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Geographical Distribution of Disasters Caused by Natural Hazards in Data-scarce Areas: Methodological exploration on the Samala River catchment, Guatemala
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. (CNDS)ORCID iD: 0000-0003-0908-7176
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

An increasing trend in both the number of disasters and affected people has been observed, especially during the second half of the 20th century. The physical, economic and social impact that natural hazards have had on a global scale has prompted an increasing interest of governments, international institutions and the academia. This has immensely contributed to improve the knowledge on the subject and has helped multiply the number of initiatives to reduce the negative consequences of natural hazards on people. The scale on which studies supporting disaster risk reduction (DRR) actions are performed is a critical parameter. Given that disasters are recognized to be place-dependent, studying the geographical distribution of disasters on a local scale is essential to make DRR practical and feasible for local authorities, organizations and civilians. However, studying disasters on the local scale is still a challenge due to the constraints posed by scarce data availability. Social vulnerability in many disaster-prone areas is however a pressing issue that needs to be swiftly addressed despite of the many limitations of data for such studies.

This thesis explored methodological alternatives to study the geographical distribution of natural disasters and their potential causes in disaster-prone and data-scarce areas. The Samala River catchment in Guatemala was selected as a case study, which is representative of areas with high social vulnerability and data scarcity.  Exploratory methods to derive critical disaster information in such areas were constructed using the geographical and social data available for the study area. The hindrances posed by the available data were evaluated and the use of non-traditional datasets such as nightlights imagery to complement the available data were explored as a way of overcoming the observed limitations.

The exploratory methods developed in this thesis aim at (a) deriving information on natural disasters under data-scarce circumstances, (b) exploring the correlation between the spatial distribution of natural disasters and the physical context in order to look for causalities, (c) using open data to study the social context as a potential cause of disasters in data-scarce areas, and (d) mapping vulnerabilities to support actions for disaster risk reduction. Although the available data for the case study was limited in quantity and quality and many sources of uncertainty exist in the proposed methods, this thesis argues that the potential contribution to the development of DRR on a local scale is more important than the identified drawbacks. The use of non-traditional data such as remotely sensed imagery made it possible to derive information on the occurrences of disasters and, in particular, causal relationships between location of disasters and their physical and social context.

Abstract [es]

El número de desastres y personas afectadas por esos desastres en el mundo han mostrado una tendencia creciente, especialmente en la segunda mitad del siglo veinte. El impacto físico, económico y social que las amenazas naturales han causado a nivel global ha causado que gobiernos, instituciones internacionales y la academia se interesen cada vez más en los desastres causados por esas amenazas. Este interés ha contribuido a mejorar el conocimiento existente sobre desastres y ha contribuido a multiplicar las iniciativas orientadas a reducir sus efectos negativos en las personas. La escala en la cual las iniciativas para la reducción del riesgo de desastres (RRD) se llevan a cabo es un parámetro crítico para su materialización. Hoy en día se reconoce la estrecha relación que existe entre los desastres y los lugares donde éstos se registran. Por esta razón, estudiar la distribución de los desastres en una escala local es esencial para que la RRD sea práctica y factible para autoridades y organizaciones locales, y también para la sociedad civil. Sin embargo, estudiar los desastres en una escala local es aún un problema por resolver debido a las restricciones impuestas por la escasa disponibilidad de datos de alta resolución. A pesar de las dificultades y limitaciones identificadas, la vulnerabilidad social en las regiones propensas a desastres es un problema importante que necesita ser atendido con prontitud.

La presente tesis exploró alternativas metodológicas para estudiar la distribución geográfica de los desastres naturales y sus causas potenciales, particularmente en áreas propensas a desastres y en condiciones de información limitada. La cuenca del Río Samalá fue seleccionada como caso de estudio debido a que es un área representativa de áreas propensa a desastres con alta vulnerabilidad social y además escasez de datos. El trabajo de investigación propone métodos exploratorios para extraer información crítica sobre desastres utilizando la información geográfica y social que esté disponible, evaluando los obstáculos impuestos por la reducida disponibilidad de datos. La información existente fue complementada con el uso de fuentes de información no tradicional, e.g. imágenes satelitales de luces nocturnas, como una manera de superar las limitaciones identificadas.

Los métodos desarrollados en este trabajo de tesis tuvieron como objetivos (a) obtener información sobre desastres naturales en condiciones de escasez de datos, (b) explorar la correlación entre la distribución espacial de los desastres naturales y su contexto físico para identificar causalidades, (c) utilizar información de libre acceso para estudiar el contexto social de los desastres como causa potencial de los desastres en áreas con escasez de datos, y (d) mapear vulnerabilidades para sustentar acciones para la RRD. Este trabajo de tesis sostiene que la contribución potencial de los métodos propuestos al desarrollo de la RRD en la escala social es más importante que las incertidumbres que implican y las limitaciones creadas por la reducida calidad y cantidad de información para el caso de estudio. El uso de fuentes de información no tradicionales tales como imágenes satelitales hizo posible incrementar la información sobre las incidencias de desastres y, en particular, buscar relación de dependencia entre los lugares particulares en los que los desastres fueron registrados y su contexto físico y social.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2015. , 77 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1275
Keyword [en]
natural disasters, Guatemala, data-scarce areas, natural disaster science methods, natural disaster maps
National Category
Geosciences, Multidisciplinary
Research subject
Earth Science with specialization in Physical Geography
Identifiers
URN: urn:nbn:se:uu:diva-260708ISBN: 978-91-554-9310-3 (print)OAI: oai:DiVA.org:uu-260708DiVA: diva2:848061
Public defence
2015-10-09, Hambergsalen, Villavägen 16, Uppsala, 10:00 (English)
Opponent
Supervisors
Funder
Sida - Swedish International Development Cooperation Agency, 54100006
Available from: 2015-09-17 Created: 2015-08-24 Last updated: 2015-10-01
List of papers
1. Deriving information on disasters caused by natural hazards from limited data: a Guatemalan case study
Open this publication in new window or tab >>Deriving information on disasters caused by natural hazards from limited data: a Guatemalan case study
2015 (English)In: Natural Hazards, ISSN 0921-030X, E-ISSN 1573-0840, Vol. 75, no 1, 71-94 p.Article in journal (Refereed) Published
Abstract [en]

This work proposes a method to overcome data limitations encountered when analyzing disasters at a local scale in disaster-prone areas. Research is required to understand the processes underlying the disasters in disaster-prone areas. However, many such areas lack sufficient data for the statistically significant studies that would strongly support disaster risk-reduction measures. Disasters are studied extensively at the national scale, but local-scale disaster research is greatly needed, specifically because the hazard exposures and vulnerabilities of populations are mainly site specific. The proposed method compiles data using two databases: the System of Information Management in case of Emergency or Disaster (SISMICEDE) and the Disaster Inventory System (DesInventar). SISMICEDE has a short time span and high spatial resolution, while DesInventar has a longer time span but low spatial resolution. SISMICEDE’s spatial distribution was used to sort DesInventar disaster data, analyzing them spatially and temporally at a local scale. The Samala River basin in Guatemala was selected to exemplify a disaster-prone area for which there are insufficient disaster data. The results indicate that it was useful to combine the two databases to optimally describe disasters over time and space in the studied area. The refinement of the disaster data highlighted the discrepancies between administrative boundaries and local particularities. The results indicate that the municipal scale is too sparse for spatial analyses and that specific location details are needed. According to the limited data available, disasters, during the rainy season, are increasing over time in the study area. This work demonstrates a way to perform local-scale disaster studies of areas for which data are not readily available. These local-scale studies would enable research and actions intended to improve disaster risk-reduction management and measures. This study could also help promote an improved information system in Guatemala that includes complete information useful for emergency response and post-disaster analyses.

Place, publisher, year, edition, pages
Springer Netherlands, 2015
Keyword
Disaster data analyses, Disaster temporal and spatial analyses, Guatemala, Disaster data compilation, Local scale
National Category
Physical Geography
Research subject
Administrative Law
Identifiers
urn:nbn:se:uu:diva-241471 (URN)10.1007/s11069-014-1305-2 (DOI)000345971600005 ()
Funder
Sida - Swedish International Development Cooperation Agency
Available from: 2015-01-12 Created: 2015-01-12 Last updated: 2017-12-05Bibliographically approved
2. Spatial Distribution of Disasters Caused by Natural Hazards in the Samala River Catchment, Guatemala
Open this publication in new window or tab >>Spatial Distribution of Disasters Caused by Natural Hazards in the Samala River Catchment, Guatemala
2015 (English)In: Geografiska Annaler. Series A, Physical Geography, ISSN 0435-3676, E-ISSN 1468-0459, Vol. 97, no 1, 181-196 p.Article in journal (Refereed) Published
Abstract [en]

Understanding the conditions of the locations where disasters are reported and applying that knowledge to disaster risk reduction actions is essential and especially needed on the local scale. This study assessed how important the physical configuration is as cause of disasters by studying the links between the locations where disasters have been reported and the physical attributes of those locations. The Samala River catchment in Guatemala was used as a case study because it is a relatively small but complex area exposed to multiple natural hazards. Disasters of hydro-meteorological origin were addressed for the study because they are the most frequent type of disasters reported in the area. The method proposed in this work classified the study area into geomorphological units that were used to analyze where disasters were reported, the physical conditions of the particular locations of disaster reports, and to what degree disasters are spatially linked to slope and temporally to precipitation. We found that analyzing the study area based on the geomorphological configuration was useful and allowed analyses on comparatively homogeneous zones and to hypothesize on the particular geomorphological processes related to the occurrences of disasters. For steep geomorphological units we found a clear spatial relationship between the number of disasters reported and the slope of the locations, with higher frequency of disasters in the less sloping areas of the unit. The need to consider social factors for understanding this relationship was emphasized. As expected there was a very strong temporal relationship between disaster occurrence and wetness, as estimated from the antecedent rainfall, with high risk for disaster at high wetness. The applied methodological approach provides a tool for disaster research on physically complex areas, which is common to active tectonic and volcanic regions.

Keyword
spatial distribution, natural disasters, physical causes of natural disasters, Guatemala
National Category
Physical Geography
Identifiers
urn:nbn:se:uu:diva-251500 (URN)10.1111/geoa.12097 (DOI)000350500400012 ()
Available from: 2015-04-23 Created: 2015-04-20 Last updated: 2017-12-04Bibliographically approved
3. Remotely Sensed Nightlights to Map Societal Exposure to Hydrometeorological Hazards
Open this publication in new window or tab >>Remotely Sensed Nightlights to Map Societal Exposure to Hydrometeorological Hazards
2015 (English)In: Remote Sensing, ISSN 2072-4292, E-ISSN 2072-4292, Vol. 7, no 9, 12380-12399 p.Article in journal (Refereed) Published
Abstract [en]

This study used remotely sensed maps of nightlights to investigate the etiology of increasing disaster losses from hydrometeorological hazards in a data-scarce area. We explored trends in the probability of occurrence of hazardous events (extreme rainfall) and exposure of the local population as components of risk. The temporal variation of the spatial distribution of exposure to hydrometeorological hazards was studied using nightlight satellite imagery as a proxy. Temporal (yearly) and spatial (1 km) resolution make them more useful than official census data. Additionally, satellite nightlights can track informal (unofficial) human settlements. The study focused on the Samala River catchment in Guatemala. The analyses of disasters, using DesInventar Disaster Information Management System data, showed that fatalities caused by hydrometeorological events have increased. Such an increase in disaster losses can be explained by trends in both: (i) catchment conditions that tend to lead to more frequent hydrometeorological extremes (more frequent occurrence of days with wet conditions); and (ii) increasing human exposure to hazardous events (as observed by amount and intensity of nightlights in areas close to rivers). Our study shows the value of remote sensing data and provides a framework to explore the dynamics of disaster risk when ground data are spatially and temporally limited.

Keyword
Natural disasters trends, nighttime satellite images, nightlights, exposure mapping, local scale, Guatemala
National Category
Geosciences, Multidisciplinary
Identifiers
urn:nbn:se:uu:diva-260706 (URN)10.3390/rs70912380 (DOI)000362511400065 ()
Funder
Sida - Swedish International Development Cooperation Agency, 54100006
Available from: 2015-08-24 Created: 2015-08-24 Last updated: 2017-12-04Bibliographically approved
4. A Simple Method to Map Spatial Vulnerability and Support Crisis Management
Open this publication in new window or tab >>A Simple Method to Map Spatial Vulnerability and Support Crisis Management
(English)Manuscript (preprint) (Other academic)
Keyword
Spatial vulnerability, vulnerability map, vulnerability geographical distribution
National Category
Geosciences, Multidisciplinary
Identifiers
urn:nbn:se:uu:diva-260707 (URN)
Funder
Sida - Swedish International Development Cooperation Agency, 54100006
Available from: 2015-08-24 Created: 2015-08-24 Last updated: 2015-10-01

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