Hydrometeorological Conditions Research Articles

ПОВТОРЯЕМОСТЬ ЗАСУХ НА ТЕРРИТОРИИ БЕЛАРУСИ В СВЯЗИ С АТМОСФЕРНОЙ ЦИРКУЛЯЦИЕЙ В АТЛАНТИКО-ЕВРОПЕЙСКОМ СЕКТОРЕ

In the paper, the frequency and spatial distribution of atmospheric and hydrological droughts over the territory of Belarus in 1945-2020 is assessed. Aridity is evaluated using the standardized precipitation and streamflow indices (SPI and SSFI). Trends in monthly total precipitation are determined, the features of the streamflow formation during the open-channel period are revealed. The frequency of anticyclones that determines hydrometeorological conditions on the territory of Belarus is calculated. The statistically significant increase in the number of the days with anticyclonic weather over the country during the warm season is found. The increasing frequency of dry conditions in summer months against the background of a rise in the precipitation intensity is highlighted. A simultaneous increase in the frequency of very-low-flow periods on rivers and an increase in the height of warm rainfall floods in some river basins are revealed.

Natural groundwater outflows in the Biebrza Valley: Temporal stability, geochemical composition and role in ecohydrological processes of valley wetlands

Natural groundwater outflows are very sensitive to changes in the environment. In the era of changing climate and progressive anthropogenic activity, they often disappear, retreat, and water quality deteriorates. Inefficient sources in lowland areas are the most vulnerable to these processes. In 2021, we conducted an inventory of natural groundwater outflows in the Biebrza Valley. Most of the existing outflows are non-concentrated outflows (exudations, linear leakages, fens). The outflow of several outflows exceeded 5 dm3·s−1. Their distribution within the Biebrza Basin is uneven. We identified the largest concentration of linear seepages on the right bank of the lower Biebrza basin near the village of Ruś. The most common types in the BNP are di- and tri-ionic waters, characteristic of lowland areas of Poland. The increase in nitrogen and phosphorus compounds in the spring water indicates the impact of the developing agricultural activity (cattle breeding). The increase in DOC concentration may reflect changing hydro-meteorological conditions (droughts and torrential rains). The values of most parameters in spring water were lower than in shallow groundwater. This gives a better picture of the quality of shallow groundwater. The physical and chemical characteristics of natural groundwater outflows in the BNP fall within the hydro-chemical background of the waters of the first aquifer in this area.

Long-term Assessment of Precipitation Behaviour in Bihar (1901-2021): Patterns, Trends and Observed Variability

Rainfall is an important variable that governs the climate and hydrological conditions of any region. During the past century, an increase in global emissions of greenhouse gases has caused changes in the patterns of hydro-meteorological conditions across the world. It has resulted in changed patterns and trends of rainfall, causing episodic occurrences of droughts and floods. This increasing variability of rainfall has triggered and intensified extreme events that pose potential future risks under different climate change scenarios. This projected variability may induce drastic changes in the flood affected states like Bihar where even a slightest change in rainfall variability may affect hydrological cycle and agriculture conditions.

Photosynthetic capacity, canopy size and rooting depth mediate response to heat and water stress of annual and perennial grain crops

Perennial grain crops are promoted as an alternative to annual staple crops to reduce negative environmental effects of agriculture and support a variety of ecosystem services. While perennial grains have undergone extensive testing, their vulnerability to projected future warmer and drier growing conditions remains unclear. To fill this gap, we compared leaf temperature and gas exchange rates of annual wheat and different perennial wheat ideotypes using a multi-layer process-based eco-hydrological model. The model combines leaf-level gas exchange, optimality principles regulating stomatal conductance, energy balance, radiative and momentum transfer inside the canopy, as well as soil water balance. Wheat ideotypes are parameterized based on an extensive review of field data. When compared with annual wheat, perennial wheat ideotypes with high leaf area index had between 12% and 39% higher canopy transpiration and net CO2 assimilation, depending on their photosynthetic capacity and water status. Differences in leaf temperature and instantaneous water use efficiency between annual wheat and the perennial ideotypes were moderate (-0.5 to +0.4 °C and -6 to +2%, respectively). Low soil water availability did not alter the ranking of ideotypes in terms of canopy temperature and gas exchanges. During a prolonged dry down, cumulated water use was higher and canopy temperature lower in perennial than annual ideotypes, thanks to the deeper roots, whereas cumulated net CO2 fixation depended on the specific traits and air temperature. Leaf-specific and whole plant characteristics interacted with hydro-meteorological conditions in defining the perennial's vulnerability envelopes to potential heat and water stress. These findings underline the importance of plant characteristics, and particularly leaf area and rooting depth, in defining the suitability of perennial grain crops under future climates.

Prediction of soil moisture using BiGRU-LSTM model with STL decomposition in Qinghai-Tibet Plateau.

Ali Network data based on the Qinghai-Tibetan Plateau (QTP) can provide representative coverage of the climate and surface hydrometeorological conditions in the cold and arid region of the QTP. Among them, the plateau soil moisture can effectively quantify the uncertainty of coarse resolution satellite and soil moisture models. With the objective of constructing an "end-to-end" soil moisture prediction model for the Tibetan Plateau, a combined prediction model based on time series decomposition and a deep neural network is proposed in this article. The model first performs data preprocessing and seasonal-trend decomposition using loess (STL) to obtain the trend component, seasonal component and random residual component of the original time series in an additive way. Subsequently, the bidirectional gated recurrent unit (BiGRU) is used for the trend component, and the long short-term memory (LSTM) is used for the seasonal and residual components to extract the time series information. The experiments based on the measured data demonstrate that the use of STL decomposition and the combination model can effectively extract the information in soil moisture series using its concise and clear structure. The proposed model in this article has a stable performance improvement of 5-30% over a single model and existing prediction models in different prediction time domains. In long-range prediction, the proposed model also achieves the best accuracy in the shape and temporal domains described by using dynamic time warping (DTW) index and temporal distortion index (TDI). In addition, the generalization performance experiments show that the combined method proposed in this article has strong reference value for time series prediction of natural complex systems.

Integrating ecosystem services closely related to human well-being into the restoration and management of deep lakes facing multiple stressors: Lessons from long-term practice in Qiandao Lake, China

Deep-lake (reservoir) ecosystems provide valuable ecosystem services (ES) and generate significant ecosystem service values (ESV); however, reservoir ecosystems have suffered great losses from environmental changes and human activities. Currently, studies on ES and its correlations with stressors remain insufficient and the integration of ES into ecological restoration and management poses numerous challenges. Here, we combined four types of stressors with six ES closely related to human well-being to discuss their interactions in Qiandao Lake (a representative deep lake in China). Our results indicate that all ESV showed a consistent growth trend throughout the study period, reaching 5203.8 million CNY in 2018, and the cultural service value surpassed the provisioning service value for the first time in 2004. Almost all the ESV were limited during the cyanobacterial bloom in Qiandao Lake. Redundancy analysis and partial least squares structural equation modeling jointly revealed that socioeconomic development was the most important direct driver of the increase in ESV (0.770) and that hydro-meteorological conditions (0.316) and pollutant loads (0.274) positively affected ESV by mediating lake trophic status. The trophic status of the lake is the result of the interaction of multiple stressors, which has a negative impact on ESV. Therefore, to continuously protect the provisioning and cultural service values of deep-lake ecosystems from damage, the government must rationally formulate SED goals and reduce pollutant loads during lake development, operation, and utilization. This work provides valuable insights into the interactions between ES, which are closely related to human well-being, and stressors in deep-lake ecosystems.

Cod distribution in the Barents Sea under climate changes

The aim of the paper is to assess the impact of climate changes and oceanographic conditions on the distribution of cod stocks in the Barents Sea in recent decades. The material for the study was oceanographic data obtained during surveys in the Barents Sea by PINRO and other available information on hydrometeorological conditions of the sea in 1981–2021, as well as data onRussian catches of cod in the Barents Sea based on bottom trawl fishing operations. Methods of descriptive statistics as well as comparative, correlation and regression analyses were applied. Results: The modern changes in the climate and oceanographic conditions of the Barents Sea are described. Since the early 1980s, the warming has been observed against the background of increasing storm activity, having peaked in 2016. After that, despite still warm and low-ice conditions, there has been a cooling trend in the Barents Sea. Under climate changes in recent decades, cod made increasingly long migrations north and east, spreading more widely in the feeding areas. The most informative predictors in assessing the impactof climate changes and oceanographic conditions on the distribution of cod stocks in the Barents Sea were Arctic ice extent, area-averaged temperature at a depth of 100 m, Atlantic water area in the 50–100 m layer, and parameters of the Barents Sea thermal frontal zones. Practical significance: The obtained results are useful for a better understanding of the processes occurring in the Barents Sea ecosystem and, in the future, will be used to predict cod distributions in the sea, depending on oceanographic conditions and climate changes.

Widespread and complex drought effects on vegetation physiology inferred from space

The response of vegetation physiology to drought at large spatial scales is poorly understood due to a lack of direct observations. Here, we study vegetation drought responses related to photosynthesis, evaporation, and vegetation water content using remotely sensed data, and we isolate physiological responses using a machine learning technique. We find that vegetation functional decreases are largely driven by the downregulation of vegetation physiology such as stomatal conductance and light use efficiency, with the strongest downregulation in water-limited regions. Vegetation physiological decreases in wet regions also result in a discrepancy between functional and structural changes under severe drought. We find similar patterns of physiological drought response using simulations from a soil–plant–atmosphere continuum model coupled with a radiative transfer model. Observation-derived vegetation physiological responses to drought across space are mainly controlled by aridity and additionally modulated by abnormal hydro-meteorological conditions and vegetation types. Hence, isolating and quantifying vegetation physiological responses to drought enables a better understanding of ecosystem biogeochemical and biophysical feedback in modulating climate change.

Navigation Safety on Shipping Routes during Construction

Construction work or other maintenance and repair activities in navigational channels are crucial to ensure and improve ships’ movement on the selected routes. However, during the performance of these works, the ships’ navigation along the construction area becomes more difficult due to the decreased parameters of passages for vessels and the operation of specific equipment on the route, e.g., dredgers and floating cranes. During construction work in navigational channels, it is impossible to stop navigation or limit ships’ parameters because there may not be other possibilities for vessels to reach their planned ports or other dedicated areas. The prior determination of ships’ sailing conditions and restrictions is essential to ensure maritime safety in such areas. The aim of this study is to develop a methodology that allows the precise determination of minimum passage parameters for the navigation of ships sailing through the areas in navigational channels where construction or development works are being carried out. The theoretical basis for the minimum passage parameter calculation is presented. The methodology for assessing the conditions and restrictions of navigation during construction work is proposed. The minimum width of the shipping passages in defined navigational, hydro-meteorological, and hydrological conditions and the possible minimum parameters sufficient to guarantee navigational safety are considered in a case study. The research results may be interesting for port authorities, shipping companies, and other entities involved in the organization of ships’ movement during construction work in navigational channels or other areas.

Mapping river turbidity at a large basin-scale with a spatially transferable ensemble model using Landsat 8 multispectral imagery

ABSTRACT Mapping river water quality at a basin scale with satellite image data represents a tremendous technical challenge, since traditional empirical remote sensing models calibrated for specific reaches of a river cannot be applied to all the rivers and streams in the basin with an adequate prediction accuracy. In this study, we developed a multi-predictor ensemble model to map and assess water turbidity for all rivers and streams in the Tombigbee River Basin with Landsat 8 multispectral images. Coincident with Landsat 8 satellite overpass on 2 May 2019, we conducted boat-based water quality data collection in the confluence area of Tombigbee River and Black Warrior River near the city of Demopolis, Alabama. Based on the coincident satellite image and field water samples, we calibrated and evaluated the multi-predictor ensemble model, which consists four component empirical models. Our evaluations suggest that the multi-predictor ensemble model can improve turbidity estimation accuracy by 79% in comparison with the best traditional empirical model. More importantly, our multi-predictor ensemble model can be applied to other river and stream reaches across three major sub-basins with a high prediction accuracy. With the multi-predictor ensemble model, we derived a turbidity map for all rivers and streams with a width greater than 90 m in the basin, by processing three Landsat 8 image scenes. This basin-wide turbidity map indicates that the turbidity of rivers and streams exhibits longitudinal gradients and distinct spatial trends within the basin, which were related to the basin land cover/land use, hydrometeorological condition, and the spatial distribution of dams. Owing to its strong spatial transferability and high prediction accuracy, the ensemble model, in conjunction with synoptic multispectral satellite image data, is recommended as an effective and efficient tool for mapping and monitoring river and stream water quality at a large basin or regional scale.

Observational evidence of legacy effects of the 2018 drought on a mixed deciduous forest in Germany

Forests play a major role in the global carbon cycle, and droughts have been shown to explain much of the interannual variability in the terrestrial carbon sink capacity. The quantification of drought legacy effects on ecosystem carbon fluxes is a challenging task, and research on the ecosystem scale remains sparse. In this study we investigate the delayed response of an extreme drought event on the carbon cycle in the mixed deciduous forest site ’Hohes Holz’ (DE-HoH) located in Central Germany, using the measurements taken between 2015 and 2020. Our analysis demonstrates that the extreme drought and heat event in 2018 had strong legacy effects on the carbon cycle in 2019, but not in 2020. On an annual basis, net ecosystem productivity was sim 16,% higher in 2018 (sim 424,{hbox {g}_{text {C}}}hbox {m}^{-2}) and sim 25,% lower in 2019 (sim 274,{hbox {g}_{text {C}}}hbox {m}^{-2}) compared to pre-drought years (sim 367,{hbox {g}_{text {C}}}hbox {m}^{-2}). Using spline regression, we show that while current hydrometeorological conditions can explain forest productivity in 2020, they do not fully explain the decrease in productivity in 2019. Including long-term drought information in the statistical model reduces overestimation error of productivity in 2019 by nearly 50,%. We also found that short-term drought events have positive impacts on the carbon cycle at the beginning of the vegetation season, but negative impacts in later summer, while long-term drought events have generally negative impacts throughout the growing season. Overall, our findings highlight the importance of considering the diverse and complex impacts of extreme events on ecosystem fluxes, including the timing, temporal scale, and magnitude of the events, and the need to use consistent definitions of drought to clearly convey immediate and delayed responses.

Optimized Turning Basin Design for Inland Waterways

Concept design guidelines for ship turning basins are often not met in practice due to environmental, economic, or geotechnical restrictions. In these cases, a detailed design procedure is followed to develop an optimized turning basin geometry within the environmental constraints. Then, real-time ship maneuvering simulations are used to evaluate the maneuvers in the proposed geometry. However, such a detailed design procedure is costly, especially if a large number of simulations are required. To restrict the number of simulations, the waterway authority [Voies navigables de France (VNF)] ordered a study to find a generic and optimal design for a turning basin which could be suitable for the upgrade in the northern part of their inland waterway network. Therefore, the turning maneuvers for two typical inland navigation vessels were simulated in real time under different hydrometeorological conditions. This study was conducted in three stages. First, maneuvers in traditional circular and trapezoidal turning basins of different sizes were executed and analyzed. Second, optimized turning basin geometries were developed. Finally, the turning maneuvers in those optimized geometries were analyzed. Based on the results of this analysis, a stepwise approach was proposed to select an optimized turning basin geometry that was based on the conditions present on site. This stepwise approach for the design of turning basins could reduce the real-time simulations that are required when upgrading a waterway network.

Using isotopic tracers to enhance routine watershed monitoring – Insights from an intensively managed agricultural catchment

Experimental (research-based) and non-research-based watershed monitoring programs often differ with respect to sampling frequency, monitored variables, and monitoring objectives. Isotopic variables, which are more commonly incorporated in research-based programs, can provide an indication of water sources and the transit time of water in a catchment. These variables may be a valuable complement to traditional water quality monitoring variables and have the potential to support improved hydrologic process-related insights from long term monitoring programs that typically have low resolution sampling. The purpose of this investigation is to explore the utility of incorporating isotopic variables (specifically δ18O, δ2H, and 222Rn) into routine monthly sampling regimes by comparing insights gained from these variables to monitoring only specific conductivity and chloride. A complete annual cycle of monthly groundwater and surface water monitoring data collected from the Upper Parkhill watershed in southwestern Ontario, Canada was used to characterize baseline watershed conditions, evaluate watershed resilience to climate change, and examine contamination vulnerability. Study results provide an improved understanding of appropriate tracer use in agricultural regions with isotopic variables able to provide important insights into the seasonality of hydrologic phenomena, such as the timing of groundwater recharge. A comparison of monitoring variables to present-day hydro-meteorological conditions suggests the importance of a winter dominated hydrologic regime and the potential influence of changes in precipitation on groundwater-surface water interactions. Estimated transit time dynamics indicate the likelihood for rapid contaminant transport through surface and shallow subsurface flow and highlight the possible effects of agricultural tile drainage. The sampling approach and data analysis methods adopted in this study provide the basis for improving routine watershed monitoring programs in agricultural regions.

Application of the method of territorial long-term forecasts to determine the maximum water discharge rates under the conditions of spring flood 2022-2023 formation across the Desna basin

Despite the conditions of both climate change and long-term trend to decrease of hydrological characteristics of the Ukrainian rivers' spring flood that was established by many authors, the formation of high-water river floods accompanied by rising water levels and release of water to floodplains still remains probable.
 Thus, according to the data of the Ukrainian Hydrometeorological Center (UkrHMC) of the State Emergency Service of Ukraine (web: www.meteo.gov.ua), the hydrometeorological conditions of snowmelt and rain runoff formation during the autumn-winter and spring periods of 2022-2023 across the basins of the Dnipro and Desna rivers and their tributaries were characterized as those having a complex nature. This led to a rise of these rivers' water levels with flooding of floodplains, disruption of transport connections, as well as flooding of populated areas in Kyiv, Chernihiv and other Ukrainian regions.
 The purpose of this study is the issues related to determination of natural factors that lead to extreme large-scale spring floods, and long-term forecasting of maximum runoff of spring floods in 2022-2023 across the Desna River basin.
 To ensure operational forecasting support and assessment of the spring floods size across the basin of the Desna River and other left tributaries of the Middle Dnieper, the research used a method of territorial long-term forecasts of spring floods maximum runoff. The method takes into account a complex of hydrometeorological factors which, when combined annually, lead to the formation of spring floods of different sizes.
 The results of the long-term forecast for maximum water discharge rates during the spring flood in 2022-2023 retrieved from the forecasting computer complex "SEYM" show satisfactory statistical estimates of the forecast for maximum water discharge rates during a spring flood provided that a high pre-flood water content of the rivers during recession of a winter flood is considered. The forecast lead time for maximum water discharge rates of the spring flood in 2022-2023 varied from 20-30 days for small tributaries of the Desna River to two months for the Desna and Seim rivers themselves.
 Application of the method of territorial long-term forecasts of characteristics of river spring floods allows spatial monitoring of the rivers' water content provided that forecasting is conducted using the methodology of maximum water discharge rates for any rivers of a certain territory, including those with relation to which there are no observations of their water runoff.
 An early warning about a dangerous river water level during winter-spring periods can significantly reduce the scale of negative consequences and ensure achievement of socio-economic and environmental effects.

Determination of drought resistance of soybean breeding material

The purpose and objectives of the study. To determine the resistance of soybean genotypes to drought according to drought resistance indices based on the analysis of yield in years contrasting in terms of hydrometeorological conditions.
 Materials and research methods. The material for determining the influence of year conditions on the level of average yield of soybeans and drought resistance were varieties and breeding numbers of the competitive variety test (CVT). Experiments were carried out in four repetitions with a plot area of 25 m2. Drought intensity (D) was determined by the formula proposed by Fischer R.A. and Maurer R. Differentiation of breeding numbers and varieties of CVT soybeans was carried out according to yield in 2016 and 2018 according to indices of drought susceptibility (DSI), drought tolerance (TOL), average yield (MP), yield stability (YSI), yield (YI), stress tolerance (STI), geometric mean yield (GMP). Processing of research results was carried out according to B.O. Dospehov [27] using STATISTICA 10 and Excel programs.
 The discussion of the results. During the research period (2008–2021), the highest yield of soybeans in CVT was obtained in 2016 – 2.57 t/ha, and the lowest in 2018 – 0.50 t/ha. A comparison of soybean yield in CVT in 2016 and 2018 showed that the average yield loss due to drought was 2.07 t/ha, or 81%. At the minimum yield, losses were equal to 1.78 t/ha, or 84.8%. At the maximum – 2.19 t/ha and 75.5%, respectively. Therefore, the minimum yield difference was greater than the maximum yield difference. The level of drought intensity (D) in the dry year of 2018 was equal to 0.81.
 According to yield indicators, a number of indices were calculated and analyzed, which characterize the resistance of samples to drought. The value of the drought susceptibility index (DSI) ranged from 0.87 to 1.09, with an average value of 1.00. The drought tolerance index (TOL) was 1.61–2.41 with an average value of 2.11. The average yield (MP) was in the range of 2.34–3.15 t/ha and had an average value of 2.85 t/ha. The yield stability index (YSI) value varied from 0.12 to 0.30 with an average value of 0.19. The yield index under stress conditions (YI) was 64.6–143.3%, with an average value of 98.9%. The stress yield index (YI) ranged from 64.6% to 143.3%, with an average value of 98.9%. The geometric mean (or proportional mean) yield (GMP) of the studied samples ranged from 0.92 t/ha to 1.38 t/ha, with a median value of 1.11 t/ha.
 According to each index, the researched soybean samples were differentiated and drought-resistant breeding material was selected.
 Conclusions. According to most indices: stress susceptibility (DSI), drought tolerance (TOL), crop stability (YSI), productivity (YI), stress tolerance (STI) and geometric mean yield (GMP) number CVT 23-18 (3836 / 76-130 selection). According to five indices: stress susceptibility (DSI), yield stability (YSI), yield (YI), stress tolerance (STI) and geometric mean yield (GMP) number CVT 16-18 (Volgohradka / Mriya) stood out. Number CVT 49-18 (Kharkivska 56 / Ilsoy) stood out according to the indicators of four indices: average yield (MR), yield (YI), stress tolerance (STI) and geometric mean yield (GMP). According to three indices, it is identified as drought-resistant number CVT 22-18 (selection №14) – according to indices of stress susceptibility (DSI), drought tolerance (TOL) and yield stability (YSI); numbers CVT 36-18 (Kharkivska zernokormova / Yug 30) and CVT 24-18 (Kharkivska 62 / Hodson) – according to indices of yield (YI), stress tolerance (STI) and geometric mean yield (GMP). Selection number CVT 28-18 (4305-04) stood out according to stress tolerance index (TOL) and average yield level (MR). Number 29-18 (Narrow-leaved / mutant 82-205) stood out according to the stress tolerance index (TOL) and the level of average yield (MR). Numbers CVT 50-18 (selection from Pasteter Schwarus) and CVT 37-18 (Success / Dream) were distinguished by indices of susceptibility to stress (DSI) and yield stability (YSI). According to the level of average yield (MR), number CVT 20-18 (Kharkivska 35 / Kyivska 27) and Podyaka variety stood out. The Roksolana variety stood out according to the stress tolerance index (TOL). Selected genotypes of soybeans with a high level of resistance to abiotic stress are recommended for use in crop breeding for high drought resistance.

An Emergency Port Decision-Making Method for Maritime Accidents in Arctic Waters

The complex and variable hydro-meteorological conditions in Arctic waters and scattered and limited port infrastructures pose a great threat and challenge to Arctic emergency search and rescue. It is crucial to determine an available and effective emergency port for rescue in the event of a maritime accident occurring in Arctic waters. In the present study, a directed-weighted emergency port network consisting of maritime accident nodes and port nodes for maritime accident-prone areas in Arctic waters is developed based on complex network theory. For this, the maritime accident nodes are identified by using a K-means clustering algorithm based on historical accident data; the port nodes are determined by screening of the port location and scale; the weights for edges between accident nodes and port nodes are characterized in terms of ERT (emergency rescue time) and PEC (port emergency capacity), and the PECs for different emergency ports along Arctic waters are acquired by entropy-weighted TOPSIS. With the developed emergency port network, the topological properties associated with the accident nodes, port nodes, and the edge weights between accident nodes and port nodes are analyzed. What is more, the emergency ports for each maritime accident point occurring in Arctic waters are obtained and ranked.

Analysis of Hydrometeorological Characteristics and Water Demand in Semi-Arid Mediterranean Catchments under Water Deficit Conditions

Drought is one of the most complex and poorly understood catastrophes on the planet. Between the Greek mainland and Turkey, there is an area of Greece known as the South Aegean Islands, that experiences water supply issues. As a result, there are issues related to the socioeconomic growth of some of these islands, and the need for water transportation by water vessels. Water transportation by ships to the Cyclades and Dodecanese areas from the mainland or other adjacent islands to satisfy urgent demands, on the other hand, is exceptionally expensive. The situation deteriorates during the summer, when drinking water needs can reach five times the norm, due to the heavy tourist season. Given these conditions, the aim of this research is to estimate hydrometeorological conditions, calculate the water balance, and determine water needs in three southern Aegean islands (Mykonos, Naxos, and Kos), where there is a water shortage, particularly during the summer months when tourism activity is at its peak. The modified Thornthwaite–Mather monthly hydrological balance model was applied to determine the water balance. Various water use datasets (drinking water, irrigation, water transportation) were employed to quantify the water demands in the three islands. According to the results, the available water (runoff + infiltration) seems to be more than sufficient to meet the needs of the islands of Naxos and Kos, since it far exceeds the increased needs of the islands. Yet, it appears that in Mykonos, where the water resources have been nearly entirely utilized, the available water, is just enough to meet the water needs. It is evident that all three islands present significant sources of available water, which could meet the growing needs of the residents. However, the absence of the necessary water exploitation projects, mainly concerning the surface runoff, has contributed to the intense water supply problems of the islands. The importance of the water harvesting projects becomes even more urgent under the conditions of climate change, with the decrease in annual rainfall likely to be a highly possible scenario, especially in arid and semi-arid regions.

NUMERICAL SIMULATION OF A GEAR

To navigate safely, the ship must be manoeuvrable and have good stability. The steering of the ship depends on a number of factors such as: the means of steering used, the geometric shapes of the hull (stern area), the ratios between the main dimensions (LCWL/B and B/T), the number, position and direction of rotation of the engine. and the hydro-meteorological conditions in which they sail (water, air, wind, waves). Every ship, with the exception of barges, must have a robust and safe steering system to ensure manoeuvrability and sea stability. These installations can be: rudder with hydrodynamic profile, installation with adjustable nozzles and other installations approved by the Classification Societies. In this particular study an analysis on a gear pump fitted in the azimuth system of a chemical tanker is being made, using a CFD technology. The main aim is to study the efficiency of this pump by comparing the CFD analysis results with the results in real operational condition. Main parameters focused on are outlet flow, suction column, power and pump efficiency. There are several differences registered in the case of suction column and power, but they are not that high, while parameters outlet flow and pump efficiency are almost identical.

Overview of the classification of mobile offshore drilling unit semi-submersible by generation

The article describes the diversity of views of specialists in the shipbuilding and oil and gas industries, insurance brokers, analytical agencies, employees of specialized departments and classification societies, as well as drilling contractors and employees of operating companies on the classification of mobile offshore drilling unit semi-submersible, and is reduced to a unified systematization of these opinions on generations of technologies that depend not only on the depth of operation, drilling, loads on the hook and year of construction, but also from other important factors, such as: the presence of trolleys for drill pipes, an active crown block compensator (compensator for vertical movements of drill pipes), the number of personnel, the number of preventers and drilling pumps, the volume of fuel and technical oils on board. This takes into account the usual classification of installations based on their functionality, architectural and structural type, operating area and hydrometeorological conditions. In addition, the work carried out an integrated analysis of the global market of companies in the industry operating in the field of offshore drilling services. The authors of the article, based on the composition of the drilling fleet of the industry leader and the characteristics of ocean technology equipment, offer an up-to-date view of the classification by generations.

The soviet hydrometeorological service and the Red army’s counteroffensive at Stalingrad

The article discusses the organization of hydrometeorological support of the Red Army in the Battle of Stalingrad. Hydrometeorological conditions are described, their influence on the activities of the ground forces, aviation, and the Volga Flotilla is revealed, and specific examples are given. The structure of hydrometeorological bodies, units and subunits involved in providing the Red Army is disclosed in detail.