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Graduate Theses and Dissertations Graduate School
January 2013
Short and Long Term Volcano Instability Studies atConcepción Volcano, NicaraguaJose Armando SaballosUniversity of South Florida, [email protected]
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Scholar Commons CitationSaballos, Jose Armando, "Short and Long Term Volcano Instability Studies at Concepción Volcano, Nicaragua" (2013). GraduateTheses and Dissertations.http://scholarcommons.usf.edu/etd/4757
Short and Long Term Volcano Instability Studies at Concepcion Volcano, Nicaragua
by
Jose A. Saballos
A dissertation submitted in partial fulfillmentof the requirements for the degree of
Doctor of PhilosophyDepartment of Geology
College of Arts and SciencesUniversity of South Florida
Co-Major Professor: Charles B. Connor, Ph.D.Co-Major Professor: Rocco Malservisi, Ph.D.
Sarah E. Kruse, Ph.D.Peter La Femina, Ph.D.
Timothy H. Dixon, Ph.D.
Date of Approval:May 1, 2013
Keywords: Concepcion volcano, residual Bouguer anomaly, GPS baseline, volcano spreading,time series analysis, Nicaragua
Copyright c© 2013, Jose A. Saballos
DEDICATION
To my son Armando Antonio, my wife Edith,
my parents Armando & Marıa,
my sisters Carolina & Jacqueline, my brother Pabhel
my nieces Helen, Martha, Marıa del Pilar & Cristina.
ACKNOWLEDGMENTS
I would like to thank my advisors Professor Charles B. Connor and Professor Rocco Malservisi,
and the rest of my PhD committee for their great patience and guidance throughout my program
at USF. Field assistance from Koji, Phable, Chuck, Laura, Lara, Sean, Adam, and Ometepe Ex-
pedition people is highly appreciated. Dual-frequency GPS equipment borrowed from UNAVCO
for several campaigns, and the differential GPS kit from CIGEO-UNAN-Managua made possible
the success of my gravity and geodetic studies at Concepcion. I benefited from invaluable lo-
gistic support from Angelica, Allan, Hoffman, Antonio, Virginia, Emilio, Julio, Wilfried, Martha
N. and Rosario from Direccion de Geofısica de INETER. I also want to thank my lab mates and
grad-colleagues : Leah, Mikel, Ana, Alain, Sophie, John P., Heather, Wayne, Mel, Koji, John O.,
Sylvain, Aurelie, Catie, Jacob and Ophelia. The co-authors of my research papers are thanked for
their suggestions, ideas, and patience. Mike Ramsey from Pittsburgh University provided some
ASTER scenes, and the other ASTER imageries were acquired through the GEO-GRID project
(http://www.geogrid.org /en/index.html). Access to the Landsat data was possible through the Glo-
vis server (http://glovis. usgs.gov/). Financial support from the USF Geology Department made
possible my staying in the PhD program and in the US. Funding for field research was also pro-
vided by the USF Geology Department and the Institute for the Study of the Latin America and the
Caribbean. Many other people in the Geology Department encouraged me to keep going and made
my life easier with paperwork, and many other things, and I will be in debt to them, especially
Judy, Mandy, Mary, Lynn, Paul B. and Connie. Gracias a toda mi familia alla en Nicaragua, te amo
hijo, tambien te amo mi nena.
TABLE OF CONTENTS
LIST OF TABLES iii
LIST OF FIGURES iv
ABSTRACT vii
CHAPTER 1 INTRODUCTION 1
CHAPTER 2 GRAVITY AND GPS OF CONCEPCION VOLCANO, NICARAGUA 32.1 Introduction 32.2 Tectonic and Geological setting 42.3 Concepcion volcano 82.4 Gravity 10
2.4.1 Data and processing 102.4.2 Estimate of the bulk density of Concepcion volcano 112.4.3 Description of gravity anomalies 132.4.4 Modeling gravity data with GROWTH2.0 15
2.5 Geodetic GPS time series 182.5.1 Data and processing 182.5.2 GPS results 22
2.6 Discussion and Conclusions 26
CHAPTER 3 RELATIVELY SHORT-TERM CORRELATION AMONG DEFORMA-TION, DEGASSING AND SEISMICITY: A CASE STUDY FROM CON-CEPCION VOLCANO, NICARAGUA 32
3.1 Introduction 323.2 Concepcion volcano 33
3.2.1 2010 eruption 343.3 Data collection and analysis 35
3.3.1 Geodetic GPS data 353.3.2 Real–time seismic amplitude data 353.3.3 Remotely-sensed SO2 data 373.3.4 Data gaps 38
3.4 Results 383.5 Modeling 443.6 Discussion and Conclusions 47
i
CHAPTER 4 LAHAR DELINEATION FROM SATELLITE DATA AT CONCEPCIONVOLCANO 50
4.1 Introduction 504.2 Concepcion volcano 524.3 Slope stability of Concepcion volcano 54
4.3.1 Slope aspect of Concepcion volcano 564.4 Remote sensing of lahars 574.5 Satellite data and methodology 594.6 Results 614.7 Discussion 654.8 Conclusions 704.9 Recommendations 71
REFERENCES 73
APPENDICES 84Appendix A Supplementary figures for Chapter 2 85Appendix B Concepcion’s volcano gravity data 98Appendix C PERL script to compute the complete terrain correction for gravity
data 108Appendix D Supplementary figures for Chapter 3 116
ABOUT THE AUTHOR End Page
ii
LIST OF TABLES
Table 2.1 List of input/initial parameters used in GROWTH2.0 (Camacho et al., 2011).Table 2.2 summarized main results. 17
Table 2.2 List of output parameters from GROWTH2.0 (Camacho et al., 2011) using asinput the data shown in Table 2.1. 18
Table 2.3 Concepcion volcano’s GPS stations’ coordinates in the WGS-84 referenceellipsoid. 24
Table 3.1 Parameters of the open pipe model (Bonaccorso and Davis, 1999) used to ex-plain the geodetic GPS deformation observed at Concepcion volcano duringthe 2010 erupting phase. 47
Table 4.1 Reported lahars at Concepcion volcano since last decade 56
Table 4.2 Planimetric area inundated by lahars at Concepcion volcano. 66
Table B.1 Gravity data gathered at Concepcion volcano, Nicaragua, during campaignscarried out between 2007 and 2010. 98
iii
LIST OF FIGURES
Figure 2.1 Location of Ometepe Island on the western side of Lake Nicaragua. 6
Figure 2.2 Residual gravity anomaly interpolated using the cubic spline algorithm drapedatop of a shaded relief map of Ometepe Island. 14
Figure 2.3 3-D inversion of the gravity data shown in Figure 2.2 using the GROWTH2.0model developed by Camacho et al., (2011). 19
Figure 2.4 3-D display of the location of the total anomalous center of masses obtainedfrom the gravity data inversion using GROWTH2.0. 20
Figure 2.5 CON1-SINT baseline changes running NW-SE across the volcano shown inthe inset. 25
Figure 2.6 MOYO-SABA baseline change running W-NE across the volcano. 26
Figure 3.1 Shaded relief map of Concepcion volcano. 36
Figure 3.2 Time series of the 2010 and 2011 data used in this study. 40
Figure 3.3 Periodograms. 42
Figure 3.4 Cross-Correlograms among all time series. 43
Figure 3.5 Schematic representation of the open pipe model, after Bonaccorso and Davis(1999). 46
Figure 4.1 Geometric relationships used by Iverson et al. (1998) to derive the semi-empirical relationships of a debris-flow’s. 53
Figure 4.2 Shaded relief map of Concepcion volcano showing main towns. 55
Figure 4.3 Slope map of Concepcion volcano generated from a 20-m-resolution digitalelevation model produced in 2004. 58
Figure 4.4 Comparison of different approaches to highlight debris flows on Concepcionusing the same Landsat 7 image acquired on January 27, 2001. 62
Figure 4.5 False color composite Landsat image, acquired on January 27, 2001 producedby the band combination R: band 4, G: ARVI. 64
iv
Figure 4.6 Temporal evolution of the lahar deposits heading down to La Flor town fromthe western slopes of Concepcion volcano. 65
Figure 4.7 Temporal evolution of the lahar deposits of the flows threatening Los Ramostown southeastern side of Concepcion volcano. 67
Figure 4.8 Temporal evolution of the lahar deposits north of San Jose del Sur town SSWslopes of Concepcion volcano. 68
Figure 4.9 Time series of inundated areas by lahar deposits extracted from satellite data. 68
Figure A.1 Simple Bouguer anomaly map computed using a density of 2500 kg m−3 usedin gravitational spreading models (e.g. Borgia and van Wyk de Vries, (2003)). 85
Figure A.2 Simple Bouguer anomaly map computed using a density of 1539 kg m−3 pro-vided with the 1-D Nettleton (Nettleton, 1939) and Parasnis’(Parasnis, 1997)methods. 86
Figure A.3 3-D inversion of the gravity data shown in Figure 2.2 using the GROWTH2.0model developed by Camacho et al., (2011). 87
Figure A.4 3-D inversion of the gravity data shown in Figure 2.2 using the GROWTH2.0model developed by Camacho et al., (2011). 88
Figure A.5 Time series for the three components of station CON1 for all the campaigns. 89
Figure A.6 Time series for the three components of station COS2. 90
Figure A.7 Time series for the three components of station MOYO. 91
Figure A.8 Time series for the three components of station SABA. 92
Figure A.9 Time series for the three components of station SINZ. 93
Figure A.10 Time series changes for the Longitude component of all stations around Con-cepcion volcano during April through July 2010. 94
Figure A.11 Time series changes for the Latitude component of all stations around Con-cepcion volcano during April through July 2010. 95
Figure A.12 Time series changes for the vertical component of all stations around Con-cepcion volcano during April through July 2010. 96
Figure A.13 Temporal changes of Latitude component of GPS station MANA betweenJanuary 2007 and August 2010. 97
Figure A.14 Temporal changes of Longitude component of GPS station MANA betweenJanuary 2007 and August 2010. 97
Figure D.1 Periodograms for GPS baseline changes during 2010 and 2011. 116
v
Figure D.2 Periodograms for RSAM daily average during 2010 and 2011. 117
Figure D.3 Periodograms for SO2 daily average during 2010 and 2011. 118
Figure D.4 Scatter plots of the data used in this study. 119
vi
ABSTRACT
Concepcion is the most active composite volcano in Nicaragua, and is located on Ometepe
Island, within Lake Nicaragua. Moderate to small volcanic explosions with a volcanic explosivity
index (VEI) of 1–2 have been characteristic of this volcano during the last four decades. Although
its current activity is not violent, its volcanic deposits reveal stages of violent activity involving
Plinian and sub-Plinian eruptions that deposited vast amounts of volcanic tephra in the Atlantic
Ocean. These observations, together with the 31,000 people living on the island, make Concepcion
volcano an important target for volcanological research.
My research focuses on the investigation of the stability of the volcano edifice of Concepcion,
using geophysical data such as gravity, geodetic global positioning system (GPS), sulphur dioxide
(SO2) flux, real-time seismic amplitude (RSAM), and satellite remotely-sensed data. The integra-
tion of these data sets provides information about the short-term behavior of Concepcion, and some
insights into the volcano’s long-term behavior.
This study has provided, for the first time, information about the shallow dynamics of Con-
cepcion on time scales of days to weeks. I furnish evidence that this volcano is not gravitationally
spreading in a continuous fashion as previously thought, that its bulk average density is comparable
to that of a pile of gravel, that the volcano edifice is composed of two major distinctive lithologies,
that the deformation field around the volcano is recoverable in a matter of days, and that the defor-
mation source is located in the shallow crust. This source is also degassing through the relatively
open magmatic conduit. There are, however, several remaining questions. Although the volcano is
not spreading continuously there is the possibility that gravitational spreading may be taking place
in a stick-slip fashion. This has important implications for slope stability of the volcano, and the
associated hazards. The factors influencing the long term slope stability of the volcano are still
vii
not fully resolved, but internal volcanic processes and anthropogenic disturbances appear to be the
major factors.
viii
CHAPTER 1
INTRODUCTION
Volcanoes and volcanic eruptions are beautiful natural phenomena. Unfortunately, volcanoes
also jeopardize the integrity of their surrounding landscape, and threaten human lives. Because
of the fertile soils volcanoes produce, people settle around volcanoes to farm the land, often not
knowing the hazards their volcano poses to them, and in some cases not even realizing they are
living next to a volcano, rather than just a “mountain”.
The end product of volcanology is the hazard mitigation and prevention of disasters from pro-
cesses associated to both active and inactive volcanoes. To reach that goal we first need to under-
stand what the volcano did in the past, what the volcano is doing now, and then we will be able to
build models to attempt to foresee what the volcano may do in the future within certain levels of
confidence.
A single scientific technique is by no means capable of revealing all the processes operating
in an active volcano. This is why volcanology is multidisciplinary. Advances in science and tech-
nology have dramatically improved the way we look at volcanic processes, allowing us to greatly
improve the physical and numerical models in volcanology at all levels.
Through the research presented in this dissertation, I contribute to the understanding of an
active volcano (Concepcion) located on Ometepe Island, within lake Nicaragua, hosting more than
31,000 inhabitants. This research provides valuable information for volcanologists and decision-
makers involved in volcanic crisis, and also demonstrates that there is still a lot to be done to clearly
understand the complex dynamics of this volcano.
My research focuses on the interpretation of geophysical data (gravity and geodetic global
positioning system, GPS) gathered at Concepcion volcano, Nicaragua, since the last decade. It
begins by describing results derived from gravity and GPS data to look at the structure of the
1
volcano edifice, and assess its short term surface response to the processes operating in its shallow
plumbing system. Then, this dissertation describes in more detail what monitoring techniques
such as GPS, real-time seismic amplitude, and sulphur dioxide emission detect when the volcano
is in a moderate erupting phase, and what they record when the volcano is not erupting. A joint
interpretation of these data sets is given together with a conceptual model that depicts a possible
scenario (in a very simplified way) of the dynamics of the Concepcion’s plumbing system. Finally,
this work ends by providing a chronology of the mass wasting processes triggered by rainfall during
the last three decades at Concepcion volcano, which shed light on the picture of intermediate and
long term stability of this volcano.
The pronoun “we” used in Chapters 2 and 3 reflects co-authors contribution on those manuscripts
submitted for publication and in preparation. Chapter 2 is in press in the Geological Society of
America special paper volume entitled Understanding open-vent volcanism and related hazards,
edited by W. I. Rose, J. L. Palma, H. Delgado Granados and N. Varley. Chapter 3 will be soon
submitted to Bulletin of Volcanology, and chapter 4 is part of a manuscript in preparation that will
be submitted to a scientific journal after lahar numerical modelling is incorporated.
2
CHAPTER 2
GRAVITY AND GPS OF CONCEPCION VOLCANO, NICARAGUA
2.1 Introduction
Volcanoes evolve depending on the nature of eruptions and eruptive products through time,
the gravitational load of the volcano, and its interaction with the crust (Borgia, 1994; Borgia et
al., 2000; Merle and Borgia, 1996; van Wyk de Vries and Borgia, 1996; van Wyk de Vries and
Matela, 1998). As the edifice of a volcano grows, the load of this edifice on the crust may cause the
volcano to spread radially, and the resulting deformation affects hazards (e.g., potential for flank
collapse and the location of potential flank eruptive vents). In this paper we use gravity and global
positioning system (GPS) measurements collected at Concepcion volcano, Nicaragua to improve
knowledge of its structure, and to investigate the possibility that the volcano is laterally spread-
ing under its own load. Concepcion, along with Maderas volcano, forms Ometepe Island in Lake
Nicaragua (Figure 2.1). This small composite volcano is built upon sedimentary rocks and uncon-
solidated sediments in the lake, and has been frequently cited as an example of a spreading volcano
(Merle and Borgia, 1996; Borgia et al., 2000; Borgia and van Wyk de Vries, 2003; Delcamp et al.,
2008). This potential spreading clearly has important implications for how volcanic hazards are
assessed in populated areas on the island and possibly for all those living on the shores of Lake
Nicaragua.
Bulk density is a crucial parameter contributing to the potential for a volcano edifice to spread
(Merle and Borgia, 1996; Borgia et al., 2000). Essentially, the higher the density of the volcano
edifice the more likely this load, added to the crust in a relatively short time, will cause isostatic
adjustments. Isostatic adjustment, in turn, may enhance instability of slopes of the volcano or
the response of the edifice to subsequent intrusions (Borgia, 1994; Borgia and van Wyk de Vries,
3
2003). Gravity surveys are widely used to study the structure of volcanoes (Yokoyama, 1963;
Budetta et al., 1983; Rymer and Brown, 1986; Brown et al., 1987; Connor and Williams, 1990;
Rout et al., 1993; Camacho et al., 1997; Affleck et al., 2001). In particular, gravity data provide
direct information about volcano density (Finn and Williams, 1982; Brown et al., 1991; Deplus et
al., 1995; Schulz et al., 2005; Cassidy et al., 2007), which is of fundamental importance for deter-
mining the potential for a volcano edifice to spread laterally under its own load (Merle and Borgia,
1996; Borgia et al., 2000; Jordan et al., 2009). Similarly, GPS is one of the main tools for the study
of volcano deformation (Dixon, 1991; Murray et al., 2000; Blewitt, 2007; Dzurisin, 2007), and
offers the most direct evidence of whether a volcano is spreading and at what rate. Therefore, we
undertook gravity investigations at Concepcion with the goal of investigating the structure and bulk
density of the volcano, and GPS investigations in order to investigate the deformation (specifically
the change in baseline length between geodetic GPS stations) over time.
In the following we describe the geologic and tectonic setting of Concepcion volcano with
special reference to volcano spreading models. Then, we describe our new gravity map of Con-
cepcion volcano and how these data are used to estimate bulk density of the edifice and to refine our
understanding of the major structural features of the volcano. GPS results from campaigns in 2001–
2010 are presented and these position data analyzed on long-term (yearly) and short term (daily)
timescales. If permanent deformation associated with gravitational spreading is occurring at a high
rate, then lengthening of the baselines between GPS stations positioned around the volcano should
be observed on a long-time scale. Instead, deformation is observed on short timescales (daily),
and is associated with episodes of volcanic unrest, and is recoverable (resulting in elongation and
shortening of baselines repeatedly).
2.2 Tectonic and Geological setting
Concepcion volcano is an∼1600 m-high composite volcano (Figures 2.1, and 2.2). Concepcion
is part of the Central American Volcanic Arc, the result of Cocos plate subduction beneath the
Caribbean plate. The volcanic arc is located within the Nicaraguan Depression, an Oligocene
- Pliocene half-graben that extends ∼500 km in length from northern Costa Rica to the Gulf of
4
Fonseca and has a width ranging from 40 km (northwest) to 70 km (southeast) (McBirney and
Williams 1965; Weinberg, 1992; Funk et al., 2009). Although there have been several different
theories as to the tectonic significance, geomorphology and history of the Nicaraguan Depression,
we are here primarily interested in the stratigraphy of the Nicaragua Depression and the current
tectonics of the margin at the latitude of Concepcion volcano.
The Nicaraguan Depression is flanked to the northeast by the late Oligocene to middle Miocene
volcanic arc (El Coyol Group volcanics; Ehrenborg, (1996)) and Nicaraguan highlands composed
of pre-Mesozoic crust (Sundblad et al., 1991). The volcanic arc migrated to the Nicaragua De-
pression during the middle Miocene (e.g., Ehrenborg, (1996); Plank et al., (2002); Carr et al.,
(2007); Saginor et al., (2011)) and resides there today. The depression is a half-graben with down-
to-the-northeast displacement along margin-parallel (i.e., northwest-trending) normal faults along
the southwestern margin. On the western edge of Lake Nicaragua, the boundary is composed of
late Cretaceous to Miocene sedimentary and volcaniclastic rocks of the Sandino Basin that were
folded and uplifted, and then faulted (Weyl, 1980; Weinberg, 1992; Ranero et al., 2000; Funk et
al., 2009). The Pliocene El Salto Formation unconformably overlies the top of the Sandino Basin
sequence (i.e., the middle Miocene El Fraile Formation, which is interbedded with the Tamarindo
Group volcanics). The upper section of the El Salto Formation is interbedded with the Pleistocene
Las Sierras Group volcanics, which represent the initiation of the ‘modern’ volcanic arc (Weyl,
1980).
The stratigraphic thicknesses of the Late Cretaceous to Pliocene stratigraphy are best estimated
from well logs from offshore and onshore wells (Ranero et al., 2000). The thicknesses of these
formations are dramatically thinner than reported by Weyl (1980 and references therein) based on
mapping studies. For example, the Sandino Basin sequence is reported as ∼10 km in thickness
by Weyl, (1980); however, the maximum thickness as measured in wells is 4.2 km (Ranero et
al., 2000). The Pliocene El Salto Formation is thicker (>700 m) in offshore wells (Argonaut-
1 and Corvina-1 wells; Ranero et al., (2000)) than has been mapped onshore (100 m thickness;
Weyl, 1980). The Las Sierras Group has been mapped at a thickness of 680 m (Weyl, 1980).
Unfortunately, the thickness of Quaternary alluvium and lacustrine sediments in Lake Nicaragua
5
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6
are not known. Various researchers have estimated or assumed the thicknesses of these deposits,
with estimates ranging from ∼100 m to >1000 m (Swain, 1966; Elming and Rasmussen, 1997;
Borgia and van Wyk de Vries, 2003). The only direct measurement of Quaternary deposits in the
Nicaragua Depression is from the M16 exploratory drill hole at the Momotombo geothermal field,
approximately 140 km NW of Concepcion volcano, that suggests 150 m of Quaternary sediment
and ignimbrite that unconformably overlies Tertiary ignimbrites (van Wyk de Vries, 1993). We
know of no wells in the Nicaraguan Depression that have reported well logs. Recent seismic
reflection data collected in Lake Nicaragua indicate >20 m of sediment (Funk et al., 2009), but
could not confirm total thickness of the sediments due to rapid attenuation of seismic waves.
The neotectonics of the Central American margin have been the focus of recent studies to
investigate the kinematics of deformation of the forearc and volcanic arc. Geodetic studies indi-
cate that the forearc is migrating from central Costa Rica to Guatemala at rates of 8–17 mm yr−1
(Norabuena et al., 2004; Correa et al., 2009; La Femina et al., 2009; Alvarado et al., 2011). Al-
though it is debated how this forearc motion is accommodated in Nicaragua, it is clear that there
are three active structural trends, 1) northwest-trending right-lateral strike-slip and normal faults;
2) northeast-trending left-lateral strike-slip and normal faults; and 3) north-trending normal faults
and volcanic alignments.
Recent seismic reflection data collected in Lake Nicaragua imaged three faults that vertically
displace the lake bottom: the San Ramon, Jesus Marıa and Morrito fault zones (Funk et al., 2009).
The San Ramon fault zone, SRFZ, is a northwest-trending, down-to-the northeast, dip-slip normal
fault that is located at the southwestern end of Maderas volcano and extends 25 km to the southeast
(Funk et al., 2009). The Jesus Marıa fault zone (JMFZ; Figure 2.1) is a northeast-trending, irreg-
ularly surfaced topographic high with ∼4-7 m vertical scarps (Funk et al., 2009). This structure is
located directly southwest and aligned with an extended peninsula of Concepcion volcano, and a
broader topographic high between Ometepe Island and the western edge of Lake Nicaragua (Funk
et al., 2009). The Morrito fault zone is a 20 km long by 5 km wide northeast-trending depression
with 5–7 m scarps located northeast of Ometepe Island (Funk et al., 2009).
7
In addition to these fault zones, a magnetic anomaly along the southeastern shore of Lake
Nicaragua has been interpreted qualitatively as the Lake Nicaragua fault zone (Funk et al., 2009),
a northeast dipping depression bounding normal fault. Funk et al., (2009) propose that these faults
are reactivated as dextral oblique-slip faults in the current kinematic regime to accommodate fore-
arc motion, however, no historical seismicity is known to be associated with these fault systems.
Instead, there have been two recent earthquakes located on northeast-trending left-lateral strike
slip faults northwest and southeast of Ometepe Island; the 1987 Mw 6.1 Lake Nicaragua and 2005
Mw 6.3 Ometepe earthquakes, respectively.
2.3 Concepcion volcano
The volcano is predominantly composed of clinopyroxene–plagioclase bearing andesite rocks
found low and high on the slopes exposed in gorges. Basalts also occur and are found mostly on
lateral vents and in some summit eruptions. A dacite pumice deposit is found at the north base of
the volcano (McBirney and Williams 1965; van Wyk de Vries, 1993; Borgia and van Wyk de Vries,
2003). Lahars, pyroclastic units, and lava flows are all common products of Concepcion (McBirney
and Williams 1965; van Wyk de Vries, 1993; Borgia and van Wyk de Vries, 2003). Van Wyk de
Vries (1993) and Borgia and van Wyk de Vries, (2003) provide a detailed magmatic evolution
of the volcanic system. Stratigraphically older magmas erupted from Concepcion are termed the
Quebrada Grande stage and are low-alumina (∼16 wt % Al2O3) and high-magnesium (∼8 wt %)
basalts. Following the Quebrada Grande stage, magmas evolved to a more silica- and alumina-rich
composition, culminating in the dacite amphibole-bearing Tierra Blanca tephra deposits (∼63-
66 wt % SiO2) (van Wyk de Vries, 1993; Borgia and van Wyk de Vries, 2003). The Tierra Blanca
tephra is widespread throughout the region and is found in cores collected off-shore, in the Pacific
Ocean. The Tierra Blanca tephra is dated at ∼19 ka (Kutterolf et al., 2008) and marks the most
explosive (Plinian-style) activity known to have occurred at Concepcion. Following the Tierra
Blanca eruption, most tephra and lava compositions have been 50-55 wt % SiO2, although the top
sections of the tephra erupted in 1957 had ∼62 wt % SiO2 (Borgia and van Wyk de Vries, 2003),
8
and eruptions from lateral vents generally have less silicic compositions than central vent eruptions
(Figure 2.1) (van Wyk de Vries, 1993).
A geodynamic model of Concepcion proposed by Borgia and van Wyk de Vries, (2003) sug-
gests that spreading of the volcano edifice began after the Tierra Blanca eruption, during the El
Mogote phase, when the volume of newly erupted products became sufficient for the load of the
edifice to initiate spreading on the underlying ductile lake sediments. In their model this spreading
involves a thicker portion of the sedimentary section, and even the magma chamber, over time.
As the increased load of the volcano edifice drives spreading, deformation with spreading should
be continuous (Borgia et al., 2000), but may be episodic if the Maxwell relaxation time is small
compared to the characteristic spreading time (Borgia and van Wyk de Vries, 2003). Characteristic
spreading time, T , is given by Borgia et al., (2000) as:
T =3µL2
ρgHvH2d
(2.1)
where µ is the viscosity of the deforming ductile layer of thickness Hd beneath the volcano
of radius L, bulk density ρ and height Hv, and g is gravitational acceleration. Thus, a low bulk
density and thin ductile layer will result in longer characteristic spreading time than a high bulk
density and thick ductile layer, for a volcano of a given geometry. Although the viscosity of the
ductile substratum layer can vary by several orders of magnitude, at Concepcion it is assumed to
be low because it is composed of soft clayey sediments (van Wyk de Vries, 1993; Borgia and van
Wyk de Vries, 2003). Van Wyk de Vries and Matela (1998) proposed a viscosity in the range of
1015−18 Pa· s.
N–S trending fissures and aligned eruptive vents on the volcano edifice may be a manifestation
of overall E–W extension associated with spreading (Borgia and van Wyk de Vries, 2003), although
N–S trending fissures and vent alignments are ubiquitous on volcanoes in this part of the arc and
are generally attributed to extension within the dextral shear zone that defines Central America
fore-arc motion relative to the Caribbean, without requiring volcano spreading.
9
The most recent comparatively large-volume effusive eruption of Concepcion was in 1957
(volcanic explosivity index, VEI 2), and a minor effusive eruption took place in 1986 (VEI 1)
(McBirney and Williams 1965; Siebert et al., 2011). Ash explosions from small to moderate size
occur frequently, characterized by VEI of 1 and 2 (Siebert et al., 2011). This activity is sufficient
to maintain a summit pyroclastic cone, degradation of which results in seasonal lahars that reach
populated and agricultural areas at the base of the volcano.
2.4 Gravity
2.4.1 Data and processing
A total of 206 gravity readings were collected on and around Concepcion volcano during four
different campaigns between 2007 and 2010, covering an area of approximately 18 km× 12 km on
Ometepe Island (Figure 2.2). The 2007 gravity campaign was carried out with a G-58 LaCoste &
Romberg instrument. The 2008 – 2010 campaigns were conducted with a Burris gravity meter (B-
38). During all surveys the observation points were positioned with a differential global positioning
system instrument to achieve absolute vertical accuracies of at least 10 cm. The observed data
were reduced using the standard procedure described by LaFehr, (1991) and Nowell, (1999), by
applying corrections for : solid earth tide, instrument drift, geographical latitude, free-air, Bouguer
slab (simple Bouguer correction or Bullard A correction), spherical cap (Bullard B correction), and
terrain (complete Bouguer, or Bullard C correction). All gravity data are provided in Appendix B.
Terrain corrections were computed in three steps using a 20-m digital elevation model (DEM),
provided by the Instituto Nicaraguense de Estudios Territoriales (INETER). These three steps are
based on the distance from the gravity observation point to points on the DEM grid (a copy of
this code is provided in Appendix C). The inner zone correction accounts for topographic variation
within Hammer’s zone C, 53.3 m, and was computed using the quarter-wedge method described by
Nowell, (1999), an improved version of the power-law approximation method of Campbell, (1980).
The intermediate zone correction was performed for DEM grid points that fall between Hammer’s
zone D, >53.3 m, and outer radius of Hammer’s zone K, 9903 m. This terrain correction was done
using the simplified gravity attraction of a prism approximated as an annular ring, described by
10
Kane, (1962). The far-field terrain correction was performed for distances >9903 m and up to the
extent of the input DEM, including all of the area of Ometepe Island. This far-field correction
was carried out by means of the vertical line mass approximation described by Blais and Ferland,
(1984), which is the approximation of the gravity attraction due to a prism in the far-field. The
lack of precise bathymetry data from Lake Nicaragua prevented implementation of a correction
for the gravitational attraction from the water lake layer, but this effect must be small compared to
the island terrain correction as lake depth is shallow, around 20 m in maximum depth in the region
around Ometepe Island, and 43 m at its maximum reported depth in the central part of the lake
(Swain, 1966). The maximum terrain correction obtained using this method was 5.27 mGal, for a
station located on the highest point along the ridge on the SW flank of the volcano and located very
near the San Jose del Sur, SJS, gully (Figure 2.1). Only points located on the slopes of the volcano
have terrain corrections > 1 mGal.
A residual gravity anomaly was computed by subtracting the complete Bouguer anomaly (the
anomaly obtained after the application of the terrain correction) from an assumed regional trend,
estimated by fitting a plane to the complete Bouguer anomaly map using the generalized least-
squared method (Figure 2.2).
2.4.2 Estimate of the bulk density of Concepcion volcano
A primary goal of collection of gravity data on Ometepe Island is to estimate the bulk density
of Concepcion volcano. Initially, the bulk density of the volcano edifice was estimated using the
Nettleton (Nettleton, 1939) and Parasnis (Parasnis, 1997) methods, using gravity stations along two
profiles that cross the volcano edifice. These methods are based on the observation that complete
Bouguer gravity anomalies should be minimally correlated with topography in geologically ho-
mogeneous terrains. Ometepe Island is constructed predominantly of tephras and lavas in an area
where lake sediments are dominated by volcaniclastic material (Swain, 1966), so this assumption
is reasonable. The Nettleton and Parasnis methods yield a bulk average density of the volcano of
1439± 67 kg m−3 and 1539± 89 kg m−3 on each profile. However, the resulting Bouguer anomaly
maps are too positively correlated with topography (such densities produce Bouguer anomalies of
11
78 mGal in amplitude, -28 – 50 mGal, see Appendix A), indicating that these densities are lower
than the actual bulk density of the terrain.
To improve the density estimate, we extended the Nettleton’s method from 1-D to a 2-D grid
by encompassing the entire volcano edifice (including many more observed points) and computing
the correlation between the topography and Bouguer gravity anomaly, for a series of bulk densities.
The most likely bulk density of the volcano minimizes this correlation. The density thus obtained
was 1764 kg m−3. We do not know the uncertainty in the model due to the real density hetero-
geneities below the targeted area (i.e., the volcano edifice), but from the analysis of regression
we estimate uncertainty to be ± 111 kg m−3. Thus, we deem the latter value as the uncertainty’s
lower bounds for the bulk average density estimation. This density gives rise to a Bouguer anomaly
amplitude of 49 mGal, -14 – 35 mGal. This bulk density is significantly less than values used in
previous volcano spreading models (Borgia and van Wyk de Vries, 2003) but is consistent with the
density of other volcanoes dominated by the accumulation of pyroclasts (Minakami, 1941; Brown
et al., 1991; Affleck et al., 2001; Cassidy et al., 2007). Using a bulk density of 2500 kg m−3 (e.g.,
Borgia and van Wyk de Vries, 2003) produces a Bouguer anomaly map that is negatively corre-
lated with topography (this yields a Bouguer anomaly of 94 mGal in amplitude, -44 – 54 mGal),
indicating that 2500 kg m−3 is an overestimate of the density (see maps in Appendix A).
If we model the volcano edifice of Concepcion as a frustum of a cone with a height of h
(1570 m, elevation difference between volcano’s maximum elevation an the elevation of its base),
a radius of upper base r (150 m), and a radius of lower base R (3500 m), and using the bulk average
density we have estimated from the gravity data (ρ = 1764 kg m−3), we can get an estimation of the
mass of the volcano by the product of the density and volume (i.e., Mv = ρV ). Thus, the formula
we need to compute the mass of the volcano, Mv, is :
Mv =ρπh
3(R2 + rR+ r2) (2.2)
12
Plugging in the corresponding values we get a mass for Concepcion volcano of about 0.37 x
1014 kg. Later, in section 2.6, we compare this mass, Mv, to the total anomalous mass below our
surveyed gravity area that will be estimated using a 3-D inversion model.
2.4.3 Description of gravity anomalies
The distribution of gravity anomalies clearly reveals additional structure within the edifice of
Concepcion volcano and on Ometepe Island (Figure 2.2). First, the gravity map of the volcano
is dominated by a gravity low in the upper edifice of the volcano and comparatively high gravity
values low on the edifice. The transition between the high and low values correlates with a slight
break-in slope visible on the flanks of the volcano produced by the Tierra Blanca explosive phase,
and the subsequent addition of pyroclastic material (Figure 2.2C). The low gravity values (< 10
mGal, Figure 2.2A) found on the upper slopes of the volcano are interpreted to reflect the low
density pyroclastic cone that forms the summit area of the volcano. In contrast, the lower slopes of
the volcano have a slightly higher density, resulting in a positive gravity anomaly.
Sharp gradients in the residual gravity anomaly map (Figure 2.2A) delineate faults that are par-
tially and/or completely buried by young volcanic products. The low residual gravity anomaly
< -7 mGal trending N40◦W (parallel to the subduction zone in Nicaragua) on the NE side of
Concepcion (Figure 2.2A), may represent a fault, possibly an extension of the mapped faults on
Maderas volcano with about the same strike, and matches the fault partially mapped NNE of Con-
cepcion by van Wyk de Vries (1993). If this anomaly is indeed associated with a normal fault,
its hanging-wall block should be down-to-the-NE. The other low residual gravity anomaly SW
of Concepcion volcano is more complex in geometry (Figure 2.2) and may be related to possible
structural discontinuities of volcanic products within mudstones, which may also be associated
with an extension of the SRFZ and JMFZ (Funk et al., 2009).
The profile P1P2 shown in Figure 2.2C suggests two main features. The first one is that the
residual gravity anomaly is not flat as assumed in the model for estimating the bulk average density.
This does not imply that our volcano density estimation is wrong, since it minimizes the correlation
between the Bouguer anomaly and the topography. But, this indicates that there are significant
13
6450
00
6450
00
6600
00
1264000
1264000
1276000
1276000
Res
idu
al A
no
mal
y (
mG
al)
Hig
h: 2
4
Low
: -22
02.
55
7.5
10K
m
−2
1−
14
−7
14
21
Re
sid
ual
An
om
aly
(mG
al)
07
P1
P2
La
ke
Nic
ara
gu
a
0
200
400
600
800
1000
1200
1400
1600
Ele
vatio
n (m
)
0 2000 4000 6000 8000 10000 12000 14000 16000
Distance along profile (m)
Res
idua
l gra
vity
(m
Gal
)
−5
0
5
10
15
20Residual gravityTopography
AB
C
P1 P2
Figu
re2.
2.(A
)Res
idua
lgra
vity
anom
aly
inte
rpol
ated
usin
gth
ecu
bic
splin
eal
gori
thm
drap
edat
opof
ash
aded
relie
fmap
ofO
met
epe
Isla
nd.
The
resi
dual
grav
ityan
omal
yw
asco
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ted
bysu
btra
ctin
ga
linea
rre
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altr
end
from
the
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eB
ougu
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1764±
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ete
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obse
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Whi
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serv
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npo
ints
used
toco
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ted
the
bulk
-ave
rage
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ityof
the
volc
ano
bym
eans
ofth
e1-
DN
ettle
ton
(Net
tleto
n,19
39)
and
Para
snis
’(P
aras
nis,
1997
)m
etho
ds.
The
resi
dual
grav
ityan
omal
ym
apre
veal
conc
eale
dge
olog
icst
ruct
ures
ofth
evo
lcan
o,an
dpo
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ults
onth
eno
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este
rnsi
des.
(B)
Poin
tcol
or-m
apof
resi
dual
grav
ityan
omal
yon
Con
cepc
ion
volc
ano.
(C)
Profi
leP 1
P 2co
mpa
ring
topo
grap
hyan
dre
sidu
algr
avity
anom
aly,
see
text
ford
iscu
ssio
n.
14
inhomogeneities (small spatial scale in the order of tens of meters) within the area used to compute
the bulk average density, i.e., the volcano edifice and its nearby surroundings. The second important
feature is that we can better appreciate the variations of the residual gravity anomaly with regard to
the topography, mainly at the volcano edifice. The gravity residual anomalies < 10 mGal (Figure
2.2A) mark the transition from the high to low gravity anomalies and occur at elevations between
800 and 1000 m along the volcano profile shown in Figure 2.2C.
2.4.4 Modeling gravity data with GROWTH2.0
We cannot build a direct subsurface structural density model of our study area from the grav-
ity data since there is no detailed geologic information below our study area (i.e., stratigraphic
data hundreds to thousands of meters below Concepcion volcano from cores, or other geophysical
observations). Thus, a non-subjective inversion model is the best approach to model our grav-
ity data for Concepcion volcano and investigate its subsurface structure. One of such a model is
GROWTH2.0 developed by Camacho et al., (2011). This is a non-subjective and almost automatic
three-dimensional (3-D) model, which is based on the gravity inversion growing bodies model pre-
viously developed by Camacho et al., (2000, 2002). GROWTH2.0 is a non-linear inversion method
that looks for the geometrical properties of the anomalous bodies fitting the gravity observations
(Camacho et al., 2011). The major assumptions in GROWTH2.0 are that the subsurface anomalous
structure is characterized by a prescribed density contrast (positive and negative values are accepted
simultaneously), that the gravity data are unevenly spatially sampled and imprecise values, with a
Gaussian uncertainty, that the model parameters are also subjected to Gaussian uncertainties, and
that the data contain a linear regional trend (Camacho et al., 2000, 2002, 2011).
The determination of the geometry of the anomalous bodies is carry out by dividing (seed-
ing) the subsurface volume into discrete 3-D prismatic elements (cells) that are systematically and
step-by-step tested for possibilities of model growth, in which “increased” prisms correspond to
previously prescribed positive values of density contrast, “decreased” prisms correspond to nega-
tive values, and unchanged prisms correspond to null values. The problem of the non-uniqueness
solution in the gravity data inversion is treated by GROWTH2.0 through a least square minimiza-
15
tion of the residuals (model fitness), and the l2 minimization of the total anomalous mass (model
smoothness; Camacho et al., 2000, 2002, 2011). Mathematically, the minimization algorithm of
GROWTH2.0 is expressed as (Camacho et al., 2011) :
νT Q−1
D ν +λ f 2mT Q−1M m = min (2.3)
where ν is the matrix vector of residuals; QD is the covariance matrix of gravity data uncertain-
ties, λ is a positive dimensionless factor to balance model fitness and smoothness (by default λ =
30 in GROWTH2.0, for higher values of λ the inversion yields a simple model with a poor fit to the
data, and for lower values the inversion produces a complex model of the subsurface structure with
very good fit to the observations; an optimal value for λ yields a value of ' 0 for autocorrelation
of residuals); f is a scale factor for fitting the modeled anomalies (initially each cell is assigned
with a value of f ≥ 1, then during a subsequent iteration the value of f of a given cell decreases
depending on its contribution to the model fitness, finally the growth criteria of the cell stops when
f reaches a value of ' 1); m is the matrix of the prescribed density contrast values; and QM is the
uncertainty model parameters’ matrix (Camacho et al., 2011). Readers are referred to Camacho et
al., (2011; and references therein) for further details of the GROWTH2.0 model.
We carried out inversion of our gravity data gathered at Concepcion volcano using the cited
GROWTH2.0 model (Camacho et al., 2011). We ran the model several times varying the input
parameters. In Table 2.1 we have summarized three sets of input parameters that, in general,
embrace the majority of the solutions that converge, and are also appropriate in our geological
context. These set of parameters also yielded low values (close to 0) for the autocorrelation, a
parameter related with the quality of the inversion based on the ratio between short distances among
gravity observation points and data “noise” (Camacho et al., 2011), shown in Table 2.2. The
homogeneity parameter used as part of the input to GROWTH2.0 (Table 2.1) is defined by Camacho
et al., (2011) as the factor controlling the homogeneity distribution of the density within and at
the boundaries of the modeled anomalous bodies. High values of homogeneity (very close to, or
16
Table 2.1. List of input/initial parameters used in GROWTH2.0 (Camacho et al., 2011). Table 2.2summarized main results.
Set Depth to MBa Mean CLb No. of cells Initial DC rangec Homogeneityd
(m) (m) (kg/m3)1 -4883 601 8045 -400 – 400 0.52 -3000 500 9430 -300 – 300 0.23 -4000 600 7542 -400 – 400 0.6
aModel bottom (depth is negative).bInitial cells’ length of subsurface elements.cInitial density contrast range to start the model.dThis parameter takes values between 0 and 1, and defines density transition across anomalousbodies. See text for details.
equal to 1) produce anomalous bodies with smoothed and diffuse boundaries, with extreme density
values at the center of the bodies that decrease towards the edges (Camacho et al., 2011). A low
homogeneity value (very close to, or equal to 0) yields anomalous bodies with abrupt boundaries,
with homogeneous geometries, and with a single density value (Camacho et al., 2011).
In Table 2.2 we present the main outputs from the corresponding input parameters shown in
Table 2.1. obtained from GROWTH2.0. The maximum range of density contrast that best fit the
inversion model is -440 to 410 kg/m3, and the anomalous mass is around 1 x 1014 kg. Figure 2.3
depicts these results. In Appendix A (Figures A.3 and A.4), we show the figures resulting from the
other two sets of parameters summarized in Tables 2.1 and 2.2. The three selected outputs from
GROWTH2.0 share great similarities. They represent Concepcion volcano as a cone dominated by
a negative density contrast in its central and upper part. While its lower slopes and deeper parts are
characterized by a positive density contrast anomaly, which implies that the lower slopes are denser
than the upper part of the volcano (Figure 2.3). A significant low density anomaly zone is located
between the NE side of the volcano and the shoreline, trending NW-SE (Figure 2.3A). Whereas, on
the SW side of the study area (Figure 2.3A) there is another low density anomaly zone, although
more diffuse than that on the NE side. The cross-sections drawn by GROWTH2.0 and presented
in Figures 2.3B and C show that the negative anomaly in the upper part of the volcano extends up
to 1 km depth, while the higher density anomaly (that seems to compose the lower slopes of the
volcano) surrounds the lower density anomaly, and extends up to depth of around 4.5 km. The
17
Table 2.2. List of output parameters from GROWTH2.0 (Camacho et al., 2011) using as input thedata shown in Table 2.1.
Set Model fitted DCa Balance factor, λb Auto-correlationc TA massd
(kg/m3) (x 1014 kg)1 -440 – 410 36 -0.05 1.162 -440 – 410 44 0.05 1.023 -370 – 310 36 -0.05 1.16
Location of center of total anomalous masse
Set Easting (m) Northing (m) Depth(m) (m) (m)
1 650900 1276129 -21592 650010 1275368 -16973 650600 1275880 -2057
aDensity contrast range fitted by the model.bOptimal value of the balance factor found by the model.cSee text for explanation.dTotal Anomalous mass, i.e., cumulative of excess and deficit masses.eThe center of mass is virtually located below the volcano whose crater location is at 650500(Easting), and 1275550 (Northing), see Figure 2.4.
other two models are very similar to that of Figure 2.3, but in those the higher density anomaly
extends to greater depths below the volcano (see Appendix A).
2.5 Geodetic GPS time series
2.5.1 Data and processing
To assess the current deformation of Concepcion volcano’s edifice, dual-frequency GPS data
were collected at 6 different points on the volcano between 2001 and 2010. The first 2 sites (CON1
and COS1, Figure 2.1) were installed during a campaign in late 2001. Three more sites (COS2,
MOYO, and SABA) were installed during the 2008 campaign (Figure 2.1). A water well was con-
structed in late 2009 a few meters from the COS1 site. Because of the potential for displacements
associated with water pumping from the new well, in April 2010 a new GPS site (SINT, ∼2.5 km
northeast of COS1, Figure 2.1) was installed to replace COS1. A week of data were collected
18
W E
N
S
N S
W E
6505
00
1275550
Density contrast (kg/m3)
0 5 Km
0
Km-5
A
B
C
0
-3 km
Figure 2.3. 3-D inversion of the gravity data shown in Figure 2.2 using the GROWTH2.0 modeldeveloped by Camacho et al., (2011). The input parameters used in the modeling correspond to thefirst set of parameters summarized in Table 2.1. (A) Structural density map at 1 km depth (-1000 m)of Concepcion volcano and its surroundings. (B) East-West cross-section of structural density map.(C) North-South cross-section of structural density map.
simultaneously between the two sites to perform a tie and construct a common time series between
COS1 and SINT.
Data were collected in campaign mode (EGPS) in 2001, 2005, 2007, and nearly on an annual
basis since 2008. Unfortunately, the two receivers used during the 2007 campaign had problems
with firmware and provided results that are not reliable and with a large formal error in the mea-
sured position, a problem noted also for other sites where the instruments were utilized (H. Turner,
2007, personal communication). For completeness we present these data in the graph, but they are
not used in the analysis. During all campaigns the geodetic markers were observed by mounting
the antenna on fixed height spike mounts to reduce uncertainties in vertical displacement. All the
19
6.4
6.45
6.5
6.55
x 105
1.271.2721.2741.2761.2781.28
x 106
−2100
−2000
−1900
−1800
−1700
Easting (m)Northing (m)
Dep
th (
m)
x 106
set 1
set 3
set 2
VE: 2x1
VE: 15x1
N<
Figure 2.4. 3-D display of the location of the total anomalous center of masses obtained fromthe gravity data inversion using GROWTH2.0. VE stands for vertical exaggeration. The set labelsrefers to the set of parameters listed in Tables 2.1 and 2.2. The center of the total anomalous masses(solid circles, Table 2.1) are located to depth between -1700 and -2200 m, and almost directly belowthe volcano. The total anomalous mass is ∼1 x 1014 kg (Table 2.2), and the mass of the volcano is∼0.4 x 1014 kg (section 2.4.2), see text for details.
20
observations lasted at least 2 full UTC days to diminish the noise in the measured positions (in
particular for effects due to troposphere, tide, and signal multi-path). The success rate in collecting
the full day was significant and we made an effort to analyze only files with at least 20 hours of
continuous data collection. Every other epoch that for various reasons (e.g., power supply failure)
had fewer data was discarded.
All GPS data were processed to produce non-fiducial daily solutions with the Jet Propul-
sion Laboratory (JPL)’s software GIPSY-OASIS 6.1.2 using the standard precise point-positioning
(PPP) analysis strategy described by Zumberge et al., (1997) with non-fiducial orbits, clocks, and
Earth orientation parameters provided by JPL (ftp://sideshow.jpl.nasa.gov/pub/JPL GPS Prod-
ucts/Final/). To improve the PPP of each daily solution we resolved phase ambiguity using the
single receiver phase ambiguity resolution algorithm of Bertiger et al., (2010). The fiducial-free
daily solutions were transformed into the International Terrestrial Reference Frame 2008 (ITRF08,
Altamimi et al., (2011)) through a seven-parameter transformation using parameters provided by
JPL. The final product of the analysis consists of time series of the three components (E–W, N–S,
and up–down) of the daily position for each site with respect to the ITRF08 reference frame.
The horizontal components of the daily solutions of our GPS sites at Concepcion were de-
trended using the data from the Continuously Operating Reference Stations MANA, located in
Managua, Nicaragua (∼95 km away from our network). This step was not implemented for the
geodetic baseline computation as it does not require it. This approach will enhance the volcanic
signal by minimizing most tectonic effects. The MANA site is about the same distance from the
subduction trench as our network and is within the same tectonic block (Demets, 2001). The long
term velocity of the MANA site was computed by applying the same PPP analysis previously de-
scribed for EGPS sites to daily observations from the continuous site. To avoid co- and post- seis-
mic effects related to the October 2004 earthquake in the Nicaraguan part of the subduction zone,
only data after December 2006 were analyzed. Long term velocities of MANA in the North and
East direction with respect to ITRF08 were computed by linear fitting of the latitude and longitude
time series, respectively (9.5 ± 0.4 mm yr−1 for the north direction, and 7.8 ± 0.7 mm yr−1 for the
east direction, velocity uncertainties were computed using the Hackl et al., (2011) algorithm). We
21
used these velocities to detrend the Concepcion’s network time series (see supplemental material
provided in Appendix A for the resulting time series).
To better understand the deformation of the Concepcion volcano and to increase the signal to
noise ratio we mainly analyze the change in length of two baselines across the volcanic edifice.
The first baseline runs in a NW-SE direction on the northeastern side of the volcanic edifice and
connects the two oldest sites CON1 and SINT (after tying COS1 with SINT, Figure 2.1 and 2.5).
The mean length of the baseline is 5,915.765 m and has a time span of observations of 8.625 yr. The
time series for the CON1-SINT baseline length is presented in Figure 2.5. The second baseline runs
across the volcano along an East-West direction and connects the sites MOYO and SABA (Figure
2.1 and 2.6). The mean baseline length is 11,146.439 m and it covers 1.882 yr; this time series is
plotted in Figure 2.6. Both baselines cover time with unusual seismic activity near Concepcion
volcano as reported by INETER (INETER, 2002c; INETER, 2002b; INETER, 2002a; INETER,
2002e; INETER, 2002d; INETER, 2003b; INETER, 2005b; INETER, 2005a; INETER, 2008a)
and documented in the scientific literature by French et al., (2010). Such periods are indicated
by light-gray vertical bars in Figures 2.5, 2.6 and those in the supplemental material (Appendix
A). They also cover time of volcanic activity consisting of the emission of volcanic ash through
small to moderate explosions (VEI 6 2), which have been indicated by dark-gray vertical bars in
Figures 2.5, 2.6 and in the supplemental material. In particular the MOYO-SABA baseline time
series begins in mid August 2008 (Figure 2.6), 19 days after June 30 when a seismic event was
recorded at the Concepcion seismic station and the Civil Defense reported two ash explosions from
Concepcion volcano (INETER, 2008a).
2.5.2 GPS results
Table 2.3 presents the six stations’ coordinates we have observed around Concepcion volcano
as part of this study. We have subtracted from our GPS daily positions the effects of the surface
deformation (coseismic offsets) caused by the Mw 6.3 August 3, 2005 earthquake whose epicen-
ter was located about 10 km south of Maderas volcano. We used the fault geometry parameters
22
provided by French et al., (2010), and modeled as a rectangular dislocation embedded in a elastic
half-space (Okada, 1985). These results are shown in Table 2.3.
Overall, the two baselines do not suggest long-term permanent deformation, at least within the
detection limits of our data, described below. The maximum amplitude of baseline length change
is observed in the CON1-SINT baseline between 2001 and 2005 period (Figure 2.5B), which is of
about 40 mm. A weighted least-square line (weighted with regard to the error position) for this time
window, 37 days, gives a velocity of 81.89 ± 147.01 mm/yr (Figure 2.5B). In principle, this could
be compatible with episodic spreading of the volcanic edifice but it is very difficult to attribute
it to a particular phenomenon (or phenomena) due to the large temporal gap and the significant
seismic activity between the two GPS observation campaigns, and the July – September 2005 ash
explosions from Concepcion volcano. In addition to the large Mw 6.8 October 9 2004 subduction
earthquake that should not have affected our network, INETER (INETER, 2002c; INETER, 2002b;
INETER, 2002a; INETER, 2002e; INETER, 2002d; INETER, 2003b) documented seismic activity
at Concepcion between June and October 2002, and April and June through August 2003 consist-
ing of low-frequency volcanic tremor, and low magnitude earthquakes (i.e., ML ≤ 2.7, INETER,
2002a; INETER, 2003b). Furthermore, during the campaigns with longer period of observation
(CON1-SINT 2005 and 2010), the data contain large scatter, covering a range of deformation as
large as the 2001-2005 signal (Figure 2.5). During the 2005-2010 period, within the scattering of
the data the average length of the two baselines does not apparently change.
A similar situation was observed during the 2010 campaign when the volcano was erupting ash
and emitting gas from March (INETER, 2010a) through May of that year. It is interesting to note
that the only observations made during quite periods (2001 and 2009) seem to have a narrower
distribution of the observed baseline length (note that these observations also correspond to short
observations of only 2 full UTC days). A closer look at the data during the 2010 campaign (Figure
2.5C) indicates that the scattering of the data is not likely related to a purely stochastic processes,
but instead reveals a very high temporal correlation. The data show periods of high frequency
inflation- and deflation-like elastic deformation (∼30 mm in amplitude) in May 2010. A number of
possible processes can cause this type of deformation, including volcanic or hydrothermal activity,
23
Table 2.3. Concepcion volcano’s GPS stations’ coordinates in the WGS-84 reference ellipsoid.
Coseismic offsetsb
Site ID Latitude Longitude HAEa North East Vertical(◦N) (◦E) (m) (mm) (mm) (mm)
CON1 11.565 -85.625 261 -6.1 -4.7 -0.6COS1 11.514 -85.603 238 -7.5 -7.1 -0.9COS2 11.489 -85.649 58.4 3.6 -14.7 3.2MOYO 11.538 -85.689 105.9 3.0 -10.5 1.4SABA 11.548 -85.588 145.2 -12.4 -3.7 -2.3SINT 11.529 -85.585 162.2 -13.1 -4.5 -2.7
aHeight above reference ellipsoid.bOkada’s (1985) rectangular dislocation in an elastic half-space model was used to compute thesurface displacements. Fault geometry parameters were those from French et al., (2010), namely:epicenter Lat. = 11.34◦ N, epicenter Lon. = -85.50◦ E, fault centroid depth = 12 km, strike =60◦, dip = 90◦, fault length = 16 km, fault width = 10 km, and slip = 0.9 m.
shrink and swell of the material below the GPS sites, and accumulation of volcanic ash on the
antenna. We note that the volcano was erupting ash and gas during March through May in 2010,
and so suggests that this deformation signal is directly related to volcanic activity. This non-
permanent deformation is significantly larger than the maximum deformation observed during the
full study period and can lead to large changes in baseline length in the span of a few days. For this
time period between late January and late July 2010, 182 days, a velocity of 5.54 ± 5.54 mm/yr
is obtained from a weighted least-square straight line fitting. While for the whole CON1-SINT
baseline change time series, 8.6 yr from December 2001 to July 2010, the rate of change of this
baseline is of 3.34 ± 0.81 mm/yr.
The time series of baseline change between MOYO and SABA stations (Figure 2.6) forms
almost a E-W oriented baseline across the volcano (Figure 2.1, and inset in Figure 2.6). This time
series begins in mid August, 2008, 19 days after a seismic event was recorded on the Concepcion’s
seismic station, and Civil Defense reported two ash explosions from Concepcion volcano the same
day, on July 30 (INETER, 2008a). The scatter of the data seems to be less in periods with no
volcanic activity. This baseline shows an amplitude of almost 15 mm (a rate of change of -0.48 +-
0.48 mm/yr is estimated by fitting a least-square straight line, Figure 2.6), which is about a half of
the amplitude of the change observed in the CON1-SINT baseline. MOYO station is about twice
24
−40
−30
−20
−10010203040
Changeinbaselinelength(mm)
−40
−30
−20
−10010203040
Changeinbaselinelength(mm)
JAN
02JA
N03
JAN
04JA
N05
JAN
06JA
N07
JAN
08JA
N09
JAN
10
JAN
02JA
N03
JAN
04JA
N05
JAN
06JA
N07
JAN
08JA
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JAN
10
velo
city
= 3
.34
+−
0.8
1 m
m/y
r
−40
−35
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−15
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Changeinbaselinelength(mm)
−40
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317
1421
284
Aug
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Changeinbaselinelength(mm)
JAN
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)
OCT 08 JAN 09 APR 09 JUL 09 OCT 09 JAN 10 APR 10 JUL 10
OCT 08 JAN 09 APR 09 JUL 09 OCT 09 JAN 10 APR 10 JUL 10
velocity = −0.48 +− 0.48 mm/yr
MOYO-SABA
"
"
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"
"
640000
640000
650000
650000
1270000
1280000
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0 1 2 3 4 5 Km
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____
>
MOYO
SABA
Figure 2.6. MOYO-SABA baseline change running W-NE across the volcano. Light-gray verticalbars indicate periods of unusual seismic activity on Concepcion volcano and/or near OmetepeIsland, while dark-gray vertical bars represent periods of volcanic activity characterized by ash andgas explosions. Inset shows the location of MOYO and SABA sites. The rate of change (velocity)of this baseline was estimated by a weighted least-square fitting.
as far from the volcano than the other stations involved (Figure 2.1 and 2.6) leading to a baseline
length twice longer than CON1-SINT baseline. Because we do not have baselines among other
station-pairs, we cannot investigate whether the amplitude of the variations in baselines are also
related to the distance from the volcano, or if it is simply a casual relationship. We did not compute
baselines among other GPS station-pairs because the overlapping observation time were too short.
The change with regard to the first measurement in all components for each of the five GPS sites
around Concepcion volcano are included in Appendix A. The CON1 site shows the largest scatter
during August 2005 and March–July campaigns in 2010, which were periods of comparatively
intense seismic activity and volcanic ash eruption, and is the same pattern shown by the change in
baseline from CON1 to SINT described above.
2.6 Discussion and Conclusions
New gravity data collected at Concepcion volcano allow us to estimate the bulk density of
the volcanic edifice to be 1764 ± 111 kg m−3. This value is significantly lower than densities
26
of 2500 – 2700 kg m−3, previously assumed in spreading models for this volcano (van Wyk de
Vries and Borgia, 1996; van Wyk de Vries and Matela, 1998; Borgia et al., 2000; Borgia and
van Wyk de Vries, 2003). A higher density favors gravitational spreading because the volcano
will represent a bigger load resting upon weak lake sediments. Conversely, a lower density means
less potential energy is available to deform and to induce flow of the substratum, and produce
induced-gravitational spreading of the volcanic edifice. Geodetic GPS data do not show evidence
of continuous spreading of the volcano over the time period of our observations. Nonetheless,
because the density of a volcano is not the only factor controlling spreading (proper stress field
condition, thickness and viscosity of the underlying substratum, magmatic intrusions, etc., see
e.g., van Wyk de Vries and Matela, (1998), also play an important role), we do not rule out the
occurrence of volcano spreading at Concepcion as an episodic or transient event possibly driven by
magma intrusion, as already suggested by Borgia and van Wyk de Vries, (2003), or by the interplay
with other factors such as regional and/or local seismicity.
Our longest time series baseline change that spans 8.6 yr, oriented NW-SE on the NE side of
the volcano (Figure 2.5), indicates a rate of change of 3.34± 0.81 mm/yr. While the rate of change
of the baseline across the volcano in an E–W orientation shows a rate of change of -0.48 ± 0.48
mm/yr in 1.9 yr (Figure 2.6). This, together with the results described in the previous section,
suggests that the factors driven the baseline changes at Concepcion may be of different magnitude
at different locations. On the other hand, the non-corrected for the August 3, 2005 coseismic
offsets CON1-SINT baseline change between 2001 and 2010 (8.6 yr) has a rate of change of 3.01
± 0.82 mm/yr, which is slightly lower than the corrected version. This opens the possibility that
surface deformation induced by fault activity may be one of the factors influencing to the long-term
increase of the CON1-SINT baseline length. Could aseismic slip on nearby faults to Concepcion
volcano have contributed to the increase in baseline length of CON1-SINT between 2001 and
2005 (Figure 2.5) that eventually ruptured on August 3, 2005 (main shock of Mw 6.3)? A more
dense spatial coverage of surface deformation measurement devices are required to investigate this
hypothesis further.
27
The deformation (tilting and faulting) of the deposits from the Tierra Blanca destructive phase,
and younger deposits inclusive, mapped by van Wyk de Vries, (1993) and Borgia and van Wyk
de Vries, (2003) opens the possibility that volcano spreading was at work at some time since that
eruption. In a recent study based on experimental modeling, Galland, (2012) demonstrates that the
complex pattern of surface deformation and its evolution in volcanic areas are strongly related with
the shape of the intrusion and its subsequent evolution. Concepcion volcano lies next to a shear
zone (the boundary of the Central American forearc sliver with the relatively stable Caribbean
plate (Demets, 2001; Turner et al., 2007; La Femina et al., 2009)), and other fault zones within
Lake Nicaragua (Funk et al., 2009). In addition, the gravity map, the relationships between in-
trusions and surface deformation reproduced by Galland, (2012), and the volcanic activity from
Concepcion (indicating the presence of magma bodies below the volcano), all indicate the possi-
bility that the deformation of the recent and older deposits from Concepcion may not necessarily be
related to spreading of the volcano, but rather to a complex interplay of volcano-tectonic processes
and features.
The gravity data also provide new information about the structure of the volcano, revealing
two distinct lithologies within the edifice, which we infer represents a change to a dominantly
low-energy pyroclastic activity during the rapid reconstruction phase following the Tierra Blanca
eruption, which corresponds to the second building phase of the volcano according to Borgia and
van Wyk de Vries, (2003). Instead of a spreading-related thrust anticline, as pointed out by Del-
camp et al., (2008), we infer that the linear residual gravity anomaly trending ∼N40◦W (Figure
2.2) on the northeastern side of the volcano is associated with a regional normal fault with its
down-thrown block on the NE, partially buried by volcanic products, and whose northernmost end
was mapped by van Wyk de Vries, (1993). If this is the case, this fault is associated with the
135◦–striking dextral transtensional fault zone below Maderas volcano described by Mathieu et al.,
(2011). This fault must be taken into account in the seismic hazard assessments of the Ometepe
Island and should be monitor to see if it presents any current activity. This fault may also have a
component of right-lateral strike-slip displacement produced by the accommodation of the oblique
convergence at the subduction zone in Nicaragua, similar to those found and described by Funk
28
et al., (2009), and possibly is a manifestation of tectonic escape, a product of the collision of the
Cocos Ridge in central Costa Rica (La Femina et al., 2009). Further research on both volcanoes
may help differentiate between these models and better delineate the fault zone.
The low gravity anomalies found in the southwestern side of our study area (Figure 2.2) have
a more complicated geometry that cannot be clearly discerned by our gravity survey due to our
relatively low resolution sampling coverage in that area. However, surface faulting and structural
discontinuities mapped within this area by van Wyk de Vries (1993); and Borgia and van Wyk de
Vries, (2003) are to a great extent correlated with the gravity anomalies. There is the possibility that
these anomalies may be an extension of the SRFZ and/or JMFZ (Figure 2.1; (Funk et al., 2009)).
Both gravity data (this study) and geologic mapping (previous studies) show that the southwestern
side of Concepcion volcano (Moyogalpa, Esquipulas, and Los Angeles, Figures 2.1 and 2.2) is
the locality of small-scale complex structural features (e.g. local/regional faulting). More detailed
geophysical study is required to elucidate the nature of these features, and thus estimate the hazard
they represent to the people living in the island.
On the other hand, 3-D inversion of the gravity data seems to corroborate the statement that the
upper part of the volcano is composed of lighter material than the rest of the volcano edifice, Figures
2.2 and 2.3. This inversion also supports the existence of a possible fault on the NE side of the
volcano, which is reflected in the residual gravity anomaly described in section 2.4.3. The inversion
of the gravity anomaly yields a total cumulative anomalous mass of ∼1 x 1014 kg whose center of
mass is located around 2 km below the volcano, while the volcano edifice has an estimated mass of
∼0.4 x 1014 kg, using a bulk average density of 1764 kg m−3. The volcano’s mass represents ∼40
% of the total cumulative anomalous mass, indicating that most of the anomalous mass is concealed
below the volcano.
When the GPS network was observed more regularly, as in 2005 and 2010, the volcanic edifice
undergoes significant high-frequency recoverable deformation (and possibly noise in the signal is
also affecting the measurements) that can lead to changes of the baselines up to 3 cm within a few
days. This non-permanent high-frequency signal poses a significant problem in the evaluation of
the long-term deformation of the volcano using episodic observations, as misleading interpretations
29
may result from samples collected for a short time and at large intervals. In our case, the amplitude
of the high-frequency signal is comparable, if not larger than, the largest deformation measured,
indicating that the trend observed between 2001 and 2005 may reflect poor temporal resolution. It
is clear that to fully understand the deformation of the volcanic edifice will be achieved only by
deploying permanent or semi-permanent observation stations.
Borgia and van Wyk de Vries, (2003) carried out two GPS campaigns with dual-frequency in-
struments, the first one in November 1994 and the second in May 1997. Their network consisted of
20 stations spaced between 2 and 5 km apart, and were located around the volcano’s base and half-
way up the cone. A central station was used to measure the displacements of all other points. For
baselines shorter than 10 km they used a “rapid static technique”, rather than a “static technique”,
which is the technique that yields the highest accuracy (Dzurisin, 2007) and is the one we have used
in our study. In general, the rapid static technique produces data uncertainty on the order of three
times the error of static methods (Dzurisin, 2007), or approximately 1.5–2 cm on Ometepe Island.
Nevertheless, Borgia and van Wyk de Vries, (2003) interpret their results, especially the pattern of
deformation, to be consistent with radial spreading of the volcano. However, this interpretation is
complicated by several factors, including the data collection methods used, the possibility of base
station motion during their survey, and the nature of high frequency movement we identify in our
data sets. The 2001–2010 time series of baseline length indicate possible permanent change in
baseline length over this total period of < 40 mm, or approximately 4 mm per year, a value similar
to or less than short term recoverable (non-permanent) changes in baseline length. For example,
short term recoverable deformation of 30 mm is observed in the time series in May, 2010 (Figure
2.5).
Based on the characteristic behavior shown by Concepcion volcano and herein described, we
believe that Concepcion is predominantly an open vent volcano with a shallow magmatic reservoir,
and whose upper conduit is eventually over-pressurized leading to small to moderate (VEI 1-2)
ash and gas explosions. This is reflected in the relatively small amplitude variations in the GPS
baselines, the short term recoverable deformation.
30
In conclusion, based on our observations we consider that Concepcion volcano is composed of
two distinct lithologies (a low density upper cone surrounded by a denser structure that is perhaps
the remnant of violent past eruptions), has a bulk density of 1764±111 kg m−3 and is not currently
undergoing continuous gravitational spreading. A baseline oriented E-W across the volcano shows
a zero length variation during almost 2 yr period of observations with episodic GPS campaigns
style. Spreading is perhaps taking place in a different orientation across the volcano in an episodic
fashion and is non-permanent, driven by factors other than gravitational loading (e.g., magmatic
intrusion), although surface deformation induced by fault slip (and possibly strain accumulation by
aseismic fault slip) may be influencing the increase in a baseline oriented NW-SE on the NE side
of the volcano, which presents a rate of change of ∼3.34 +- 0.81 mm/yr during 8.6 yr of episodic
GPS observations.
31
CHAPTER 3
RELATIVELY SHORT-TERM CORRELATION AMONG DEFORMATION,DEGASSING AND SEISMICITY : A CASE STUDY FROM CONCEPCION VOLCANO,
NICARAGUA
3.1 Introduction
During volcanic activity of 2010, surface deformation around Concepcion volcano, Nicaragua,
was characterized by semi-periodic changes in baseline lengths measured across the volcano of up
to∼4 cm with period of several days to weeks. Modeling the source of this deformation may lead to
improved understanding of how conduit processes govern eruption frequency and intensity in open
magma systems, like Concepcion (e.g., van Wyk de Vries, 1993; Borgia and van Wyk de Vries,
2003; Saballos et al., 2013). Insight into the form of this model can be gained by cross-correlating
time series of GPS measurements, real-time seismic amplitude measurements (RSAM), and SO2
flux data.
Joint interpretation of surface deformation, SO2 flux, and seismic data for periods of weeks
to months provide a more integral view of volcanic processes than the analysis of any single data
set (Casadevall et al., 1981; McGee and Sutton, 1994; Voight et al., 1999; Watson et al., 2000;
Williams-Jones et al., 2001; Olmos et al., 2007). With new advances in instrumentation, it has
become routine to gather multi-variable measurements at high sampling rates (up to 1 Hz), allow-
ing the study of short-term variations (seconds to hours) of the dynamics of magmatic systems
associated with individual eruptions or episodes of volcano unrest (Fischer et al., 2002; Gotts-
mann et al., 2007; Dalton et al., 2010; Kazahaya et al., 2011; Nadeau et al., 2011; Ichihara et al.,
2012). In this study we show that the comparison of daily observations of GPS geodetic measure-
ments, RSAM, and SO2 flux of intermediate length (∼2 mo sampling period during 2010) also
exhibit highly correlated behavior during one eruptive period at Concepcion volcano. In contrast,
32
during a non-eruptive period (∼2.5 mo sampling period during 2011) of this volcano, significant
cross-correlations among these variables are not present. Thus, we suggest that these features
provide important insights into volcanic processes on timescales of days to weeks during unrest
at Concepcion volcano, and develop our model to attempt to explain magma movement on these
timescales.
We also note that changes in baseline length, RSAM, and SO2 flux were not of particularly large
magnitude during the eruptive phase compared to the non-eruptive phase. That is, although anoma-
lous behavior is observed in all three times series during the eruption, these anomalies become most
clear by comparing the time series. This result is perhaps not surprising for an open-vent volcano.
However, this observation reinforces the idea that a continuous monitoring program of several geo-
physical time series, and near-realtime cross-correlation of these time series, might improve future
responses to eruptive crises at Concepcion.
3.2 Concepcion volcano
Concepcion is currently the most active composite volcano in Nicaragua, and is predominantly
composed of clinopyroxene–plagioclase bearing andesite rocks (McBirney and Williams, 1965;
van Wyk de Vries, 1993; Borgia and van Wyk de Vries, 2003). During the last four decades
volcanic activity at Concepcion has been characterized by small to moderate explosions (VEI 1-2)
of tephra and gas (van Wyk de Vries, 1993; Borgia and van Wyk de Vries, 2003; Siebert et al.,
2011). We note, however, that eruptive activity at Concepcion has not always been so mild. Plinian
and sub-Plinian tephra fallout deposits are found in the late Pleistocene and Holocene stratigraphic
record (McBirney and Williams, 1965; Borgia and van Wyk de Vries, 2003; Kutterolf at al., 2008).
Furthermore, past effusive eruptive activity has produced voluminous flank lava flows. The greatest
concern for a large eruption of Concepcion lies in the effective evacuation of the island’s ∼31,000
inhabitants (INIFOM, 2001). In addition to hazards directly related to the volcanic activity, hazards
associated with the remobilization of tephra fallout as lahars during subsequent rainfall are of
great concern. These lahars, although small in volume, have damaged infrastructure and inundated
agricultural areas (INETER, 2008b).
33
3.2.1 2010 eruption
According to reports from the Instituto Nicaraguense de Estudios Territoriales (INETER), on
March 7, 2010 a new eruptive phase began that consisted of ash- and gas-laden explosions that rose
up to 1 km above the crater (INETER, 2010b). From March 8 to March 17, INETER personnel
observed and counted the number of visible ash and gas explosions that occurred during daylight.
They registered an average of 30 explosions/day, with a minimum of 14 explosions/day on March
8, and a maximum of 43 explosions/day on March 13 (INETER, 2010b). Fewer daily explosions
were observed through March 24, then explosions became much more sporadic and the volcano
was less regularly observed (INETER, 2010b). The Washington Volcanic Ash Advisory Center
issued five reports of volcanic ash from Concepcion volcano detected by satellite. Two reports
were issued on March 8 followed by single reports on March 9, March 12, and March 13, 2010
(http://www.ssd.noaa.gov/VAAC/ARCH10/archive. html#CONC).
Reports from INETER mention that ash explosions continued until mid–April (INETER, 2010a),
and island residents reported eruptive activity until mid-May, 2010. We observed low intensity
(VEI 1) explosions during April 1 and 15 that deposited a very fine ash layer (< 1 mm thick) on the
volcano’s WSW flank and in nearby communities. In general, during this period eruptions were
characterized by an initial explosion, quickly followed by two or three additional explosions of
smaller intensity at irregular time intervals. At the time of writing (March 2013) no new unrest
have been reported from Concepcion volcano since mid–May, 2010.
Average seismic tremor frequency at Concepcion rose from a background of 0.5 Hz before
March 7 2010 to an average frequency of ∼3 Hz in the following two weeks. RSAM maximum
daily average, 94, occurred on March 20 (INETER, 2010b). During the same period, INETER
staff made mobile SO2 measurements with a Differential Optical Absorption Spectrometer, DOAS
(e.g., Galle et al., 2003), along the main road on the N and W side of Concepcion volcano obtaining
SO2 daily fluxes averages on March 9, and 13 to 15 of 133, 91, 507 and 127 tons/day, respectively
(INETER, 2010b).
34
3.3 Data collection and analysis
3.3.1 Geodetic GPS data
We collected dual-frequency GPS data at two sites simultaneously during April 8 – June 25
2010, and February 4 – April 16 2011. These sites are located on the northern (CON1) and
southeastern (SINT) flanks of Concepcion volcano. Data collected at these two sites were used
to compute a daily geodetic baseline across the northeastern side of the volcano (Figure 3.1).
GPS data were processed to produce non-fiducial daily solutions with the Jet Propulsion Lab-
oratory (JPL)’s software GIPSY-OASIS 6.1.2 using the standard precise point-positioning (PPP)
analysis strategy described by Zumberge et al., (1997) with non-fiducial orbits, clocks, and Earth
orientation parameters provided by JPL (ftp://sideshow.jpl. nasa.gov / pub/JPL GPS Products /Fi-
nal/) and FES2004 ocean loading (http://froste.oso. chalmers.se /loading/ /index.html). Ambiguity
resolution was solved using the single receiver phase ambiguity resolution algorithm of Bertiger
et al., (2010). The fiducial-free daily solutions were transformed into the International Terrestrial
Reference Frame 2008 (ITRF08, Altamimi et al., (2011)) through a seven-parameter transforma-
tion using parameters provided by JPL. The final product of the analysis consists of time series of
the three components (E–W, N–S, and up–down) of the daily position for each site with respect
to the ITRF08 reference frame. Daily baseline length computation between CON1 and SINT sites
(Figure 3.2) were also performed with the GIPSY-OASIS software. During the full period, the
average distance of the two sites was 5,915.765 m with a daily formal error of the order of 3 mm.
3.3.2 Real–time seismic amplitude data
RSAM data were collected using a broadband seismometer co-located with the CON1 GPS
site. RSAM counts consist of the average of the absolute seismic signal’s amplitude calculated
at a ten minute interval (Endo and Murray, 1991), which we averaged over a 24 hr interval to get
RSAM daily counts. In early 2011, a new seismic instrument was set up with a different gain
setting at CON1 site (V. Tenorio, personal communication, 2011) producing a background level
reading about ten times larger than the 2010 counts. To better compare the RSAM 2010 and 2011
35
"
"!
!
648000
656000
656000
12
72
00
0
12
72
00
0
12
76
00
0
12
76
00
0
12
80
00
0
0 5Km
Jap ón
CON1
SINT
M or r o
N
270˚ 272˚ 274˚ 276˚ 278˚ 280˚6˚
8˚
10˚
12˚
14˚
0 500
km
Nicarag
ua
CostaRica
Volcán Concepción
X
Figure 3.1. Shaded relief map of Concepcion volcano. Black squares depict the location of thedual-frequency GPS sites. The white “X” on the black square at CON1 shows the location of theonly continuously operating seismic station at Concepcion. White circles show the location of theSO2 mini-DOAS instruments. Inset : Regional location map of Concepcion volcano, Nicaragua,in Central America. Black triangles show the location of major Quaternary volcanoes along theCentral America volcanic front.
36
time series we divided the most recent RSAM counts by ten. This step does not affect the cross-
correlation of the RSAM data with the other variables in any way.
3.3.3 Remotely-sensed SO2 data
SO2 measurements were made by the Differential Optical Absorption Spectroscopy, DOAS,
technique (Platt and Stutz, 2008) using ground–fixed instruments developed under the Network
for Observation of Volcanic and Atmospheric Change, NOVAC, project (Galle et al., 2010). One
mini-DOAS instrument was installed in late April 2010 at a site ∼6 km southwest of the volcano’s
crater (Japon, Figure 3.1). A second instrument was installed in March 2011 ∼2.5 km west of the
volcano’s crater (Morro, Figure 3.1). The volcanic plume is scanned using a rotating mirror that
redirects the light to a telescope with a focal length of 75 mm, which couples the transmitted light
with two 16 mm optical fibers. The stray light is reduced using a Hoya U330 optical filter mounted
on the telescopes. The optical fibers transfer the light to an Ocean Optics S2000 spectrometer. The
rotation is made by a stepper motor with a resolution of 3.6 degree/step and covers 180 degrees
along the horizon (Galle et al., 2010). The plume direction is calculated by analyzing the scan and
determining the angle that corresponds to the center of mass of the plume. Given the characteristics
of the plume from Concepcion (it predominantly bends over after leaving the volcano’s crater), the
plume height is assumed to be the same as the volcano’s height (1600 m a.s.l). The plume speed is
assumed to be the same as the wind speed at the plume height, and was obtained from the Global
Forecast System models data from the National Ocean and Atmospheric Administration. The mini-
DOAS instruments run during daylight; typically from 6: 00 to 18: 00 local time (GMT-6, thus
within a single 24-hr GPS day). The maximum number of measurements within a day were 35,
with a daily average of 5.
To be consistent with the temporal resolution of GPS data, we averaged the observations to
daily fluxes. The SO2 data were post-processed using the algorithm described by Platt and Stutz,
(2008). We computed the percentage by which the standard deviation of the total measurements,
carried out during a single day, corresponded to the average value of those measurements. We
found that the standard deviation was around 34% of the daily average observed value (error bars
37
for SO2 time series in Figure 3.2). In nearly all cases, uncertainties estimated for a single SO2
measurement are smaller than 50% and greatest uncertainty is associated with change in weather
conditions during the day.
3.3.4 Data gaps
In order to compute cross-correlation and periodograms, gaps in the data, days on which no
measurements were obtained, were filled using the nearest neighbor, cubic splines, or piecewise
cubic Hermite interpolation methods, depending on which interpolation method produced the clos-
est variance to the original data set. For the 2010 period, there are no GPS data gaps. In 2011 there
were five missing days (February 16, March 13, March 31, April 3, and April 13, open circles in
Figure 3.2) mainly related to missing GPS epochs in the daily data file due to power supply failure.
RSAM time series contain three missing days in 2010 (April 11, and May 10 and 11), and none
in 2011. Gaps in the RSAM data were mainly related to problems with the telemetry system (V.
Tenorio, personal communication, 2011). 2010 SO2 data have gaps on April 30, and May 1, 8, 9,
and 24 to 26. One daily gap occurred in 2011 (April 7). Gaps in the SO2 data were due to failure to
detect the gas plume (i.e., clouds between the instruments and the volcanic plume were too dense)
and/or to failure of the automatic instruments to resolve the plume geometry, a required parameter
to compute the SO2 flux. During 2010, only one mini-DOAS instrument was in operation, whereas
two were during 2011. This fact accounts for the larger number of missing days in the SO2 data
during 2010, as opposed to only one missing day in the time series in 2011.
3.4 Results
Three time series corresponding to each data type were correlated for GPS baseline, RSAM,
and SO2 flux during 2010 (April 8 through June 25 for GPS and RSAM cross-correlation, and April
28 through June 24 for SO2 with the GPS and RSAM data sets, Figure 3.2) and 2011 (February 4
through April 16). Time series for 2010 period were collected during the final phase of eruptive
activity.
38
For 2010, the change in GPS geodetic baseline length between CON1 and SINT sites (Fig-
ure 3.1) has a total amplitude variation of 29 mm (-16 to 13 mm). This variation appears to be
time-correlated and occurs progressively over periods of days to weeks, resulting in the broad fluc-
tuations about the mean baseline length (0 mm, Figure 3.2A). The maximum GPS baseline change
took place on May 14, 2010 four days after island residents reported an explosion, the last ex-
plosion reported during the 2010 activity. On May 16 the baseline length returned to its average
value, as does the RSAM (71 RSAM units), while the SO2 was slightly above its mean value (266
tons/day; Figure 3.2A). The pattern of variation of GPS and RSAM are very similar with a sharp
increase between May 5 and 14, and a sharp decrease in the GPS data between May 24 and 31,
2010 and a coeval increase in the RSAM signal (Figure 3.2A). The SO2 emissions began to in-
crease on May 5 to reach its maximum (643 tons/day, or 7.44 kg/s) on May 10, the day of the last
reported explosion, then fall to background levels (∼200 tons/day) around May 17. Anomalously
high values for change in baseline length, RSAM, and SO2 emissions occur within a time window
between May 5 and 14 and are nearly in phase.
May 24 – 27, 2010, the GPS baseline contracts, then returns to average length by May 31
(Figure 3.2A). RSAM is elevated during this period, while the SO2 emissions remained at near
average values (Figure 3.2A).
Overall, the daily average of SO2 flux appears to correlate positively with positive changes in
GPS baseline length. Fluxes larger than 300 tons/day correspond all to positive changes (extension)
in GPS baseline (Figure 3.2A). A similar pattern is revealed by comparing SO2 and RSAM in that
all SO2 fluxes >300 tons/day occur when daily RSAM values were >77 units.
These relationships between SO2 and GPS, and SO2 and RSAM are not present in the 2011
time series data (Figure 3.2B). The amplitude in GPS baseline change in 2011 was 18 mm (-12 to
6 mm), which is 11 mm less than the 2010 counterpart (Figure 3.2A) and is characterized by ran-
dom variation about the mean, as opposed to the smoother variations observed during anomalous
episodes in 2010. In a similar way, the RSAM data collected in 2011 are characterized by random
variation about the mean. During the 2011 time series, the maximum daily average of SO2 fluxes
39
ME
PM
CP
0
100
200
300
400
500
600
700
800
SO2 (tons/day)
811
1518
2225
292
69
1316
2023
2730
36
1013
1720
24
020406080100
RSAM daily average
−25
−20
−15
−10−
5051015
GPS baseline change (mm)
811
1518
2225
292
69
1316
2023
2730
36
1013
1720
24A
pril
2010
May
201
0
Jun
201
0
Apr
il 20
10
M
ay 2
010
J
un 2
010
Feb
ruar
y 20
11
M
arch
201
1
Apr
il 20
11
Feb
ruar
y 20
11
M
arch
201
1
Apr
il 20
11
AB
0
100
200
300
400
500
600
700
800
SO2 (tons/day)
47
1114
1821
2528
47
1114
1821
2528
14
811
15
020406080100
RSAM daily average
−25
−20
−15
−10−
5051015
GPS baseline change (mm)
47
1114
1821
2528
47
1114
1821
2528
14
811
15
Figu
re3.
2.Ti
me
seri
esof
the
2010
and
2011
data
used
inth
isst
udy.
ME
Pst
ands
for
maj
orex
tens
ion
phas
ein
the
GPS
sign
al,w
hile
MC
Pm
ajor
cont
ract
ion
phas
esh
own
inth
eG
PSda
ta.
Clo
sed
circ
les
repr
esen
tob
serv
edda
ta,
whi
leop
enci
rcle
sin
terp
olat
edda
ta,
see
text
for
expl
anat
ion.
GPS
base
line
daily
chan
ges
with
rega
rdto
the
first
day
onth
etim
ese
ries
.E
rror
bars
refle
ctfo
rmal
erro
rco
mpu
ted
for
afu
llob
serv
atio
nda
yco
mpo
sed
ofm
easu
rem
ents
ever
y30
seco
nds.
RSA
Mda
ilyav
erag
eof
mea
sure
men
tsev
ery
10m
inut
es.
SO2
daily
fluxe
s.E
rror
bars
repr
esen
t34%
unce
rtai
nty
ofth
eob
serv
edva
lue
fora
full
day
com
pose
dof
vary
ing
num
bero
fmea
sure
men
ts,5
perd
ayin
aver
age,
and
upto
35m
easu
rem
ents
max
imum
.(A
)20
10pe
riod
whe
nth
evo
lcan
ow
asin
itsm
ostr
ecen
teru
ptiv
eph
ase
that
begu
non
Mar
ch7
and
exte
nded
upto
arou
ndth
een
dof
May
.(B
)The
2011
data
corr
espo
nda
peri
odw
hen
the
volc
ano
was
note
rupt
ing.
40
is 52% smaller (maximum daily flux was 309 tons/day, or 3.58 kg/s, Figure 3.2B), about 50% less
than the maximum observed values during eruptive activity in 2010.
Additional structure in the time series is revealed by computing their periodograms (Figures
3.3A-C). Significant autocorrelation exists in all three times series collected during the eruptive
episode in 2010. The relatively broad spectrum of each series confirms our qualitative interpre-
tation that signal is found in the time series during the eruptive period, characterized by autocor-
relation on timescales of 3 – 10 days, roughly, based on the decay observed in the amplitude of
the periodograms at longer periods. In contrast, the periodograms for 2011 time series collected
during a non-eruptive period are structureless; these periodograms are characterized by uniformity
low amplitudes at each period. That is, during the 2010 eruption, variation in GPS baseline length,
RSAM and SO2 emissions contained trends over time that persisted for several days to about one
week, whereas in 2011 the times series did not contain these trends.
Cross-correlograms provide further insight into the structure of the time series during the 2010
eruption and the 2011 non-eruptive period. The 2010 time series are characterized by correlation
coefficients that are significantly different from zero (Figures 3.4A, C, E), whereas the 2011 non-
eruptive period show poor or no correlation, except at lags 0 and 1 (Figures 3.4B,D, F). That is, for
time series collected during the non-eruptive period in 2011, there is a slight correlation between
GPS baseline and RSAM on any given day, for example, but this correlation does not extend to
subsequent days. During the 2010 eruptive period, significant cross-correlation persists to lags of
about ±5 days.
The largest correlation coefficients are observed between 2010 GPS baseline and SO2 emission
at lag -3 days (Figure 3.4C) and SO2 emission and RSAM at lag zero days (Figure 3.4E). The
maximum correlation coefficient at -3 days suggests that GPS baseline changes have a tendency
to lead changes in SO2 emission during the 2010 eruptive period, although this tendency is quite
subtle and may not be significant.
41
2 3 4 5 6 7 8 9 10 11 12 13 14 150
50
100
150
Period (days)
|Pow
er s
pect
ral d
ensi
ty|
GPS data, 2010
GPS data, 2011
2 3 4 5 6 7 8 9 10 11 12 13 14 150
200
400
600
|Pow
er s
pect
ral d
ensi
ty|
RSAM data, 2010
RSAM data, 2011
2 3 4 5 6 7 8 9 10 11 12 13 14 150
1
2
3
4
x 104
Period (days)
|Pow
er s
pect
ral d
ensi
ty|
SO2
data, 2010
SO2
data, 2011
A
B
C
Figure 3.3. Periodograms. All data sets were linearly detrended before computing their peri-odograms, and then were smoothed by a Hanning window (e.g., Chatfield, 1996). (A) The 2010GPS time series has significant autocorrelation with maximum at about 5-day period. (B) The 2010RSAM data and (C) The 2010 SO2 reveal similar broad autocorrelation with maxima between 5and 7 days. The periodograms of the 2011 data sets uniformity low amplitude power spectra com-pared to their 2010 counterparts, thus they do not have any meaningful autocorrelation and are bestcharacterized by random fluctuation around mean values.
42
−20
−15
−10
−50
510
1520
−0.7
−0.5
−0.3
−0.1
0.1
0.3
0.5
0.7
Lag(days)
Cross−Correlationcoeff.
GPSvsRSAM
−20
−15
−10
−50
510
1520
−0.7
−0.5
−0.3
−0.1
0.1
0.3
0.5
0.7
Lag(days)
Cross−Correlationcoeff.
GPSvsSO2
−20
−15
−10
−50
510
1520
−0.7
−0.5
−0.3
−0.1
0.1
0.3
0.5
0.7
Lag(days)
Cross−Correlationcoeff.
SO2vsRSAM
−20
−15
−10
−50
510
1520
−0.7
−0.5
−0.3
−0.1
0.1
0.3
0.5
0.7
Lag(days)
GPSvsRSAM
−20
−15
−10
−50
510
1520
−0.7
−0.5
−0.3
−0.1
0.1
0.3
0.5
0.7
Lag(days)
GPSvsSO2
−20
−15
−10
−50
510
1520
−0.7
−0.5
−0.3
−0.1
0.1
0.3
0.5
0.7
Lag(days)
SO2vsRSAM
AB
CD
EF
Figu
re3.
4.C
ross
-Cor
relo
gram
sam
ong
allt
ime
seri
es.
Das
hed
hori
zont
algr
aylin
esre
pres
entt
he95
%co
nfide
nce
inte
rval
,abo
veor
belo
ww
hich
the
corr
elat
ion
isst
atis
tical
lysi
gnifi
cant
(±2/√
N,w
here
Nis
the
num
ber
ofob
serv
edpo
ints
).A
llin
divi
dual
data
sets
wer
elin
earl
yde
tren
ded
befo
reth
eyw
ere
cros
s-co
rrel
ated
.(a)
Cro
ss-c
orre
logr
ambe
twee
nth
eG
PSan
dR
SAM
data
for2
010.
Posi
tive
corr
elat
ion
atpo
sitiv
ela
gsm
eans
RSA
Mle
ads
GPS
base
line
chan
ges;
posi
tive
corr
elat
ion
atne
gativ
ela
gsm
eans
GPS
base
line
lead
sR
SAM
chan
ges.
(b)
Cro
ss-
corr
elog
ram
betw
een
the
GPS
and
RSA
Mda
tafo
r20
11;
(c)
CG
PSan
dSO
2da
tafo
r20
10;
(d)
GPS
and
SO2
data
for
2011
;(e
)SO
2an
dR
SAM
data
for2
010;
(f)S
O2
and
RSA
Mda
tafo
r201
1.
43
3.5 Modeling
We have shown that during the 2010 eruptive phase of Concepcion volcano, March to May
2010, the GPS baseline lengthens when the volcano was erupting ash and gases, and contracts when
the explosions ceased, Figure 3.2A. These changes in GPS baseline length were accompanied by
subtle but significant changes in RSAM and SO2 emission. An important feature of the observed
change in GPS baseline is that the average change returns to zero after these short-term (a few
days long) extension and contraction phases, implying that the volcano experienced a recoverable
deformation. Thus, GPS baseline extension represents inflation of the volcano edifice (May 5 –
13, 2010; Figure 3.2), and baseline contraction represents deflation (May 23 – 29, 2010; Figure
3.2), compared to average conditions. This type of surface deformation has been observed during
small to moderate eruptions at other volcanoes, such as Mount Etna, Mount Saint Helens, Merapi,
Montserrat, Unzen, and others (Bonaccorso and Davis, 1999; Nishimura, 2009; and references
therein).
A simple model that explains these observations at Concepcion volcano is that of a magma
column connected to a shallow magma reservoir that is able to rise along the volcano conduit
(assumed to be cylindrical in shape) that is open at its top. As magma moves up toward the surface
a constant cylindrical dislocation of the conduit walls is produced because they are subjected to a
uniform pressure change (Figure 3.5), resulting in an inflation of the volcano and positive geodetic
baseline change measured across the edifice. During an explosion, the pressure in the volcano
conduit is reduced, causing the walls to contract inward, and hence a volcano deflation measured
as a geodetic baseline contraction. This open pipe model is described in detail by Bonaccorso
and Davis (1999). The model relates the surface displacements, of any given point on the ground
surface, induced by the upward displacement (from depth c2 and c1, Figure 3.5) of a cylindrical
magma pipe of radius α embedded in an uniform elastic half-space, which produces a uniform
dislocation of the vertical conduit walls, b (Bonaccorso and Davis, 1999; Figure 3.5).
44
The equations to compute the horizontal and vertical displacements are as follow (Bonaccorso
and Davis, 1999; Lisowski, 2007) :
uE =αbx
2(x2 + y2)
(c3
1
R31− 2c1(1+ν)
R1+
c32(1+2ν)+2c2(x2 + y2)(1+ν)
R32
)
uN =αby
2(x2 + y2)
(c3
1
R31− 2c1(1+ν)
R1+
c32(1+2ν)+2c2(x2 + y2)(1+ν)
R32
)
uv =−αb2
(c2
1
R31− 2ν
R1+
2νR22− c2
2
R32
)(3.1)
where uE and uN are the horizontal surface displacements in the easting and northing directions,
respectively; uv is the vertical surface displacement; ν is the Poisson’s ratio (taken to be equal to
0.25); x and y are the horizontal coordinates of the point of interest on the ground surface (e.g.,
easting and northing UTM coordinates); R21 = x2 + y2 + c2
1; and R22 = x2 + y2 + c2
2.
To estimate the baseline changes for the periods of interest (i.e., May 5 – 13, and May 23 –
29 2010) using the open pipe model (Bonaccorso and Davis, 1999) we computed first the three
components of the surface displacements with equation (1). Then, through a forward modeling ap-
proach we carried out a Chi-square goodness of fit to compared the open pipe model displacements
with the observed ones provided by the GIPSY-OASIS software. The set of parameters given the
best fit (the closest displacements from the model to the observations) were used to re-compute the
GPS baseline changes. The results are shown in Table 1, and essentially, they show that oscillation
of the depth to the top of the magma column on order of 200 m can explain the observed changes
in the GPS baseline for the periods of interest.
45
Level 1
Level 2 c1
c2
b
α
Figure 3.5. Schematic representation of the open pipe model, after Bonaccorso and Davis (1999),that we use to model the geodetic GPS deformation observed at Concepcion volcano during theinflation phase from May 5 to 14, 2010, and the deflation phase between May 24 and 31, 2010(Figure 3.2). See text for details.
46
Table 3.1. Parameters of the open pipe model (Bonaccorso and Davis, 1999) used to explain thegeodetic GPS deformation observed at Concepcion volcano during the 2010 erupting phase.
Inflation phase between May 5 and 14, 2010.Dislocation Depth pipe’s top Depth pipe’s bottom pipe’s radius
b (m) c1 (m) c2 (m) α (m)Average 4.8 378 1844 31
1σ 1.2 72 164 7Deflation phase between May 23 and 27, 2010.
Dislocation Depth pipe’s top Depth pipe’s bottom pipe’s radiusb (m) c1 (m) c2 (m) α (m)
Average 4.8 585 1838 431σ 1.2 129 191 7
3.6 Discussion and Conclusions
The correlations we have found in the 2010 time series (Figure 3.3 and 3.4) suggest that the
changes in the GPS baseline, RSAM daily counts, and SO2 emissions during the eruptive phase
may have shared a common source. Although the signal is weak in each time series, the cross-
correlation is significant. This interpretation is reinforced by the lack of such correlations observed
in the time series collected in the 2011 non-eruptive period.
The 2010 time series, however, contains gaps - days during which no data were collected. This
is a common problem with such time series collected on active volcanoes, and the significance of
these data gaps and the interpolation methods used to fill the gaps to our interpretation warrants in-
vestigation. To test this, we replaced all the interpolated points with the minimum observed values
(i.e., 27 tons/day daily flux of SO2), and recomputed the cross-correlation. Even with this extreme
interpolation method, significant cross-correlation among the time series persists. The main differ-
ence was a shift in the lag number of the significant cross-correlation, which we suggest indicates
that the -3 day lag between SO2 emissions and GPS baseline changes may not be a significant
feature of the time series. One addition test was performed to assess the robustness of our inter-
pretation of the time series. As RSAM and SO2 values are always positive, we also computed the
cross-correlation for the 2010 data sets with the absolute value of the GPS baseline changes. Again,
significant cross-correlation among the time series persisted, although the correlation coefficient at
zero lag slightly decreased.
47
As the 2011 time series were gathered during the dry season, we deem that scrubbing effects of
SO2 by interactions with hydrothermal fluids are minimal, if it is taking place at all (e.g., Symonds
et al., 2001). Part of the 2010 observations were made during the rainy season (May and June,
Figure 3.2A). However, SO2 remains correlated with GPS baseline changes and RSAM after the
onset of the rainy season. Thus, if SO2 scrubbing is taking place it is possible that is not playing
a major role in changing the SO2 emission during our observation periods. Only a longer time
series, spanning several seasonal changes, is likely to quantify how much SO2 may be scrubbed by
hydrothermal processes under Concepcion.
The mild but frequent activity at Concepcion volcano during the last four decades is consistent
with the presence of a small-volume, shallow, and relatively open magmatic system (van Wyk
de Vries, 1993; Borgia and van Wyk de Vries, 2003). We were unable to observe the onset of
2010 eruptive activity on March 7. The first set of anomalies observed between May 5 and 14,
2010 in the GPS time series (increase in baseline length of up to 12 mm), RSAM daily counts (a
maximum daily average increase of 89 units, 10 units lower than the maximum observed during
the onset of the eruption between March 7 and 9), and SO2 emission (a peak on the average daily
flux of 643 tons/day, more than %50 above background emission, Figure 3.2A) can be explained by
ascent of a magma column in the relatively open pipe. Modeling results suggest that the measured
12 mm extension between the two GPS stations is consistent with the bottom of the magma column
reaching a shallow magma reservoir at about 1.8 km depth, and its top ascending to about 370 m
depth during that period. The magma column that moved upward toward the surface (∼30 – 40 m
in radius) produced a cylindrical dislocation of the conduit walls of around 5 m (Table 1, Figure
3.5), which was observed as an inflation of the volcano edifice. Increased SO2 emission during
this period is consistent with this model, through increase exsolution of SO2 from the ascending
magma. RSAM counts during this time frame are also consistent with this model.
A few days later, May 24 – 31, the descending magma column reduced the pressure in the
volcano conduit, causing the walls to contract, which is inferred from the GPS record of deflation
(about 17 mm shortening of the GPS baseline). This deflation was accompanied by anomalous
seismic activity, reflected in daily RSAM counts of ∼80 units. No anomalous SO2 emission was
48
observed during this period (fluxes < 200 tons/day), consistent with the model of magma with-
drawal. The modeling suggests that for this event, the top of the magma column descended to a
depth of almost 600 m. This magma withdrawal event was associated with the end of the volcanic
crisis. The results of the open pipe model, showing a shallow magma reservoir below Concepcion
volcano may be located at a depth of about 1.8 km, are consistent with the modeled depth range of
the source of a negative gravity anomaly (∼1.7 – 2.1 km depth) seated below this volcano derived
from the 3-D inversion of the Concepcion gravity data (Saballos, 2012).
Overall, these results suggest that much can be gained through a more robust multidisciplinary
approach (i.e., the gathering of continuous geophysical data on dense networks), although we note
that the comparatively small dimension of Ometepe Island imposes some constraints on spatial
coverage of these networks. Such a network would, in turn, furnish vital information (e.g., magma
intrusion linked to enhanced unrest visible at the surface, and retreat of magma linked to waning or
end of volcanic activity) to decision–makers during volcanic crises. Because the magmatic system
is relatively open and of small-volume, a single data set may not provide enough information to
understand the processes taking place during intrusions, and some important details of the system
dynamics may be overlooked.
49
CHAPTER 4
LAHAR DELINEATION FROM SATELLITE DATA AT CONCEPCION VOLCANO
4.1 Introduction
Lahars (volcanic debris flows) are one of the deadliest volcanic phenomena, which have killed
approximately 50,000 people in the circum–Pacific region during historical times (Skermer and
vanDine, 2005). The most recent infamous lahars in Latin America claimed the lives of ∼25,000
people in Armero, Colombia, from Nevado del Ruız volcano in 1985 (Lowe et al., 1986); 2,500
people in Chinandega, Nicaragua, from Casitas volcano in 1998 (Kerle and Oppenheimer, 2002);
and 400 people in Panabaj, Guatemala, from Toliman volcano in 2005 (Connor et al., 2006).
Lahar generation is the product of a complex interplay of volcanic and climatic processes (Lav-
igne, 1999). Lahars can be generated during volcanic eruptions (syn–eruptive or primary lahars)
by incorporation of ejecta with water (Mastin and Witter, 2000), but can also occur long after erup-
tions (during periods of quiescence, post–eruptive or secondary lahars) by mobilization of volcanic
tephra material during heavy rainfall, natural dam failures, or melting of snow and ice (Mastin
and Witter, 2000; Vallance, 2005). Lahars can move as slowly as 1.3 m/s (∼5 km/h) or as fast as
40 m/s (144 km/h) with an incredible capacity of traveling very long distances from their sources
(Fisher et al., 1997; Scott et al., 2001; Vallance, 2005). A prehistoric lahar that descended from
Cotopaxi volcano, Ecuador, reached the Pacific Ocean traveling more than 300 km and covering at
least 440 km2 (Vallance, 2000).
Flow–routing algorithms are used to model the pathways of mass and energy through the land-
scape (Pelletier, 2008). There is no unique flow–routing method for lahars because different con-
stituents move through the landscape in different ways (Pelletier, 2008). Flow–routing models are
the key tools to runout prediction of natural hazards, and so to determine the affected areas and
50
flow intensity parameters, which are essential elements for producing hazard maps (Rickenmann,
2005). Traditional methods of assessing the hazard zones associated to gravity–driven flows on
volcanoes are based on reviews of historical records and fieldwork to identify the limits of their
deposits (Iverson et al., 1998; Stevens et al., 2003). Predictions of future hazard zones are then
based on interpolation and extrapolation of known data, and researchers’ own experience (Iverson
et al., 1998; Stevens et al., 2003). However, these techniques are less useful at volcanoes where
little data on past activity are available, in which cases physical dynamic models and empirical–
statistical approaches become more useful as predictive tools (Iverson et al., 1998; Stevens et al.,
2003; Rickenmann, 2005). Computer flow modeling is a powerful technique to delineate areas at
volcanoes vulnerable to lahar hazards, and is achieved by calculating the predicted flow path and
deposit inundation over a representation of the local topography in the form of a digital elevation
model (Stevens et al., 2003). Digital elevation models (DEMs) are the core of flow–routing mod-
eling, and are numerical representations of topographic maps. DEMs can be generated in several
ways (Meisels et al., 1995; Stevens et al., 2003; Pelletier, 2008). For a full and detailed explana-
tion of the different empirical relationships for debris flows the reader is referred to Rickenmann,
(1999); Rickenmann, (2005); and Pelletier, (2008).
Iverson et al., (1998) derived two semi–empirical equations to delineate lahar hazard zones in
valleys that head on volcano flanks. The rationale of the technique derives from scaling analysis of
generic lahar paths and statistical analyses of 27 lahar paths at nine volcanoes, Figure 4.1. The two
semi-empirical equations are (Iverson et al., 1998) :
A = 0.05V 2/3 (4.1)
B = 200V 2/3 (4.2)
51
Where A is the valley cross-sectional area in m2, B is the planimetric area of the inundated
valley in m2, and V is the lahar volume in m3. As the logarithmic relationship implies, these
parameters are related by one order of magnitude in natural systems (Iverson et al., 1998).
To estimate the volume of the lahars from Concepcion volcano that have occurred during the
last three decades, the planimetric area inundated by lahar deposits were first extracted from re-
motely sensed satellite data (Landsat 2, 3, 5 and 7; and the Advanced Spaceborne Thermal Emis-
sion and Reflection Radiometer (ASTER) sensors), and combined with ground truth data available
for one lahar deposit (Los Ramos). Then, the volume of the deposits were estimated using Eq 4.2.
4.2 Concepcion volcano
The volcano is predominantly composed of clinopyroxene–plagioclase bearing andesite rocks
found low and high on the slopes exposed in gorges (McBirney and Williams, 1965; van Wyk de
Vries, 1993; Borgia and van Wyk de Vries, 2003). Lahars, pyroclastic units, and lava flows are all
common products of Concepcion (McBirney and Williams, 1965; van Wyk de Vries, 1993; Borgia
and van Wyk de Vries, 2003). Concepcion and the currently inactive Maderas volcano together
form Ometepe Island, with approximately 31,000 inhabitants (INIFOM, 2001). Ometepe Island
is located in Lake Nicaragua also known as Lake Cocibolca (Figure 4.2), in western Nicaragua.
Concepcion is the most active composite volcano in Nicaragua, characterized by effusive activity of
basalt and basalt–andesite lava flows, and more recently by small to moderate explosive activity. A
large number of tephra explosions, VEI of 1 and 2, have been reported to have occurred during the
last 100 years at Concepcion volcano (∼30) through the Global Volcanism Program and INETER
websites, and lahars at Concepcion began to be systematically reported during the last decade, and
appear to have increased in frequency, Table 4.1.
Debris flows from Concepcion volcano have ruined crops, cut roadways, threatened the popu-
lation and properties, and eroded or covered fertile soil, but fortunately have not caused casualties
so far. However, there are a number of small towns, including schools and hotels, built upon pre-
historic debris–flow deposits mainly SSW from the volcano base all the the way to the shore lake,
which represent a direct risk to about a half of the total population of the island, and an indirect
52
volcano
100
102
104
106
108
1010
102
103
104
105
106
107
108
109
Volume (m3)
Pla
nim
etric
Are
a (m
2 )
Volcanic debris flows
Non-volcanic debris flows
(A)
(B)
Figure 4.1. (a) Geometric relationships used by Iverson et al. (1998) to derive the semi-empiricalrelationships of a debris-flow’s channel cross-sectional area (A), and planimetric inundated area(B) to the debris-flow volume, (V ); after Iverson et al. (1998). (b) Log-log plot of volume versusplanimetric inundated area by debris flows from Iverson et al. (1998). The dashed lines representthe 95% confidence intervals of the regression given by equation 4.2.
53
risk of many more thousand people (and infrastructure) living in nearby cities and towns. Thus,
it is extremely important to study the volcano instability of Concepcion, and its related volcanic
hazards, in order to mitigate the effects of any potential major lahar from this volcano.
4.3 Slope stability of Concepcion volcano
In the 19th century, before the beginning of the reactivation of Concepcion volcano in 1883
(Siebert et al., 2011), vegetation on its flanks were abundant, and began to slowly decline as the
volcanic activity increased in frequency. Erosion was accelerated by deforestation mainly from
tobacco growers who used the wood from the flanks of the volcano to fuel ovens to treat tobacco
leaves during the following decades (INIFOM, 2001). Thus, I believe that volcanic activity and
anthropogenic disturbances taking place since the last century at Concepcion volcano should be
the major factors that have undermined its slope stability. At Concepcion unstable material is
mobilized by rainfall, and this happens when sufficient water saturates (or nearly saturates) the
unstable soil mass increasing normal stress beyond the limits of the resistance imposed by shearing
stresses (e.g., Iverson et al., 1997). Debris flows triggered by rainfall involve a number of physical
processes operating on disparate timescales (Iverson, 2000).
The degree at which volcano activity is affecting the stability of Concepcion is not known yet,
but I will briefly describe the most likely processes. Edifice volcano instability associated with
geothermal systems develops when there is extensive rock dissolution and hydrothermal mineral
alteration produced by highly acidic hot fluids, which are the result of the interaction of magmatic
gases with groundwater (Lopez and Williams, 1993; Watters et al., 2000). Rock dissolution implies
that the rock mass is weakened or softened leading to clay mineral formation and precipitation that
may reach basal contacts, which ultimately favors mass sliding. Enhanced hydrothermal activity
and strain within a saturated porous medium due to magmatic intrusions can increase pore water
pressure, which in turn reduces the normal effective stress, increasing the potential for slope failures
(e.g., Voight and Elsworth, 1997). There are other effects associated with magmatic intrusions that
have been associated with collapse of volcano slopes that I will not describe here since these are of
a much bigger scale than the current laharic activity at Concepcion. I have observed hydrothermal
54
MOY
SAM
ESQ
LAC
SJS
ALT
SJN
SAB
CHI
LOR
648000
656000
656000
1272000
1272000
1280000±
0 5Km
0 500
km
Nicaragua
Costa Rica
270˚ 272˚ 274˚ 276˚ 278˚ 280˚6˚
8˚
10˚
12˚
14˚
Volcán Concepción
Honduras
Panamá
LAF
Figure 4.2. Shaded relief map of Concepcion volcano showing main towns: San Marcos (SAM),La Chirca (CHI), San Jose del Norte (SJN), Altagracia (ALT), La Sabana (SAB), La Union (LAU),Los Ramos (LOR), San Jose del Sur (SJS), Esquipulas (ESQ), Japon (JAP), Moyogalpa (MOY),La Concepcion (LAC), an La Flor (LAF). Inset : Regional location map of Concepcion volcano,Nicaragua, in Central America. Black triangles show the location of major Quaternary volcanoesalong the Central America volcanic front. Dashed-arrows indicate average flow direction of mostsignificant debris-flows during occurrence.
55
Table 4.1. Reported lahars at Concepcion volcano since last decade
Date Locationa Avg. thickness (m)b Reference2002/10/28 La Chirca 1.5 INETER, (2002d)2002/10/31 La Chirca 0.5 INETER, (2002d)2003/11/25 San Marcos 1 INETER, (2003a)2003/11/25 San Jose del Norte 2 INETER, (2003a)2003/11/25 Japon 0.6 INETER, (2003a)2004/05/21 La Chirca – INETER, (2004)2005/05/18 La Flor – INETER, (2005d)2005/05/18 San Jose del Norte 2 INETER, (2005d)2005/06/29 La Concepcion – INETER, (2005c)2005/06/29 La Chirca – INETER, (2005c)2005/06/29 La Flor – INETER, (2005c)2006/09/19 San Marcos – INETER, (2006)2008/10/04 Los Ramos 5 INETER, (2008b)2008/10/04 La Union – INETER, (2008b)2008/10/05 Urbaite – INETER, (2008b)
aSee Figure 4.2 for geographic location.bReported planimetric inundated area’s average thickness deposit.
altered rocks and soil mass high on the NW slope of Concepcion. These zone is the source region
of the debris flow that heads down to La Flor town, Figure 4.2.
Deforestation drastically decreases slope stability since trees provide mechanical stabilization
through the roots (root cohesion to the soil enhances the shearing strength of the soil), and remove
soil moisture trough transpiration reducing pore water pressure (Sidle, 1992; Nilaweera and Nuta-
laya, 1999; Ammann et al., 2009). As tree roots decay in the soil mass, gaps in the interlocking
root system of neighboring individual trees begin to form, increasing the likelihood for soil slides to
occur (Sidle and Ochiai, 2006; Ammann et al., 2009). The weight of trees on soils, however, may
not always be beneficial, since this weight increases the normal and downhill force components,
favoring slope failures as well (Sidle and Ochiai, 2006; Ammann et al., 2009).
4.3.1 Slope aspect of Concepcion volcano
To have a general idea of the slope conditions of Concepcion volcano as of 2004 I made a slope
map from a 20-m-resolution DEM, constructed in 2004, and provided by Instituto Nicaraguense de
56
Estudios Territoriales (INETER, Figure 4.3). Light-gray to white areas (slopes > 53◦, Figure 4.3)
near the SW side of the summit, and at mid elevations on the NNW slopes, mark the locations of
the deepest and largest gullies on the volcanic edifice. A close look of the slope map of Concepcion
(Figure 4.3) shows three distinct regions. The first comprises the lower flanks with slopes < 10◦ at
elevations < 300 m; the second with slopes between 11◦ and 27◦ at intermediate elevations (300 to
850–900 m); and a third region corresponding to the upper part of the cone with slopes > 28◦ that
goes up the summit at an elevation of about 1600 m. The second region matches to a great extent
the high residual gravity anomaly observed by Saballos et al., (2013), see also chapter 2 of this
work, distinguishing the denser lower flanks of the volcano, believed to be the remnants of a series
of Plinian eruptions (Borgia and van Wyk de Vries, 2003) that occurred at Concepcion about 19 ka
(Kutterolf et al., 2008), from the upper lighter (third slope region, weaker and easier erodable) cone
that is associated to a low residual gravity anomaly, see chapter 2.
4.4 Remote sensing of lahars
A brief description of the main remote sensing techniques used to study debris flows is given
here. The reader is referred to the bibliography cited in this section for further details. Currently,
there are more than 25 non-classified optical and radar sensors on board Earth orbiting satellites that
are useful in the monitoring and study of natural phenomena, including landslides and lahars (Kerle
and Oppenheimer, 2002; Pack, 2005). Ground or spatial resolution of these data range from 1 m
(IKONOS-2) to 1.1 km (NOAA-AVHRR); spectral resolutions go from the optical spectrum (∼0.4
– 0.7 µm) to microwaves (Radar X-band: 3 cm, C-band: 6 cm, L-band: 24 cm); and temporal
resolutions (satellite revisit to the same location) from 8 to 16 days for high ground resolution
sensors, up to multiple overpasses per day for lower spatial resolution sensors (Flynn et al., 2001;
Kerle and Oppenheimer, 2002; Pack, 2005). Airborne (e.g., aerial cameras and Lidar) and ground
based (e.g., digital cameras and Lidar) remote sensing devices are also of great value in the study
of landslides and debris flows, which in general offer a higher spatial resolution than satellite data
(Pack, 2005). Traditionally, optical remote sensing data have been the most common type of data
used in the study of lahar deposits, but near-infrared (NIR, ∼0.75 – 1.40 µm) data are extremely
57
640000 645000 650000 655000
127
000
012
750
00
128
000
0 Slope (deg)
0 - 1
2 - 3
4 - 6
7 - 9
10 - 13
14 - 16
17 - 20
21 - 23
24 - 27
28 - 30
31 - 33
34 - 36
37 - 39
40 - 42
43 - 44
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53 - 55
56 - 58± 0 5 Km
P1
P2
0
200
400
600
800
1000
1200
1400
1600
Elev
atio
n (m
)
0 2000 4000 6000 8000 10000 12000 14000 16000
Distance along profile (m)
Res
idua
l gra
vity
(mG
al)
−5
0
5
10
15
20Residual gravityTopography
(A)
(B)
Figure 4.3. (A) Slope map of Concepcion volcano generated from a 20-m-resolution digital eleva-tion model produced in 2004, provided by Instituto Nicaraguense de Estudios Territoriales. See textfor a detailed description. (B) Profile P1P2 comparing topography and residual gravity anomaly,see chapter 2.
58
useful when lahars destroy vegetation cover (Francis and Wells, 1988; Kerle and Oppenheimer,
2002; Davila et al., 2007). A number of vegetation index algorithms have been developed since
the late 1970s to characterize changes and conditions of vegetation cover traditionally using NIR
and optical-red (∼0.625 – 0.740 µm) bands (e.g., Tucker, 1979; Huete, 1988; Kaufman and Tenre,
1992) that can be applied to study debris-flow destruction and deposits. Also, digital elevation
models (DEMs) derived from radar and Lidar data, and sensors with stereoscopy capabilities (e.g.,
ASTER) have been widely used to model debris flows, develop more accurate hazard maps, and to
study their deposits (Pack, 2005; Hubbard et al., 2007; Huggel et al., 2008; Vianello et al., 2009).
4.5 Satellite data and methodology
Because most recent lahars (within the last few decades) at Concepcion have been relatively
small, moderate and high spatial resolution remote sensing data are the most suitable to study these
lahars. The largest lahar deposits from Concepcion (i.e., La Flor and Los Ramos, Figure 4.4 and
4.5) are visible on ASTER and Landsat images, but smaller deposits are not. All ASTER and
Landsat images used in this study were already orthorectified. The 2008 Los Ramos lahar deposit
was much larger in extent and volume than the 2009 deposit produced by a lahar that descended
from the eastern flank of Concepcion. Both the 2008 and 2009 Los Ramos lahar deposits are
too small to be visible in a 30 m x 30 m ground resolution Landsat image or in a 15 m x 15 m
ground resolution ASTER image, but the 2008 deposit is partially seen on a “jpg” sample off-nadir
panchromatic QuickBird image acquired on March 05, 2011 and downloaded from the Digital
Globe website (http://www.digitalglobe.com/). An original off-nadir panchromatic QuickBird im-
age has a ground resolution of 0.72 m, but this sample image is of lower resolution than that (actual
ground resolution is not specified in the website), but of higher resolution than a Landsat or ASTER
image. To digitize the Los Ramos lahar deposit on this QuickBird sample image, I georeferenced
it, and then overlaid a set of differential GPS ground control points collected in the field on this
deposit. The image showed part of the deposit where GPS data were not available due to vegetation
cover blocking the GPS signal during the field campaign. The distal phase of the deposit is not seen
on the QuickBird sample image, but I was able to gather GPS data along the edges of the deposit
59
at that location since there were no high trees blocking the view of the sky. This is what I refer to
as a hybrid approach in which ground control points from GPS observations measured on the lahar
deposit were used to assist the digitizing process on a georeferenced image.
I tried different approaches to extract information from satellite imagery (i.e., planimetric area
inundated by lahars). First, I tried enhancing the contrast manually of the different bands for each
single image to see how well lahar deposits can be distinguished from the background. Band
4 data (0.76 – 0.90 µm, NIR spectral region) of Landsat 7, and its equivalent band 3N (nadir
view 0.78 – 0.86 µm) of the ASTER instrument, provided the best results for any single band.
However, one of the major shortcomings of working with a single band was that lahar deposits,
lahar channels (ravines or gullies), and any other deforested area (e.g., recent lava flows) all look
the same. Thus, I decided to try two different vegetation index techniques, which involve the
mathematical combination of at least two bands to see if better results were obtained.
The Normalized Difference Vegetation Index (NDVI) was introduced by Tucker, (1979) to
estimate the cover of green vegetation:
NDV I =NIR−RedNIR+Red
(4.3)
where NIR, as stated above, is the spectral band in the near-infrared region of the electromag-
netic region (∼0.75 – 1.40 µm), and Red is the spectral band in the red region (∼0.625 – 0.740
µm) of the electromagnetic spectrum. The major pitfalls of the NDVI is its high sensitivity to soil
bakcground, atmosphere, and sun-angle conditions during image acquisition (e.g., Huete, 1988;
Kaufman and Tenre, 1992).
The Atmospherically Resistance Vegetation Index (ARVI) proposed by Kaufman and Tenre
(1992) used three wavebands to try to minimize the atmospheric effects by incorporating the “blue”
band in the vegetation index technique, and is given by:
60
ARV I =NIR−Red + γ(Blue−Red)NIR+Red− γ(Blue−Red)
(4.4)
where Blue is the band associated with blue color (∼0.450 – 0.495 µm), and γ (0 < γ ≤ 2) is
a factor related to the aerosol type present in the atmosphere.
4.6 Results
Figure 4.4 displays a comparison of the results obtained by the techniques described in the
previous section. To “isolate” the features of interest (i.e., lahar deposits), I assigned white colors
to those unwanted features by means of a semi-unsupervised classification. The NDVI (Eq 4.1) is
able to discern oldest from younger deposits when there is enough vegetation difference between
these two features. For instance, younger deposits (lahar scars, gullies, and lava flows inclusive)
shown as dark brown in Figure 4.4B are vegetation free features, while older scars and lava flows
that have a minor vegetation cover are shown in yellow. The ARVI algorithm (Eq 4.2) did not
yielded better results than the NDVI algorithm, and was technically identical than those from the
single band approach. ARVI results improved by using a value of γ ∼0.1, see Figure 4.4. In
general, all three techniques (NIR band, NDVI and ARVI) produce very similar results, and none
of them are able to distinguish between a lahar deposit and scars (i.e., barren soil and gullies) left
by the debris flow (or from a fire) on the topography or from lava flows.
A slight improvement can be gained in the distinction between the true lahar deposit and the
background by doing a traditional false color composite band combination like the one shown in
Figure 4.4D, in which the Landsat 7 image is displayed as R: Band 4 (0.76 – 0.90 µm), G: Band
5 (1.55 – 1.75 µm), and B: Band 7 (2.08 – 2.35 µm). A band combination using the results of
the algorithm previously described also provides a good contrast between lahar deposits and their
backgrounds. This is shown in Figure 4.5 where lahar deposits are in blue, and some lahar scars are
in pink and purple. Although some other features that lack vegetation, like lava flows and gullies,
are also shown in blue, lahar deposits are expected to be on the lower flanks of the volcano. The
61
648000656000
656000
12
72
00
0
12
72
00
0
12
80
00
0 648000656000
656000
12
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0
12
72
00
0
12
80
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0
648000656000
656000
12
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0
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0 648000656000
656000
12
72
00
0
12
72
00
0
12
80
00
0
A
C
B
D
0 5 km
Figure 4.4. Comparison of different approaches to highlight debris flows on Concepcion using thesame Landsat 7 image acquired on January 27, 2001. (A) Band 4. Deforested areas by debrisflows (WSW) and lava flows (NE and ESE) look the same. (B) NDVI (Tucker, 1979). Mostdeforested areas are shown in dark brown, while less severe deforested areas are in yellow. (C)ARVI (Kaufman and Tenre, 1992). Best results were obtained using a γ value of 0.1, see Eq 4.2.Explanations are provided in the text. (D) False color composite (R: band 4, G: band 5, B: band 7).Most deforested areas appear in dark purple.
62
San Jose del Sur lahar actually starts a little high on the SW slopes as depicted by the yellow lines
in Figure 4.5. This is due to a break in the slope caused by an apparent collapse of part of the slope
in that area.
I proceeded in the same way with all the available images in order to digitize lahars near La
Flor, San Jose del Sur, and Los Ramos communities (Figure 4.2 and 4.5) in order to get an estimate
of the planimetric area inundated by the deposits of these lahars. To get a rough estimate of the
uncertainty (the minimum possible value) associated with the measurements of the planimetric
area inundated by a lahar from a satellite image, I assumed that I have completely encompassed
the lahar deposit (by digitizing a polygon around the deposit), and that at the margins the deposit
covers only 50% of the image pixels. So, in this way, the uncertainty can be computed by the
number of pixels along the perimeter of the digitized polygon (lahar deposit) times 50% of the
pixel area, which depends on the spatial resolution of the satellite image. The volume of the lahar
deposits were then computed using one of the Iverson et al., (1998) empirical-statistical equations,
namely Eq 4.2. These results are presented in Table 4.2.
The chronology of the digitized lahar deposits for La Flor, Los Ramos and San Jose del Sur
communities are shown in Figures 4.6, 4.7, and 4.8, respectively, see also Table 4.2. La Flor lahar
inundated planimetric area increased between 1986 and 1987, from 1.58 x 105 to about 3.29 x 105
m2 (Figure 4.6, Table 4.2). The inundated planimetric area of the lahars in the zone of La Flor
during 2000 and 2003 are comparatively small. The deposit of a subsequent lahar seen on the
ASTER image of 2010 was relatively large, covering a similar surface area to that occurred in 1987
(Figure 4.6).
The first lahar at Los Ramos that took place in October 2008 (INETER, 2008b), was 3.5 times
larger than the second one that occurred in the same place almost a year later (Figure 4.7, Table
4.2). On the other hand, the San Jose del Sur lahar zone seems to be most active one at Concepcion,
at least from the available data set that dates back to 1978, but it does not seem to be progressively
increasing, rather the deposits in this lahar zone are slightly below 6 x 105 m2 (Figure 4.8). One
possible explanation for this may be that this volume represents the maximum volume of material,
on the volcano’s slope, the can resist failure from rainfall.
63
645000 650000 655000
127
000
012
750
00
128
000
0 ±
0 5 Km
651000 652000
127
20
00
127
30
00
±
0 500 m
San Josédel Sur
La Florlahar
(A)
(B)
LosRamos
Figure 4.5. (A) False color composite Landsat image, acquired on January 27, 2001 produced bythe band combination R: band 4, G: ARVI (see Eq 4.2), and B: NDVI (see Eq 4.1), and individuallyshown in Figure 4.4. Lahar deposits are highlighted by the yellow lines within the zoomed boxes.(B) Los Ramos 2008 and 2009 lahar deposits partially visible on a “jpg” sample image downloadedfrom the Digital Globe website. The digitizing of this lahar deposits were complemented with GPSdata gathered in the field.
64
648000
648000
127
800
0
127
800
0
0 1,000 Meters
Legend
1986-04-02
1987-10-14
2000-01-27
2003-01-10
2010-12-08
La Florlahar
Figure 4.6. Temporal evolution of the lahar deposits heading down to La Flor town from the westernslopes of Concepcion volcano. See Figure 4.2 for geographic location of La Flor town, and Table4.2 for an estimation of the area and volume of the deposits. Inset depicts the approximate locationof the lahar.
A time series of the computed lahar volumes reported in Table 4.2 is shown in Figure 4.9. The
time series for the San Jose del Sur lahar zone is the longest one with 9 lahar events unevenly
spaced in time. Due to cloud cover during the time of image acquisition we could not digitize the
La Flor lahar deposits during 1990 and 1998. The San Jose del Sur lahar deposit is almost double in
size than the largest La Flor lahar deposit, and almost five times larger than the Los Ramos deposit.
4.7 Discussion
The factors that destabilize slopes of volcanoes are very complex (e.g., Sidle, 1992; Voight and
Elsworth, 1997; Vallance, 2005). At Concepcion volcano, during the last few decades rainfall is
the chief factor that triggers lahars by mobilization of loose volcanic material on the slopes of the
volcano, which have become unstable and vulnerable to erosion mainly due to volcanic activity and
anthropogenic disturbances. Reported laharic activity at Concepcion volcano has increased during
65
Table 4.2. Planimetric area inundated by lahars at Concepcion volcano.
Datea Location Areab E. Areac Volumed E. Volumee Sensor(x105 m2) (x105 m2) (x103 m3) (x103 m3)
02/04/1978 San Jose 2.21 1.42 36.7 35.4 Landsat 3del Sur
02/04/1986 San Jose 4.13 0.86 94.0 29.3 Landsat 5del Sur
02/04/1986 La Flor 1.58 0.56 22.1 11.8 Landsat 514/10/1987 San Jose 1.31 0.57 16.7 10.9 Landsat 5
del Sur14/10/1987 La Flor 3.29 1.10 66.8 33.5 Landsat 523/01/1990 San Jose 5.73 1.29 153.4 51.8 Landsat 5
del Sur15/12/1998 San Jose 0.28 0.27 1.6 2.4 Landsat 5
del Sur27/01/2000 San Jose 4.61 1.18 110.6 42.5 Landsat 7
del Sur27/01/2000 La Flor 0.66 0.25 6.0 3.4 Landsat 710/01/2003 San Jose 5.94 0.91 161.7 37.2 ASTER
del Sur10/01/2003 La Flor 0.87 0.18 9.0 2.8 ASTER31/01/2005 San Jose 4.21 0.60 96.5 20.6 ASTER
del Sur08/12/2010 San Jose 5.64 0.66 149.9 26.3 ASTER
del Sur08/12/2010 La Flor 2.52 0.47 44.7 12.5 ASTER15/12/2008 Los Ramos 1.18 – 14.4 – Hybrid f
08/12/2010 Los Ramos 0.51 0.15 4.1 1.8 ASTER
aDate of satellite image acquisition, except for field campaign in Los Ramos during December 15,2008.bPlanimetric inundated area (B) encircle by the digitized polygon along the edges of the lahardeposit.cError estimated in the planimetric area. See text for details.dComputed using Eq 4.2.eError in volume, estimated by error propagation.f Digitizing of this lahar deposit was done with auxiliary ground-truth GPS data.
66
652000
652000
127
20
00
127
20
00
127
30
00
127
30
00
Legend
2008-12-15
2010-12-08
0 500 Meters
Los Ramoslahar
Figure 4.7. Temporal evolution of the lahar deposits of the flows threatening Los Ramos townsoutheastern side of Concepcion volcano. See Figure 4.2 for geographic location of the town, andTable 4.2 for an estimation of the area and volume of the deposits. Inset depicts the approximatelocation of the lahar.
67
648000
648000
650000
650000
12
730
00
12
730
00
Legend
1978-04-02
1986-04-02
1987-10-14
1990-01-23
0 1,000 Meters
San Josédel Surlahar
648000
6480001
27
300
0
12
730
00Legend
1998-12-15
2000-01-27
2003-01-10
2005-01-31
2010-12-08
0 1,000 Meters
(A) (B)
Figure 4.8. Temporal evolution of the lahar deposits north of San Jose del Sur town SSW slopesof Concepcion volcano. See Figure 4.2 for geographic location of the town, and Table 4.2 for anestimation of the area and volume of the deposits. Inset depicts the approximate location of thelahar. (A) Lahar chronology from 1978 to 1990. (B) Lahar chronology from 1998 to 2010.
0
1
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8
Los Ramos lahar
La Flor lahar
San José del Sur lahar
Hurricane Joan
Hurricane Mitch
Laha
r de
posi
t are
a (x
105 m
2 )
Figure 4.9. Time series of inundated areas by lahar deposits extracted from satellite data. The plotseems to show that generally a small lahar is followed by a larger one, or vice versa. It is possiblethat Hurricane Joan triggered a large lahar at San Jose del Sur in 1988, but Hurricane Mitch seemednot to have triggered any lahars at Concepcion.
68
the last decade (Table 4.1.). The lack of reported lahars in previous decades does not mean they
did not occur because reporting is inconsistent, as it has been shown in this present work through
the analysis of several satellite images dating back to 1978.
The lahar deposits that are most clearly detected with Landsat and ASTER satellite data are
those near the San Jose del Sur and La Flor communities (Figure 4.2, 4.5, and 4.7) because they
have the largest planimetric inundated areas. However, there are other lahars near La Chirca and La
Sabana (Figure 4.2, Table 4.1) that flew through relatively vegetated areas and their channel flows
and deposits are too narrow as to be seen in these satellite data, but are known to have occurred as
reported by INETER (Table 4.1).
The San Jose del Sur lahars are comparable in size to some reported at Mt. St. Helens and Mt.
Hood in 1980 (Gallino and Pierson, 1984; Major and Voight, 1986). La Flor lahars are comparable
to those reported by Rodolfo, (1989) at Mayon volcano in the Philippines triggered by a typhoon
in 1985. Hurricane Joan hit predominantly the Caribbean coast of Nicaragua in October 1988, and
it has been reported that this hurricane triggered a “mudflow” (lahar) at Concepcion (Devoli et al.,
2007; and references therein). Thus, we attribute the increase in the size of the lahar deposits,
observed in the data set available in this study, from the early 1980s to 1990 at Concepcion volcano
(Figure 4.9) to be due to the intense rainfall from the Hurricane Joan. However, the infamous
Hurrricane Mitch that badly affected the north-eastern and north-western sides of Nicaragua (and
a large portion of Central America) in late October 1998 does not seem to have triggered any
significant debris flows at Concepcion volcano, since there were no reports of such an event. This
is supported by the satellite data of this study, which do not show an increase in lahar size deposits
(Figure 4.9) even in an image acquired immediately after that this hurricane hit Nicaragua.
I have computed lahar volumes using the planimetric inundated area empirical-statistical re-
lationship of Iverson et al. (1998). These volumes can be used to simulate lahar flows surging
down the slopes of Concepcion volcano by flow routing models like LAHARZ (Schilling, 1998),
and more sophisticated numerical models such as Flo-2D (O’Brien et al., 1993), TITAN2D (Pa-
tra et al., 2005; Patra et al., 2006) and VolcFlow (Kelfoun and Druitt, 2005; Kelfoun et al., 2009).
69
These simulations can then be translated into lahar hazard maps that are valuable tools for decision-
makers like civil defense and local authorities.
The lahar volumes computed using Eq 4.2 and presented in Table 4.2 allow me to get a prelim-
inary estimates of the erosion rate of the slopes of Concepcion volcano during the period 1978 to
2012, which is 29 x 103 m3 yr−1 (29 km3 Myr−1). This should be taken as a conservative minimum
short term erosion rate, since lahar deposits at La Chirca and La Sabana (and other places) have not
been taken into account, although they are very small (INETER, 2008b). Thouret, (1999) reported
short term erosion rates for Pinatubo volcano after its massive eruption in 1991 of 136 x 103 – 219
x 103 km3 Myr−1, which are significantly higher than our current estimation for Concepcion vol-
cano. This is because the amount of material available to be eroded after the eruption of Pinatubo
was huge. In contrast, tephra deposition on the flanks from eruptions at Concepcion volcano are
very small. High erosion rates due to the removal of “fresh” tephra products on active volcanoes
tend to decline in a relatively short time, in a matter of few years, if there is no addition of new
materials (Thouret, 1999), but it may be different for other volcanoes on different geological and
geographical settings.
The predominantly tropical climate of Nicaragua, are unfavorable for the preservation of the
small volume tephra deposits erupted from Concepcion volcano in the last four decades. Thus, it
is difficult to carry out a reliable volcano mass balance for Concepcion. However, the fact that the
lahar channels are progressively growing through time, and that new lahar zones are developing
on the slopes of the volcano, may suggest that currently erosion by lahars is more significant than
mass addition to the volcano by eruptions.
4.8 Conclusions
I have shown that moderate spatial resolution satellite data is of significant importance in the
extraction of inundated areas by debris flows (those covering a planimetric area ≥104 m2), and
mainly for past events that lack enough information or ground-truth data. Nonetheless, caution
must be taken when mapping lahar deposits in this way because lahar scars and channels (and non-
vegetated areas) may be misinterpreted as part of the actual deposit, leading to an overestimation
70
of area inundated and/or volume. There is not a straightforward approach to clearly and definitely
“isolate” the lahar deposits from other features that responsd in a similar fashion within the visible
and near-infrared region of the electromagnetic spectrum. Thus, ground-truth data (e.g., comple-
mentary data from GPS measurements) is essential to constraint the actual limits of the debris flow
deposit.
A time series of the inundated areas by lahar deposits, around Concepcion volcano, extracted
from satellite data suggests that generally a small lahar is followed by a larger one, or vice versa.
The satellite set available for this study shows that the San Jose del Sur lahar zone (Figure 4.2) is
currently the most active one at Concepcion, and is also producing the more voluminous lahars (in
the order of 105m3).
New lahar zones are developing on the eastern and north-eastern slopes of Concepcion vol-
cano. As today, the deposits and channels of this debris flows are too small to be detected by
moderate ground resolution satellite images (e.g., Landsat and ASTER), but are visible in high
ground resolution satellite images.
4.9 Recommendations
A lahar monitoring and a robust educational programs should be prioritized for Ometepe Island,
focused in the prevention and mitigation of volcanic disasters associated with debris flows.
Although the real factors producing the instability of the slopes of Concepcion volcano are yet
not fully known, I propose to use the results of this study as a starting point for the elaboration
of lahar hazard maps through numerical simulations. What is known is that at Concepcion debris
flows are triggered by rainfall, so I propose that a lahar monitoring program should be focused on
rainfall-triggered lahars. At different volcanoes lahars are triggered by different amount of rainfall,
so it is important to look for the rainfall threshold at which lahars are triggered at Concepcion.
This can be achieved by at least one rain gauge recording data continuously. Under intense rain or
high cloud cover conditions, it is difficult to see the onset of a lahar, thus seismic signals associated
to the lahar must be careful filtered out from the seismograms. In this way a precise timing of
the amount of rainfall and the lahar initiation can be determined. Other hydraulic parameters are
71
also very important in a more precise determination of the factors leading to the lahar formations,
so I would recommend the installation of piezometers on the areas susceptible to failure. This
devices measure the water content of the soil, and can be attached to data-loggers and in turn to
a telemetry system to get readings in a real-time basis. Soil-saturated conditions are important
pieces of information to model debris flows initiation and their dynamics, too. Other techniques to
monitor lahars require a lot of maintenance and I think they will be worth to try in a later stage,
after a more deep understanding of the genesis of lahar is achieved for Concepcion volcano.
72
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APPENDICES
84
Appendix A Supplementary figures for Chapter 2
Figure A.1. Simple Bouguer anomaly map computed using a density of 2500 kg m−3 used in grav-itational spreading models (e.g. Borgia and van Wyk de Vries, (2003)). Note the narrow steepnegative ring-like gradient formed around the volcanic cone. This is due to an overcorrectioncaused by a density that is higher than the bulk average terrain density.
85
Appendix A (Continued)
Figure A.2. Simple Bouguer anomaly map computed using a density of 1539 kg m−3 provided withthe 1-D Nettleton (Nettleton, 1939) and Parasnis’(Parasnis, 1997) methods. Although this densitydoes a better job in removing the effect of topography from the gravity anomaly than a densityof 2500 kg m−3, there is still some positive correlation between the volcanic topography and theBouguer anomaly caused by a lower density than the best bulk average density that represents theterrain.
86
Appendix A (Continued)
W E
N
S
N S
W E
6505
00
1275550
Density contrast (kg/m3)
0 5 Km
0
Km-5
A
B
C
0
-2 km
Figure A.3. 3-D inversion of the gravity data shown in Figure 2.2 using the GROWTH2.0 modeldeveloped by Camacho et al., (2011). The input parameters used in the modelling correspond tothe second set of parameters summarized in Table 2.1. (A) Structural density map at 1 km depth(-1000 m) of Concepcion volcano and its surroundings. (B) East-West cross-section of structuraldensity map. (C) North-South cross-section of structural density map.
87
Appendix A (Continued)
W E
N
S
N S
W E
6505
00
1275550
Density contrast (kg/m3)
0 5 Km
0
Km-5
A
B
C
0
-3 km
Figure A.4. 3-D inversion of the gravity data shown in Figure 2.2 using the GROWTH2.0 modeldeveloped by Camacho et al., (2011). The input parameters used in the modelling correspond tothe third set of parameters summarized in Table 2.1. (A) Structural density map at 1 km depth(-1000 m) of Concepcion volcano and its surroundings. (B) East-West cross-section of structuraldensity map. (C) North-South cross-section of structural density map.
88
Appendix A (Continued)
−80
−40
0
40
80
Hei
ght(
mm
)
JAN 02 JAN 03 JAN 04 JAN 05 JAN 06 JAN 07 JAN 08 JAN 09 JAN 10
−20
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0
10
20
30
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itude
(mm
)
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0
5
10
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ude
(mm
)
JAN 02 JAN 03 JAN 04 JAN 05 JAN 06 JAN 07 JAN 08 JAN 09 JAN 10
CON1
CON1
CON1
Figure A.5. Time series for the three components of station CON1 for all the campaigns. Light-gray vertical bars indicate periods of unusual seismic activity on Concepcion volcano and/or nearOmetepe Island, while dark-gray vertical bars represent periods of volcanic activity characterizedby ash and gas explosions. CON1 is located slightly NW from Concepion, see Figure 1.
89
Appendix A (Continued)
0
50
100
150
Height(mm)
0
50
100
150
Height(mm)
OCT 08 JAN 09 APR 09 JUL 09 OCT 09 JAN 10 APR 10 JUL 10
−10
−5
0
5
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(mm)
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0
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(mm)
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0
5
Latitude(mm)
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−5
0
5
Latitude(mm)
OCT 08 JAN 09 APR 09 JUL 09 OCT 09 JAN 10 APR 10 JUL 10
COS2
COS2
COS2
Figure A.6. Time series for the three components of station COS2. Light-gray vertical bars indicateperiods of unusual seismic activity on Concepcion volcano and/or near Ometepe Island, while dark-gray vertical bars represent periods of volcanic activity characterized by ash and gas explosions.COS2 site, located slightly SW of the volcano, in the San Jose del Sur town (Figure 1), shows thelargest vertical variation through time, an increase, of ∼13–16 cm in 1.932 yrs.
90
Appendix A (Continued)
−40
−20
0
20
40
Heigh
t(mm)
OCT 08 JAN 09 APR 09 JUL 09 OCT 09 JAN 10 APR 10 JUL 10
−5
0
5
10
15
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itude
(mm)
−5
0
5
10
15
Latitud
e(m
m)
OCT 08 JAN 09 APR 09 JUL 09 OCT 09 JAN 10 APR 10 JUL 10
MOYO
MOYO
MOYO
Figure A.7. Time series for the three components of station MOYO. Light-gray vertical bars indi-cate periods of unusual seismic activity on Concepcion volcano and/or near Ometepe Island, whiledark-gray vertical bars represent periods of volcanic activity characterized by ash and gas explo-sions. MOYO is located of the western side of the volcano, near the town of Moyogalpa, see Figure1.
91
Appendix A (Continued)
−40
−30
−20
−10
0
10
20
Heigh
t(mm)
OCT 08 JAN 09 APR 09 JUL 09 OCT 09 JAN 10 APR 10 JUL 10
−5
0
5
10
15
Long
itude
(mm)
−10
−5
0
5
Latitud
e(m
m)
OCT 08 JAN 09 APR 09 JUL 09 OCT 09 JAN 10 APR 10 JUL 10
SABA
SABA
SABA
Figure A.8. Time series for the three components of station SABA. Light-gray vertical bars indicateperiods of unusual seismic activity on Concepcion volcano and/or near Ometepe Island, while dark-gray vertical bars represent periods of volcanic activity characterized by ash and gas explosions.SABA is located in the northeast from Concepcion volcano in the community of La Sabana, seeFigure 1.
92
Appendix A (Continued)
−50
0
50
Height(mm)
−50
0
50
Height(mm)
JAN 02 JAN 03 JAN 04 JAN 05 JAN 06 JAN 07 JAN 08 JAN 09 JAN 10
−30
−20
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0
10
Longitude
(mm)
−30
−20
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10
Longitude
(mm)
−75
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−25
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Latitude(mm)
−75
−50
−25
0
Latitude(mm)
JAN 02 JAN 03 JAN 04 JAN 05 JAN 06 JAN 07 JAN 08 JAN 09 JAN 10
SINT
SINT
SINT
Figure A.9. Time series for the three components of station SINZ. Light-gray vertical bars indicateperiods of unusual seismic activity on Concepcion volcano and/or near Ometepe Island, while dark-gray vertical bars represent periods of volcanic activity characterized by ash and gas explosions.SINT is located southeast from Concepcion volcano, in the Sintiope town, see Figure 1. In April2010 the GPS site COS1, see Figure 1, was tied to the new site SINT because a water well pumpwas built a few meters from COS1 in early 2010.
93
Appendix A (Continued)
−10
0
10
20
30
40
Long
itude
(mm)
−10
0
10
20
30
40
Long
itude
(mm)
21 28 4 11 18 25 2 9 16 23 30 6 13 20 27 4 11 18 25 1 8March April May June July August
21 28 4 11 18 25 2 9 16 23 30 6 13 20 27 4 11 18 25 1 8March April May June July August
20102010
20102010
CON1
SINT
COS2
MOYO
SABA
Figure A.10. Time series changes for the Longitude component of all stations around Concepcionvolcano during April through July 2010. Dark-gray vertical bars represent periods of volcanic ac-tivity characterized by ash and gas explosions. Time series have been offset for better visualization.
94
Appendix A (Continued)
−20
−10
0
10
20
30
40
Latitude(m
m)
−20
−10
0
10
20
30
40
Latitude(m
m)
21 28 4 11 18 25 2 9 16 23 30 6 13 20 27 4 11 18 25 1 8March April May June July August
21 28 4 11 18 25 2 9 16 23 30 6 13 20 27 4 11 18 25 1 8March April May June July August2010
2010
2010
2010
CON1
SINT
COS2
MOYO
SABA
Figure A.11. Time series changes for the Latitude component of all stations around Concepcionvolcano during April through July 2010. Dark-gray vertical bars represent periods of volcanic ac-tivity characterized by ash and gas explosions. Time series have been offset for better visualization.
95
Appendix A (Continued)
−40
0
40
80
120
160
200
Heigh
t(mm)
−40
0
40
80
120
160
200
Heigh
t(mm)
21 28 4 11 18 25 2 9 16 23 30 6 13 20 27 4 11 18 25 1 8March April May June July August
21 28 4 11 18 25 2 9 16 23 30 6 13 20 27 4 11 18 25 1 8March April May June July August 2010
2010 2010
2010
CON1
SINT
COS2
MOYO
SABA
Figure A.12. Time series changes for the vertical component of all stations around Concepcion vol-cano during April through July 2010. Dark-gray vertical bars represent periods of volcanic activitycharacterized by ash and gas explosions. Time series have been offset for better visualization.
96
Appendix A (Continued)
0
14
28
42
56
70
Latit
ude
chan
ge(m
m)
0
14
28
42
56
70
Latit
ude
chan
ge(m
m)
JAN 07 JUL 07 JAN 08 JUL 08 JAN 09 JUL 09 JAN 10 JUL 10 JAN 11 JUL 11 JAN 12
JAN 07 JUL 07 JAN 08 JUL 08 JAN 09 JUL 09 JAN 10 JUL 10 JAN 11 JUL 11 JAN 12
Mean Latitude: 12° 8' 56.186" N
MANA North component velocity 9.5 +- 0.4 mm/yr
Figure A.13. Temporal changes of Latitude component of GPS station MANA between January2007 and August 2010. This continuous site is part of International GPS Service, IGS, network,and located inside the INETER’s facilities in Managua, Nicaragua. Red line corresponds to bestlinear fit. Velocity uncertainties were computed using the Hackl et al., ( 2011) algorithm.
−8
0
8
16
24
32
40
48
Long
itude
chan
ge(m
m)
−8
0
8
16
24
32
40
48
Long
itude
chan
ge(m
m)
JAN 07 JUL 07 JAN 08 JUL 08 JAN 09 JUL 09 JAN 10 JUL 10 JAN 11 JUL 11 JAN 12
JAN 07 JUL 07 JAN 08 JUL 08 JAN 09 JUL 09 JAN 10 JUL 10 JAN 11 JUL 11 JAN 12
Mean Longitude: 86° 14' 56.372" W
MANA East component velocity 7.8 +- 0.7 mm/yr
Figure A.14. Temporal changes of Longitude component of GPS station MANA between January2007 and August 2010. This continuous site is part of International GPS Service, IGS, network,and located inside the INETER’s facilities in Managua, Nicaragua. Red line corresponds to bestlinear fit. Velocity uncertainties were computed using the Hackl et al., ( 2011) algorithm.
97
Appendix B Concepcion’s volcano gravity data
Table B.1: Gravity data gathered at Concepcion volcano,
Nicaragua, during campaigns carried out between 2007 and 2010.
Easting Northing Elevation Obs. g.a Free-airb Bullard Bc Bullard Cd Residuale
(m) (m) (m) (mGal) (mGal) (mGal) (mGal) (mGal)
642913 1275747 105.925 1589.965 0.000 0.000 0.376 0.000
643630 1275619 158.678 1578.540 4.902 0.930 1.341 -0.340
644681 1275489 140.387 1588.745 9.501 6.906 7.189 3.535
645837 1274976 198.482 1581.769 20.625 13.657 14.258 8.805
646244 1274827 229.666 1577.131 25.662 16.348 17.065 10.947
646256 1275207 231.220 1578.301 27.191 17.760 18.228 11.706
643286 1276242 145.650 1582.836 4.978 1.986 2.425 0.809
641641 1275978 38.107 1605.268 -5.707 -0.598 -0.269 1.669
644788 1276357 141.198 1591.418 12.149 9.492 9.691 4.955
645210 1277272 146.492 1595.737 17.811 14.756 15.140 8.646
645329 1276476 154.159 1594.440 19.134 15.502 15.924 9.988
645475 1276229 164.102 1593.246 21.089 16.708 16.967 10.985
644429 1278116 123.104 1597.601 12.186 10.892 11.116 5.339
643839 1279292 82.325 1608.611 10.232 12.009 12.161 6.389
644117 1278848 98.139 1604.368 11.012 11.599 12.754 6.869
644893 1279168 99.602 1605.777 12.771 13.247 13.326 5.570
644473 1274814 125.135 1588.290 4.553 3.106 3.417 0.854
643794 1274073 99.862 1589.148 -2.156 -1.699 -1.532 -1.996
642769 1273951 76.140 1592.990 -5.599 -3.355 -2.786 -1.077
644188 1273830 127.357 1582.405 -0.333 -1.947 -1.518 -2.527
Continued on Next Page. . .
98
Appendix B (Continued)
Table B.1 – Continued
Easting Northing Elevation Obs. g.a Free-airb Bullard Bc Bullard Cd Residuale
645277 1273977 141.234 1583.780 5.279 2.620 3.047 -0.286
645969 1273403 148.365 1583.388 7.272 4.076 4.562 0.418
646562 1273852 203.235 1580.839 21.520 14.194 14.484 8.705
643753 1273070 100.114 1584.683 -6.224 -5.786 -5.360 -4.739
642694 1272782 95.061 1582.966 -9.409 -8.591 -7.454 -4.426
641649 1272448 50.269 1592.642 -13.455 -9.262 -8.570 -3.119
652319 1273172 238.047 1589.819 41.464 31.520 32.017 15.404
653752 1274041 172.654 1607.606 38.785 33.761 34.233 13.886
653787 1274993 176.419 1607.043 39.082 33.774 34.328 12.958
653954 1273189 141.881 1612.601 34.551 31.843 32.345 12.445
654412 1272199 118.701 1609.772 24.881 23.918 25.067 5.242
655217 1273671 114.211 1612.886 26.140 25.516 26.351 3.444
653415 1272173 130.944 1605.552 24.449 22.565 23.376 5.570
654626 1273988 143.128 1611.556 33.637 30.835 31.112 9.069
652239 1272659 160.640 1600.205 28.115 23.995 24.404 8.464
652754 1271268 69.320 1617.875 18.035 20.792 21.512 5.934
653186 1270613 39.296 1624.024 15.123 20.143 20.583 4.796
652359 1270725 60.386 1616.705 14.280 17.710 18.237 3.991
651412 1270076 42.158 1612.330 4.484 9.288 9.909 -1.793
650697 1270751 54.765 1613.126 8.957 12.811 12.954 2.007
650015 1271178 102.493 1602.630 13.060 13.318 14.039 4.028
641870 1276813 38.704 1608.238 -2.819 2.246 2.610 3.254
642258 1276789 54.044 1605.001 -1.312 2.596 3.035 2.928
Continued on Next Page. . .
99
Appendix B (Continued)
Table B.1 – Continued
Easting Northing Elevation Obs. g.a Free-airb Bullard Bc Bullard Cd Residuale
643394 1277469 111.085 1595.530 6.610 6.221 6.870 3.810
646422 1277209 202.133 1592.392 31.664 24.421 24.715 15.859
646232 1278864 133.110 1605.009 22.445 20.397 20.560 10.430
646507 1279488 110.087 1609.302 19.431 19.118 19.403 8.098
642733 1278137 59.677 1608.877 3.873 7.357 7.902 5.496
642471 1278964 41.488 1615.808 4.926 9.781 10.179 7.471
641496 1274501 50.616 1598.321 -8.322 -4.156 -3.616 0.088
641898 1274093 59.439 1595.725 -8.065 -4.563 -3.995 -0.687
642676 1274429 74.194 1594.593 -4.749 -2.358 -1.821 -0.405
649911 1278800 261.012 1585.262 42.206 30.534 31.095 13.670
649818 1279881 153.087 1607.107 30.386 26.835 27.617 9.297
649394 1278884 223.552 1594.105 39.457 30.602 30.955 14.481
649024 1280046 136.761 1608.379 26.565 24.243 24.363 7.466
647881 1281528 38.755 1625.467 12.925 17.986 18.348 2.255
647354 1280866 54.480 1620.729 13.252 17.128 17.419 3.042
648131 1280908 57.651 1621.678 15.167 18.804 18.923 2.951
646144 1280984 42.965 1622.293 11.224 15.967 16.365 4.290
645430 1280722 41.786 1622.500 11.150 15.983 16.485 6.100
645610 1279857 102.983 1606.956 14.774 14.996 16.028 6.148
644632 1279521 88.176 1608.707 12.061 13.398 13.884 6.296
647005 1279559 104.647 1611.441 19.868 19.964 20.049 7.678
648408 1278660 219.691 1592.516 36.747 28.183 28.356 14.078
648111 1279528 132.930 1607.062 24.231 22.197 22.575 8.022
Continued on Next Page. . .
100
Appendix B (Continued)
Table B.1 – Continued
Easting Northing Elevation Obs. g.a Free-airb Bullard Bc Bullard Cd Residuale
650271 1278714 270.696 1583.122 43.083 30.683 31.483 13.424
650327 1280356 115.180 1613.526 24.951 24.254 24.319 4.507
650228 1281713 38.020 1626.057 13.229 18.345 18.636 -2.336
650789 1279590 150.529 1606.071 28.653 25.295 25.527 5.557
650825 1281527 37.810 1626.192 13.359 18.491 18.728 -3.251
651385 1280974 66.545 1618.909 15.123 18.089 18.259 -4.287
651318 1280043 112.597 1613.325 24.052 23.550 23.682 2.201
651710 1278901 195.227 1599.639 36.240 29.517 29.659 8.536
652057 1279185 149.131 1607.957 30.237 26.983 27.310 5.208
652328 1279523 112.380 1613.161 23.987 23.501 23.559 0.577
652253 1281038 72.731 1612.673 10.776 13.277 13.850 -10.496
651456 1281704 38.307 1622.873 10.137 15.231 15.507 -7.912
653233 1278845 99.901 1613.274 20.463 20.917 21.238 -2.875
652801 1278248 160.215 1605.040 31.040 26.952 28.527 5.874
653498 1279700 74.840 1612.934 12.114 14.456 14.485 -11.013
654042 1279048 83.182 1611.247 13.210 14.923 15.187 -10.748
655058 1279416 56.990 1614.218 7.978 11.664 11.867 -16.468
653960 1281249 40.047 1616.784 4.730 9.693 10.205 -17.767
653992 1276957 155.090 1602.190 27.018 23.316 23.565 -0.178
653064 1276721 258.213 1584.687 41.429 29.967 30.744 9.092
655070 1277593 95.907 1608.777 15.132 15.886 16.176 -10.360
655258 1276020 108.420 1609.460 20.178 19.990 20.474 -4.865
656070 1275199 72.781 1616.198 16.175 18.672 18.971 -7.170
Continued on Next Page. . .
101
Appendix B (Continued)
Table B.1 – Continued
Easting Northing Elevation Obs. g.a Free-airb Bullard Bc Bullard Cd Residuale
655964 1274534 78.770 1616.394 18.432 20.477 21.148 -4.116
655526 1275349 107.596 1610.858 21.536 21.410 21.800 -3.404
657696 1272613 45.825 1626.500 18.978 23.506 23.814 -2.994
656820 1273910 64.052 1619.446 17.139 20.293 22.366 -3.987
651499 1272529 177.142 1594.645 27.691 22.329 22.997 8.667
654277 1274959 142.781 1614.219 35.883 33.108 33.204 10.888
654985 1276794 120.984 1603.720 18.071 16.937 17.199 -8.368
655010 1278431 74.779 1612.348 11.913 14.259 14.481 -12.772
653990 1280460 51.830 1615.196 7.031 11.106 11.233 -16.010
656647 1279134 38.831 1615.364 3.608 8.662 9.018 -22.213
647387 1270445 58.266 1596.438 -6.553 -2.962 -2.323 -6.345
646833 1271511 95.110 1589.802 -2.153 -1.339 -1.260 -5.240
647639 1269651 39.100 1598.514 -10.141 -5.106 -4.686 -8.417
648505 1270025 54.514 1599.178 -4.837 -0.964 -0.426 -6.264
649696 1270922 104.407 1598.582 9.684 9.799 10.007 0.891
650655 1271567 131.114 1600.110 19.252 17.355 18.219 6.540
647915 1271509 126.049 1589.625 7.222 5.706 6.134 -0.008
645415 1271396 80.280 1588.394 -8.103 -6.172 -5.369 -6.398
646159 1270421 61.728 1592.115 -9.799 -6.470 -5.799 -7.341
645634 1270673 65.365 1589.852 -11.020 -7.964 -7.268 -8.012
644801 1270898 64.839 1586.911 -14.195 -11.100 -10.333 -9.635
644090 1269352 38.042 1589.827 -19.059 -13.945 -13.621 -9.956
643371 1271091 70.931 1584.328 -14.958 -12.322 -12.003 -8.638
Continued on Next Page. . .
102
Appendix B (Continued)
Table B.1 – Continued
Easting Northing Elevation Obs. g.a Free-airb Bullard Bc Bullard Cd Residuale
642328 1271172 70.007 1584.757 -14.840 -12.135 -11.603 -6.233
646589 1277167 212.413 1591.155 33.614 25.598 26.301 17.152
647474 1277059 297.922 1573.621 42.515 28.068 28.712 17.902
647832 1276928 390.459 1554.130 51.637 30.236 33.307 21.913
648253 1276619 600.936 1502.596 65.193 27.997 29.398 17.470
648838 1276259 904.131 1425.723 82.067 22.174 23.231 10.494
649071 1276172 988.414 1404.448 86.850 20.660 24.222 11.106
649504 1275934 1195.661 1349.615 96.105 14.449 16.386 2.641
649689 1275870 1311.171 1317.136 99.326 9.064 11.171 -2.880
654195 1277286 132.529 1606.946 24.705 22.701 23.167 -1.312
653552 1276794 200.131 1595.773 34.559 27.467 27.894 5.194
652722 1276558 315.535 1571.989 46.481 30.710 31.062 10.257
652199 1276348 517.477 1523.349 60.261 29.325 32.022 12.474
651927 1276374 641.580 1493.015 68.241 27.999 30.251 11.221
651470 1276382 877.125 1433.725 81.690 23.816 26.156 8.031
651087 1276267 1105.023 1374.698 93.086 18.190 20.571 3.329
650791 1276094 1329.744 1311.206 99.062 7.417 10.250 -6.229
642054 1276312 50.620 1604.202 -3.017 1.150 1.612 2.389
642825 1277534 65.194 1605.870 2.762 5.830 6.204 4.218
643751 1277432 130.432 1592.163 9.228 7.382 8.081 4.345
644710 1277695 133.897 1595.798 13.849 11.742 12.456 6.539
645458 1278102 141.585 1600.686 20.980 18.295 18.802 10.981
646174 1278762 136.546 1604.242 22.771 20.465 20.541 10.628
Continued on Next Page. . .
103
Appendix B (Continued)
Table B.1 – Continued
Easting Northing Elevation Obs. g.a Free-airb Bullard Bc Bullard Cd Residuale
646871 1279279 116.008 1610.132 22.156 21.396 21.570 9.746
647693 1279580 111.993 1610.698 21.386 20.929 21.062 7.293
648654 1279579 145.432 1606.873 27.885 24.910 25.153 9.464
649679 1279305 191.111 1600.379 35.581 29.168 29.374 11.908
650527 1279565 160.635 1604.874 30.584 26.465 26.708 7.285
651470 1279572 148.532 1605.758 27.729 24.521 24.696 3.382
652459 1279507 109.587 1613.492 23.461 23.185 23.394 0.167
653221 1279083 93.663 1612.815 18.003 18.926 19.110 -5.217
654384 1279010 83.391 1612.088 14.128 15.825 16.479 -10.103
655035 1278452 74.268 1612.854 12.255 14.640 14.891 -12.434
655104 1277798 91.092 1610.377 15.180 16.297 16.694 -10.114
654986 1276808 121.389 1604.263 18.735 17.570 17.860 -7.722
655266 1275949 107.170 1610.891 21.246 21.152 21.528 -3.757
654820 1275103 122.784 1616.851 32.296 31.026 31.550 8.004
642154 1275518 61.640 1599.114 -4.450 -1.114 -0.897 0.474
641693 1274716 50.569 1598.823 -7.903 -3.733 -3.317 -0.222
641244 1273743 46.589 1596.644 -11.001 -6.531 -6.106 -1.141
641028 1272857 44.640 1594.862 -13.103 -8.486 -8.108 -1.824
641502 1271958 53.574 1590.391 -14.530 -10.586 -10.354 -4.119
642084 1271394 63.220 1587.144 -14.619 -11.402 -10.931 -5.296
643246 1271051 74.935 1583.998 -14.039 -11.705 -10.983 -7.328
644156 1270931 76.033 1583.823 -13.837 -11.586 -10.460 -8.506
645137 1270793 62.781 1588.620 -13.088 -9.838 -9.253 -9.124
Continued on Next Page. . .
104
Appendix B (Continued)
Table B.1 – Continued
Easting Northing Elevation Obs. g.a Free-airb Bullard Bc Bullard Cd Residuale
645994 1270524 67.298 1591.515 -8.713 -5.803 -4.792 -6.106
647431 1270062 49.779 1597.669 -7.820 -3.590 -2.934 -6.661
648460 1270066 55.295 1600.025 -3.762 0.052 0.702 -5.087
649264 1270361 94.799 1594.899 3.214 4.052 4.264 -3.426
650015 1271176 103.202 1602.630 13.279 13.485 14.305 4.297
650981 1271914 147.885 1599.511 23.720 20.561 21.159 8.479
652067 1273050 214.720 1593.338 37.820 29.630 30.239 14.252
652942 1273572 220.145 1596.149 42.140 33.542 34.234 15.976
653695 1274056 177.736 1606.313 39.056 33.650 34.185 13.936
654604 1274926 130.870 1616.448 34.446 32.567 32.684 9.748
650023 1278477 314.573 1576.688 50.272 34.573 34.932 17.606
649793 1278190 417.957 1551.537 57.133 33.667 34.972 18.393
649903 1277780 569.667 1515.270 67.842 32.991 33.781 17.392
645908 1274484 187.059 1586.424 21.910 15.801 16.569 11.466
646052 1273972 183.461 1585.696 20.234 14.396 15.495 10.617
646524 1273918 210.365 1583.178 26.039 18.177 18.901 13.132
646997 1274043 259.213 1575.810 33.713 22.176 24.873 18.033
647586 1274552 352.700 1559.193 45.798 27.234 29.744 21.217
647894 1274524 393.456 1550.621 49.819 28.193 31.250 22.135
648485 1274761 546.264 1516.595 62.902 29.805 31.946 21.412
649100 1274976 793.274 1457.959 80.475 28.874 34.493 22.514
640845 1274192 41.655 1602.394 -6.917 -2.075 -1.611 3.704
640440 1273708 38.881 1601.535 -8.479 -3.428 -2.983 3.626
Continued on Next Page. . .
105
Appendix B (Continued)
Table B.1 – Continued
Easting Northing Elevation Obs. g.a Free-airb Bullard Bc Bullard Cd Residuale
641153 1273889 46.878 1600.776 -6.827 -2.378 -1.842 3.160
639678 1272584 38.268 1600.381 -9.464 -4.367 -3.987 5.270
641915 1272041 55.157 1594.076 -10.383 -6.558 -5.961 -0.635
642140 1272076 61.462 1589.569 -12.954 -9.605 -8.600 -3.759
642737 1272214 98.542 1580.712 -10.408 -9.852 -7.991 -4.483
642724 1271820 81.336 1583.638 -12.668 -10.816 -8.954 -5.024
642199 1271745 59.380 1589.229 -13.831 -10.325 -9.661 -4.606
648389 1272059 163.277 1587.878 16.793 12.475 13.434 5.794
648689 1272962 244.662 1575.685 29.440 18.997 19.488 10.346
648760 1273693 344.361 1557.201 41.505 23.567 24.947 14.931
648773 1274013 410.686 1542.998 47.679 24.758 26.112 15.750
648920 1274244 466.839 1530.713 52.659 25.522 26.490 15.602
642775 1271698 68.205 1586.270 -14.051 -11.210 -10.650 -6.701
643326 1272180 84.868 1584.047 -11.284 -9.697 -9.101 -6.736
644286 1272332 90.152 1585.341 -8.406 -7.218 -6.543 -6.248
643807 1273113 101.761 1584.583 -5.829 -5.516 -5.086 -4.615
644311 1273696 144.993 1577.486 0.235 -2.707 -1.192 -2.314
645585 1273936 152.678 1582.705 7.750 4.230 4.807 0.899
646053 1273726 166.147 1583.262 12.533 7.998 8.595 3.959
646308 1273481 164.033 1584.805 13.501 9.126 9.564 4.664
642664 1274217 74.511 1593.780 -5.396 -3.030 -2.370 -0.718
652090 1273441 278.896 1580.770 44.942 31.925 33.133 16.710
651427 1273525 309.475 1571.303 44.889 29.573 30.077 14.895
Continued on Next Page. . .
106
Appendix B (Continued)
Table B.1 – Continued
Easting Northing Elevation Obs. g.a Free-airb Bullard Bc Bullard Cd Residuale
651210 1273981 454.333 1537.190 55.358 29.160 31.431 16.227
651137 1274268 581.557 1505.984 63.346 27.603 29.776 14.433
aObserved gravity corrected for earth solid tide and instrumental drift (mGal).
bFree-air gravity anomaly (mGal).
cSimple Bouguer anomaly (mGal).
dComplete Bouguer anomaly, terrain corrected (mGal).
eResidual gravity anomaly left after removal of the regional field (mGal).
107
Appendix C PERL script to compute the complete terrain correction for gravity data
## PERL SCRIPT TO COMPUTE THE TERRAIN CORRECTION OF GRAVITY DATA
## BY J. A. SABALLOS, USF-GEOLOGY-VOLCANO GROUP
##
## The terrain correction (TC) is implemented in three stages,
## described below:
##
## 1] Inner TC up to Hammer’s zone C, 53.3 m using the quarter-wedge
## method described by Nowel (1999, JAG), which is an improved
## version of the Campbell (1980, Geophysics) technique.
##
## 2] Intermediate TC from Hammer’s zone D up to a desired distance,
## e.g Hammer’s zone K, but it’s up to the user. This stage is done
## using the simplified gravity attraction of a prism approximated as
## an annular ring, described by Kane (1962, Geophysics). This
## method computes the TC much faster than the Plouff (1976) or
## Nagy (1966) methods that consist of up to 24 terms per prism,
## while Kane (1962) is just a single equation with 4 terms.
##
## 3] Far-field or Outer TC, for distances beyond the the Intermediate
## TC up to the extent of the input DEM. This stage is done using
## the vertical line mass described by Blais & Ferland (1984, CJES),
## which is the simplified approximation of the gravity attraction of a
## prism in the far-field
##########################################################
## INPUT DEM format: It must be a 3-column file like this:
108
Appendix C (Continued)
## Column 1: X-UTM coordinate in meters.
## Column 2: Y-UTM coordinate in meters.
## Column 3: elevation in meters.
##
## INPUT Gravity data file: It is a 4-column file format like this
## Column 1: X-UTM station coordinate in meters.
## Column 2: Y-UTM station coordinate in meters.
## Column 3: Bouguer anomaly to be terrain corrected in milli Gals.
## Column 4: satation elevation in meters.
##########################################################
#!/usr/bin/perl
##
######## NAME OF INPUT DEM FILE IN THE NEXT LINE #########
$in_dem="dem.xyz"; # Replace ’dem.xyz’ by your input DEM file name.
##
####### NAME OF INPUT Gravity FILE IN THE NEXT LINE #########
$in_grav="gravity.dat"; #GRAVITY FILE to be terrain corrected (mGals)
##
### NAME OF THE OUTPUT GRIDDED FILE IN THE NEXT LINE ####
$out_cor="terrain_corrections.dat"; # Output file containing the TCs
##
## FORMAT OF THIS OUTPUT FILE:
## Column 1: X-UTM COORDINATE in meters
## Column 2: Y-UTM COORDINATE in meters
## Column 3: Complete Bouguer anomaly, Bullard-C, i.e., gravity
## input data + terrain corrections (mGals)
109
Appendix C (Continued)
## Column 4: Terrain Correction only in mGals
##
##########################################################
############### DEFINING GLOBAL CONSTANTS ##############
##########################################################
$rho=1764; ## TERRAIN’S DENSITY IN kg/m^3 #
$near=53.3; # Maximum extent of the inner terrain zone (m) #
$far=10E+3; # Distance considered to be the far field for outer TC (m)
$gamma=6.672E-11; ## Universal Grav. Const. in m^3/(Kg s^2)
$pi=atan2(1,1)*4;
##
#########################################################
######## THE SCRIPT IS GONNA TAKE IT FROM HERE #########
#########################################################
use Math::Trig;
$dem_ct=0;
print"Getting DEM data...\n";
open(DEM,"$in_dem") || die "WRONG input DEM file name: $in_dem";
## GETTING THE DEM DATA ONLY ##
while(<DEM>)
{
($dx, $dy, $dz)=split " ", $_;
$x_dem[$dem_ct]=$dx;
$y_dem[$dem_ct]=$dy;
if($dz <= 0)
{
110
Appendix C (Continued)
$z_dem[$dem_ct]=0;## CHANGE THIS ACCORDINGLY ##
}
if($dz > 0)
{
$z_dem[$dem_ct]=$dz;
}
$dem_ct++;
}
close(DEM);
print"DEM data read successfully\n";
print"the DEM contains $dem_ct points\n";
#
## LET’S COMPUTE THE DEM "X & Y" RESOLUTION ##
$resx=$resy=0;
$ix=1; # Inner counter in X-direction DEM #
$iy=1; # Inner counter in Y-direction DEM #
# For "X" #
until($resx != 0)
{
$resx = $x_dem[$ix] - $x_dem[$ix-1];
if($resx < 0) { $resx = $resx*(-1);}
$ix++;
}
# For "Y" #
until($resy != 0)
{
111
Appendix C (Continued)
$resy = $y_dem[$iy] - $y_dem[$iy-1];
if($resy < 0) { $resy = $resy*(-1);}
$iy++;
}
print"DEM X-resolution at element $ix-1: $resx (m)\n";
print"DEM Y-resolution at element $iy-1: $resy (m)\n";
#########################################################
##### Getting gravity station data & terrain-uncorrected gravity
## INPUT FILE FORMAT PER COLUMN:
## Column 1: X-UTM (m)
## Column 2: Y-UTM (m)
## Column 3: Elevation (m)
## Column 4: Terrain-uncorrected gravity data (mGals)
#########################################################
open(GRAV,"$in_grav") || die "WRONG GRAVITY file name: $in_grav";
$gra_ct=0;
print"\nGetting gravity data now...\n";
while(<GRAV>)
{
($gx, $gy, $gg, $gz, $ds)=split " ", $_;
$x_st[$gra_ct]=$gx; # Grav. station X-coord (m) #
$y_st[$gra_ct]=$gy; # Grav. station Y-coord (m) #
$g_unc[$gra_ct]=$gg;# Bullard B anomaly #
$z_st[$gra_ct]=$gz; # Grav. station elevation #
$site[$gra_ct]=$ds; # Grav. station ID #
$gra_ct++;
112
Appendix C (Continued)
}
close(GRAV);
print"A total of $gra_ct gravity data points were read successfully.\n";
##
print"Computing the terrain corrections, please be patient...\n";
##### COMPUTING THE TERRAIN CORRECTION #########
for($i3=0; $i3 < $gra_ct; $i3++)
{
$sum_1=$sum_2=$sum_3=0; # For inner , Far & intermediate TCs
for($ct4=0;$ct4 < ($dem_ct-1); $ct4++) ## DEM COUNTER ##
{
$deltax2 = ($x_st[$i3]-$x_dem[$ct4])**2;
$deltay2 = ($y_st[$i3]-$y_dem[$ct4])**2;
$H_rad=sqrt($deltax2 + $deltay2); #2-D distance#
if( ($H_rad <= $near) && ($H_rad > 0) )## INNER TC ##
{
$dist_3D=sqrt(($H_rad**2) +(($z_st[$i3]-$z_dem[$ct4])**2));
$g_inner=0.5*$pi*$gamma*$rho*$H_rad*($dist_3D-$H_rad)/
$dist_3D;
$sum_1+=$g_inner;
}# if, $R <= $near #
##
if ($H_rad >= $far) # Far distance outer TC #
{
113
Appendix C (Continued)
$xarea=$resy*$resx; # xs-sect. area of the DEM prism #
$d3=sqrt((($H_rad**2) + ($z_st[$i3]-$z_dem[$ct4])**2));
$far_c=$gamma*$rho*$xarea*((1/$H_rad)-(1/$d3));
$sum_3+=$far_c; # Terrain correction for far distances #
}
if (($H_rad < $far) && ($H_rad > $near)) # Interm. outer TC #
{
$side=sqrt(($resy**2)+($resx**2));
$R_minus = $H_rad-(0.63*$side);
$R_plus = $H_rad+(0.63*$side);
$hgt = $z_st[$i3]-$z_dem[$ct4]; # elevation diff. #
$numerator1 = (1.26*$side) + sqrt(($R_minus**2)+
($hgt**2)) - sqrt(($R_plus**2) +
($hgt**2));
$g_int = $gamma*$rho*$side*$numerator1*1E+5/(1.26*$H_rad);
$sum_2+=$g_int; # Intermmediate TC in mGals #
} ## if, ($H_rad < $far) && ($H_rad > $near) ##
} # ’ct4’ for ##
$inner_cor[$i3]= $sum_1*1E+5; # Near-field TC #; ## INNER TC ##
$inter_cor[$i3]= $gamma*$rho*$sum_2*1E+5;# INTERMEDIATE TC
to# Conversion mGals #
$outer_cor[$i3]= $sum_3*1E+5; # Far-field TC ## FAR OUTER TC
} # for($i3 #
##############################################################
################### GENERATING OUTPUT FILE##################
114
Appendix C (Continued)
##############################################################
open(CORR,">$out_cor");
print CORR "#X-UTM Y-UTM Complete_B_anomaly(mGal) inner_TC(mGal)
interm_TC(mGal) Outer_TC(mGal) site\n";
for($ct3=0;$ct3 < $gra_ct; $ct3++) ## GRAV. STATIONS COUNTER ##
{
## Complete CORRECTED Bouguer Anomaly ##
$BC_cor[$ct3]=$g_unc[$ct3] + $outer_cor[$ct3] + $inter_cor[$ct3] +
$inner_cor[$ct3];
print CORR "$x_st[$ct3] $y_st[$ct3] $BC_cor[$ct3] $inner_cor[$ct3]
$inter_cor[$ct3]
$outer_cor[$ct3] $site[$ct3]\n";
}
close(CORR);
print"Terrain correction computations are DONE!!\n";
print"The output file you’ve been waiting for is: $out_cor\n\n";
##################### END OF SCRIPT ##########################
115
Appendix D Supplementary figures for Chapter 3
0 5 10 15 20 25 30 35 40 450
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GPS data, 2010
GPS data, 2011
Figure D.1. Periodograms for GPS baseline changes during 2010 and 2011. Upper panel : Longperiodogram. Bottom panel : Fifteen-day periodogram to better appreciate the short term period-icity.
116
Appendix D (Continued)
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RSAM data, 2010
RSAM data, 2011
Figure D.2. Periodograms for RSAM daily average during 2010 and 2011. Upper panel : Long pe-riodogram. Bottom panel : Fifteen-day periodogram to better appreciate the short term periodicity.
117
Appendix D (Continued)
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SO2
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Period (days)
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SO2
data, 2010
SO2
data, 2011
Figure D.3. Periodograms for SO2 daily average during 2010 and 2011. Upper panel : Long peri-odogram. Bottom panel : Fifteen-day periodogram to better appreciate the short term periodicity.
118
Appendix D (Continued)
−20 −15 −10 −5 0 5 10 15
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GPS baseline change (mm)
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E F
A B
C D
2010
2010
2010
2011
2011
2011
Figure D.4. Scatter plots of the data used in this study. For clarity error bars were not plotted. Allthe 2011 data go from February 4 through April 16, a period when the volcano was not erupting.(A) GPS baseline changes versus RSAM daily average. The 2010 data go from April 08 throughJune 25. The largest positive GPS baseline changes corresponds to the largest RSAM values, those>83 RSAM units. Amplitude in GPS baseline change is 29 mm. (B) GPS baseline changes versusRSAM daily average for the 2011 period. Amplitude in GPS baseline change is 18 mm (when thevolcano was not erupting), which is 11 mm less than the amplitude observed in 2010 during thefinal phase of the volcano’s most recent erupting activity. There is not any clear correspondencebetween the 2011 GPS and RSAM data. (C) GPS baseline changes versus SO2 fluxes. These datago from April 28 through June 24 2010. All SO2 fluxes > 350 tons/day correspond to positivevalues of GPS baseline changes. (D) GPS baseline changes versus SO2 fluxes for the 2011 period.SO2 fluxes decreased by 52% with regard to the 2010 period. (E) SO2 versus RSAM daily average.The 2010 data go from April 28 through June 24. SO2 fluxes > 300 tons/day are associated withRSAM values > 70 units. (F) SO2 versus RSAM daily average for the 2011 period. There is notany clear correspondence between the 2011 SO2 and RSAM data.
119
ABOUT THE AUTHOR
Jose Armando Saballos was born in Belen, Rivas, Nicaragua. He received his Bachelor in
Physics, with a minor in Geophysics from Universidad Nacional Autonoma de Nicaragua, Man-
agua, in 2002. Later that year he got a scholarship from the Department of International Develop-
ment of the UK to undertake a Master’s in Environmental Monitoring, Modeling and Management
of the Environmental change at King’s College London, University of London, and graduated in
2003. Later in 2007 he joined the Department of Geology at the University of South Florida
(USF) to began a PhD under the supervision of Professor Charles B. Connor and Professor Rocco
Malservisi on the application of Geophysics techniques to study short– and long–term behavior of
Concepcion volcano in Nicaragua, while working as a teaching assistance in the Geology Depart-
ment at USF. He participated on several field trips and conferences in Nicaragua, Costa Rica and
the USA. Mr. Saballos has published several papers in international journals and was awarded two
mini–grants from the USF Institute for the Study of Latin America and the Caribbean (2009 and
2010) two support part of his field trips.
