Abstract
The Digital Elevation Model (DEM) is one of the most important inputs when working on computer simulations to define areas potentially affected by gravity-driven flow hazards. Sometimes there is only one DEM available in the study area, although nowadays the availability of several different DEMs of varying resolutions and precision is more frequent, the characteristics of which are not necessarily familiar for the users. This availability may increase during emergency events in high-risk areas where updated and more precise DEMs may be calculated every few months using less expensive and more advanced methods. In order to design gravity-driven flow hazard maps, it is critical to understand the changes that may be taking place in computer simulations that use various DEMs to get a general understanding, for example, of the drainage network representation or how resolution changes may make the flow paths differ and how this may affect the interpretation of existing hazard maps that may be enhanced with the new DEM and cartography-base maps. To support researchers in these tasks, a simple and flexible ANSI C software tool called MDTanaliza has been developed. The aim of this tool is to analyze all possible gravity-driven flow paths, recreating former or new morphologies and calculating various different basic morphometric parameters in order to understand and compare the DEMs available in a study area. We have also developed some innovative approaches to improve the gravity-driven flow path analysis: the Filling Depression function to work with non-depressionless DEM and to reduce the time computing; the Pathway Force Interaction function that allows the previous gravity-driven flow paths to be considered in the next path calculation; and the Restricted Multiflow function to control the dispersion in the Multi-Directional flow model. As an example, the summit area of the Cotopaxi volcano has been used.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Alexanderson GL (2000) The random walks of George Pólya. Spectrum, mathematical Association of America, California. USA, DOI 0-88385-528-3 Barnikel F (2004) the value of historical documents for hazard zone mapping. Nat Hazards Earth Syst Sci 4(4):599–613. https://doi.org/10.5194/nhess-4-599-2004
Barnikel F 2004. The value of historical documents for hazard zone mapping Natural. Hazards and Earth System Sciences, 4, 599–613. https://doi.org/10.5194/nhess-4-599-2004
Beguería S (2006) Validation and evaluation of predictive models in hazard assessment and risk management. Nat Hazards 37(3):315–329. https://doi.org/10.1007/s11069-005-5182-6
Bernard B, Battaglia J, Proaño A, Hidalgo S, Vásconez F, Hernandez S, Ruiz M (2016) Relationship between volcanic ash fallouts and seismic tremor: quantitative assessment of the 2015 eruptive period at Cotopaxi volcano. Ecuador Bulletin of Volcanology 78(80). https://doi.org/10.1007/s00445-016-1077-5
Berti M, Simoni A (2014) DFLOWZ: A free program to evaluate the area potentially inundated by a debris flow. Version 1.0. Dipartimento di Scienze Biologiche, Geologiche e Ambientali Universit di Bologna, Italy, URL http://137.204.103.162/geoappl/dflowz/DFLOWZ10_Guide.pdf
Burrough PA, McDonnell RA (1998) Principles of geographical information systems. Oxford University Press, New York
Cáceres B, Jordan E, Ungerechts L, Francou B, Peñafiel A (2005) Evaluación geométrica del casquete glaciar del volcán Cotopaxi usando fotogrametría digital. Memorias del VI Congreso Latinoamericano de Geología. Quito, URL, In http://www.cepeige.org/Revista/CASQUETE%20GLACIAR_COTOPAXI.pdf
Chu T, Tsai T (1995) Comparison of accuracy and algorithms of slope and aspect measures from dem. In: Proceedings of GIS AM/FM ASIA95, pp 21–24
EORC, JAXA (2016) Alos global digital surface model (dsm) “alos world 3d-30m” (aw3d30) dataset. techreport, Earth Observation Research Center (EORC), Japan Aerospace Exploration Agency (JAXA), URL http://www.eorc.jaxa.jp/ALOS/en/aw3d30/aw3d30v11_format_e.pdf, accessed on: 2015/06/01
EPPL7 Team (1992) Environmental planning and programming language, version 7, release 2.1: User’s guide. techreport, Land Management Information Center
Ettinger S, Mothes P, Paris R, Schilling S (2007) The 1877 lahar deposits on the eastern flank of Cotopaxi volcano. Géomorphologie: relief, processus, environnement 13(3):271–280. https://doi.org/10.4000/geomorphologie.4022
Felpeto A (2002) Modelización física y simulación numérica de procesos eruptivos para la generación de mapas de peligrosidad volcánica. Tesis doctoral, Dep. de Física de la Tierra, Astronomía y Astrofísica. Facultad de Ciencias Físicas. Universidad Complutense de Madrid, Madrid. España
Felpeto A, Araña V, Ortiz R, Astiz M, García A (2001) Assessment and modelling of lava flow Hazard on Lanzarote (Canary Islands). Nat Hazards 23(2–3):247–257. https://doi.org/10.1023/A:1011112330766
Felpeto A, Martí J, Ortiz R (2007) Automatic GIS-based system for volcanic hazard assessment. J Volcanol Geotherm Res 166(2):106–116. https://doi.org/10.1016/j.jvolgeores.2007.07.008
Fleming MD, Hoffer RM (1979) Machine processing of landsat mss data and dma topographic data for forest cover type mapping. In: LARS Symposia. Paper 302, pp 373–390, URL http://docs.lib.purdue.edu/lars_symp/302
Garcés C, Cspedes F, Intriago G (2012) Proyecciones de la población de la república del ecuador 2010–2050. techreport, Instituto Nacional de Estadística y Censos (INEC), URL http://www.ecuadorencifras.gob.ec//documentos/web-inec/Poblacion_y_Demografia/Proyecciones_Poblacionales/metodologia.pdf
Gerstenecker C, Läufer G, Steineck D, Tiede C, Wrobel B (2005) Validation of digital elevation models around Merapi volcano, Java. Indonesia Natural Hazards and Earth System Sciences 5(6):863–876. https://doi.org/10.5194/nhess-5-863-2005
Golden Software, LLC (2018) Raster format *.grd. URL http://www.goldensoftware.com/, updated January 26, 2018. Golden, Colorado 80401
GRASS Development Team (2015) Geographic resources analysis support system (grass) software, version 7.0. software, Open Source Geospatial Foundation, URL http://grass.osgeo.org
Hall M, Mothes P (2008) The rhyolitic–andesitic eruptive history of Cotopaxi volcano, Ecuador. Bull Volcanol 70(6):675–702. https://doi.org/10.1007/s00445-007-0161-2
Harris AJ, Rowland S (2001) Flowgo: a kinematic thermo-rheological model for lava flowing in a channel. Bull Volcanol 63:20–44. https://doi.org/10.1007/s004450000120
Horn BK (1981) Hill shading and the reflectance map. Proc IEEE 69(1):14–47 URL http://ieeexplore.ieee.org/document/1456186/
INEC INEC (2010) Base de datos-censo de poblacin y vivienda 2010 a nivel de manzana. In: URL http://www.ecuadorencifras.gob.ec/base-de-datos-censo-de-poblacion-y-vivienda-2010-a-nivel-de-manzana/
Iverson RM, Schilling SP, Vallance JW (1998) Objective delineation of lahar-inundation hazard zones. Geol Soc Am Bull 110(8):972–984 URL https://profile.usgs.gov/myscience/upload_folder/ci2013Mar07174554246641998.Iverson.etal.GSA.Bull.pdf
Jenson SK, Domingue JO (1988) Extracting topographic structure from digital elevation data for geographic information system analysis. Photogramm Eng Remote Sens 54(11):1593–1600 URL http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.138.6487&rep=rep1&type=pdf
Jones KH (1998) A comparison of algorithms used to compute hill slope as a property of the dem. Comput Geosci 24(4):315–323. https://doi.org/10.1016/S0098-3004(98)00032-6
Jordan E, Ungerechts L, Cáceres B, Penafiel A, Francou B (2005) Estimation by photogrammetry of the glacier recession on the Cotopaxi volcano (Ecuador) between 1956 and 1997/estimation par photogrammétrie de la récession glaciaire Sur le Volcan Cotopaxi (Equateur) entre 1956 et 1997. Hydrol Sci J 50(6):949–961. https://doi.org/10.1623/hysj.2005.50.6.949
Marrero J, García A, Llinares A, De la Cruz-Reyna S, Ramos S, Ortiz R (2013) Virtual tools for volcanic crisis management, and evacuation decision support: applications to El Chichón volcano (Chiapas, Mexico). Nat Hazards 68:955–980, DOI https://doi.org/10.1007/s11069-013-0672-4
Mothes PA (1992) Lahars of Cotopaxi volcano, Ecuador: hazard and risk evaluation. In: McCall G, Laming D, Scott S (eds) Geohazards. Springer, pp 53–63. https://doi.org/10.1007/978-94-011-2310-5_7
Mothes P, Hall ML, Andrade D, Yepes H, Pierson TC, Gorki Ruiz A, Samaniego P (2004) Character, stratigraphy and magnitude of historical lahars of Cotopaxi volcano (Ecuador). Acta Vulcanol 16(1–2):1000–1023 URL http://www.torrossa.it/resources/an/2231623
Mothes P, Espín P, Hall M, Vásconez F, Sierra A, Andrade D (2016a) Mapa regional de amenazas volcánicas potenciales del volcán cotopaxi, zona norte. Mapa de peligros, Instituto Geofísico. Escuela Politécnica Nacional, URL http://www.igepn.edu.ec/cotopaxi-mapa-de-peligros
Mothes P, Espín P, Hall M, Vásconez F, Sierra A, Andrade D (2016b) Mapa regional de amenazas volcánicas potenciales del volcán cotopaxi, zona sur. Mapa de peligros, Instituto Geofísico. Escuela Politécnica Nacional, URL http://www.igepn.edu.ec/cotopaxi-mapa-de-peligros
O’brien J, Julien P, Fullerton W (1993) Two-dimensional water flood and mudflow simulation. J Hydraul Eng 119(2):244–261. https://doi.org/10.1061/(ASCE)0733-9429(1993)119:2(244)
O’Callaghan JF, Mark DM (1984) The extraction of drainage networks from digital elevation data. Computer Vision, Graphics, and Image Processing 28(3):323–344. https://doi.org/10.1016/S0734-189X(84)80011-0
Pierson TC, Wood NJ, Driedger CL (2014) Reducing risk from lahar hazards: concepts, case studies, and roles for scientists. J Appl Volcanol 3(1):1–25. https://doi.org/10.1186/s13617-014-0016-4
Pistolesi M, Cioni R, Rosi M, Cashman KV, Rossotti A, Aguilera E (2013) Evidence for lahar-triggering mechanisms in complex stratigraphic sequences: the post-twelfth century eruptive activity of Cotopaxi volcano. Ecuador Bulletin of volcanology 75:698. https://doi.org/10.1007/s00445-013-0698-1
Pistolesi M, Cioni R, Rosi M, Aguilera E (2014) Lahar hazard assessment in the southern drainage system of Cotopaxi volcano, Ecuador: results from multiscale lahar simulations. Geomorphology 207:51–63. https://doi.org/10.1016/j.geomorph.2013.10.026
QGIS Development team (2016) Qgis geographic information system. Software, open source geospatial foundation project, URL http://qgis.osgeo.org
Quinn P, Beven K, Chevallier P, Planchon O (1991) The prediction of hillslope flow paths for distributed hydrological modelling using digital terrain models. Hydrol Process 5(1):59–79. https://doi.org/10.1002/hyp.3360050106
Salazar D, D’Ercole R (2009) Percepción del riesgo asociado al volcán Cotopaxi y vulnerabilidad en el Valle de Los Chillos (Ecuador). Bulletin de l’Institut français d’études andines 38(3):849–871 URL http://bifea.revues.org/2522
Schilling SP (1998) LAHARZ; GIS programs for automated mapping of lahar-inundation hazard zones. Tech. Rep. Open-file report 98–638, US Geological Survey; Information Services [distributor],, URL http://pubs.usgs.gov/of/1998/0638/report.pdf
Schilling SP (2014) Laharz_py: GIS tools for automated mapping of lahar inundation hazard zones. Tech. Rep. Open - file report 2014–1073, US Geological Survey, URL http://pubs.usgs.gov/of/2014/1073/pdf/ofr2014-1073.pdf
Sharpnack DA (1969) An algorithm for computing slope and aspect from elevations. Photogramm Eng 35(3):247–248 URL https://www.asprs.org/wp-content/uploads/pers/1969journal/mar/1969_mar_247-248.pdf
Shipman JW (2013) Tkinter 8.5 reference: a GUI for Python. URL http://infohost.nmt.edu/tcc/help/pubs/tkinter/web/index.html
Smolka A (2006) Natural disasters and the challenge of extreme events: risk management from an insurance perspective. Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences 364(1845):2147–2165. https://doi.org/10.1098/rsta.2006.1818
Smyth MA (1991) Movement and emplacement mechanisms of the Río Pita volcanic debris avalanche and its role in the evolution of Cotopaxi Volcano. PhD thesis, Univerity of Aberdeen, UK, URL http://gradworks.umi.com/U5/45/U545613.html
Souris M (2006) Dem for all ecuador using continental ecuador from 1:25000, 1:50000 and 1:100000 igm topographic maps,. URL http://www.savgis.org/ecuador.htm, accessed on: 2015/06/01
Stevens N, Manville V, Heron D (2003) The sensitivity of a volcanic flow model to digital elevation model accuracy: experiments with digitised map contours and interferometric SAR at Ruapehu and Taranaki volcanoes, New Zealand. J Volcanol Geotherm Res 119(1):89–105. https://doi.org/10.1016/S0377-0273(02)00307-4
Tang J, Pilesjö P (2011) Estimating slope from raster data: a test of eight different algorithms in flat, undulating and steep terrain. Transactions on Ecology and the Environment 146:143–154. https://doi.org/10.2495/RM110131
Tarboton DG (1997) A new method for the determination of flow directions and upslope areas in grid digital elevation models. Water Resour Res 33(2):309–319. https://doi.org/10.1029/96WR03137
Technical Committee X3J11 on the C Programming Language (1988) Ansi c. techreport Proyect 381-D. SPARC Document 83–079, American National Standards Institute (ANSI). American National Standards Committee on Computers and Information Processing, URL http://web.archive.org/web/20161223125339/http://flash-gordon.me.uk:80/ansi.c.txt
Travis MR, Elsner GH, Iverson WD, Johnson CG (1975) Viewit: computation of seen areas, slope, and aspect for land-use planning. techreport, Southwest Research Station, Forest Service, US Department of Agriculture, URL https://www.fs.fed.us/psw/publications/documents/psw_gtr011/gtr-011part1.pdf
UN/ISDR ISfDR (2004) Living with risk: A global review of disaster reduction initiatives, vol 1. United Nations Publications, New York and Geneva, URL http://www.unisdr.org/files/657_lwr1.pdf
Unwin DJ (1981) Introductory spatial analysis, vol 748. University paperbacks, London and New York
Wahlstrom M, Guha-Sapir D (2015) The human cost of weather-related disasters 1995–2015. Tech. rep., Centre for Research on the Epidemiology of Disasters (CRED). United Nations International Strategy for Disaster Reduction., Geneva, URL https://reliefweb.int/sites/reliefweb.int/files/resources/COP21_WeatherDisastersReport_2015_FINAL.pdf
Wang L, Liu H (2006) An efficient method for identifying and filling surface depressions in digital elevation models for hydrologic analysis and modelling. Int J Geogr Inf Sci 20(2):193–213. https://doi.org/10.1080/13658810500433453
Wood J (1996) the geomorphological characterisation of digital elevation models. Phdthesis, University of Leicester. Dept. of geography, URL http://hdl.handle.net/2381/34503
Zhang W, Montgomery DR (1994) Digital elevation model grid size, landscape representation, and hydrologic simulations. Water Resour Res 30(4):1019–1028. https://doi.org/10.1029/93WR03553
Zhou Q, Liu X (2004) Error analysis on grid-based slope and aspect algorithms. Photogramm Eng Remote Sens 70(8):957–962 URL https://pdfs.semanticscholar.org/67fc/0828220e7b12cd3c7b4affa70cf7376b5659.pdf
Acknowledgements
This work has been ostensibly supported by the Secretaría de Educación Superior de Ciencia, Tecnología e Innovación (SENESCYT) of the Government of Ecuador under the PROMETEO Programme (PROMETEO-CEB-004-2015 and PROMETEO-CEB-009-2016). We thank editor and an anonymous reviewers for their constructive comments that helped to improve the manuscript.
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by: H. A. Babaie
Rights and permissions
About this article
Cite this article
Marrero, J.M., Vasconez, F., Espín, P. et al. MDTanaliza: understanding digital elevation models when facing gravity-driven flows in a hazard assessment context. Earth Sci Inform 12, 257–274 (2019). https://doi.org/10.1007/s12145-018-0372-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12145-018-0372-4