Hydrogeological Prognoses in Infrastructure Projects : A Case Study of Stockholm Bypass, Hjulsta Norra

Sammanfattning: As cities expand, urban planning and efficient land use becomes more important and presents new challenges. A city that is exposed to these challenges is Stockholm, Sweden (Stockholms stad, 2018). The expansion of the city can lead to expensive acquisition of land above ground, which therefore results in an increase of subsurface infrastructure being constructed. The construction below ground level also imposes challenges affecting our urban environments above ground. One of the challenges when working below ground level is the management of groundwater. The groundwater exists in filled pores of soil and rock below the groundwater table and can potentially leak to a subsurface construction. However, redirecting the groundwater requires permission from the environmental court (SGU, 2017).  The purpose of this thesis is to examine how well a hydrogeological prognosis corresponds to the outcome of a specific infrastructure project; the contract Hjulsta Norra in the Stockholm Bypass. More specifically, the thesis has been divided in four different objectives relating to the main purpose. The thesis has been conducted through literature studies of reports and studies within relevant subjects as well as specific data analysis for the case of Hjulsta Norra.  The literature studies attempt to explain how hydrogeology relates to infrastructure, the building process, environmental legislation and the hydrogeological prognoses purpose. The case study is conducted for a part of the Stockholm Bypass that is developed by NCC; Hjulsta Norra. The Stockholm Bypass project is developed to increase accessibility around the Stockholm region (Trafikverket, 2020a). The contract consists of the construction of a tray and two concrete tunnels (NCC Infrastructure, 2017a) and the building process is divided into several stages (Montelius, 2020). Geologically, the area of the contract Hjulsta Norra is varied but mainly consists of gneiss or granite overlaid by friction soil and sometimes clay. The friction soil layer is partially below the groundwater level and therefore two different groundwater storages are found within the study area; Järva 6 and Järva 7 (Runesson, 2014). A hydrogeological prognosis has been developed by NCC for the purpose of investigating hydrogeological effects in the study area, how to maintain groundwater levels and if artificial infiltration is required to maintain the groundwater levels. The prognosis has been largely focused around attempting to model different cases of friction soil hydraulic conductivity, as this is a parameter that largely affects the groundwater levels in the area (Lundgren, 2017a; Lundgren, 2017b).  The results are presented in three sections. The first results present different components that may exist in a hydrogeological prognosis based upon literature studies. The second part evaluates the hydrogeological prognosis developed by NCC and the third part compares the actual outcome to the prognosis. The discussion is mainly focused around the specific case and the conclusions that can be drawn for the case study is that the hydrogeological prognosis is simplified and presents rather homogenous hydrogeological environments that results in a simple conceptual model. The differences between the prognosis and outcome are larger in some respects than others; among which the largest differences are the need for artificial infiltration in Järva 6. Some risks for development of the prognosis are brought forward relating to communication between stages of the building process, homogeneity in the prognosis and replacing investigated results with experience. Further, some possibilities for the development of the case study prognosis have been identified.  Finally, in accordance with the objectives, some transferable conclusions have been found in the case study that can be used in other projects. These conclusions relate to risk and uncertainty analysis, communication between stages of the building process, learning from other prognoses, combining methods of data gathering and analysis as well as making the prognosis easy to evaluate and compare.