PROBABILISTIC AND PSEUDO-DETERMINISTICSEISMIC HAZARD ASSESSMENT FOR NEIVA –COLOMBIA
Andrés José ALFARO CASTILLO
Mónica Andrea BOHÓRQUEZ FIERROABSTRACT
Neiva is located in a region with a significant seismic hazard due to the proximity of several active
faults that have generated large earthquakes like that of February 9th,1967 the epicenter of which waslocated just a few kilometers away from the city. Said earthquake caused a significant number ofcasualties and considerable damage. In this study, earthquakes with magnitude MS greater than 4.0were analyzed within a 33,400 km2 area. Earthquakes of this intensity can cause victims and damages
in a country such as Colombia. Peak ground acceleration is 272 gals for a 475 years return period.
Pseudo-deterministic analysis shows a credible maximum acceleration of 339 gals due to the Dina
Fault.
Key words: Neiva, Huila, Colombia, hazard, earthquakes, probabilistic, deterministic, Dina
Fault.
INTRODUCTION
Neiva, the capital of Huila province, is located 304 km southwest of Bogota, between the eastern andcentral mountain ranges of the Andes, in the Magdalena River Valley. This study has examined anarea of 33,400 km2 around Neiva which includes three major fault systems (Figure 1): the Romeral
Fault System, under the western flank of the Cordillera Central, which extends across Colombia fromthe Caribbean Sea to Ecuador and has generated significant earthquakes such as those of 1983 near
Popayan, 1994 to the west of Huila, and 1999 in Quindio province; in second place, the Magdalena
Fault System, which crosses the western edge of the Magdalena River Valley and has sufferedintermediate intensity earthquakes as those of 1805, 1816, 1824 and 1942 may be related to this fault
system; and finally, the Guaicaramo Fault System, beneath the Eastern Cordillera, which is consideredvery active and has generated large earthquakes like those of 1827 in Huila, 1834 in Nariño, 1967 inHuila, and the 1995 earthquake in northern Huila (Ramírez 1975; Paris et al. 2000). Because ofcompleteness of seismic catalog and deterministic approach, this paper supplements the Bohórquez(2007) and Bohórquez & Alfaro (2008) studies.
Three earthquakes have caused disasters in the city of Neiva are the earthquake of November
16th, 1827; the earthquake of February 9th, 1967 and the earthquake of June 6th, 1994. Following theearthquake of 1827, the Suaza river was dammed for 55 days due to landslides and rupture of the dam,which caused flooding and devastation in Neiva. The macro-earthquake of Huila on April 9th, 1967 isknown as such because "It was felt from Caracas to Iquitos in Peru and from Buenaventura on thePacific Coast to Mitú on the border with Brazil." It was recorded by more than 500 seismic stations allover the world and it left 15 dead and nearly 100,000 affected in Neiva.” (Ramírez 1967).

Ingetec S.A. and CIEES. Bogotá. Colombia. email: alfaro@ciees.org
Ingetec S.A. Bogotá. Colombia. email: ingecil@gmail.com

The seismic station Bogota BOG recorded more than 350 aftershocks. The focus was located
58 km beneath the Eastern Cordillera with the epicenter at coordinates 9.02 º N and 74.8 º W (Ramírez1967). According to Blume & Associates (1968) the magnitudes estimated are between 7.3 and 7.5. InBogota (400 km away from the epicenter) thirty structures were seriously affected. Finally, the 1994
earthquake, which had a magnitude Ms of 7.6, caused an avalanche in the Páez River basin, leaving
approximately 1,000 dead and 30,000 homeless.

Figure 1. Major Faults in the area studied: 34. Cucuana; 15. Sistema Romeral; 15d. Piendamó; 45. La
Plata-Chusma; 46. Irlanda; 47. La Dina; 29f. Servitá-Santa María; 29h. Algeciras; 29j. Suaza; 29i.
Garzón-Pitalito (Paris et al., 2000).
PROBABILISTIC SEISMIC HAZARD ANALYSISThis study has followed the methodologies of Hanks & Cornell (1994) and Takada (2005). The
following seismic catalogs were used: Ramírez (1975); the U.S. Geological Survey (USGS 2010), thiscatalog includes SISRA (Program for Mitigating the Effects of Earthquakes in the Andean Region)
data for the period 1766-1981 and data from the PDE (Preliminary Determination of Epicenters) forthe period 1973-2010. The ISC International Seismological Center catalog (2010) was also used.
Following the Takada (2005) methodology, earthquakes with magnitudes greater than 4.0 wereanalyzed. This kind of earthquakes can cause casualties and/or damage in the Colombian case (Figure2).
The method of Hanks and Cornell (1994) assumes that the occurrence of earthquakes in theregion approaches a Poisson process, with a constant rate of earthquakes in time and space. Figure 3
shows that it is possible to analyze a relatively homogeneous time distribution from 1944 to 2010. A
completeness analysis of earthquake catalog was done using the Stepp (1971, 1972) methodology(Figure 4).

According to Stepp(1972) it has been suggested by Allen et al (1965) that a 29-year
sample drawn from small regions of the dimension of interest in earthquake hazard mapping
may not give earthquake recurrence estimates that represent long term Seismicity. Therefore itis necessary to use longer samples that give more accurate statistical averages of the large
earthquakes of primary engineering interest (Benjamin, 1968).
Following Stepp(1972), the usual method in practice has been to choose the intervalof data to be fitted by inspection of a plot of log N(Mo) on Mo. The smallest magnitude isusually selected as the value where log N(mo) clearly departs from a straight line plot, whilethe largest earthquake sample is usually included. However this procedure cannot be used inwhole cases.
According to Stepp(1972) in order to analyze the nature of the incompleteness of thedata sample in this detail earthquakes are grouped in magnitude classes and each magnitudeclass is modeled as a point process in time. Use is made of the property of statisticalestimation that the variance of the estimate of a sample mean is inversely proportional to thenumber of observations in the sample. Thus the variance can be made as small as desired bymaking the number of observations in the sample large enough, provided that reporting iscomplete in time and the process is stationary, i.e. , the mean, variance and other moments ofeach observation stay the same. To obtain an efficient estimate of the variance of the sample
mean, it is assumed that the earthquake sequence can be modeled by the Poisson distribution.
If k1,k2,k3,…,kn, are the number of quakes per unit time interval, then an unbiased estimate of
the mean rate per unit time interval of this sample is
1 nkin i =1∑(1)

σ λ2 = λ n(2)λ=And its variance is

Where n is the number of unit time intervals. Taking the unit time interval to be one yeargives

σλ = λ / T(3)As the standard deviation of the estimate of the mean, where T is the sample length.
Thus, assuming stationarity, it is expected that σλ behaves as 1 / T in the subintervalof the sample in which the mean rate of occurrence in a magnitude is constant. If the mean
rate of occurrence is constant it is expected stability to occur only in the subinterval that islong enough to give a good estimate of the mean but short enough that it does not include
intervals in which reports are incomplete (Stepp, 1972).

To assess peak ground acceleration it is necessary to estimate the attenuation of acceleration
with distance. Multiple equations have been developed worldwide; Douglas (2001, 2002) collected
more than 200 robust equations determined in numerous sites all over the world. Currently, no robust
attenuation equation is available for Colombia, which implies the use of equations developed in otherparts of the world. The Fukushima and Tanaka (1990) equation was used in the present study(Equation 4).

Log a = 0.41Ms − log(R + 0.032x100.41Ms) – 0.0034R+ 1.30

(4)

In the field of seismic engineering it is common to express results in a return time. A period of475 years corresponds to a lifespan of 50 years structure and a probability of 10%. In the Neiva casethe result for a return period of 475 years is 272 gals.

PSEUDO-DETERMINISTIC SEISMIC HAZARD ANALYSIS
In this study the possible magnitudes generated by geological faults, characterized by Paris et al.
(2000), using the empirical equations by Wells and Coppersmith (1994) and Stirling et al. (2002),
were assessed (Equations 5 and 6).

Mw=5.16 + 1.12 Log L(5)Mw=5.45 + 0.95 Log L(6)

Each scenario is represented by the occurrence of an earthquake at a source and the epicenter
was located to the minimal distance from the site. Table 1 shows the deterministic analysis results andvalues of peak ground acceleration in rock using the Fukushima and Tanaka (1990) attenuation
equation. The maximum peak ground acceleration that might happen in Neiva would be 339 gals andwould be caused by an earthquake on the Dina fault.
Table 1. Pseudo-deterministic Seismic Hazard Analysis
Fault Id
(Figure1)

FAULT

47

La Dina

29H
29F

StrikeSense ofmovement

Type

RuptureLength[km]

Distance
to the site[km]MW(Wells andCoppersmith, 1994)

pga
gals

MW
(Stirlinget al,2002)

pga
gals

207

N32.9°E

R

25

15

6,6284

7,0339157
296

N51.6°E
N42.3°E

SS
R

15
30

27
50

6,16,7136
111

6,87,1

213
146

126

N48.9°E

R

15436,2946,8139

113

N39.0°E

R

15626,261

6,893

4629G

AlgecirasServitáSanta
María
GarzónPitalito
La PlataChusma
IrlandaGuayuriba

Rdextral
DextralRdextral

55
131

N23.9°E
N40.7°E

SS
R

15
15

65
83

6,16,250
406,86,887
62

34
29J

Cucuana
Suaza

141
126

N67.9°E
N50.9°E

SSR

15
15

94
95

6,16,22832

6,86,851
51

15C

Paraíso35

N12.5°E

R

15

97

6,2

316,849

29I
45

Length[km]

RdextralRdextral
DextralRdextral
DextralRdextralRdextralFault Id(Figure1)

FAULT

15D
29K

Piendamó
Mocoa

La
Macarena
SS = Strike Slip Fault
R = Reverse Fault
30

LengthStrike

Sense ofmovement

TypeRupture
Length[km]

Distance
to the site[km]MW(Wells andCoppersmith, 1994)

pga
gals

MW
(Stirlinget al,2002)

pga
gals

28
117

N8.4°W
N55.1°E

SSR

15
15

106
106

6,16,223
27

6,86,8434250

N0.6°E

DextralRdextral
RR

15

127

6,2

196,8

31

[km]

CONCLUSIONSThe city of Neiva is located in a earthquake-prone zone, with evidence of earthquakes that havecaused damage and casualties. The most recent earthquakes happened on February 9th, 1967 and June
6th, 1997. The pseudo-deterministic and probabilistic analyses were made in an area between latitudes
2° to 4° north and between longitudes 74.3° and 76.3° west. The time window used was from 1944 to2010. A completeness analysis of earthquake catalog using the methodology of Stepp (1971, 1972)
was done. Deterministic hazard assessment took into account the following faults: La Dina, Algeciras,Servitá-Santa Maria, Garzon-Pitalito, La Plata- Chusma, Irlanda, Guayuriba, Cucuana, Suaza, Paraiso,Piendamó, Mocoa and La Macarena. The probabilistic analysis showed an acceleration of 272 gals fora return period of 475 years. Pseudo-deterministic analysis shows a peak ground acceleration of 339
gals due to the Dina Fault.

Figure 2. Location of epicenters and focal mechanisms for the studied area.

Figure 3. Earthquake time distribution in the area studied from 1910 to 2010.
110100Standar Deviation of the estimate of the mean of the annual number ofevents

1

Teoretical Curves
4,0
4,1
4,3
4,4
4,5
4,6
4,7
4,8
4,9
5,0
6,0
6,3
6,4
6,5

0,10,01Time (Years)

Figure 4. Standard Deviation of the estimate of the mean of the annual number of events as afunction of sample length and Magnitude MS class.

ACKNOWLEDGEMENTS
Figure 2 was developed by using GMT (Wessel and Smith, 2004). Figure 3 was developed by using
Gnuplot (Williams and Kelley, 2007). We also appreciate the recommendations of the anonymousreferee how helped us to improve the original manuscript.

REFERENCES
Allen, C.R., P. St. Amand, C.F. Richter and J.M. Nordquist (1965) Relationship between Seismicityand geologic structure in the southern California Region. Bull. Seis. Soc. Am., Vol 50, pp 447-471.
Benjamin, J.R. (1968) Probabilistic models for seismic force design. Journ. Struct. Div. ASCE, Vol 94,pp. 1175-1196.
Blume, J. and Associates (1968). 1967 Colombian earthquakes. Research Division. San Francisco,California.
Bohórquez, M. (2007). Evaluación Probabilística de la Amenaza Sísmica Regional para Neiva. Thesis.
Civil Engineering. Universidad de La Salle, 2007.
Bohórquez M. and Alfaro A (2008). Análisis probabilístico de la amenaza sísmica de Neiva-Colombia- 40 años del macrosismo del Huila (1967 – 2007). Revista Épsilon Nº 11: 41-48 / July –December.
Douglas, J. A (2001). Comprehensive Worldwide Summary of Strong-Motion Attenuation
Relationships for Peak Ground Acceleration and Spectral Ordinates (1969 to 2000). London:
Imperial College of Science, Technology and Medicine, 2001.
Douglas, J.A. (2002). Errata and Additions to ESEE Report No. 01-1 “A comprehensive worldwide
for peak ground acceleration and spectral ordinates (1969 to 2000)”. London: Imperial College of
Science Technology and Medicine, 2002.
Fukushima, Y. and Tanaka, T. (1990). A new attenuation relation for peak horizontal acceleration ofstrong earthquake ground motion in Japan. Bull.Seism. Soc. Am., 80(4), 757–783. 1990.
Hanks, T. Y and Cornell, C. (1994). Probabilistic Seismic Hazard Analysis: A Beginner's Guide. In
Proceedings of the Fifth Symposium on Current Issues Related to Nuclear Power Plant Structures,Equipment and Piping. North Carolina State University, Raleigh. (1994): I/1-1 to I/1-17.
International Seismological Centre (2010), On-line Bulletin, http://www.isc.ac.uk, Internatl. Seis.
Cent., Thatcham, United Kingdom. Consultation date: January 28, 2010.
Paris G,. Machette, M. Dart, R. and K. Haller (2000). Map and Database of Quaternary Faults andFolds in Colombia and its Offshore Regions. USGS.
Ramírez, J. E. (1967) Macrosismo del Huila. Revista Javeriana, N° 333, Bogota.
Ramírez, J. E. (1975) Historia de los Terremotos en Colombia. Instituto Geográfico Agustín Codazzi,Bogota: 1975.
Stepp, J.C. (1971) An investigation of earthquake risk in the Puget Sound area by use of the Type I
Distribution of largest extremes, PhD thesis, Pennsylvania State Univ., Dept. of Geosciences.
Stepp, J. C. (1972). Analysis of Completeness of the Earthquake Sample in the Puget Sound Area andIts Effect on Statistical Estimates of Earthquake Hazard. Proc. Microzonation Conf. University ofSeattle, Washington: Vol. 2, 897-909.
Stirling M., D. Rhoades and K. Berryman (2002) Comparison of Earthquake Scaling Relations
Derived from Data of the Instrumental and Preinstrumental Era. Bull. Seism. Soc. Am. Vol. 92, No.
2, pp. 812-830.
Takada T. (2005) Seismic Macro Zonation. International Institute of Seismology and EarthquakeEngineering. Lecture Notes. 2005. 50 pp.

USGS (2010). www.earthquake.usgs.gov. Catálogo de Terremotos para América del sur. Project ofCERESIS. (Consultation date: September 25, 2010).
Wells D.L. y K.J. Coppersmith. (1994) New Empirical Relationships among Magnitude, Rupture
Length, Rupture Width, Rupture Area, and Surface Displacement. Bull Seism. Soc. Am. (84)4:974-1002.
Wessel, P. and Smith, W. (2004) The Generic Mapping Tools Version 4 - Technical Reference andCookbook. URL: <http://gmt.soest.hawaii.edu>.
Williams Th. and C. Kelley (2007) Gnuplot- An Interactive Plotting Program. URL:<http://www.gnuplot.info>