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The hydro-energy resources are considered as promising renewable energy sources, which emphasizes the need for assessment of theoretical hydrokinetic energy resources stored in Lithuanian rivers. This article presents the results of an investigation of the theoretical hydrokinetic energy in small and medium-size rivers. A total of 282 rivers (1487 segments) were examined and the relationships were established for evaluation of their hydrological and morphological indicators, such as river depth, width, and flow velocity. Only 41 rivers (328 segments) were identified as having a theoretical hydrokinetic potential. The total length of these valuable river segments reaches 2000 km. The estimated kinetic energy capacity calculated for a 1 km channel segment is 45.3 kW in South-eastern, 40.8 kW in Western, and 38.2 kW in Central Lithuania.

Uncertainties of runoff projections arise from different sources of origin, such as climate scenarios (RCPs), global climate models (GCMs) and statistical downscaling (SD) methods. Assessment of uncertainties related to the mentioned sources was carried out for selected rivers of Lithuania (Minija, Nevėžis and Šventoji). These rivers reflect conditions of different hydrological regions (western, central and southeastern). Using HBV software, hydrological models were created for river runoff projections in the near (2021–2040) and far (2081–2100) future. The runoff projections according to three RCP scenarios, three GCMs and three SD methods were created. In the Western hydrological region represented by the Minija River, the GCMs were the most dominant uncertainty source (41.0–44.5%) in the runoff projections. Meanwhile, uncertainties of runoff projections from central (Nevėžis River) and southeastern (Šventoji River) regions of Lithuania were related to SD methods and the range of uncertainties fluctuates from 39.4% to 60.9%. In western Lithuania, the main source of rivers' supply is precipitation, where projections highly depend on selected GCMs. The rivers from central and southeastern regions are more sensitive to the SD methods, which not always precisely adjust the meteorological variables from a large grid cell of GCM into catchment scale.

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The increase in hydrological extremes during the last two decades has had a significant impact on natural and social environments. These hydrological extremes depend greatly on changes in the meteorological parameters. The task of this research was to evaluate the impact of meteorological factors (snow water equivalent and heavy rainfall) on the formation of spring floods in the basins of the Nemunas, Lielupė and Venta rivers. Five Lithuanian rivers (Venta, Šešuvis, M uša, Merkys and Žeimena) from these basins were analysed in detail. These rivers fall within the Western, Central and Southeastern hydrological regions of Lithuania. Long-time-series data for daily discharge, precipitation and thickness of snow cover from 12 meteorological and five hydrological gauging stations were used. The evaluation of the relation between these factors was carried out for two periods: 1961-1987 and 1988-2014. The relation between the maximum discharge of the spring flood, the maximum snow water equivalent before the flood and the precipitation amount 10 days before the flood was analysed by multiple regression analysis. The high correlation co-efficients between the observed and predicted maximum discharges of the spring flood for the created regression models fluctuated between 0.63 and 0.86. The verification of the selected regression model was performed with Hydrologiska Byråns Vattenbalansavdelning (HBV) software, which also showed a high correlation co-efficient (0.71). The applied methodology of this research could be used for better perception of flood-formation consequences in different hydrological regions of Europe.