In 2020 and 2021 the city of Moscow, Russia, has experienced two historical rainfall events that had caused major flooding of small rivers. Based on long-term observation datasets from the surrounding weather stations, regional mesoscale COSMO-CLM climate model results, and a detailed hydrological and water quality monitoring data collected in 2019–2021, we performed pioneer climate change and urbanization impact assessment on flooding hazard and water quality of case study urban Setun river. Statistically significant rise of moderate extremity indices and absence of significant trends for the most extreme indices was revealed for the 1966‑2020 period. The combined impact of climate change and increased urbanization is highly non-linear and results in as much as a four-fold increase in extreme floods and shift of water regime features which lead to formation of specific seasonal flow patterns. The rainstorm flood wave catchment response, involving infiltrated and hillslope-routed fraction of rainfall, is accounted as 6 to 11 hours, which it is more than twice as rapid as compared to the non-urbanized nearby catchments. Behaviour of four types of chemicals in the river water during rainstorms was identified, as well as main differences compared to the spring freshet period revealed. Based on the obtained results we conclude that lack of research focused on the combined impacts of climate change and urbanization on flooding and water quality in the Moscow urban area is a key problem in water management advances.

In 2020 and 2021 the city of Moscow, Russia, has experienced two historical rainfall events that had caused major ooding of small rivers. Based on long-term observation datasets from the surrounding weather stations, regional mesoscale COSMO-CLM climate model results, and a detailed hydrological and water quality monitoring data collected in 2019-2021, we performed pioneer climate change and urbanization impact assessment on ooding hazard and water quality of case study urban Setun river. Statistically signi cant rise of moderate extremity indices and absence of signi cant trends for the most extreme indices was revealed for the 1966-2020 period. The combined impact of climate change and increased urbanization is highly non-linear and results in as much as a four-fold increase in extreme oods and shift of water regime features which lead to formation of speci c seasonal ow patterns. The rainstorm ood wave catchment response, involving in ltrated and hillslope-routed fraction of rainfall, is accounted as 6 to 11 hours, which it is more than twice as rapid as compared to the non-urbanized nearby catchments. Behaviour of four types of chemicals in the river water during rainstorms was identi ed, as well as main differences compared to the spring freshet period revealed. Based on the obtained results we conclude that lack of research focused on the combined impacts of climate change and urbanization on ooding and water quality in the Moscow urban area is a key problem in water management advances.

<p>Environmental geochemical studies of urban territories involve heterogeneous information that can be most effectively processed within a unified database (DB). Since a significant portion of the accumulated data is georeferenced, geographic information technologies should be used at all stages of the researches. The purpose of this work is to consider the structure of the DB for information support of ecological and geochemical studies of different urban environments in Moscow within the framework of the Russian Science Foundation project No. 19-77-30004 "Integrated technology for environmental assessment of Moscow megacity based on chemical analysis of microparticle composition in the "atmosphere - snow - road dust - soil - surface water" system (Megacity)".</p><p>The project aims to develop technologies for the chemical analysis of the urban environments impacted by the pollutants coming from vehicles, industry, and construction sites, as well as the assessment of the environmental state of the megacity. Various components of the environment are analyzed at several spatial scales: for the entire Moscow city, for administrative districts, for drainage basins of two urban rivers (Moskva and its tributary Setun). The composition of pollutant emissions is characterized using monitoring aerosol data at the Meteorological Observatory of Lomonosov Moscow State University. Microparticles PM<sub>10</sub> and PM<sub>2.5</sub> are analyzed for the content of elemental carbon, ionic and organic compounds, as well as potentially toxic elements, under different meteorological conditions and seasonal variations. The fallout of aerosols during winter is determined by the chemical analysis of dissolved and solid fractions of snow samples and its comparison with a natural background. Water migration of pollutants is assessed by analyzing river flows (water and suspended/bottom sediments) at reference stations in the Moskva River basin. The ecological state of road dust and soils that accumulate pollutants is estimated in geochemical surveying. Finally, source apportionment is quantified using statistical methods of multivariate analysis.</p><p>The development of a DB with the integrated geographic information system (GIS) allows systematizing the spatial and non-spatial information accumulated in field works, chemical and analytical studies, and organizing effective data storage and processing along with providing geoinformation support for DB users. We created four DB subsystems designed for: (1) processing georeferenced data (GIS); (2) working with time series; (3) handling regulatory and reference information; (4) assessing pollution and environmental hazard with computational models. For Moscow megacity, GIS brings together two large blocks of information: spatial layers stored within the geodatabase and spreadsheets with the results of field studies and chemical analyses. The main functions of the GIS are geoprocessing, execution of non-spatial and spatial queries, data analysis (including exploratory spatial data analysis and modeling), visualization of the results.</p><p>The report will present subsystems of the DB and the interrelationships between them. The use of the database in practice will be considered on the example of assessing the pollution of road dust with benzo(a)pyrene, accounting for anthropogenic and natural factors.</p>