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Construction below the ground surface and underneath the groundwater table is often associated with groundwater leakage and drawdowns in the surroundings which subsequently can result in a wide variety of risks. To avoid groundwater drawdown-associated damages, risk-reducing measures must often be implemented. Due to the hydrogeological system’s inherent variability and our incomplete knowledge of its conditions, the effects of risk-reducing measures cannot be fully known in advance and decisions must inevitably be made under uncertainty. When implementing risk-reducing measures there is always a trade-off between the measures’ benefits (reduced risk) and investment costs which needs to be balanced. In this paper, we present a framework for decision support on measures to mitigate hydrogeological risks in underground construction. The framework is developed in accordance with the guidelines from the International Standardization Organization (ISO) and comprises a full risk-management framework with focus on risk analysis and risk evaluation. Cost–benefit analysis (CBA) facilitates monetization of consequences and economic evaluation of risk mitigation. The framework includes probabilistic risk estimation of the entire cause–effect chain from groundwater leakage to the consequences of damage where expert elicitation is combined with data-driven and process-based methods, allowing for continuous updating when new knowledge is obtained.
Johanna Merisalu; Jonas Sundell; Lars Rosén. A Framework for Risk-Based Cost–Benefit Analysis for Decision Support on Hydrogeological Risks in Underground Construction. Geosciences 2021, 11, 82 .
AMA StyleJohanna Merisalu, Jonas Sundell, Lars Rosén. A Framework for Risk-Based Cost–Benefit Analysis for Decision Support on Hydrogeological Risks in Underground Construction. Geosciences. 2021; 11 (2):82.
Chicago/Turabian StyleJohanna Merisalu; Jonas Sundell; Lars Rosén. 2021. "A Framework for Risk-Based Cost–Benefit Analysis for Decision Support on Hydrogeological Risks in Underground Construction." Geosciences 11, no. 2: 82.
We present a method for risk assessment of groundwater drawdown induced land subsidence when planning for sub-surface infrastructure. Since groundwater drawdown and related subsidence can occur at large distances from the points of inflow, the large spatial extent often implies heterogeneous geological conditions that cannot be described in complete detail. This calls for estimation of uncertainties in all components of the cause-effect chain with probabilistic methods. In this study, we couple four probabilistic methods into a comprehensive model for economic risk quantification: a geostatistical soil-stratification model, an inverse calibrated groundwater model, an elasto-plastic subsidence model, and a model describing the resulting damages and costs on individual buildings and constructions. Groundwater head measurements, hydraulic tests, statistical analyses of stratification and soil properties and an inventory of buildings are inputs to the models. In the coupled method, different design alternatives for risk reduction measures are evaluated. Integration of probabilities and damage costs result in an economic risk estimate for each alternative. Compared with the risk for a reference alternative, the best prior alternative is identified as the alternative with the highest expected net benefit. The results include spatial probabilistic risk estimates for each alternative where areas with significant risk are distinguished from low-risk areas. The efficiency and usefulness of this modelling 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 railway tunnel in Varberg, Sweden.
Jonas Sundell; Ezra Haaf; Johannes Tornborg; Lars Rosén. Comprehensive risk assessment of groundwater drawdown induced subsidence. Stochastic Environmental Research and Risk Assessment 2019, 33, 427 -449.
AMA StyleJonas Sundell, Ezra Haaf, Johannes Tornborg, Lars Rosén. Comprehensive risk assessment of groundwater drawdown induced subsidence. Stochastic Environmental Research and Risk Assessment. 2019; 33 (2):427-449.
Chicago/Turabian StyleJonas Sundell; Ezra Haaf; Johannes Tornborg; Lars Rosén. 2019. "Comprehensive risk assessment of groundwater drawdown induced subsidence." Stochastic Environmental Research and Risk Assessment 33, no. 2: 427-449.
A procedure is presented for valuation of information analysis (VOIA) to determine the need for additional information when assessing the effect of several design alternatives to manage future disturbances in hydrogeological systems. When planning for groundwater extraction and drawdown in areas where risks—such as land subsidence, wells running dry and drainage of streams and wetlands—are present, the need for risk-reducing safety measures must be carefully evaluated and managed. The heterogeneity of the subsurface calls for an assessment of trade-offs between the benefits of additional information to reduce the risk of erroneous decisions and the cost of collecting this information. A method is suggested that combines existing procedures for inverse probabilistic groundwater modelling with a novel method for VOIA. The method results in (1) a prior analysis where uncertainties regarding the efficiency of safety measures are estimated, and (2) a pre-posterior analysis, where the benefits of expected uncertainty reduction deriving from additional information are compared with the costs for obtaining this information. In comparison with existing approaches for VOIA, the method can assess multiple design alternatives, use hydrogeological parameters as proxies for failure, and produce spatially distributed VOIA maps. The method is demonstrated for a case study of a planned tunnel in Stockholm, Sweden, where additional investigations produce a low number of benefits as a result of low failure rates for the studied alternatives and a cause-effect chain where the resulting failure probability is more dependent on interactions within the whole system rather than on specific features. Une procédure est présentée qui vise l’évaluation de l’analyse des informations (EDAI) dans le but de déterminer le besoin en connaissances supplémentaires quand on estime l’effet de plusieurs alternatives de conception pour gérer les perturbations futures au sein des systèmes hydrogéologiques. Dans le cas d’une planification de l’exploitation et de l’abaissement des eaux souterraines dans les zones où des risques—comme l’affaissement du sol, l’assèchement des puits, le drainage des cours d’eau et des zones humides—sont présents, le besoin de mesures de sécurité réduisant le risque doit être soigneusement évalué et géré. L’hétérogénéité du sous-sol nécessite une évaluation du compromis entre les avantages d’une information supplémentaire destinée à réduire le risque lié à des décisions erronées et le coût de la collecte de cette information. Une méthode est proposée, qui combine les procédures existantes de modélisation probabiliste inverse des eaux souterraines et une méthode nouvelle pour l’EDAI. La méthode aboutit (1) à une analyse a priori là où les incertitudes concernant l’efficacité des mesures de sécurisation sont estimées, et (2) à une analyse a postériori, là où les...
Jonas Sundell; Tommy Norberg; Ezra Haaf; Lars Rosén. Economic valuation of hydrogeological information when managing groundwater drawdown. Hydrogeology Journal 2019, 27, 1111 -1130.
AMA StyleJonas Sundell, Tommy Norberg, Ezra Haaf, Lars Rosén. Economic valuation of hydrogeological information when managing groundwater drawdown. Hydrogeology Journal. 2019; 27 (4):1111-1130.
Chicago/Turabian StyleJonas Sundell; Tommy Norberg; Ezra Haaf; Lars Rosén. 2019. "Economic valuation of hydrogeological information when managing groundwater drawdown." Hydrogeology Journal 27, no. 4: 1111-1130.
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.
Jonas Sundell; Ezra Haaf; Tommy Norberg; Claes Alén; Mats Karlsson; Lars Rosén. Risk Mapping of Groundwater-Drawdown-Induced Land Subsidence in Heterogeneous Soils on Large Areas. Risk Analysis 2017, 39, 105 -124.
AMA StyleJonas Sundell, Ezra Haaf, Tommy Norberg, Claes Alén, Mats Karlsson, Lars Rosén. Risk Mapping of Groundwater-Drawdown-Induced Land Subsidence in Heterogeneous Soils on Large Areas. Risk Analysis. 2017; 39 (1):105-124.
Chicago/Turabian StyleJonas Sundell; Ezra Haaf; Tommy Norberg; Claes Alén; Mats Karlsson; Lars Rosén. 2017. "Risk Mapping of Groundwater-Drawdown-Induced Land Subsidence in Heterogeneous Soils on Large Areas." Risk Analysis 39, no. 1: 105-124.
Sub-surface construction in urban areas generally involves drainage of groundwater, which can induce subsidence in soil deposits. Knowledge of where compressible sediments are located and how thick these are is essential for estimating subsidence risk. A probabilistic method for coupled bedrock-level and soil-layer modeling to detect compressible sediments is presented. The method is applied in an area in central Stockholm, where clay is the compressible sediment layer. First, a bedrock-level model was constructed from three sources of information: (a) geotechnical drillings reaching the bedrock; (b) drillings not reaching the bedrock; and (c) mapped bedrock outcrops. Input data for the probabilistic bedrock-level model was generated by a stepwise Kriging procedure. Second, a three layer soil model was constructed, including the following materials: (a) coarse grained post glacial and filling material below the ground surface; (b) glacial and post-glacial clays; and (c) coarse grained glaciofluvial and glacial till deposits above the bedrock. Layer thicknesses were transformed to proportions of the total soil thickness. Since Kriging requires data to be normally distributed, the proportions were transformed from proportions (P) to standard normal quantiles (z). In each iteration of a Monte-Carlo simulation, a spatial distribution of the bedrock level was simulated together with the transformed values for the soil-layer proportions. From the iterations, the probability density of the clay thickness (compressible sediments) at each grid cell was calculated. The results of the case study map the expected value (mean) and the 95th percentile of the probability of compressible sediments at specific locations. The resulting model is geologically realistic and validated through a cross-validation procedure in order to be in good agreement with a reference dataset. The case study showed that the method can efficiently handle large amounts of data and requires little manual adjustment. Moreover, the mapped results can provide useful decision support when planning risk-reducing measures and when communicating with stakeholders. Although this novel method is developed for risk assessment of groundwater drawdown induced subsidence, it is useful for other applications involving spatial soil strata modeling.
Jonas Sundell; Lars Rosén; Tommy Norberg; Ezra Haaf. A probabilistic approach to soil layer and bedrock-level modeling for risk assessment of groundwater drawdown induced land subsidence. Engineering Geology 2016, 203, 126 -139.
AMA StyleJonas Sundell, Lars Rosén, Tommy Norberg, Ezra Haaf. A probabilistic approach to soil layer and bedrock-level modeling for risk assessment of groundwater drawdown induced land subsidence. Engineering Geology. 2016; 203 ():126-139.
Chicago/Turabian StyleJonas Sundell; Lars Rosén; Tommy Norberg; Ezra Haaf. 2016. "A probabilistic approach to soil layer and bedrock-level modeling for risk assessment of groundwater drawdown induced land subsidence." Engineering Geology 203, no. : 126-139.