Investigation of a group of landforms and their underlying deposits on the eastern margin of the Fenland in East Anglia has demonstrated that they represent a series of glaciofluvial delta-fan and related sediments. Section logging, borehole records and previous descriptions combine to indicate that the sediments were deposited in icemarginal deltaic settings in an ice-marginal lake. The internal structure and form of the fan-like deltas has been demonstrated using extensive ground-penetrating radar investigation. The lake formed by the ice damming westward-aligned river valleys. Together, this evidence confirms historical descriptions of a glaciation of the Fenland, and clarifies the interpretation of gravels of the eastern Fenland margin. Recent reinterpretations of the latter as of fluvial rather than glacial meltwater origin are shown to be incorrect. It is concluded, on the basis of regional correlation, supported by optically stimulated luminescence dating, that the glaciation occurred at c. 160 kyr, i.e. in the Wolstonian (= Saalian) Stage (broadly equivalent to MIS ?11b-6). Comparison with The Netherlands' sequence shows a similarity of glacial marginal morphology, and the dates confirm the time equivalence with that during the late Saalian Drenthe Substage, Amersfoort ice-pushed ridge complex. The implications include that the c. 200 kyr interval, between the Hoxnian (Holsteinian) temperate Stage and the Wolstonian glaciation, was a period during which fluvial and periglacial activity modified the landscape under cold climates, with organic sediments laid down during warmer events. Palaeolithic humans were periodically present during this interval, their artefacts having been reworked by the subsequent glaciation.

A novel high-resolution (2-4 m source and receiver spacing) reflection and refraction seismic survey was carried out for aquifer characterization and to confirm the existing depositional model of the interlobate esker of Virttaankangas, which is part of the Säkylänharju-Virttaankangas glaciofluvial esker-chain complex in southwest Finland. The interlobate esker complex hosting the managed aquifer recharge (MAR) plant is the source of the entire water supply for the city of Turku and its surrounding municipalities. An accurate delineation of the aquifer is therefore critical for long-term MAR planning and sustainable use of the esker resources. Moreover, an additional target was to resolve the poorly known stratigraphy of the 70-100-m-thick glacial deposits overlying a zone of fractured bedrock. Bedrock surface as well as fracture zones were confirmed through combined reflection seismic and refraction tomography results and further validated against existing borehole information. The highresolution seismic data proved successful in accurately delineating the esker cores and revealing complex stratigraphy from fan lobes to kettle holes, providing valuable information for potential new pumping wells. This study illustrates the potential of geophysical methods for fast and cost-effective esker studies, in particular the digital-based landstreamer and its combination with geophone-based wireless recorders, where the cover sediments are reasonably thick.

Convolutional neural networks can provide a potential framework to characterize groundwater storage from seismic data. Estimation of key components, such as the amount of groundwater stored in an aquifer and delineate water table level, from active‐source seismic data are performed in this study. The data to train, validate and test the neural networks are obtained by solving wave propagation in a coupled poroviscoelastic–elastic media. A discontinuous Galerkin method is applied to model wave propagation, whereas a deep convolutional neural network is used for the parameter estimation problem. In the numerical experiment, the primary unknowns estimated are the amount of stored groundwater and water table level, while the remaining parameters, assumed to be of less of interest, are marginalized in the convolutional neural network‐based solution. Results, obtained through synthetic data, illustrate the potential of deep learning methods to extract additional aquifer information from seismic data, which otherwise would be impossible based on a set of reflection seismic sections or velocity tomograms.

Sedimentary sequences in Isoniemi and Hangaskangas in the Oulu area of Finland have been studied using conventional sedimentological techniques including structural and clastfabric measurements on fold and fault structures and till units. Four different facies were identified from the sequence in the Isoniemi area and three in the Hangaskangas area. In the Isoniemi area, the measurements of glaciotectonic deformation and till clast-fabric analyses can be related to the ice movement from the south-west and the subsequent ice front oscillation from the north-west. These ice movement phases are thought to have taken place during the Late Weichselian. In the Hangaskangas area, the south-western shearstress direction crosscuts the sediment strata indicating that the latest ice movement came from that direction during the Late Weichselian. However, there is also indication of an earlier shear-stress in the Hangaskangas area indicating the north-western ice movement. The age of this ice movement phase is thought to be older than the Late-Weichselian.

The behaviour of arsenic (As) derived from tailings was investigated at the Yara Siilinjärvi apatite mine and industrial site in eastern Finland. The study assessed factors influencing the migration and fate of As and compared the anthropogenic As load to the natural geogenic background. Environmental risks related to As were assessed by examining the As concentrations in humus, glacial till, aquatic sediments, groundwater, and surface water. The occurrence and fractionation of As and the presence of secondary precipitates and geochemical transformations in the tailings and in the ambient soil and sediment were evaluated by selective extraction. The water-derived emissions were evaluated by field measurements, hydrogeochemical analysis, and modelling. Results indicate elevated environmental risks due to dust and seepage emissions from the tailings since the concentrations and mobility of As and other potentially harmful elements (PHEs) such as Co, Ni, and Zn were elevated relative to the geogenic background. These elements were mainly associated with Fe (oxy)hydroxides in the soil and their mobility was closely linked to Fe biogeochemistry. Additionally, although the concentrations of As and PHEs were high in the tailings pond and seepage water, they decreased in ambient groundwater and surface water, indicating Fe (oxy)hydroxide stability. This was supported by hydrogeochemical modelling, which indicated precipitation of Fe oxides and hydroxides. According to speciation modelling, As was present mainly as toxic trivalent arsenious acid (H 3 AsO 3 ) in groundwater and as the less toxic pentavalent As acid (H 2 AsO 4 -and HAsO 4 2-) in surface water.