E3S Web of Conferences 415, 05009 (2023)
DFHM8

https://doi.org/10.1051/e3sconf/202341505009

Definition of Rainfall Thresholds for Shallow Landslides inColombian Tropical Mountainous Catchments as Debris Flow
Triggering Mechanism
Ricardo Jaramillo-González1, Luis Martínez1, Edier Aristizábal1, Edwin García2 and Roberto J. Marín2
1Departamento de Geociencias y Medio Ambiente, Universidad Nacional de Colombia sede Medellín, Colombia
2 Departamento de Ingeniería, Universidad de Antioquia, Colombia

Abstract. As a cascade precursor of the Debris Flow phenomenon, landslides generate economic losses
and human fatalities worldwide, especially in mountainous and tropical countries like Colombia. This work
proposes two different methodologies of defining rainfall thresholds as a tool for Early Warning Systems
for Debris Flow occurrence in Colombian urban and mountainous catchments: Empirical-Statistical andPhysically based. Empirical-Statistical rainfall thresholds are defined using several data sources such as rain
gauges (pluviometers), radar, and satellite data allowing a different timing and spatial resolution in thedefinition. The definition of physically based rainfall thresholds the TRIGRS software is used in
mountainous catchments with rainfall data from rain gauges, with the information from the safety factor
map resulting in the simulations calculated as the cumulative density function from the histogram of the
distributed safety factor allowing the understanding of how the instability varies in a catchment during
different storms events

1 Introduction
Landslides generate economic losses and humanfatalities worldwide, especially in mountainous andtropical countries like Colombia. According to theGeohazards
database(www.geohazards.com.co),10.438 landslides have been registered in the ColombianAndean between 1921-2020, with almost 7.313 fatalities[1]. The Colombian Andean region exhibits a complex
tropical hydrometeorological dynamic affected bydifferent temporal and spatial scale climate processes. It
is composed of a diverse geological andgeomorphological setting characterized by high steep
slopes and morphogenic conditions that are predisposed
to gravitational hillslope processes [2,3]. Most of theColombian population is established in the Andeanregion occupying large hilly areas without adequateplanning control representing a risk condition that inrecent years has encouraged the development of forecast
models like Rainfall Thresholds and more complex andcomplementary tools like Early Warning Systems(EWS).
Early warning systems based on precipitation thresholds
can be defined by empirical-statistical and physicalmethods. The empirical-statistical ones are based on
historical rainfall and mass movement data, and thephysically based models consider the effects of rainfall
by coupling distributed hydrological and geotechnicalmodels that provide the spatial distribution of landslides
by calculating the distributed factor of safety. This paper
presents the application of both methodologies for thedefinition of critical rainfall thresholds at basin scale in
the Colombian Andean region. Rainfall thresholds areproposed for the Valle de Aburrá basin in Medellín,Colombia; from the intensity (I) or magnitude of arainfall expressed in millimeters per hour, for a givenduration (D), it is possible to generate the so-called ID
curves, which allow, through the analysis ofprecipitation data, interpretation of variables andcorrelations, to identify minimum rainfall thresholds
associated with the occurrence of landslides, serving asa starting point for knowledge and risk management. In
this work, different sources of pluviometric data wereused to compare and discuss the generation of thresholds
for each of them. In this sense, use was made of twosystems of hydrometeorological stations or terrestrial
sensors, owned by the public companies of Medellín andthe Área Metropolitana del Valle de Aburrá: EPM andSIATA; NASA's GPM satellite database; and data takenwith radar, also owned by SIATA. Then, an inventoryof landslides with a defined time of occurrence wascarried out, from which pluviometric data of rainfall
events recorded during or before the mass movement
were associated, defined as triggering rainfall events,and managing to form a database of 63 landslides in theperiod 2008-2018 (Table 1).

2 Discussion
Much of the discussion generated in the study of thegeneration of thresholds with statistical methods fromdifferent sources focus on the comparison of theresulting ID plots in each case. In general, the rainfall
data measured in the field by hydrometeorologicalstations allow for greater analysis and can be more easily
associated with the recorded landslides, despite the great© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0(https://creativecommons.org/licenses/by/4.0/).

E3S Web of Conferences 415, 05009 (2023)
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https://doi.org/10.1051/e3sconf/202341505009

Table 1. Precipitation data sources for statistical methodology. The type of data source, the available range of data, the number oflandslides triggered by rainfall recorded in each source, the period in which the landslides are recorded, and finally the temporal andspatial resolution are detailed.
SourceTypeRange Available

Landslides

PeriodTemporal

SourceEPM

Rain Gauge (14)1948-201645

2008-2016

5 min- 15 min-SIATA

Rain Gauge (19)2012-present36

2013-2018

1 min- 5min

-GPM

Satellite

2000- present

63

2008-2018

30 min0.1°x0.1° (10x10 km)

SIATA

Radar

2013-201936

2013-2018

5 min

600x600m

Fig. 1. Intensity-duration (ID) plots for each rainfall data source. Four points with different symbologies are distinguished, eachrepresenting the same triggering rainfall event captured independently by each source, reflecting that the rain gauge data are more
useful for recording triggering rainfall events. Whereas the radar and satellite data omit local rainfall periods.

Fig. 2. Cumulative Density Function CDF Curves and Histograms of the distributed Safety Factor in Basin A for 2 years of return(Tr2) (A), 25 years of return (Tr25), 100 years of return (C)2

E3S Web of Conferences 415, 05009 (2023)
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https://doi.org/10.1051/e3sconf/202341505009

variability in the intensity and duration conditions,which generally reflect intensities that do not exceed 8mm/h and variable durations of up to 4 hours. On theother hand, radar or satellite-estimated rainfall data
reflect a greater difficulty in capturing landslidetriggering rainfall events, mainly due to reduced spatial
resolution (Figure 1).
Conversely, physically-based rainfall thresholds
consider the spatial distribution or location of thelandslides by approaches grounded on physical laws thatconsider the occurrence of landslides by calculating
statistical or distributed safety factors. They are basedon the physical relationship between soil resistanceforces and hydraulic-dynamic forces associated with
rainfall instability effects, considering the effects ofrainfall coupling hydrological and geotechnical models.
This dynamic nature of subsurface hydrology depends
on the complex interactions among precipitation inputs,
physical properties, and heterogeneity of soils, bedrock,
local geomorphology, vegetation, and associatedbiomass. These factors influence (i) the timing oflandslides with respect to precipitation inputs andantecedent soil moisture, (ii) landslide type and failuremode, providing a wide understanding of the physicalbehavior of the rainfall throw the hillslope andassociated infiltration. These models provide the spatial
and timing distribution of the phenomenon.
In this order of ideas, proposing an approach where thedefinition of the rainfall thresholds integrates IDF
gauge-based rainfall data, and the physically-basedmodel (TRIGRS) [4] allows performing simulations
with different intensity rainfall values in somecatchments in the Colombian Andean region. Moreover,calculating the cumulative density function from thehistogram of the distributed safety factor (Figure 2)
within a catchment resulting from the simulation
provides a better comprehension of the instability andthe response to heavy rainfall events from different
years of return in a catchment scale in tropicalmountainous terrains where the occurrence of debris
flow is associated with shallow landslides fromhillslopes from the upper part of the catchment.

information resulting from this study can be used for thedevelopment of Early Warning Systems (EWS) tocouple the occurrence of shallow landslides andsubsequent debris flows considering the distribution ofinstability under different return years and extreme
precipitation events associated with the dynamics ofclimate change.

References
1.
2.

3.

4.

3 Conclusions
The definition of precipitation thresholds using
physically based models in the Colombian tropicalAndean region at the basin scale could provide
information on the timing and location of distributed
instability reflected in shallow landslides considered thefirst trigger of debris flows in tropical regions. On theother hand, the statistically-based thresholds and ID
relationship analysis generated in this study, allow anunderstanding of the influence of the triggering factor
rainfall in mass movements in the Colombian Andes,
particularly in densely populated areas, however, does
not provide information on the location of the landslide,but allows using rainfall data in real-time to generate
alerts and better assistance to the emergency, in addition
to providing important information on the triggering
rains of landslides in high mountains that can dam rivers
and increase the chances of a debris flow. Therefore, the3www.geohazards.com.co
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Fortran program for transient rainfall infiltrationand grid-based regional slope-stability analysis, inU.S. Geological Survey Open-File Report 02–0424 (2002)