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The assessment and mapping of riverine flood hazards and risks is recognized by many countries as an important tool for characterizing floods and developing flood management plans. Often, however, these management plans give attention primarily to open-water floods, with ice-jam floods being mostly an afterthought once these plans have been drafted. In some Nordic regions, ice-jam floods can be more severe than open-water floods, with floodwater levels of ice-jam floods often exceeding levels of open-water floods for the same return periods. Hence, it is imperative that flooding due to river ice processes be considered in flood management plans. This also pertains to European member states who are required to submit renewed flood management plans every six years to the European governance authorities. On 19 and 20 October 2022, a workshop entitled “Assessing and mitigating ice-jam flood hazard and risk” was hosted in Poznań, Poland to explore the necessity of incorporating ice-jam flood hazard and risk assessments in the European Union’s Flood Directive. The presentations given at the workshop provided a good overview of flood risk assessments in Europe and how they may change due to the climate in the future. Perspectives from Norway, Sweden, Finland, Germany, and Poland were presented. Mitigation measures, particularly the artificial breakage of river ice covers and ice-jam flood forecasting, were shared. Advances in ice processes were also presented at the workshop, including state-of-the-art developments in tracking ice-floe velocities using particle tracking velocimetry, characterizing hanging dam ice, designing new ice-control structures, detecting, and monitoring river ice covers using composite imagery from both radar and optical satellite sensors, and calculating ice-jam flood hazards using a stochastic modelling approach.

Natural treatment systems for wastewater (NTSW) allow us to not only reduce environmental pollution with sewage, but also to facilitate the reuse of water. This study presents almost 2.5 years of operation of a NTSW pilot plant, where the purpose of which was to purify domestic sewage from the building of the Institute of Applied Ecology (with three permanent residents and up to five employees) to the quality of drinking water. The NTSW consists of a septic tank, compost beds, and denitrification, phosphorus, and active carbon beds. With an active area of 3 m2 per person and a hydraulic residence time (HRT) of 6 days (excluding the HRT of the tank of 8 days), the NTSW allowed for a mean reduction of 99%, 95%, and 98% for the biological oxygen demand (BOD), chemical oxygen demand (COD), and total suspended solids (TSSs), respectively. The renewed water was characterized by average concentrations of 2.2 mg O2/dm3, 17.8 mg O2/dm3, 2.1 mg/dm3, 4.9 mg O2/dm3, and 0.6 nephelometric turbidity units for BOD, COD, TSS, oxidation, and turbidity, respectively. Thus, it met Polish and European drinking water requirements in terms of oxidation and turbidity. This water can be reused for toilet flushing and irrigation.

<p lang="en-US" align="justify">Water surface slope (WSS) of rivers is a key parameter in hydrological modelling, which allows for estimation of the transport and erosion capacity of a river, its flow velocity and discharge. On a local scale, WSS can be measured with a GNSS receiver installed on a boat, using remote sensing techniques (e.g. airborne lidar) or from a Digital Elevation Model (DEM). The most accurate method to measure WSS avoiding high-cost field campaigns is based on Water Surface Elevations (WSE) measured at in-situ stations. However, in poorly gauged rivers the neighboring gauges can be up to hundreds of kilometers apart, which inhibits a proper river profile observation. The gap in decreasing number of gauge readings is partially filled with satellite altimetry over rivers. Altimetry based WSE can be used to estimate WSS between neighboring measurements. Here, we present an innovative approach for estimating high-resolution WSS derived from multi-mission satellite altimetry for the largest Polish rivers.</p> <p lang="en-US" align="justify">In this study, we used measurements from 9 altimetry missions: CryoSat-2, Envisat, ICESat-2, Jason-2/-3, SARAL, Sentinel-3A/-B, and Sentinel-6A. These observations cover the years from 2002 to 2022. We extracted the river centerlines from the global “SWOT Mission River Database” (SWORD). In order to validate the obtained results, we used WSE from 81 gauges, which are maintained by the Institute of Meteorology and Water Management – National Research Institute (Instytut Meteorologii i Gospodarki Wodnej – Państwowy Instytut Badawczy, IMGW-PIB). These measurements are referenced to the Kronsztadt’86 vertical datum and they range from 01.2016 to 05.2022. Additionally, we used the reach-scale “ICESat-2 River Surface Slope” (IRIS) and the DEM-derived WSS values from SWORD.</p> <p lang="en-US" align="justify">To obtain WSS, we first determined WSE at each satellite pass crossing the studied river. Next, we split rivers into sections without dams and reservoirs. The Support Vector Regression (SVR) has been applied to reject outliers. Then, water levels were assigned to a given river kilometer (bin). For each of them a median WSE has been calculated. Finally, WSS were calculated at river sections between bins, excluding those disrupted by hydraulic structures. Finally, we weighted the section-wise WSS inversely proportional to the length of each section and applied a Least Square Adjustment with an additional Laplace condition to obtain bin-wise WSS for each river kilometer.</p> <p lang="en-US" align="justify">To assess the accuracy of the proposed approach, we compared the obtained WSS with the slopes between IMGW-PIB gauges. For large rivers (Vistula, Odra, Warta), the multi-mission approach revealed high accuracy with preliminary Root Mean Squared Error (RMSE) below 30 mm/km. For smaller, mountain rivers (San, Dunajec) the preliminary errors were slightly larger (RMSE ~100 mm/km). We also compared our accuracies with those of the slopes based on DEM models, lidar data, ICESat-2 altimetry, and SWORD database. In general, the multi-mission approach revealed the highest accuracy. The research is supported by the National Science Centre, Poland, through the project no. 2020/38/E/ST10/00295.</p>