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The meso-scale habitat simulation model MesoHABSIM was applied in three Lithuanian lowland rivers to study the effect of low-head hydropower plants (HPPs) on the fish habitats. Stream flow time series on a daily scale for the period 1970–2015 were used to describe flow regime downstream of HPPs for periods before and after their installation. Conditional habitat suitability criteria were developed for 4 species of cyprinid fish, schneider ( Alburnoides bipunctatus ), dace ( Leuciscus leuciscus ), roach ( Rutilus rutilus ) and vimba ( Vimba vimba ) to simulate their available habitat at different water discharges. Modelling results showed that HPPs have a significant impact on habitat availability in the low flow period in dry years below HPPs due to insufficient released flow. The environmental flow, as prescribed by the Lithuanian national law, is estimated between 80 and 95% exceedance probability of the mean minimum discharge of 30 days. This flow leads to a significant reduction in frequency and duration of available suitable habitats for vimba and schneider during low flow period. The roach habitat is the least affected. The results of habitat modelling are in line with the actual data on the occurrence and relative abundance of considered fish species in the studied river stretches. A general comparison of the relative abundance of modelled fish species in 42 natural river stretches and 20 stretches below the HPPs also showed that the relative abundance of roach is significantly higher, and that of schneider is significantly lower in river sections below the HPPs than the abundance in natural river sections. All results indicate that the current environmental flow does not secure survival of certain fish species. The applicability of the average low flow release during summer could be a plausible alternative to the current environmental flow in order to maintain ecosystem health and services.

Climate is probably the most important factor affecting river discharge and flow dynamics. Low flows in rivers during the warm period cause stress to aquatic ecosystems and pose a challenge to sustainable water management. Previous research has shown that the average minimum discharge of the 30 driest continuous days, known as Q30, is a suitable measure for ecological flow estimation in Lithuania. This study aims to examine whether large-scale atmospheric processes, so-called teleconnections, can have an impact on Q30 during the warm period. Hydrological data for 1961–2020 from 25 water gauging stations were used to search for hydrological response signals with five selected climate indices (NAO, SCA, POL, EA/WR, and EA). Pearson correlation and Wilcoxon–Mann–Whitney test approaches were applied. The results suggested that the EA/WR and NAO had the strongest influence on Q30 in the studied region during the warm period. The positive phases of the indices tended to cause a greater decrease in Q30 values due to the prevailing easterly edge of the anticyclonic circulation over the studied region determined by the EA/WR and NAO indices, while the negative phases of the mentioned indices caused an increase and greater dispersion of Q30.

Climate projections based on global climate models (GCMs) are generally subject to large uncertainties, as the models only reflect the local climate in the past to a limited extent. Statistical downscaling is the most cost-effective approach to identify the systematic biases of the GCMs from the past and eliminate them in the projections. This study seeks to evaluate the effectiveness of GCMs in capturing local climatic characteristics at the river basin district scale by applying gridded statistical downscaling techniques using global and regional datasets. The historical observational datasets E-OBS and GloH2O were selected to downscale the raw data of 17 GCMs from ~1° grid cells to 0.25° resolution. E-OBS is a regional dataset supported by a dense network of meteorological stations in Europe, while GloH2O is a global dataset covering all continents. The results show that the suitability of the GCMs varies depending on the selected parameter. The statistical downscaling revealed the advantages of the performance of E-OBS in representing local climate characteristics during the historical period and emphasized the crucial role of regional datasets for good climate depiction. Such an approach provides the possibility to assess the relative performance of GCMs based on the high-resolution observational and reanalysis datasets, while generating statistically downscaled datasets for the best ranked GCMs. The strategies used in this study can help to identify the most appropriate models to assemble the right ensemble of GCMs for specific studies.

This study assesses the suitability of UAV aerial imagery-based photogrammetry for reconstructing underwater riverbed topography and its application in two-dimensional (2D) hydrodynamic modelling, with a particular focus on comparing RGB, multispectral, and fused RGB–multispectral imagery. Four Lithuanian rivers—Verknė, Šušvė, Jūra, and Mūša—were selected to represent a wide range of hydromorphological and hydraulic conditions, including variations in bed texture, vegetation cover, and channel complexity. High-resolution digital elevation models (DEMs) were generated from field-based surveys and UAV imagery processed using Structure-from-Motion photogrammetry. Two-dimensional hydrodynamic models were created and calibrated in HEC-RAS 6.5 using measurement-based DEMs and subsequently applied using photogrammetry-derived DEMs to isolate the influence of terrain input on model performance. The results showed that UAV-derived DEMs systematically overestimate riverbed elevation, particularly in deeper or vegetated sections, resulting in underestimated water depths. RGB imagery provided greater spatial detail but was more susceptible to local anomalies, whereas multispectral imagery produced smoother surfaces with a stronger positive elevation bias. The fusion of RGB and multispectral imagery consistently reduced spatial noise and improved hydrodynamic simulation performance across all river types. Despite moderate vertical deviations of 0.10–0.25 m, relative flow patterns and velocity distributions were reproduced with acceptable accuracy. The findings demonstrate that combined spectral UAV aerial imagery in photogrammetry is a robust and cost-effective alternative for hydrodynamic modelling in shallow lowland rivers, particularly where relative hydraulic characteristics are of primary interest.

The European Union (EU) Water Framework Directive is of paramount importance for water management. According to the legal text, coordination with other directives like the Floods Directive is imperative and motivated by potential synergy effects. In this paper, the degree to which such coordination is achieved is evaluated for five Nordic and Baltic countries. The evaluation is based on legal documents, management plans, as well as on organizational structure in the five countries. The results show that the coordination between the Water Framework Directive and the Floods Directive (or flood management for Norway's case), have been successful for Estonia and Lithuania, whereas Norway, Finland, and especially Sweden need to improve more.

Aquatic ecosystems are particularly vulnerable to anthropogenic activity and climate change. The changes in flow regimes in Lithuanian lowland rivers due to the operation of hydropower plants (HPPs) and the impact of altered flow on some fish species have already been studied. The impact of climate change on future natural river runoff and the structure of fish assemblages was also investigated. However, it is still unknown how the combined effect of climate change and flow regulation related to hydropower generation may affect fish assemblages in the downstream river reaches below the Lithuanian HPPs. In this study, the physical habitat modelling system MesoHABSIM was used to simulate spatial and temporal changes in aquatic habitats availability for different fish species under the influence of HPP at different climate change scenarios. Changes in the available habitat were assessed for common fish species in four HPP-affected rivers representing different hydrological regions of Lithuania. The modelling results showed that the operation of HPP under climate change conditions in most rivers could be beneficial for small benthic fish species such as gudgeon Gobio gobio and stone loach Barbatula barbatula. Meanwhile, for larger fish species (e.g., chub Squalius cephalus and vimba Vimba vimba) the alteration in the temporal availability of suitable habitat was relatively higher.

Hydromorphology of rivers assessed through direct measurements is a time-consuming and relatively expensive procedure. The rapid development of unmanned aerial vehicles and machine learning (ML) technologies enables the usage of aerial images to determine hydromorphological units (HMUs) automatically. The application of various direct and indirect data sources and their combinations for the determination of river HMUs from aerial images was the main aim of this research. Aerial images with and without the Sobel filter, a layer of boulders identified using Yolov5x6, and a layer of direct measurements of depth and streamflow velocity were used as data sources. Three ML models were constructed for the cases if one, two, or three data sources were used. The ML models for HMU segmentation were constructed of MobileNetV2 pre-trained on ImageNet data for the feature extraction part and U-net for the segmentation part. The stratified K-fold cross-validation with five folds was carried out to evaluate the performance of the model due to the limited dataset. The analysis of the ML results showed that the measured metrics of segmentation using direct measurements were close to the ones of the model trained only on the combination of boulder layer and aerial images with the Sobel filter. The obtained results demonstrated the potential of the applied approach for the determination of HMUs only from the aerial images, and provided a basis for further development to increase its accuracy.

The Nemunas River basin falls within the territories of five different countries – Belarus, Lithuania, Russia, Poland and Latvia. In general, the beginning of spring floods highly depends on rapid rise of air temperature, heavy precipitation and sudden snow melting in the analysed basin. In this paper, the conditions of formation and consequences of two catastrophic floods in 1958 and 1979 in the Nemunas River basin were studied regarding the hydrometeorological parameters (maximum snow water equivalent before the beginning of flood and precipitation amount during the flood) as well as runoff coefficients for each selected catastrophic flood. Differences between the main drivers and evolution of these floods were analysed. Spatial distribution of maximum snow water equivalent and precipitation, as well as runoff coefficient in different parts of the river basin, were identified as having the most significant impact on the formation of the studied catastrophic floods.

Drought events and their impacts vary spatially and temporally due to diverse pedo-climatic and hydrologic conditions, as well as variations in exposure and vulnerability, such as demographics and response actions. While hazard severity and frequency of past drought events have been studied in detail, little is known about the effect of drought management strategies on the actual impacts and how the hazard is perceived by relevant stakeholders. In a continental study, we characterised and assessed the impacts and the perceptions of two recent drought events (2018 and 2019) in Europe and examined the relationship between management strategies and drought perception, hazard, and impact. The study was based on a pan-European survey involving national representatives from 28 countries and relevant stakeholders responding to a standard questionnaire. The survey focused on collecting information on stakeholders' perceptions of drought, impacts on water resources and beyond, water availability, and current drought management strategies on national and regional scales. The survey results were compared with the actual drought hazard information registered by the European Drought Observatory (EDO) for 2018 and 2019. The results highlighted high diversity in drought perception across different countries and in values of the implemented drought management strategies to alleviate impacts by increasing national and sub-national awareness and resilience. The study identifies an urgent need to further reduce drought impacts by constructing and implementing a European macro-level drought governance approach, such as a directive, which would strengthen national drought management and mitigate damage to human and natural assets.