Studies of the Dispersed Composition of Atmospheric Aerosol and Its Relationship with Small Gas Impurities in the Near-Water Layer of Lake Baikal Based on the Results of Ship Measurements in the Summer of 2020

The atmosphere over Lake Baikal covers a vast area (31,500 square meters) and has more significant differences in the composition and variability of gaseous and aerosol components in atmospheric air than in coastal continental areas and is still a poorly studied object. In recent years, the anthropogenic impact on the ecosystem of Lake Baikal has been increasing due to the development of industry in the region, the expansion of tourist infrastructure and recreational areas of the coastal zone of the lake. In addition, one of the significant sources of atmospheric pollution in the Baikal region is the emissions of smoke aerosol and trace gases from forest fires, the number of which is increasing in the region. This article presents the results of experimental studies of the dispersed composition of aerosols and gas impurities, such as ozone, sulfur dioxide, and nitrogen oxides during route ship measurements in the water area of Lake Baikal in the summer of 2020.

Appraisal of hydro-ecology, geomorphology, and sediment behavior during low and high floods in the Lower Indus River Estuary

The riverine ecosystem is beholden by the freshwater; however, morphological changes and sediment load destabilize the natural river system which deteriorates the ecology and geomorphology of the river ecosystem. The Lower Indus River Estuary (LIRE) geomorphological response was synthesized using satellite imagery (1986–2020) and evaluated against the field measurements. The estuary sinuosity index has an increasing trend from 1.84 (1986) to 1.92 (2020) and the estuary water area is increased from 101.41 km2 (1986) to 110.24 km2 (2020). The sediment load investigation at Kotri barrage indicated that the median size of bed material samples during the low-flow period falls between 0.100 and 0.203 mm and the bed material after the high flow has clay and silt (<0.0623 mm) ranging from 17–95% of the total weight of samples. The vegetated land loss on the banks is positively correlated with the peak runoff at Kotri barrage (r2=0.92). The bank erosion was computed with high precision (r2=0.84) based on an improved connection of the coefficient of erodibility and excess shear stress technique. This study will be helpful for policymakers to estimate the ecological health of LIRE, and sediment fluxes play an essential role in the mega-delta system and coastal management.

Fiber-optic vector acoustic receiver based on adaptive holographic interferometer

A mobile scalar–vector acoustic receiver is proposed, experimentally implemented and investigated. The key components of the receiver are (a) the six-channel fiber-optic coil-type sensor configured as to detect three projections of acoustic intensity vector, (b) the six-channel optical phase demodulator based on six-channel adaptive holographic interferometer configured with use of dynamic holograms multiplexed in a photorefractive crystal of cadmium telluride and (c) the signals recording ADC-based system combined with software package for data processing. Field tests of the developed receiver applied for obtaining scalar and vector parameters of acoustic waves generated by a stationary and moving acoustic source in open air and water area are carried out. Experimental results show perceptiveness of use of the fiber-optical adaptive interferometry system for bearing of weak acoustic sources in real conditions.

Multi-Scale Feature Aggregation Network for Water Area Segmentation

Water area segmentation is an important branch of remote sensing image segmentation, but in reality, most water area images have complex and diverse backgrounds. Traditional detection methods cannot accurately identify small tributaries due to incomplete mining and insufficient utilization of semantic information, and the edge information of segmentation is rough. To solve the above problems, we propose a multi-scale feature aggregation network. In order to improve the ability of the network to process boundary information, we design a deep feature extraction module using a multi-scale pyramid to extract features, combined with the designed attention mechanism and strip convolution, extraction of multi-scale deep semantic information and enhancement of spatial and location information. Then, the multi-branch aggregation module is used to interact with different scale features to enhance the positioning information of the pixels. Finally, the two high-performance branches designed in the Feature Fusion Upsample module are used to deeply extract the semantic information of the image, and the deep information is fused with the shallow information generated by the multi-branch module to improve the ability of the network. Global and local features are used to determine the location distribution of each image category. The experimental results show that the accuracy of the segmentation method in this paper is better than that in the previous detection methods, and has important practical significance for the actual water area segmentation.

A Framework for Multivariate Analysis of Land Surface Dynamics and Driving Variables—A Case Study for Indo-Gangetic River Basins

The analysis of the Earth system and interactions among its spheres is increasingly important to improve the understanding of global environmental change. In this regard, Earth observation (EO) is a valuable tool for monitoring of long term changes over the land surface and its features. Although investigations commonly study environmental change by means of a single EO-based land surface variable, a joint exploitation of multivariate land surface variables covering several spheres is still rarely performed. In this regard, we present a novel methodological framework for both, the automated processing of multisource time series to generate a unified multivariate feature space, as well as the application of statistical time series analysis techniques to quantify land surface change and driving variables. In particular, we unify multivariate time series over the last two decades including vegetation greenness, surface water area, snow cover area, and climatic, as well as hydrological variables. Furthermore, the statistical time series analyses include quantification of trends, changes in seasonality, and evaluation of drivers using the recently proposed causal discovery algorithm Peter and Clark Momentary Conditional Independence (PCMCI). We demonstrate the functionality of our methodological framework using Indo-Gangetic river basins in South Asia as a case study. The time series analyses reveal increasing trends in vegetation greenness being largely dependent on water availability, decreasing trends in snow cover area being mostly negatively coupled to temperature, and trends of surface water area to be spatially heterogeneous and linked to various driving variables. Overall, the obtained results highlight the value and suitability of this methodological framework with respect to global climate change research, enabling multivariate time series preparation, derivation of detailed information on significant trends and seasonality, as well as detection of causal links with minimal user intervention. This study is the first to use multivariate time series including several EO-based variables to analyze land surface dynamics over the last two decades using the causal discovery algorithm PCMCI.

Changing parameters of waters chemical composition in the Lake Arakhley water column (Eastern Transbaikalia)

The need to preserve the quality of water resources under conditions of anthropogenic impact is one of the most urgent problems of our time. The purpose of this work was to study the features of the distribution of the parameters of the chemical composition of the waters of Lake Arakhley in a vertical section. The investigated waters are characterised by a constancy of mineralisation and chemical composition, both within the water area and in the vertical section. The waters are ultra-fresh (salinity less than 200 mg / L), neutral and slightly alkaline (average pH 7.9), HCO3 Mg-Ca chemical composition. The carbon dioxide content in the water column has a significant impact on the concentration of hydrogen ions, as evidenced by the inverse relationship between pH and CO2 content. The observed increase in the nitrogen form and CO2 contents in the bottom part of the lake is most likely related to the life processes of organisms and vegetation. The recorded excess concentrations of Mn, Cu, Ni, and Al over maximum permissible concentrations indicate the need for additional studies to identify their sources.

Regional management of the Bay of Bengal water area. The challenges of maritime security

The Bay of Bengal is the largest bay in the world that forms the northeastern part of the Indian Ocean, bordered mostly by the Eastern Coast of India, southern coast of Bangladesh and Sri Lanka to the west and Myanmar and the Andaman and Nicobar Islands (part of India) to the east. The regional management of the Bay of Bengal water area is performed by regional organisations such as ASEAN, SAARC, BIMSTEC and IORA unifying Bay’s coastal states. Nevertheless, differences in political and economic interests of the states, separate conflicts between states and consequences of the pandemic not only challenged the integrity of the regional management but also led to rising insecurity of the Bay of Bengal and fears to navigate in that area. In this article, the authors, in a more detailed way, will disclose existing regional management systems, concerns related to maritime security and give recommendations on how to increase efficiency in collective management of maritime security issues and how the concept of due diligence may play the vital role in the regulation of not only maritime security aspects but also aspects of environmental protection and potential transition to the blue economy.

THE DESIGN OF 3 GT FISHING VESSELS USING DC ELECTRIC POWER AS DRIVING AND ELECTRICITY

The purpose of this study was to design a 3 Gross Tonnage (GT) fishing boat with a speed of 6 knots to obtain the shape and size of the vessel that is suitable for the water area that using the solar panel energy system. The ship was planned to travel about a maximum of 18 Km from the departure point. The steps of the research method for the design of fishing vessels include determining the principal size of the ship, making line drawings, drafting a general plan, construction design, ship tonnage capacity, electricity requirements, and then designing solar panel energy systems. This research resulted in a ship design with a length of 8 meters, 1.75 meters wide, and 1.3 meters high. Those specifications are used as constraints to determine the number of solar panels and batteries. To satisfy all of the goals, the 3 GT boat has limited 0.9KWh solar panels to travel for 9.7 NM (18 KM) at a speed of 6 knots, forcing daytime and night fishing fishermen to idle for 1 day. The difference is in the number of night fishing batteries that are 49% more than the daytime fishing which using 25 pcs 3.2V 100Ah. With the use of 51 pcs of battery, night fishing can move into daytime fishing so that it can fish more frequently than night fishing mode only