Quantifying the role of vegetation in slope stability: A case study in Tuscany (Italy)

Schwarz, Massimiliano; Preti, Federico; Giadrossich, Filippo; Lehmann, Peter; Or, Dani

doi:10.1016/j.ecoleng.2009.06.014

Cited by 233 publications

(195 citation statements)

References 22 publications

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“…Parameter maps for the effects of vegetation accounting for these attributes could further improve the model's predictive performance (e.g. Schwarz et al, 2010Schwarz et al, , 2012.…”

Section: Discussionmentioning

confidence: 99%

Sensitivity analysis and calibration of a dynamic physically based slope stability model

Zieher

Rutzinger

Schneider‐Muntau

et al. 2017

Nat. Hazards Earth Syst. Sci.

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Abstract. Physically based modelling of slope stability on a catchment scale is still a challenging task. When applying a physically based model on such a scale (1 : 10 000 to 1 : 50 000), parameters with a high impact on the model result should be calibrated to account for (i) the spatial variability of parameter values, (ii) shortcomings of the selected model, (iii) uncertainties of laboratory tests and field measurements or (iv) parameters that cannot be derived experimentally or measured in the field (e.g. calibration constants). While systematic parameter calibration is a common task in hydrological modelling, this is rarely done using physically based slope stability models. In the present study a dynamic, physically based, coupled hydrological-geomechanical slope stability model is calibrated based on a limited number of laboratory tests and a detailed multitemporal shallow landslide inventory covering two landslide-triggering rainfall events in the Laternser valley, Vorarlberg (Austria). Sensitive parameters are identified based on a local one-at-a-time sensitivity analysis. These parameters (hydraulic conductivity, specific storage, angle of internal friction for effective stress, cohesion for effective stress) are systematically sampled and calibrated for a landslide-triggering rainfall event in August 2005. The identified model ensemble, including 25 "behavioural model runs" with the highest portion of correctly predicted landslides and non-landslides, is then validated with another landslide-triggering rainfall event in May 1999. The identified model ensemble correctly predicts the location and the supposed triggering timing of 73.0 % of the observed landslides triggered in August 2005 and 91.5 % of the observed landslides triggered in May 1999. Results of the model ensemble driven with raised precipitation input reveal a slight increase in areas potentially affected by slope failure. At the same time, the peak run-off increases more markedly, suggesting that precipitation intensities during the investigated landslide-triggering rainfall events were already close to or above the soil's infiltration capacity.

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“…Parameter maps for the effects of vegetation accounting for these attributes could further improve the model's predictive performance (e.g. Schwarz et al, 2010Schwarz et al, , 2012.…”

Section: Discussionmentioning

confidence: 99%

Sensitivity analysis and calibration of a dynamic physically based slope stability model

Zieher

Rutzinger

Schneider‐Muntau

et al. 2017

Nat. Hazards Earth Syst. Sci.

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“…After 15 years of enclosure, environmental factors and litter layer (litter thickness reaches 3-5 cm) lead to bad soil aeration which influences the renewal seedling, forage regeneration, and finally the stability of the system. Bad soil aeration directly inhibits the normal growth and development of grass and the formation of species diversity leading to the decline of natural regeneration of grassland and remarkable decrease in biomass [25][26][27][28][29][30]. Species composition of plant community is an important symbol of grassland community property, structure, and function.…”

Section: Discussionmentioning

confidence: 99%

“…However, the change of environmental factors plays a crucial role in community evolution. Human activities, such as cutting and grazing, are considered as the most influential factors affecting grassland habitat by obviously influencing the composition and structure of grassland species diversity [18][19][20][21][22][23][24][25][26][27][28][29][30]. A seven-year research of short forage grassland shows that heavy grazing can reduce total grass production by about 40% in growth season from June to July, and the highest production can be obtained by heavy grazing in the late growth season [2,3,27,28].…”

Section: Discussionmentioning

confidence: 99%

“…Plant compensatory growth can be decided by the net effect of inhibition and promotion, which relates to the community type, stocking rate, environment condition, and grazing history [5]. Domestic and foreign studies on plant compensatory growth mostly focus on theory and model, and the study through comprehensive and systematic experiment is very much limited [15,[25][26][27][28][29]. …”

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confidence: 99%

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Dynamic Changes of Stipa bungeana Steppe Species Diversity as Better Indicators for Soil Quality and Sustainable Utilization Mode in Yunwu Mountain Nature Reserve, Ningxia, China

Cheng

et al. 2011

CLEAN Soil Air Water

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Due to serious degradation of typical Stipa bungeana steppe community on the Loess Plateau, a 26-year (1982-2007) experiment has been carried out by methods of forbidden grazing, cutting, and rotational grazing. Our results show that the process of succession of long-term enclosed S. bungeana community can be divided into two stages: 1980-1996, the forward succession stage, when the species diversity and biomass reach the peak (33.7 species/m 2 and 1349.41 g/m 2 , respectively); 1997-2007, the slow succession stage, when the gradually thickening of litter layer (litter depth reaches 3-5 cm) directly causes the reduction of species diversity and biomass to 19.1 species/m 2 and 863.19 g/m 2 , respectively. While under the cutting and rotational grazing methods, grassland succession can be divided into four stages: 1st-5th year, the continuing growth stage; 6th-9th year, the vigorous competing stage; 10th-15th year, the aggregation growth stage of constructive species with biomass reaching the peak (1444.19 g/m 2 ); and 16th-23rd year, stable growth stage of constructive species, which form sub-climax and are eventually dominated by S. bungeana, with the species diversity and biomass of 25-27 species/m 2 and 956.76-1165.35 g/m 2 , respectively. The constructive species suddenly change in the 24th year, and the population of S. grandis increases rapidly to 21 m À2 accounting for 25% of the total plant population. Long-term enclosure leads to decreased species diversity and biomass and is not beneficial for grassland renewing. The species diversity and biomass of degraded grassland continuously decrease to 10 species/m 2 and 392.1 g/m 2 due to long-term artificial failure and transitionally grazing, leading to harden soil with slow rainfall infiltration, where plants can only sustain life under the drought condition. Therefore, reasonable cutting and rotational grazing are the methods of choice for the gradual increase of species diversity and promotion of the natural renewal and forward succession of the grassland on Loess Plateau. These results provide reliable information for the diversity dynamic change as better indictors of soil quality and sustainable utilization mode.Keywords: Nature reserve; Soil quality; Species diversity dynamics; Stipa bungeana steppe; Sustainable utilization mode IntroductionGrassland is one of the globally important terrestrial ecosystems, and the increase in species diversity and productivity of grassland community depends greatly on the long-term management [1][2][3][4][5][6][7]. More research indicates that the species diversity of grassland has important ecology functions [8][9][10][11][12], species diversity is positively related to productivity, especially aboveground biomass [13][14][15]. Stipa bungeana steppe is a major community of middle temperate semi-arid typical grassland in the Eurasian section, widely distributes in western China and Loess Plateau region, and is mainly used for grazing and cutting. Typical grassland has important position in the temperate steppe in Chin...

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“…Overall, the advantages quantifying root reinforcement in term of forcedisplacement behavior with a minimal computational effort makes the RBMw attractive for its implementation in slope stability model at large temporal and spatial scales. Recent studies (Schwarz et al, 2010a; have shown the importance of the dynamic of root reinforcement during the triggering of shallow landslides remarking the importance of changes in stiffness and total mobilized energy of rooted soil volumes loaded under tension and compression. In particular Schwarz et al (2010b) propose an upscaling framework of root reinforcement at the hillslope scale considering the structure and the type of forest cover.…”

Section: Implications Of Root Reinforcement Quantification In Hydrolomentioning

confidence: 99%

Modeling root reinforcement using a root-failure Weibull survival function

Schwarz

Giadrossich

Cohen

2013

Hydrol. Earth Syst. Sci.

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Abstract. Root networks contribute to slope stability through complex interactions with soil that include mechanical compression and tension. Due to the spatial heterogeneity of root distribution and the dynamics of root turnover, the quantification of root reinforcement on steep slopes is challenging and consequently the calculation of slope stability also. Although considerable progress has been made, some important aspects of root mechanics remain neglected. In this study we address specifically the role of root-strength variability on the mechanical behavior of a root bundle. Many factors contribute to the variability of root mechanical properties even within a single class of diameter. This work presents a new approach for quantifying root reinforcement that considers the variability of mechanical properties of each root diameter class. Using the data of laboratory tensile tests and field pullout tests, we calibrate the parameters of the Weibull survival function to implement the variability of root strength in a numerical model for the calculation of root reinforcement (RBMw). The results show that, for both laboratory and field data sets, the parameters of the Weibull distribution may be considered constant with the exponent equal to 2 and the normalized failure displacement equal to 1. Moreover, the results show that the variability of root strength in each root diameter class has a major influence on the behavior of a root bundle with important implications when considering different approaches in slope stability calculation. Sensitivity analysis shows that the calibration of the equations of the tensile force, the elasticity of the roots, and the root distribution are the most important steps. The new model allows the characterization of root reinforcement in terms of maximum pullout force, stiffness, and energy. Moreover, it simplifies the implementation of root reinforcement in slope stability models. The realistic quantification of root reinforcement for tensile, shear and compression behavior allows for the consideration of the stabilization effects of root networks on steep slopes and the influence that this has on the triggering of shallow landslides.

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Quantifying the role of vegetation in slope stability: A case study in Tuscany (Italy)

Cited by 233 publications

References 22 publications

Sensitivity analysis and calibration of a dynamic physically based slope stability model

Sensitivity analysis and calibration of a dynamic physically based slope stability model

Dynamic Changes of Stipa bungeana Steppe Species Diversity as Better Indicators for Soil Quality and Sustainable Utilization Mode in Yunwu Mountain Nature Reserve, Ningxia, China

Modeling root reinforcement using a root-failure Weibull survival function

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