Strategies to improve the explanatory power of a dynamic slope stability model by enhancing land cover parameterisation and model complexity

被引:10
|
作者
Schmaltz, Elmar M. [1 ,2 ]
Van Beek, L. P. H. [3 ]
Bogaard, Thom A. [4 ]
Kraushaar, Sabine [2 ]
Steger, Stefan [5 ]
Glade, Thomas [2 ]
机构
[1] Fed Agcy Water Management, Inst Land & Water Management Res, Pollnbergstr 1, A-3252 Petzenkirchen, Austria
[2] Univ Vienna, ENGAGE Geomorphol Syst & Risk Res, Fac Earth Sci Geog & Astron, Vienna, Austria
[3] Univ Utrecht, Dept Phys Geog, POB 80115, NL-3508 TC Utrecht, Netherlands
[4] Delft Univ Technol, Water Resources Sect, Stevinweg 1, NL-2628 CN Delft, Netherlands
[5] Inst Earth Observat, EURAC Res, Drususallee 1, I-39100 Bozen Bolzano, Italy
关键词
Shallow translational landslides; land cover dynamics; parameterisation; physically based slope stability modelling; STARWARS; PROBSTAB; predictive performance; SHALLOW LANDSLIDE SIZE; ROOT STRENGTH; FOREST COVER; WATER; VEGETATION; FLOW; SOIL; INTERCEPTION; PERFORMANCE; VORARLBERG;
D O I
10.1002/esp.4570
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Despite the importance of land cover on landscape hydrology and slope stability, the representation of land cover dynamics in physically based models and their associated ecohydrological effects on slope stability is rather scarce. In this study, we assess the impact of different levels of complexity in land cover parameterisation on the explanatory power of a dynamic and process-based spatial slope stability model. Firstly, we present available and collected data sets and account for the stepwise parameterisation of the model. Secondly, we present approaches to simulate land cover: 1) a grassland landscape without forest coverage; 2) spatially static forest conditions, in which we assume limited knowledge about forest composition; 3) more detailed information of forested areas based on the computation of leaf area development and the implementation of vegetation-related processes; 4) similar to the third approach but with the additional consideration of the spatial expansion and vertical growth of vegetation. Lastly, the model is calibrated based on meteorological data sets and groundwater measurements. The model results are quantitatively validated for two landslide-triggering events that occurred in Western Austria. Predictive performances are estimated using the Area Under the receiver operating characteristic Curve (AUC). Our findings indicate that the performance of the slope stability model was strongly determined by model complexity and land cover parameterisation. The implementation of leaf area development and land cover dynamics further yield an acceptable predictive performance (AUC similar to 0.71-0.75) and a better conservativeness of the predicted unstable areas (FoC similar to 0.71). The consideration of dynamic land cover expansion provided better performances than the solely consideration of leaf area development. The results of this study highlight that an increase of effort in the land cover parameterisation of a dynamic slope stability model can increase the explanatory power of the model. (c) 2018 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.
引用
收藏
页码:1259 / 1273
页数:15
相关论文
共 50 条
  • [1] Dynamic land cover evapotranspiration model algorithm: DyLEMa
    Han, Jeongho
    Guzman, Jorge A.
    Chu, Maria L.
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2024, 220
  • [2] Land Cover Dynamic Monitoring model of Three Gorges area
    Zhu, Lifen
    Tian, Yongzhong
    Zhou, Wenzuo
    REMOTE SENSING AND MODELING OF ECOSYSTEMS FOR SUSTAINABILITY V, 2008, 7083
  • [3] A dynamic simulation model of land cover in the Dulce Creek Basin, Argentina
    Lourdes, Lima
    Karina, Zelaya
    Pedro, Laterra
    Hector, Massone
    Nestor, Maceira
    SPATIAL STATISTICS 2011: MAPPING GLOBAL CHANGE, 2011, 7 : 194 - 199
  • [4] Model Predictive Control to improve the power system stability
    Sebaa, Karim
    Moulahoum, Samir
    Houassine, Hamza
    Kabache, Nadir
    PROCEEDINGS OF THE 13TH INTERNATIONAL CONFERENCE ON OPTIMIZATION OF ELECTRICAL AND ELECTRONIC EQUIPMENT, VOLS 1-5, 2012, : 208 - 212
  • [5] Sensitivity analysis and calibration of a dynamic physically based slope stability model
    Zieher, Thomas
    Rutzinger, Martin
    Schneider-Muntau, Barbara
    Perzl, Frank
    Leidinger, David
    Formayer, Herbert
    Geitner, Clemens
    NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2017, 17 (06) : 971 - 992
  • [6] Reducing model complexity of DFIG-based wind turbines to improve the efficiency of power system stability analysis
    Bu, S. Q.
    Zhang, X.
    Xia, S. W.
    Xu, Y.
    Zhou, B.
    Lu, X.
    PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON APPLIED ENERGY, 2017, 142 : 971 - 976
  • [7] Effect of Slip Surface's Continuity on Slope Dynamic Stability Based on Infinite Slope Model
    Liu, Chuanzheng
    Wang, Gang
    Han, Wei
    MATHEMATICS, 2019, 7 (01):
  • [8] Dynamic Model of Blended Biogeography Based Optimization for Land Cover Feature Extraction
    Goel, Lavika
    Gupta, Daya
    Panchal, V. K.
    CONTEMPORARY COMPUTING, 2012, 306 : 8 - +
  • [9] Model Predictive Control in Power Electronics: Strategies to Reduce the Computational Complexity
    Karamanakos, Petros
    Geyer, Tobias
    Oikonomou, Nikolaos
    Kieferndorf, Frederick
    Manias, Stefanos
    39TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY (IECON 2013), 2013, : 5818 - 5823
  • [10] Entropy Complexity and Stability of a Nonlinear Dynamic Game Model with Two Delays
    Han, Zhihui
    Ma, Junhai
    Si, Fengshan
    Ren, Wenbo
    ENTROPY, 2016, 18 (09)