title: A methodology for estimating risks associated with landslides of contaminated soil into rivers.
abstract: 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.
authors.affiliation: Department of Land use Planning and Climate Adaptation, Swedish Geotechnical Institute, SE-412 96 Gothenburg, Sweden; Department of Water Resources Engineering, Lund University, SE-221 00 Lund, Sweden. Electronic address: gunnel.goransson@swedgeo.se.
authors.forename: Gunnel
authors.initials: G
authors.lastname: Göransson
authors.affiliation: Department of Land use Planning and Climate Adaptation, Swedish Geotechnical Institute, SE-412 96 Gothenburg, Sweden; Department of Civil and Environmental Engineering, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden. Electronic address: jenny.norrman@chalmers.se.
authors.forename: Jenny
authors.initials: J
authors.lastname: Norrman
authors.affiliation: Department of Water Resources Engineering, Lund University, SE-221 00 Lund, Sweden. Electronic address: magnus.larson@tvrl.lth.se.
authors.forename: Magnus
authors.initials: M
authors.lastname: Larson
authors.affiliation: Department of Civil and Environmental Engineering, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden. Electronic address: claes.alen@chalmers.se.
authors.forename: Claes
authors.initials: C
authors.lastname: Alén
authors.affiliation: Department of Civil and Environmental Engineering, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden. Electronic address: lars.rosen@chalmers.se.
authors.forename: Lars
authors.initials: L
authors.lastname: Rosén
mesh_terms: D004784:Environmental Monitoring / Q000379:methods*; D055876:Landslides / Q000706:statistics & numerical data*; D008962:Models, Theoretical; D011336:Probability; D018570:Risk Assessment; D045483:Rivers; D012987:Soil / Q000737:chemistry*; D013548:Sweden; D014876:Water Pollution / Q000706:statistics & numerical data*
chemical_list: D012987:Soil
keywords: Contaminated sites; Environmental risk assessment; Landslide risk assessment; Monte Carlo simulation; Pollution transport; Water quality