The effects of variability in bank material properties on riverbank stability: Goodwin Creek, Mississippi

Bank retreat is an important area of research within fluvial geomorphology and is a land management problem of global significance. The Yazoo River Basin in Mississippi is one example of a system which is experiencing excessive erosion and bank instability. The properties of bank materials are important in controlling the stability of stream banks and past studies have found that these properties are often variable spatially. Through an investigation of bank material properties on a stretch of Goodwin Creek in the Yazoo Basin, Mississippi, this study focuses on: i) how and why effective bank material properties vary through different scales; ii) how this variation impacts on the outputs from a bank stability model; and iii) how best to appropriately represent this variability within a bank stability model. The study demonstrates the importance that the variability of effective bank material properties has on bank stability: at both the micro-scale within a site, and at the meso-scale between sites in a reach. This variability was shown to have important implications for the usage of the Bank Stability and Toe Erosion Model (BSTEM), a deterministic bank stability model that currently uses a single value to describe each bank material property. As a result, a probabilistic representation of effective bank material strength parameters is recommended as a potential solution for any bank stability model that wishes to account for the important influence of the inherent variability of soil properties. © 2008 Elsevier B.V. All rights reserved

Toward a tool aimed to quantify soil compaction risks at a regional scale: application to Wallonia (Belgium)

The spatial analysis of the soil compaction risk has been developed at the regional level and applied to Wallonia (Belgium). The methodology is based on the estimation of the probability of exceeding the preconsolidation stress due to the application of loads on the soil. Preconsolidation stresses (Pc) are computed from the pedotransfer functions of Horn and Fleige (2003) at pF 1.8 and 2.5 and classified into 6 categories ranging from very low Pc ( 150 kPa). The computation requires the knowledge of pedological (texture, organic content), mechanical (bulk density, cohesion, internal friction angle), and hydraulic variables (water content available, non-available water content, air capacity, saturated hydraulic conductivity). These variables are obtained from databases like HYPRES or AARDEWERK or from pedotransfer functions. The computation of Pc takes into account the spatial structure of the data: in some cases, data are abundant (e.g. texture data) and spatial variability is taken into account through geostatistical methods. In other cases, the data is sparse but uncertainty information can be extracted from the knowledge of the statistical distribution. Maps of the most probable Pc class are produced. Uncertainty is computed as the classification error probability. Implementation of these methods in Wallonia showed that Pc values higher than 120 kPa are reached either on 64 % of the territory at pF 2.5 or on 55 % at pF 1.8. A higher uncertainty was found at pF 2.5 than at pF 1.8. Uncertainty was also found higher for clay and clayed loess than for other textural classes present in Wallonia. The risk of compaction is defined as the probability that Pc is exceeded by the stress created by a load applied to the soil at a depth of 40 cm, the loads being similar to those induced by agricultural or forestry tires. It appeared that subsoil compaction risks exist mainly in loamy forest soils with small coarse fragments supporting loads similar to that existing on logging machines. In the zones where the uncertainty is low, the developed tool could be used as a basis for providing policy measures in order to promote soil-friendly farming and forest practices.Etude de la compaction des sols de Walloni

Improving predictive power of physically based rainfall-induced shallow landslide models: a probabilistic approach

Distributed models to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides are based on deterministic laws. These models extend spatially the static stability models adopted in geotechnical engineering, and adopt an infinite-slope geometry to balance the resisting and the driving forces acting on the sliding mass. An infiltration model is used to determine how rainfall changes pore-water conditions, modulating the local stability/instability conditions. A problem with the operation of the existing models lays in the difficulty in obtaining accurate values for the several variables that describe the material properties of the slopes. The problem is particularly severe when the models are applied over large areas, for which sufficient information on the geotechnical and hydrological conditions of the slopes is not generally available. To help solve the problem, we propose a probabilistic Monte Carlo approach to the distributed modeling of rainfall-induced shallow landslides. For the purpose, we have modified the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis (TRIGRS) code. The new code (TRIGRS-P) adopts a probabilistic approach to compute, on a cell-by-cell basis, transient pore-pressure changes and related changes in the factor of safety due to rainfall infiltration. Infiltration is modeled using analytical solutions of partial differential equations describing one-dimensional vertical flow in isotropic, homogeneous materials. Both saturated and unsaturated soil conditions can be considered. TRIGRS-P copes with the natural variability inherent to the mechanical and hydrological properties of the slope materials by allowing values of the TRIGRS model input parameters to be sampled randomly from a given probability distribution. [..]Comment: 25 pages, 14 figures, 9 tables. Revised version; accepted for publication in Geoscientific Model Development on 13 February 201

Integrated effect of parameter uncertainty in riverbank stability modelling

River morphodynamics and sediment transportBank erosion and protectio

Reliability-based Assessment of Concrete Dam Stability

Risk management is increasingly used in dam safety and includes risk analysis, risk evaluation and risk reduction. Structural Reliability Analysis (SRA) is a probabilistic methodology that may be used in the risk assessment process. SRA has been frequently used for calibration of partial factors in limit state design codes for structures (not dams). In a reliability analysis a mathematical description of the failure mode, a limit state function, is defined. All parameters describing the limit state function should be random variables and are described by stochastic distributions (or, where appropriate, a deterministic value). The safety index (or probability of failure) may be determined by e.g. First Order Reliability Method and the result is compared to a target safety index to determine if the structure is safe enough. Several difficulties exists in the use of SRA for concrete dams, mainly due to the fact that only a few examples of such analysis for dams exist. One difficulty is how to define the failure modes. In this thesis a complete system of failure modes is identified, where failure is considered as a series system of “failure in the concrete part”, “failure in the concrete-rock interface” and “failure in the rock mass”. Failure in the concrete-rock interface may occur due to sliding or overturning. Sliding is the joint occurrence of sliding with a partially bonded contact (fails at very small displacement) and sliding with broken contact (fails at larger displacement) and both have to occur for sliding to occur, hence they are treated as a parallel system. Adjusted overturning is a combination of overturning and crushing of the concrete or crushing of the rock. A substantial part of the work has been to define the necessary input data. - Cohesion in the interface is very important. Due to the expected brittle failure in a partly intact interface, treatment of the shear resistance as a brittle parallel system is proposed. - Description of the headwater results in a series system; either failure occurs for water levels at retention water level (rwl) or for water levels above rwl, the latter described by an exponential distribution. - Uplift is one of the most important loads. A geostatistical simulation procedure is presented, where the hydraulic conductivity field of the foundation is described by a variogram and uplift is simulated by a FE-analysis. This methodology is demonstrated to be very useful and gives estimates of the statistical distribution of uplift. Three papers on this subject are included; the first is a description of the methodology, the second presents a sensitivity analysis performed for a large number of different combinations of input data and the last is an application to a Brazilian dam, where water pressure tests and monitoring results are available. In two papers SRA is applied to concrete dams and the system reliability is determined. In the first paper a spillway section where information of e.g. cohesion, friction angles etc. were available is analysed. In the last paper an idealized dam and a power intake structure are analysed. The conclusions are that SRA may be used for assessment of concrete dam stability and that it is well fitted for the dam safety risk management process. Every dam is a unique prototype and SRA enables specific behaviour and properties of a certain structure to be taken to consideration. The system reliability analysis is a very valuable tool in understanding the relationship between failure modes and enables the safety for the whole structure to be determined. In a reliability analysis the most important parameters may be identified and thus safety measures can be focused where it gives the best possible output. A general safety consideration is that development of the safety concept for concrete dams, from deterministic to probabilistic or semi-probabilistic, will give a known and more uniform level of safety

Soil characterization for shallow landslides modeling: a case study in the Northern Apennines (Central Italy)

In this paper, we present preliminary results of the IPL project No. 198 \u201cMulti-scale rainfall triggering models for Early Warning of Landslides (MUSE).\u201d In particular, we perform an assessment of the geotechnical and hydrological parameters affecting the occurrence of landslides. The aim of this study is to improve the reliability of a physically based model high resolution slope stability simulator (HIRESSS) for the forecasting of shallow landslides. The model and the soil characterization have been tested in Northern Tuscany (Italy), along the Apennine chain, an area that is historically affected by shallow landslides. In this area, the main geotechnical and hydrological parameters controlling the shear strength and permeability of soils have been determined by in situ measurements integrated by laboratory analyses. Soil properties have been statistically characterized to provide more refined input data for the slope stability model. Finally, we have tested the ability of the model to predict the occurrence of shallow landslides in response to an intense meteoric precipitation

Spatio-temporal variability analysis of territorial resistance and resilience to risk assessment

Natural materials, such as soils, are influenced by many factors acting during their formative and evolutionary process: atmospheric agents, erosion and transport phenomena, sedimentation conditions that give soil properties a non-reducible randomness by using sophisticated survey techniques and technologies. This character is reflected not only in the spatial variability of soil properties which differ punctually, but also in their multivariate correlation as function of reciprocal distance. Cognitive enrichment, offered by the response of soils associated with their spatial variability, implies an increase in the evaluative capacity of contributing causes and potential effects in the field of failure phenomena. Stability analysis of natural slopes is well suited to stochastic treatment of the uncertainty which characterized landslide risk. In particular, the research activity has been carried out in back-analysis to a slope located in Southern Italy that was subject to repeated phenomena of hydrogeological instability - extended for several kilometers and recently reactivated - applying spatial analysis to the controlling factors and quantifying the hydrogeological susceptibility through unbiased estimators and indicators. A natural phenomenon, defined as geo-stochastic process, is indeed characterized by interacting variables leading to identifying the most critical areas affected by instability. Through a sensitivity analysis of the local variability as well as a reliability assessment of the time-based scenarios, an improvement of the forecasting content has been obtained. Moreover, the phenomenological characterization will allow to optimize the attribution of the levels of risk to the wide territory involved, supporting decision-making process for intervention priorities as well as the effective allocation of the available resources in social, environmental and economic contexts