r.massmov: an open-source landslide model for dynamic early warning systems

被引:9
|
作者
Molinari, Monia Elisa [1 ]
Cannata, Massimiliano [2 ]
Meisina, Claudia [1 ]
机构
[1] Univ Pavia, Dept Earth & Environm Sci, I-27100 Pavia, Italy
[2] SUPSI, Inst Earth Sci, CH-6952 Canobbio, Switzerland
关键词
Modeling; Landslide; GIS; Calibration; Sensitivity analysis; Multi-spatial resolution; UCODE; GRASS; GIS; CALIBRATION; SIMULATION; EQUATIONS;
D O I
10.1007/s11069-013-0867-8
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
This paper illustrates the main characteristics of the newly developed landslide model r.massmov, which is based on the shallow water equations, and is capable of simulating the landslide propagation over complex topographies. The model is the result of the reimplementation of the MassMov2D into the free and open-source GRASS GIS with a series of enhancements aiming at allowing its possible integration into innovative early warning monitoring systems and specifically into Web processing services. These improvements, finalized at significantly reducing computational times, include the introduction of a new automatic stopping criterion, fluidization process algorithm, and the parallel computing. Moreover, the results of multi-spatial resolution analysis conducted on a real case study located in the southern Switzerland are presented. In particular, this analysis, composed by a sensitivity analysis and calibration process, allowed to evaluate the model capabilities in simulating the phenomenon at different input data resolution. The results illustrate that the introduced modifications lead to important reductions in the computational time (more than 90 % faster) and that, using the lower dataset resolution capable of guaranteeing reliable results, the model can be run in about 1 s instead of the 3.5 h required by previous model with not optimized dataset resolution. Aside, the results of the research are a series of new GRASS GIS modules for conducting sensitivity analysis and for calibration. The latter integrates the automated calibration program "UCODE" with any GRASS raster module. Finally, the research workflow presented in this paper illustrates a best practice in applying r.massmov in real case applications.
引用
收藏
页码:1153 / 1179
页数:27
相关论文
共 50 条
  • [1] r.massmov: an open-source landslide model for dynamic early warning systems
    Monia Elisa Molinari
    Massimiliano Cannata
    Claudia Meisina
    Natural Hazards, 2014, 70 : 1153 - 1179
  • [2] An Open-Source Earthquake Early Warning Display
    Cauzzi, Carlo
    Behr, Yannik
    Clinton, John
    Kastli, Philipp
    Elia, Luca
    Zollo, Aldo
    SEISMOLOGICAL RESEARCH LETTERS, 2016, 87 (03) : 737 - 742
  • [3] Geographical landslide early warning systems
    Guzzetti, Fausto
    Gariano, Stefano Luigi
    Peruccacci, Silvia
    Brunetti, Maria Teresa
    Marchesini, Ivan
    Rossi, Mauro
    Melillo, Massimo
    EARTH-SCIENCE REVIEWS, 2020, 200
  • [4] Meteorological Early Warning of Landslide Based on I⁃D⁃R Threshold Model
    Liu X.
    Yin K.
    Xiao C.
    Chen L.
    Zeng T.
    Li Y.
    Liu Z.
    Gong Q.
    Chen W.
    Diqiu Kexue - Zhongguo Dizhi Daxue Xuebao/Earth Science - Journal of China University of Geosciences, 2024, 49 (03): : 1039 - 1051
  • [5] APEXSENSUN: An Open-Source Package in R for Sensitivity Analysis and Model Performance Evaluation of APEX
    Talebizadeh, Mansour
    Moriasi, Daniel
    Steiner, Jean L.
    Gowda, Prasanna
    Tadesse, Haile K.
    Nelson, Amanda M.
    Starks, Patrick
    JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, 2018, 54 (06): : 1270 - 1284
  • [6] Simulating LTE Cellular Systems: An Open-Source Framework
    Piro, Giuseppe
    Grieco, Luigi Alfredo
    Boggia, Gennaro
    Capozzi, Francesco
    Camarda, Pietro
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2011, 60 (02) : 498 - 513
  • [7] MultiscaleDTM: An open-source R package for multiscale geomorphometric analysis
    Ilich, Alexander R.
    Misiuk, Benjamin
    Lecours, Vincent
    Murawski, Steven A.
    TRANSACTIONS IN GIS, 2023, 27 (04) : 1164 - 1204
  • [8] Regional dynamic early warning model for rainfall-induced landslide in Fujian, China
    Dou, Hongqiang
    Chen, Yongda
    Sun, Yongxin
    Guo, Chaoxu
    GEOMATICS NATURAL HAZARDS & RISK, 2024, 15 (01)
  • [9] Landslide susceptibility mapping with r.landslide: A free open-source GIS-integrated tool based on Artificial Neural Networks
    Bragagnolo, L.
    da Silva, R. V.
    Grzybowski, J. M. V.
    ENVIRONMENTAL MODELLING & SOFTWARE, 2020, 123
  • [10] EnergyScope TD: A novel open-source model for regional energy systems
    Limpens, Gauthier
    Moret, Stefano
    Jeanmart, Herve
    Marechal, Francois
    APPLIED ENERGY, 2019, 255