HS7.4

The current patterns estimation of the water regime under climate change is one of the most urgent tasks in Ukraine and the world. Such changes are determined by fluctuations in the main climatic characteristics - precipitation and air temperature, which are defined the value of evaporation. These parameters influence on the annual runoff distribution and long-term runoff fluctuations. In particular, the annual precipitation redistribution is reflected in the corresponding changes in the river runoff.
The assessment of the current state and nature of changes in precipitation and river runoff of the Siverskyi Donets River Basin was made by comparing the current period (1991-2018) with the period of the climatological normal (1961-1990).
In general, for this area, it was defined the close relationship between the amount of precipitation and the annual runoff. Against the background of insignificant (about 1%) increase of annual precipitation in recent decades, it was revealed their redistribution by seasons and separate months. There is a decrease in precipitation in the cold period (November-February). This causes (along with other factors) a decrease in the amount of snow and, accordingly, the spring flood runoff. There are frequent cases of unexpressed spring floods of the Siverskyi Donets River Basin. The runoff during March-April (the period of spring flood within the Ukrainian part of the basin) decreased by almost a third.
The increase of precipitation during May-June causes a corresponding (insignificant) increase in runoff in these months. The shift of the maximum monthly amount of precipitation from May (for the period 1961-1990) to June (in the current period) is observed.
There is a certain threat to water supply in the region due to the shift in the minimum monthly amount of precipitation in the warm period from October to August. Compared with October, there is a higher air temperature and, accordingly, higher evaporation in August, which reduces the runoff. Such a situation is solved by rational water resources management of the basin. The possibility of replenishing water resources in the basin through the transfer runoff from the Dnieper (Dnieper-Siverskyi Donets channel) and the annual runoff redistribution in the reservoir system causes some increase in the river runoff of summer months in recent decades. This is also contributed by the activities of the river basin management structures, which control the maintenance water users' of minimum ecological flow downstream the water intakes and hydraulic structures in the rivers of the basin.
Therefore, in the period of current climate change, the annual runoff distribution of the Siverskyi Donets River Basin has undergone significant changes, which is related to the annual precipitation redistribution and anthropogenic load on the basin.

How to cite: Bolbot, H. and Grebin, V.: The «rainfall-runoff» system and its long-term fluctuations in the Siverskyi Donets River Basin (Ukraine), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13350, https://doi.org/10.5194/egusphere-egu21-13350, 2021.

During the last decades, scientific research in the field of flood risk management has provided new insights and strong computational tools towards the deeper understanding of the fundamental probabilistic and stochastic behaviour that characterizes such natural hazards. Flood hazards are controlled by hydrometeorological processes and their inherent uncertainties. Historically, a high percentage of flood disasters worldwide are inaccurately or ineffectively reported regarding the aggregated number of the affected people, economic losses and generated flood insurance claims. In this respect, the recently published National Flood Insurance Program (NFIP) data by the Federal Emergency Management Agency (FEMA), including more than two million claims records dating back to 1978 and more than 47 million policy records for transactions, may provide new insights into flood impacts. The aim of this research is to process the actual insurance data derived from this database, in order to detect the underlying patterns and investigate its stochastic structure, paving the way for the development of more accurate flood risk assessment and modelling strategies.

How to cite: Papoulakos, K., Iliopoulou, T., Dimitriadis, P., Tsaknias, D., and Koutsoyiannis, D.: Investigating the stochastic structure of the recently published Redacted Claims data set by the FEMA National Flood Insurance Program, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15007, https://doi.org/10.5194/egusphere-egu21-15007, 2021.

Changes in the land cover occur all the time at the surface of the Earth both naturally and anthropogenically. In the last decades, certain types of land cover change, including urbanization, have been correlated to local temperature increase, but the general dynamics of this relationship are still not well understood. This work examines whether land cover is a parameter affecting temperature increase by employing global datasets of land cover change, i.e. the Historical Land-Cover Change Global Dataset, and daily temperature from the NOAA database. We thoroughly investigate the temperature variability and its possible correlation to the different types of land-cover changes. A comparison is specifically made between the rate of temperature increase measured in urban areas, and the same rate measured in nearby non-urban areas.

How to cite: Lagos, A., Sigourou, S., Dimitriadis, P., Iliopoulou, T., and Koutsoyiannis, D.: Land Cover Change: Does it affect temperature variability?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9000, https://doi.org/10.5194/egusphere-egu21-9000, 2021.

Surface water resources are extremely vulnerable to climate variability and are seriously threatened by human activities. The depletion of surface water is expected to rapidly increase due to the combination of future climate change and world population growth projections. Under this scenario, the impacts of climate and human dynamics on surface water resources represent a global issue, requiring the definition of adequate management strategies that prevent water crisis and guarantee equitable access to freshwater resources. Remote sensing provides data that allow to monitor environmental change processes, such as changes in climatic conditions, land use, and spatial allocation of human settlements and activities. Although many products describing surface water dynamics and urban growth obtained from satellite imagery are available, an integrated analysis of such geospatial information has not been performed yet. Here, we explore the driving role of the variation in key climatic variables (e.g.,  precipitation, temperature, and soil moisture) and the extent of urban areas in the depletion of surface water across the watersheds in the United States by using data derived from remote sensing images and performing a correlation analysis. From our preliminary results, we observe that there is a positive correlation between surface water loss and the level of urbanization in each basin of our study area, meaning that surface water loss increases with the extent of urban area. On the contrary, we find that the correlation between surface water loss and precipitation has a counter-intuitive trend which needs to be further examined.

How to cite: Ceola, S. and Palazzoli, I.: Contribution of urbanization and climate variability on surface water depletion across USA watersheds, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-484, https://doi.org/10.5194/egusphere-egu21-484, 2021.

Since the pre-industrial era at the end of the 18^th century, the atmospheric carbon dioxide concentration (CO₂) has increased by 47.46% from the level of 280 ppmv (parts per million volume) to 412.89 ppmv (Mauna Loa – NOAA Station, November 2020). These increased concentrations caused by natural & anthropogenic activities, interact with the aquatic environment which acts as a safety valve. Nevertheless, the absorbed CO₂ amounts undergo chemical transformations, resulting in increasing ionized concentrations that can significantly reduce the water’s pH, a process described as ocean acidification. Here, we use the HOT (Hawaii-Ocean-Time series) to perform time series analysis for temperature, carbon dioxide partial pressure and pH. More specifically, we analyze their temporal changes in month and annual time lag. Then, we proceed in comparisons with relevant studies on atmospheric data to evaluate the produced results. Finally, we make an effort to disentangle the results with simplified assumptions connected with the observed impact of ocean acidification on the aquatic ecosystems.

How to cite: Vagenas, G., Iliopoulou, T., Dimitriadis, P., and Koutsoyiannis, D.: Stochastic analysis of time-series related to ocean acidification, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2637, https://doi.org/10.5194/egusphere-egu21-2637, 2021.