-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathlahars.html
More file actions
executable file
·177 lines (161 loc) · 6.88 KB
/
lahars.html
File metadata and controls
executable file
·177 lines (161 loc) · 6.88 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
<!DOCTYPE HTML>
<html>
<head>
<title>Gustavo Bejar</title>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1, user-scalable=no" />
<link rel="stylesheet" href="assets/css/main.css" />
</head>
<body class="is-preload">
<!-- Header -->
<header id="header">
<div class="inner">
<a href="index.html" class="image avatar"><img src="images/avatar.jpg" alt="" /></a>
<h1><strong>Hola, I'm Gustavo</strong></h1>
Visiting Assistant Professor at Albion College
</div>
</header>
<!-- Main -->
<div id="main">
<!-- One -->
<section id="one">
<header class="major">
<h2>🌋 Volcán de Fuego Lahars</h2>
</header>
<p>As part of my PhD, I study lahars, fast-moving volcanic flows
that threaten communities like those around Volcán de Fuego in Guatemala.
I focus on three main tasks: 1) describing the seismology
of these flows to develop machine learning-based lahar detectors,
2) estimating predictors for lahar initation and flow behavior
based on rainfall data, and 3) numerical lahar flow models.
Click below to learn more about my work. </p>
<p> Check the pre-print from this work in the link below.</p>
<ul class="actions">
<li><a href="https://doi.org/10.22541/essoar.174835401.10991195/v1"
class="button icon solid fa-book">Link to
Pre-print</a></li>
</ul>
</section>
<!-- Two -->
<section id="two">
<h2>1. LaharML: A Machine Learning-Based Flow Detector</h2>
<div class="box alt">
<div class="row gtr-50 gtr-uniform">
<div class="col-12"><span class="image fit no-overlay"><img src="images/lahar_1.jpeg"
alt="" /></span>
</div>
</div>
</div>
<p>Lahars are a family of volcanic sediment-laden flows that threaten
communities around active volcanoes. They are difficult to detect and monitor, especially in remote
areas.
We developed a machine learning-based lahar detector that uses seismic data to identify lahars in
real-time.
The model is trained on a large dataset of seismic signals from lahars and other volcanic processes, and
it can
detect lahars with high accuracy. The model is currently being tested at Volcán de Fuego in Guatemala
thanks
to a collaboration with the local agency INSIVUMEH.
</p>
<p>
The figure above illustrates the operation of the detector. This is K-Nearest Neighbors (KNN) model that
classifies real-time data depending on their similarity to a training set of seismic signals.
To do this, it extracts features that describe the signal in the time and frequency domains, power
ratios, and
statistical functions. These features are samples from windowed data and the results undergo a
post-processing
validation that reduces erroneous classifications and returns lahar activity intervals.
</p>
<p>
This tool is currently being tested at Volcán de Fuego via INSIVUMEH. In addition, the methodology is
being adapted to work with lahars at Santiaguito, and other types of flows such as pyroclastic density
current.
Furthermore, this work is currently in the process of submission for peer-review.
</p>
</section>
<!-- Three -->
<section id="three">
<h2>2. Rainfall controls on lahar generation and propagation</h2>
<div class="box alt">
<div class="row gtr-50 gtr-uniform">
<div class="col-12"><span class="image fit no-overlay"><img src="images/lahar_2.jpeg"
alt="" /></span>
</div>
</div>
</div>
<p>Lahar activity at Volcán de Fuego is strongly influenced by rainfall. Because these flows are typically
triggered during intense or prolonged rainfall events, understanding precipitation patterns is key to
improving lahar forecasts and hazard mitigation. We are exploring how both the occurrence and physical
characteristics of lahars respond to rainfall input, using rain gauge measurements and seismic data from
stations along the lahar pathways.</p>
<p>
The figure above shows a comparison between rainfall accumulation and seismic lahar detections over a
multi-year period. Each colored dot represents a detected lahar, with its position corresponding to
cumulative rainfall, flow duration (left), or seismic energy (right). We observe that lahars tend to
cluster during the rainy seasons, and their intensity—measured here as flow duration or energy—generally
scales with the amount of antecedent rainfall. This suggests a threshold behavior where wetter
conditions not only make lahars more likely but also influence their dynamics and size. Ongoing work is
focused on deriving intensity–duration thresholds and exploring how rainfall structure (e.g. bursts vs.
steady rain) controls lahar evolution.
</p>
</section>
<!-- Four -->
<section id="four">
<header>
<h2>3. Lahar flow modeling and comparison with geophysical data</h2>
<p>Coming soon</p>
</header>
</section>
<!-- End -->
<section id="end">
<h2>Get In Touch</h2>
<div class="row">
<div class="col-12 col-12-small">
<ul class="labeled-icons">
<li>
<h3 class="icon solid fa-building"><span class="label">Address</span></h3>
Albion College<br />
Palenske 126<br />
611 E Porter St<br />
Albion, MI 49224<br />
United States
</li>
<li>
<h3 class="icon solid fa-envelope"><span class="label">Email</span></h3>
<a href="mailto:gbejar@albion.edu">gbejar@albion.edu</a>
</li>
</ul>
</div>
</div>
</section>
</div>
<!-- Footer -->
<footer id="footer">
<div class="inner">
<ul class="icons">
<li><a href="https://www.instagram.com/gbejarl" class="icon brands fa-instagram"><span
class="label">Instagram</span></a></li>
<li><a href="https://www.linkedin.com/in/gbejarl" class="icon brands fa-linkedin"><span
class="label">Linked-In</span></a></li>
<li><a href="https://www.github.com/gbejarl" class="icon brands fa-github"><span
class="label">Github</span></a></li>
<li><a href="https://www.youtube.com/gbejarl" class="icon brands fa-youtube"><span
class="label">YouTube</span></a></li>
<li><a href="mailto:gbejar@albion.edu" class="icon solid fa-envelope"><span
class="label">Email</span></a></li>
</ul>
<ul class="copyright">
<li>© Gustavo Bejar, 2025</li>
<li>Design: <a href="http://html5up.net">HTML5 UP</a></li>
</ul>
</div>
</footer>
<!-- Scripts -->
<script src="assets/js/jquery.min.js"></script>
<script src="assets/js/jquery.poptrox.min.js"></script>
<script src="assets/js/browser.min.js"></script>
<script src="assets/js/breakpoints.min.js"></script>
<script src="assets/js/util.js"></script>
<script src="assets/js/main.js"></script>
</body>
</html>