Claes Alén

A methodology for estimating risks associated with landslides of contaminated soil into rivers.

Urban areas adjacent to surface water are exposed to soil movements such as erosion and slope failures (landslides). A landslide is a potential mechanism for mobilisation and spreading of pollutants. This mechanism is in general not included in environmental risk assessments for contaminated sites, and the consequences associated with contamination in the soil are typically not considered in landslide risk assessments. This study suggests a methodology to estimate the environmental risks associated with landslides in contaminated sites adjacent to rivers. The methodology is probabilistic and allows for datasets with large uncertainties and the use of expert judgements, providing quantitative estimates of probabilities for defined failures. The approach is illustrated by a case study along the river Göta Älv, Sweden, where failures are defined and probabilities for those failures are estimated. Failures are defined from a pollution perspective and in terms of exceeding environmental quality standards (EQSs) and acceptable contaminant loads. Models are then suggested to estimate probabilities of these failures. A landslide analysis is carried out to assess landslide probabilities based on data from a recent landslide risk classification study along the river Göta Älv. The suggested methodology is meant to be a supplement to either landslide risk assessment (LRA) or environmental risk assessment (ERA), providing quantitative estimates of the risks associated with landslide in contaminated sites. The proposed methodology can also act as a basis for communication and discussion, thereby contributing to intersectoral management solutions. From the case study it was found that the defined failures are governed primarily by the probability of a landslide occurring. The overall probabilities for failure are low; however, if a landslide occurs the probabilities of exceeding EQS are high and the probability of having at least a 10% increase in the contamination load within one year is also high.

Risk Mapping of Groundwater-Drawdown-Induced Land Subsidence in Heterogeneous Soils on Large Areas

Abstract Groundwater leakage into subsurface constructions can cause reduction of pore pressure and subsidence in clay deposits, even at large distances from the location of the construction. The potential cost of damage is substantial, particularly in urban areas. The large‐scale process also implies heterogeneous soil conditions that cannot be described in complete detail, which causes a need for estimating uncertainty of subsidence with probabilistic methods. In this study, the risk for subsidence is estimated by coupling two probabilistic models, a geostatistics‐based soil stratification model with a subsidence model. Statistical analyses of stratification and soil properties are inputs into the models. The results include spatially explicit probabilistic estimates of subsidence magnitude and sensitivities of included model parameters. From these, areas with significant risk for subsidence are distinguished from low‐risk areas. The efficiency and usefulness of this modeling approach as a tool for communication to stakeholders, decision support for prioritization of risk‐reducing measures, and identification of the need for further investigations and monitoring are demonstrated with a case study of a planned tunnel in Stockholm.

A framework for Risk Assessment of Groundwater Drawdown Induced Subsidence

Sub-surface constructions generally involve drainage of groundwater, which can induce land subsidence in compressible soil deposits and cause extensive damage costs in urban areas. A probabilistic framework, in accordance with the risk management framework outlined by the International Standard Organization (ISO), for assessing risks of groundwater drawdown induced subsidence is presented here. The framework consists of five modules: (1) A stratified geostatistical (Kriging) procedure for probabilistic spatial analysis of soil layers. This module is necessary for a detailed understanding of the soil stratification, drainage paths, and their potential spatial variations; (2) A stochastic hydrogeological model capable of representing possible groundwater drawdowns for a specific sub-surface construction; (3) A stochastic subsidence model; (4) A model for estimating the economic consequences and calculating the risk, i. e. the expected cost, of groundwater induced subsidence; and (5) A module for evaluating the need for additional information to reduce the risk of erroneous decisions with respect to risk acceptance criteria based on economic Value of Information Analysis (VOIA), i. e. a cost-benefit analysis (CBA) of additional information collection alternatives for suggested strategies to reduce or control subsidence. The modelled land-area is represented by a grid with calculation points. When the three first modules are linked together in a Monte Carlo-simulation, it is possible to estimate the spatial distribution of probability of subsidence and evaluate the sensitivity to different model and parameter assumptions. An estimation of the risk of subsidence is performed by combining the probability of land subsidence with the locations and expected damage costs of existing buildings across the modeled area (module 4). With sensitivity analysis, significant weaknesses can be identified and robust safety measures at locations with significant risks for subsidence can be planned for. Uncertainties can be communicated by mapping and comparing different outcomes of the model, e. g. the expected value and the 95th percentile of the risk. Together with affected stakeholders the assumptions and the outcomes of the model should be discussed - both how well the model describes the system dynamics and how safety measures should be implemented.