(Table 2) Geochemical composition of suspended matter samples from the northern Dvina River

The results of the analysis of samples of the Northern Dvina River's suspended particulate matter obtained by the sedimentation method from large water volumes in the periods of the spring high water and summer low water are presented. By the method of sequential leaching using different reagents, four fractions have been separated: the F1 is the sorbed complex and carbonates, the F2 is the amorphous hydroxides of Fe and Mn, the F3 is the form connected with the organic matter, and the F4 is the residual or silicate-detrital (inert) form. The data have shown that all ten elements determined were grouped with respect to the ratio of the distinguished forms: F4 is the predominant form for Al and Fe (73-88% of all the forms; however, the summer sample contains only 38% of this form of iron, and F2 is the predominant form for this period with 46.6%). As to Mn, the F1, F2, and F4 are nearly equally distributed in the spring high water samples, and only the F3 form is less important (5.4%). In the summer sample, the manganese sorbed complex is predominant (53.5%); for Cu, Ni, Cr, and Co, the inert F4 form is predominant (60-70%) in the sample of the spring suspended matter. The summer low water suspended matter has a lower F4 contribution (25-45%); for Zn, Pb, and Cd, the equal distribution of the forms in the spring samples is typical, while the summer suspended matter differs by the F2 form's predominance (53-61% for Zn and Pb). The main conclusion from the acquired data is that the geochemical mobility of all the studied elements, except for cadmium, in the summer low water suspended matter is higher than in the spring suspended matter. The more intensive biogeochemical processes in August, the high level of organic matter, and the higher contribution of phytoplankton lead to the intensification of the metals' geochemical activity in the Northern Dvina suspended matter in the end of the summer compared to the spring high water period when the physical processes are predominant over the biogeochemical ones due to the high speeds of the freshened waters flow.

Robust trends of landscape dynamics in the Arctic Lena Delta with temporally dense Landsat time-series stacks, with links to GeoTIFFs

Arctic permafrost landscapes are among the most vulnerable and dynamic landscapes globally, but due to their extent and remoteness most of the landscape changes remain unnoticed. In order to detect disturbances in these areas we developed an automated processing chain for the calculation and analysis of robust trends of key land surface indicators based on the full record of available Landsat TM, ETM +, and OLI data. The methodology was applied to the ~ 29,000 km**2 Lena Delta in Northeast Siberia, where robust trend parameters (slope, confidence intervals of the slope, and intercept) were calculated for Tasseled Cap Greenness, Wetness and Brightness, NDVI, and NDWI, and NDMI based on 204 Landsat scenes for the observation period between 1999 and 2014. The resulting datasets revealed regional greening trends within the Lena Delta with several localized hot-spots of change, particularly in the vicinity of the main river channels. With a 30-m spatial resolution various permafrost-thaw related processes and disturbances, such as thermokarst lake expansion and drainage, fluvial erosion, and coastal changes were detected within the Lena Delta region, many of which have not been noticed or described before. Such hotspots of permafrost change exhibit significantly different trend parameters compared to non-disturbed areas. The processed dataset, which is made freely available through the data archive PANGAEA, will be a useful resource for further process specific analysis by researchers and land managers. With the high level of automation and the use of the freely available Landsat archive data, the workflow is scalable and transferrable to other regions, which should enable the comparison of land surface changes in different permafrost affected regions and help to understand and quantify permafrost landscape dynamics.