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At the beginning of the 21st century, ongoing climate change led to research into extreme streamflow phenomena. This study aimed to assess the patterns of low-flow changes in different hydrological regions of Lithuania using selected hydrological indices (the annual minimum 30-day flow (m3 s−1) of the warm period—30Q), its duration, and deficit volume (below the 80th and 95th percentile flow: 30Q80 and 30Q95). Differences in low-flow indices in separate hydrological regions and over different periods (1961–2020, 1961–1990, 1991–2020) were analyzed, applying the HydroOffice tool, the TREND software package, and mapping using the Kriging interpolation. The highest specific indices of 30Q were estimated in the Southeastern hydrological region (3.97 L/s·km2) and the lowest in the Central hydrological region (1.47 L/s·km2). In general, the 30Q values in the periods 1961–2020 and 1991–2020 had no trends. In 1961–1990, trends in 30Q data were significantly positive, and positive in most investigated rivers of the Western and Central hydrological regions. The average number of dry days at both thresholds decreased in the Western and Southeastern hydrological regions and increased in the Central hydrological region comparing two subperiods.

The problem of droughts is acute due to climate change. The study aims to assess the temporal and spatial drought patterns in Lithuanian lowland rivers in the past and to project these phenomena according to climate scenarios and models. Drought analysis was based on Standardized Precipitation Index (SPI), Reconnaissance Drought Index (RDI) and Streamflow Drought Index (SDI). To evaluate the past patterns, the hydrometeorological data of 17 rivers were used from 1961–2020. Future drought changes were analyzed in 2021–2100 according to the selected RCPs (Representative Concentration Pathways) using the hydrological model HBV. There were different patterns of droughts in three hydrological regions of Lithuania (Western, Central and Southeastern). The Southeastern region was more prone to extreme summer hydrological droughts, and they had a shorter accumulation period compared to the other two regions. SPI and RDI indices showed that the number of dry months and the minimum value of the index increased, extending the accumulation period. The highest correlation was recorded between RDI-12/SPI-12 and SDI-12. The amplitude between extremely wet and dry values of river runoff will increase according to RCP8.5. The projections indicated that hydrological drought intensity in the Central region is expected to increase under both analyzed RCPs.

The potential effects of climate change on nutrient (total N and total P) loads in four large-scale (A=2940 6771 km2) river basins in Lithuania were analyzed. The climate impact assessment was based on an ensemble of four (RCP2.6, RCP4.5, RCP6.0 and RCP8.5) future climate projections, representing the averaged outputs from three (GFDL-CM3, NorESM1-M and HadGEM2-ES) global climate models. For each climate projection, near-future (2016 2035) and distant-future (2081 2100) time periods were compared to the baseline period (1986 2005) to distinguish future changes. The results have shown a decreasing trend in the annual nutrient loads in most of the studied rivers under the projected climate change. Seasonal changes in nutrient loads are also predicted with an increase occurring during the winter months and a fairly high decrease occurring in the spring and early summer months. These changes are consistent with the projected changes in the seasonal stream flow.

Within the SMIRES COST Action (Science and Management of Intermittent Rivers & Ephemeral Streams, www.smires.eu), examples of intermittent rivers across Europe were collected, including gauged catchments with both natural and highly influenced river flow regimes. The examples will be published in a catalogue to give a good overview of the variety of intermittent streams in Europe. Information on the gauged intermittent rivers is summarised in a two-page template: The first page of the template describes the main characteristics of the catchments (land-use, geology, climate, etc.) and the river flow regime. Two panels display hydrographs and flow durations curves and a table gives metrics specific to river flow intermittence relevant for ecology. These hydrological indices have been computed by the SMIRES R package (https://homepage.boku.ac.at/h0540352/smires/framework.html) applied to daily discharge data. The second page of the template is dedicated to the description and reasons for intermittence. A short description about the spatio-temporal pattern of zero-flow events (encompassing seasonal behaviour, observed long-term trends, locations with frequently observed zero-flow events along the river network, etc.). The monitoring network, including gauging stations and other types of observations (e.g. visual inspection of the flow states at different locations along the river) in the catchment, is also described. This presentation gives examples of the pages in the catalogue and a preliminary classification of intermittent rivers at the European scale.

Particular attention is given to the reliability of hydrological modelling results. The accuracy of river runoff projection depends on the selected set of hydrological model parameters, emission scenario and global climate model. The aim of this article is to estimate the uncertainty of hydrological model parameters, to perform sensitivity analysis of the runoff projections, as well as the contribution analysis of uncertainty sources (model parameters, emission scenarios and global climate models) in forecasting Lithuanian river runoff. The impact of model parameters on the runoff modelling results was estimated using a sensitivity analysis for the selected hydrological periods (spring flood, winter and autumn flash floods, and low water). During spring flood the results of runoff modelling depended on the calibration parameters that describe snowmelt and soil moisture storage, while during the low water period—the parameter that determines river underground feeding was the most important. The estimation of climate change impact on hydrological processes in the Merkys and Neris river basins was accomplished through the combination of results from A1B, A2 and B1 emission scenarios and global climate models (ECHAM5 and HadCM3). The runoff projections of the thirty-year periods (2011–2040, 2041–2070, 2071–2100) were conducted applying the HBV software. The uncertainties introduced by hydrological model parameters, emission scenarios and global climate models were presented according to the magnitude of the expected changes in Lithuanian rivers runoff. The emission scenarios had much greater influence on the runoff projection than the global climate models. The hydrological model parameters had less impact on the reliability of the modelling results.

Extreme floods can be caused by various combinations of hydrological and meteorological factors and river basin conditions that have not been observed for a long time. Long-term observational series permit estimation of both the frequency and variation of spring floods – the key issues of protection systems. Fortunately, Baltic States have a long-term record of hydrological data for the last 80 years. In this research, spring flood parameters (maximum discharge, height of maximum discharge and its timing) for the Baltic countries were assessed for four periods (1922–2008, 1941–2008, 1961–2008 and 1991–2008). In total, 70 hydrological data series of spring flood parameters were used. To detect trends in time series for these periods, the Mann–Kendall test and the nonparametric Sen's method for the magnitude of the trend were used. The index flood method was used to estimate the maximum discharge in ungauged catchments. The results showed that maximum discharges and heights of spring floods decreased over a longer period. Spring flood peaks took place on earlier dates. Only some significant trends of maximum discharges and their timing were found in the last time period (1991–2008). All these changes could be caused by the increasing ambient temperature and precipitation in the later decades.

The river discharge changes in three Baltic States and its relation to changes in the main climatic variables such as precipitation and air temperature were analyzed using observed data and methods of empirical statistical analysis. The study is important for the development of efficient water resource management systems and validation of climate change impact models. The application of the Mann-Kendall test reveals that a significant increasing trend in winter air temperature and precipitation was determined for all 3 investigated periods (1923–2003, 1941–2003 and 1961–2003). The same trend was found for the winter and annual discharge time series. No trend was observed for the spring, summer and autumn seasonal streamflow and summer low flow series for most of the Baltic region. In general the relation between the main meteorological and hydrological parameters and the tendency in river discharge trends is common for all of the Baltic States, and might be associated with the regional impacts of global climate change.

This study compiles a new dataset, consisting of the longest available flow series from across Europe, and uses it to study the spatial and temporal clustering of flood events across the continent. Hydrological series at 102 gauging stations were collected from 25 European countries. Five geographically distinct large-scale homogeneous regions are identified: (i) an Atlantic region, (ii) a Continental region, (iii) a Scandinavian region, (iv) an Alpine region, and (v) a Mediterranean region. The months with a higher likelihood of flooding were identified in each region. The analysis of the clustering of annual counts of floods revealed an over-dispersion in the Atlantic and Continental regions, forming flood-rich and flood-poor periods, as well as an under-dispersion in the Scandinavian region that points to a regular pattern of flood occurrences at the inter-annual scale. The detection of trends in flood series is attempted by basing it on the identified regions, interpreting the results at a regional scale and for various time periods: 1900-1999; 1920-1999; 1939-1998 and 1956-1995. The results indicate that a decreasing trend in the magnitude of floods was observed mainly in the Continental region in the period 1920-1999 with 22% of the catchments revealing such a trend, as well as a decreasing trend in the timing of floods in the Alpine region in the period 1900-1999 with 75% of the catchments revealing this trend. A mixed pattern of changes in the frequency of floods over a threshold and few significant changes in the timing of floods were detected. (C) 2015 Elsevier B.V. All rights reserved.

Estimation of both the frequency and variation of spring floods is a key issue for the assessment and management of flood risks. Changes in river floods in Estonia, Latvia and Lithuania have been investigated in few national studies. However, there are no studies of the changes of flood patterns by using a common methodology for the rivers of this region. In this study flood pattern changes in the rivers of the Baltic countries were estimated applying trend and frequency analysis for the periods of 1922–2010, 1922–1960, 1961–2010 and 1991–2010, i.e. for the whole spring flood data sets, periods before and after 1960 (this year was considered as the beginning of the remarkable climate change), as well as for the two past decades. A comparative study of five probability distributions was performed in order to estimate which distribution at best represents statistical characteristics of the flood data. The results showed that maximum discharges of spring floods decreased over the whole studied period. Only some insignificant positive trends of maximum discharges were found in the last time period in continental and transitional rivers. Generalized extreme value distribution provided the best approximation to the maximum discharge data series of the rivers of Baltic countries for the whole observation period. First published online: 08 Jul 2014

The Kaunas Reservoir was formed during construction of the Kaunas Hydroelectric Plant (Kaunas HP) on the Nemunas River in 1960. Since 1992 it has also been serving as a lower reservoir for the Kruonis Hydroelectric Pumped-Storage Plant (Kruonis HPP), which currently has four generating units with 200 MW of installed capacity each. There are plans to increase the capacity of this power plant by constructing additional four generating units. Operation of the Kruonis HPP is already changing the hydrophysical regime (water levels and flow velocities) of the Kaunas Reservoir and new units can seriously aggravate the situation by inducing bottom erosion. The objective of this study is to determine the optimal number of generating units so that the impact of the Kruonis HPP on the hydrophysical regime of the reservoir would be acceptable. The hydrodynamic model MIKE 21 was used to calculate the flow velocity and water level fluctuation in the Kaunas reservoir for different number of the Kruonis HPP generating units. The Kaunas HP was considered as operating with minimal load or under conditions equivalent to a big flood (2,000 m3/s). The modelling results indicate that the impact of four units is acceptable while simultaneous operation of the eight units at Kruonis HPP would not be desirable.