in any type of research. However, during catastrophic events taking place on extensive areas where information is scarce, a regional modelling provides a good starting point to understand land-

34

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

scape dynamics and to foresee particular sites to be further investigated. This does not imply that the performed regional modelling would be sufficient to address specific issues such as landslide mechanisms, but it would help decision-makers to select areas of priority.

7. Landslide susceptibility index A list of records compiled by the Civil Protection System of the province of Puebla was used as a base for the development of a general mass movement inventory (Fig. 12). Field observations as well as the interpretation of aerial photographs taken after the event were incorporated into the database. This database comprises the geo-referenced locations of mass movements, extent, produced impact and involved materials.

The DEM of the area, just as the geological (Fig. 13) and material properties maps, were rasterized to be used in the landslide susceptibility index. The use of DEMs offers significant advantages in relation to data manipulation, where the distribution of topographic attributes in space of a given landscape can be related to the acting processes, in this particular case to mass movement. Attributes such as slope gradient, compound topographic index and specific catchment area can be related to landsliding. Slope gradient is directly involved to calculate instability by using the infinite slope model, whereas saturation zones are specific catchment areas useful to determine potential instability. The analysis of digital elevation data for hydrological purposes involves the difficulty of the drainage path definition when the DEM contains flat areas or depressions (Moore et al., 1993), which can be resulted from natural features or data errors (Jenson

Fig. 12. Inventory of the landslides occurred during October 1999 (landslides not to scale).

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

35

Fig. 13. Geological units of the research site.

and Domingue, 1988; Hutchinson, 1989). In order to avoid this problem, the DEM was corrected using ARC/INFO grid hydrological surface modelling to calculate flow direction, flow accumulation, presence of sinks, delineation of watersheds, streamlines, stream orders and filling of sinks. After correcting the DEM, the input parameters such as morphological units, cohesion (c’), angle of internal friction (/’), soil unit weight (c), depth of the slip plane (Z) and water table above the slip plane (m) were prepared as grids to be incorporated within the slope stability analysis. A great variety of slope stability models has been developed and applied worldwide. In particular, cou-

pled terrain and stability models are based on exceeding a potential stability threshold that can be calculated by the slope angle derived from a DEM and the mechanical properties of the concerned site. The hillslope stability is commonly expressed in terms of a factor of safety (F of S) or ratio of the shearing strength to the shearing stress, where stability exists when F of S>1.0 and failure occur when F of S < 1.0. Shallow translational slides are frequently analysed by the infinite slope model, a two-dimensional analysis that involves a single linear equation for problems related to failures parallel to the surface given a slope of infinite extent. This model was first used by

36

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

Table 6 Parameters used in the infinite slope model within the ARC/INFO platform Parameters

Ignimbrite deposits Limestone Limestone-lutite Basalt Limolite-sandstone Granite Schist

Lithological units / (degrees)

b (degrees)

20.5 35 32 40 30 40 25

Derived Derived Derived Derived Derived Derived Derived

from from from from from from from

Skmepton and De Lory (1957) to analyse the lowangle slopes in the London clay and later widely applied to a great variety of situations due to its apparent simplicity. The applicability of this method has been recognised in a large number of investigations including hydrological (Anderson and Howes, 1985; Iverson and Major, 1986) and geomorphic

DEM DEM DEM DEM DEM DEM DEM

c V (kN/m2)

c (kN/m3)

Z (m)

11.7 30 18 35 20 35 15

10.79 19 17 22 17 20 18

3–5 3–7 3–7 3–7 3–7 3–7 3–7

approaches (Dietrich et al., 1992; Montgomery and Dietrich, 1988, 1989). Given the nature of landslides in the Sierra Norte, mainly of translational type, the infinite slope model was chosen for analysing the slope stability of the region. Furthermore, the character of this method allows integration within a GIS framework developed

Fig. 14. Landslide susceptibility indicator.

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

by the calculation of safety factors for each one of the grid cells. For that reason, the following formula was incorporated into the modelling: F¼

c Vþ ðcz cos2 b
uÞtan/V cz sinbcosb

where c V= effective cohesion (kN/m2), /V= angle of internal friction (degrees), b = slope angle (degrees), z = depth of the slip plane (m), c = bulk unit weight of the soil (kN/m3) and u = pore water pressure (kPa), where u ¼ yw m cos2 b where yw = unit weight of water (9.81 kN/m3) and m = height of water table above the slip plane. Based on the prepared grids derived from the regional maps, the infinite slope model was integrated and run within ARC/INFO. The lack of material properties data for many of the geological units was replaced by universal values (c, c Vand /V), although data concerned with the ignimbrite deposits, the most affected lithological unit, were taken from Mendoza et al. (2000) and from field and laboratory testing. Slope angle was derived from the digital elevation model, whereas height of water table was interpolated from field observations. It is worth to mention that as a result of the permeability of the ignimbrite deposits, water table was very close to the surface. Table 6 shows the parameters used to run the infinite slope model within the ARC/INFO platform. Results of the application of the infinite slope model were represented by safety factor values for all grid cells. Values equal and lower than the unit were considered for the development of the landslide susceptibility indicator (Fig. 14). Digital elevation model resolution and grid size as previously explained was 100 m, so that factors of safety were calculated also considering a mesh space of the same size. This resolution would not allow identifying unstable zones smaller than 100 m; however, for the case of the Sierra Norte, such constraint is not so significant, given that in most affected areas, critical movements had an extent bigger than 100 m. Therefore, when using this approach, determination of areas susceptible to failure was largely concentrated in places where mass movements actually were produced and had a considerable impact. Certainly, a mesh with better resolution would

37

improve results and determination of smaller areas potentially unstable would be possible. The ideal situation would be to be able to use the regional susceptibility indicator before and during the occurrence of landsliding and developing local stability indicators for specific localities.

8. Discussion and conclusion Rainfall-induced landslides have caused catastrophic disasters worldwide. Consequently, several investigations have addressed their understanding and predictability by trying to define intensity-duration rainfall thresholds to limit stability. Such thresholds are not universally applicable because of the complex slope interactions. However, rainfall analyses may offer some sight to elucidate likely instability occurrence for a certain region. Total and cycle rainfall coefficients for landslide-triggering rainfalls were defined for the Sierra Norte. Results indicated that a total coefficient higher than 0.8 would be needed to trigger landsliding at the beginning of the wet season, whereas at the end of it, values superior to 0.4 would cause instability. Landsliding is a complex process that involves the interaction of different elements such as material properties, terrain topography, wetness, vegetation cover, climate, etc. In particular, rainfall-induced shallow landslides take place affecting large areas, so that the development of failure susceptibility indicators reflecting their spatial distribution is necessary. Those susceptibility indicators can be regarded as a first approach for understanding and analysing such processes, as well as their implications in terms of hazards. The development of landslide susceptibility indicators is determined by the needs and the available resources of the hazard area. Generally, the methodology for such development is based on engineering or geomorphic perspectives. The former is related to a large extent to the specific site conditions given by the material properties of the slopes, whereas the latter is associated to the morphological attributes of the terrain and their relation with factors such as erosion and wetness. Indeed, the combination of both would give a precise output and would reflect the interactions of all the elements involved in mass failure. However, in many cases, where there is a lack of time

38

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

and resources to understand and analyse effectively the process itself, as well as the associated hazard, the task becomes much more complicated. The aim of this investigation was to develop a landslide susceptibility indicator that could be used to point out areas prone to mass movement and therefore as an aid tool for the regional civil protection authorities to prioritize zones of mitigation. This task was satisfactorily achieved throughout the elaborated index. Field validation indicated that this approximation provides a good spatial representation of shallow translational failures. Eighty one percent of the failures included within the database were considered as zones of potential instability in the resulting landslide susceptibility map. It is worth mentioning that in the latter, there are some areas potentially unstable which correspond to zones with no landslides; however, such features can be explained by bearing in mind that most of the mass movements registered within the database were those affecting communities. The landslide susceptibility indicator developed for the Sierra Norte reflects the slope processes on a regional basis. Although it is not expected to be considered 100% accurate, it was developed as an index of potential zones of failure, where one of the most significant aspects is the establishment of areas likely to fail. The geological setting of the area is a very important factor influencing landsliding. In the case of the shallow failures associated to an extreme rainfall event that occurred in Puebla, the ignimbritic materials induced the infiltration and development of a perched water table that caused slope instability. Furthermore, field observations indicated that deforestation has played an important role in the development of areas prone to failure, given the high incidence of instability on areas with vegetation removal. Although this issue was not considered for this analysis, further investigations are being conducted to shed light on that topic. More accurate landslide modelling would be achieved if on one hand, all the failures could be included in the database, and on the other, if the anthropic activities enhancing instability could be integrated in a realistic way. Nonetheless, results have been used by the relevant authorities to further investigate particular study cases, as well as for the development of disaster prevention strategies.

For cases such as the Sierra Norte, landslide hazards are better targeted in a short term through the development of susceptibility indicators with reference to likelihood rather than pure numerical modelling. Numerical measures rely upon accurate data to avoid uncertainty as much as possible. Such data require a proper site evaluation and characterisation, as well as resources and time, and cannot be fulfilled under circumstances similar to the Sierra Norte. However, the previous statement does not mean that numerical modelling is not desirable. When processes of low frequency and high magnitude take place affecting entire communities, actions are required to be as quick as possible. Therefore, the development of indicators like the one presented here offers the information needed for a fast response on a regional basis. Certainly, at a subsequent stage, detailed studies would help to fully understand such processes. What is more, this type of DEM-based hazard assessment can be extremely valuable before any landslide-related event, so that disaster preparedness and planning could be adequately structured.

Acknowledgements This research is being undertaken as a part of the project J33428-T, kindly supported by the National Research Council of Mexico (CONACyT). Meteorological information was gently provided by Servicio Meteorolo´gico Nacional. Special thanks are due to Prof. Guillermo Melgarejo-Palafox, director of the Civil Protection System of Puebla for the given facilities, to Dr. Jose´ Lugo H. and Dr. Jose´ Juan Zamorano.

References Alca´ntara-Ayala, I., Thornes, J.B., 1996. Structure and hydrology in controlling mass failure in space and time: the case of the Guadalfeo failures. In: Chaco´n, J., Irigaray, C., Ferna´ndez, T. (Eds.), Landslides, Proceedings of the Eighth International Conference and Field Trip on Landslides, Granada, Spain, 27 – 28 September. Ed. Balkema, Rotterdam, pp. 89 – 96. Alva-Valdivia, L.M., Urrutia-Fucugauchi, J., Zamorano-Orozco, J.J., Goguitchaichvili, A., Ferrari, L., Rosas-Elguera, J., 2000. Paleomagnetic data from the Trans-Mexican Volcanic Belt: im-

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40 plications for tectonics and volcanic stratigraphy. Earth, Planets and Space 52, 467 – 478. Amaral, C., 1993. Local landslide inventory of Rio de Janeiro. In: Novosad, S., Wagner, P. (Eds.), Proceedings of the Seventh International Conference and Field Workshop on landslides in Czech and Slovak Republics. Ed. Balkema, Rotterdam, pp. 3 – 6. Anderson, M.G., Howes, S., 1985. Development and application of a combined soil water-slope stability model. Quarterly Journal of Engineering Geology 18, 225 – 236. Beven, K.J., Kirkby, M.J., 1979. A physically-based, variable contributing area model of basin hydrology. Hydrology Society Bulletin, 24. Bitra´n, D., 2000. Caracterı´sticas e impacto socioecono´mico de los principales desastres ocurridos en Me´ xico en el perı´odo 1980 – 99. Serie Impacto Socioecono´mico, No.1, CENAPRED. 107 pp. Bitra´n, D., Reyes, C., 2000. Evaluacio´n del impacto econo´mico de las inundaciones ocurridas en octubre de 1999 en el estado de Puebla. In: Bitra´n, D. (Ed.), Evaluacio´n del impacto socioecono´mico de los principales desastres naturales ocurridos en la Repu´blica Mexicana durante 1999. Cuadernos de Investigacio´n 50, CENAPRED, pp. 161 – 194. Caine, N., 1980. The rainfall intensity-duration control of shallow landslides and debris flows. Geografiska Annaler A 62, 23 – 27. Carrara, A., Cardinali, M., Detti, R., Guzzetti, F., Pasqui, V., Reichenbach, P., 1991. GIS techniques and statistical models in evaluating landslide hazard. Earth Surface Processes and Landforms 16, 427 – 445. Chaco´n, J., Irigaray, C., Ferna´ndez, T., 1993. Methodology for large scale landslide hazard mapping in a GIS. In: Novosad, S., Wagner, P. (Eds.), Proceedings of the Seventh International Conference and Field Workshop on landslides in Czech and Slovak Republics. Ed. Balkema, Rotterdam, pp. 77 – 82. Chang, K.T., Tsai, B.W., 1991. The effect of DEM resolution on slope and aspect mapping. Cartography and Geographic Information Systems 18, 69 – 77. Dai, F.C., Lee, C.F., 2002. Landslide characteristics and slope instability modeling using GIS, Lantau Island, Hong Kong. Geomorphology 42, 213 – 228. Dhakal, A.S., Amada, T., Aniya, M., 2000. Landslide hazard mapping and its evaluation using GIS: an investigation of sampling schemes for a grid-cell based quantitative method. Photogrammetric Engineering and Remote Sensing 66, 981 – 989. Dietrich, W.E., Wilson, C.J., Montgomery, D.R., McKean, J., Bauer, R., 1992. Erosion thresholds and land surface morphology. Geology 20, 675 – 679. Dymond, J.R., Jessen, M.R., Lovell, L.R., 1999. Computer simulation of shallow landsliding in New Zealand hill country. ITC Journal 2, 122 – 131. Ferna´ndez, T., Irigaray, T., Chaco´n, J., 1994. Large Scale Analysis and Mapping of Determinant Factors of Landsliding Affecting Rock Massifs in the Eastern Costa del Sol (Granada, Spain) in a GIS. VII Congress of the International Association of Engineering Geology, Lisbon, Portugal. Ferrari, L., Lopez-Martinez, M., Aguirre-Diaz, G., Carrasco-Nunez, G., 1999. Space-time patterns of Cenozoic arc volcanism

39

in central Mexico: from the Sierra Madre Occidental to the Mexican Volcanic Belt. Geology 27, 303 – 306. Finlay, P., Fell, R., Maguire, P., 1997. The relationship between the probability of landslide occurrence and rainfall. Canadian Geotechnical Journal 34, 811 – 824. Florinsky, I.V., 1998. Accuracy of local topography variables derived from digital elevation models. International Journal of Geographical Information Science 12, 47 – 61. Garland, G.G., Olivier, M.J., 1993. Predicting landslides from rainfall in a humid, sub-tropical region. Geomorphology 8, 165 – 173. Glade, T., Crozier, M., Smith, P., 2000. Applying probability determination to refine landslide-triggering rainfall thresholds using an empirical ‘Antecedent Daily Rainfall Model’. Pure and Applied Geophysics 157, 1059 – 1079. Guidicini, G., Iwasa, O.Y., 1977. Tentative correlation between rainfall and landslides in a humid, tropical environment. Bulletin of the International Association of Engineering Geology 16, 13 – 18. Hutchinson, M.F., 1989. A new procedure for gridding elevation and stream line data with automatic removal of spurious pits. Journal of Hydrology 106, 211 – 232. Irigaray, T., Ferna´ndez, T., Chaco´n, J., 1994. GIS landslide inventory analysis and determinant factors in the sector of Rute (Co´rdoba, Spain). In: Oliveira, R., Rodrı´gues, L.F., Cohelo, A.G., Cunha, A.P. (Eds.), 7th IAEG Congress, Lisbon, vol. VI. Balkema, Rotterdam, pp. 4659 – 4668. Iverson, R.M., Major, J.J., 1986. Groundwater seepage vectors and the potential for hillslope failure and debris flow mobilization. Water Resources Research 22, 1543 – 1548. Jenson, S.K., Domingue, J.O., 1988. Extracting topographic structure from digital elevation data for geographic information system analysis. Photogrammetric Engineering and Remote Sensing 54, 1593 – 1600. Kerle, N., de Vries, B.V.W., 2001. The 1998 debris avalanche at Casita volcano, Nicaragua—investigation of structural deformation as the cause of slope instability using remote sensing. Journal of Volcanology and Geothermal Research 105 (1 – 2), 49 – 63. Larsen, M.C., Simon, A., 1993. A rainfall intensity-duration threshold for landslides in a humid-tropical environment, Puerto Rico. Geografiska Annaler Series A 75 A (1 – 2), 13 – 23. Lin, M.L., Jeng, F.S., 2000. Characteristics of hazards induced by extremely heavy rainfall in Central Taiwan-Typhoon Herb. Engineering Geology 58, 191 – 207. Lugo, J., Garcı´a-Arizaga, T., Zamorano, J., Salas, O., 1996. Landslide in Metztitla´n (State of Hidalgo), Me´xico—causes and effects, stability. Zeitschrift fur Geomorphologie. Supplement band 103, 323 – 343. Lugo, J., Va´zquez-Conde, M.T., Melgarejo-Palafox, G., Garcı´a-Jime´nez, F., Matı´as, G.L., 2001. Procesos gravitacionales en las montan˜as de Puebla. Ciencia y Desarrollo 27 (157), 24 – 33 Me´xico, CONACyT. Mendoza, M.J., Noriega, I., Domı´nguez, L., 2000. Deslizamientos de laderas en Teziutla´n, pue., provocados por las lluvias intensas de octubre de 1999. SEGOB, CENAPRED, Me´xico. Montgomery, D.R., Dietrich, W.E., 1988. Where do channels begin? Nature 336, 232 – 234.

40

I. Alcantara-Ayala / Geomorphology 61 (2004) 19–40

Montgomery, D.R., Dietrich, W.E., 1989. Sources areas, drainage density, and channel initiation. Water Resources Research 25, 1907 – 1918. Montgomery, D.R., Dietrich, W.E., 1994. A physically based model for the topographic control on shallow landsliding. Water Resources Research 30, 1153 – 1171. Montgomery, D.R., Sullivan, K., Greenberg, H.M., 1998. Regional test of a model for shallow landsliding. Hydrological Processes 12, 943 – 955. Moore, I.D., O’Loughlin, E.M., Burch, G.J., 1988. A contour-based topographic model for hydrological and ecological applications. Earth Surface Processes and Landforms 13, 305 – 320. Moore, I.D., Grayson, R.B., Ladson, A.R., 1993. Digital terrain modelling: a review of hydrological, geomorphological and biological applications. In: Beven, K.J., Moore, I.D. (Eds.), Terrain Analysis and Distributed Modelling in Hydrology. Wiley, Chichester, p. 247. O’Loughlin, E.M., 1986. Prediction of surface saturation zones in natural catchments by topographic analysis. Water Resources Research 22, 794 – 804. Pack, R.T., Tarboton, R.G., Goodwin, C.N., 1999. GIS-based landslide susceptibility mapping with SINMAP. Proceedings of the 34th Symposium on Engineering Geology and Geotechnical Engineering, vol. 34. Utah State University, Logan Utah, pp. 219 – 231. Quinn, P., Beven, K., Chevallier, P., Planchon, O., 1991. The prediction of hillslope flow paths for distributed hydrological modelling using digital terrain models. Hydrological Processes 5, 59 – 79. Saha, A.K., Gupta, R.P., Arora, M.K., 2002. GIS-based landslide hazard zonation in the Bhagirathi (Ganga) Valley, Himalayas. International Journal of Remote Sensing 23, 357 – 369.

Skmepton, A.W., De Lory, F.A., 1957. Stability of natural slopes in London Clay. Proc. 4th Int. Conf. On Soils Mechanics, Foundation Engineering, London, vol. 2, pp. 378 – 381. London, UK. Theobald, D.M., 1989. Accuracy and bias issues in surface representation. In: Goodchild, M., Gopol, S. (Eds.), Accuracy of Spatial Databases. Taylor and Francis, Bristol, PA, pp. 99 – 106. Thieken, A.H., Lucke, A., Diekkruger, B., Richter, O., 1999. Scaling input data by GIS for hydrological modelling. Hydrological Processes 13, 611 – 630. Thompson, J.A., Bell, J.C., Butler, C.A., 2001. Digital elevation model resolution: effects on terrain attribute calculation and quantitative soil-landscape modelling. Geoderma 100, 67 – 89. Van Westen, C.J., Terlien, M.T.J., 1996. An approach towards deterministic landslide hazard analysis in GIS. A case study from Manizales (Colombia). Earth Surface Processes and Landforms 21, 853 – 868. Va´zquez-Conde, M.T., Lugo, J., Matı´as, L.G., 2001. Heavy rainfall effects in Me´xico during early October 1999. In: Gruntfest, E., Handmer, J. (Eds.), Coping with Flash Floods. Kluwer Academic Publishing, Amsterdam, pp. 289 – 299. The Netherlands. Wieczorek, G.F., Larsen, M.C., Eaton, L.S., Morgan, B.A., Blair, J.L., 2001. Debris-flow and flooding hazards associated with the December 1999 storm in coastal Venezuela and strategies for mitigation. Open File Report 01-0144. U.S. Geological Survey. Wolock, D.M., Price, C.V., 1994. Effects of digital elevation model map scale and data resolution on a topography based watershed model. Water Resources Research 30, 3041 – 3052. Zhang, W., Montgomery, D.R., 1994. Digital elevation model grid size, landscape representation, and hydrological simulations. Water Resources Research 30, 1019 – 1028.