Lake Area Research Articles

Ecological Factors Affecting Distribution of the Aquatic Beetles (Coleoptera: Hydrophilidae, Helophoridae) of Beyşehir Lake and Adjacent Areas in Turkey

Ecological Factors Affecting Distribution of the Aquatic Beetles (Coleoptera: Hydrophilidae, Helophoridae) of Beyşehir Lake and Adjacent Areas in Turkey

A Multi-Sensor Approach to Characterize Winter Water-Level Drawdown Patterns in Lakes

Artificial manipulation of lake water levels through practices like winter water-level drawdown (WD) is prevalent across many regions, but the spatiotemporal patterns are not well documented due to limited in situ monitoring. Multi-sensor satellite remote sensing provides an opportunity to map and analyze drawdown frequency and metrics (timing, magnitude, duration) at broad scales. This study developed a cloud computing framework to process time series of synthetic aperture radar (Sentinel 1-SAR) and optical sensor (Landsat 8, Sentinel 2) data to characterize WD in 166 lakes across Massachusetts, USA, during 2016–2021. Comparisons with in situ logger data showed that the Sentinel 1-derived surface water area captured relative water-level fluctuations indicative of WD. A machine learning approach classified lakes as WD versus non-WD based on seasonal water-level fluctuations derived from Sentinel 1-SAR data. The framework mapped WD lakes statewide, revealing prevalence throughout Massachusetts with interannual variability. Results showed WDs occurred in over 75% of lakes during the study period, with high interannual variability in the number of lakes conducting WD. Mean WD magnitude was highest in the wettest year (2018) but % lake area exposure did not show any association with precipitation and varied between 8% to 12% over the 5-year period. WD start date was later and duration was longer in wet years, indicating climate mediation of WD implementation driven by management decisions. The data and tools developed provide an objective information resource to evaluate ecological impacts and guide management of this prevalent but understudied phenomenon. Overall, the results and interactive web tool developed as part of this study provide new hydrologic intelligence to inform water management and policies related to WD practices.

Rodent-Proof Wall: An Efficient Physical Method for Controlling Rodents and its Efficiency Statistics.

Rodent damage poses a significant threat to crops, human life, and health. Compared to chemical rodent control, such as placing poisonous baits, it is more economical and environmentally friendly to use physical methods, such as building a rodent-proof wall. This study introduces a method of physically controlling harmful rodents and four methods of calculating the effect of rodents control. To understand the controlling effect of the rodent-proof wall, an investigation was conducted on the Dongting Lake beach and corresponding farmland in the embankment in April and July 2012. Our findings illustrated that the density of the reed vole Microtus fortis in the farmland with rodent-proof walls was 0.52%, significantly lower than that in the farmland without rodent-proof walls (1.76%) after artificial trapping and drug extermination (χ2 = 3.900, P = 0.048). The density of M. fortis that had migrated into the farmland in dikes with a rodent-proof wall decreased by 98.53%, significantly higher than the decrease of density in dikes without a rodent-proof wall (86.61%) (χ2 = 11.060, P = 0.01). The results demonstrated the effectiveness of rodent-proof wall control. Therefore, building a rodent-proof wall should be advocated and vigorously promoted to prevent the migration of rodents into the Dongting Lake area and similar environments, as they cause harm.

Effects of land use/cover change on heavy metal distribution of soils in wetlands and ecological risk assessment

This study aimed to determine the impact of land use/cover changes on the heavy metal content in the Sultan Marshland and surrounding area and assess the pollution status. 54 topsoil samples (0–20 cm) were collected from the Rangeland, Farmland, Scrubland, Southern Marshland, Northern Marshland, and Dry Lake areas. The heavy metal contents of the soil samples (Cr, Pb, Fe, Zn, Cu, Co, Mn, Cd, Mo, As, and Ni) were determined using ICP-MS and ICP-OES devices. The impact of land use/cover change on soil heavy metal content was evaluated using variance analysis, while differences between groups were identified using the Duncan test. Principal Component Analysis (PCA) was conducted to identify potential sources of heavy metals. The contamination status of the soils was evaluated based on land use/cover using the Contamination Factor (Cf), Pollution Load Index (PLI), Ecological Risk Factor (Er), and Potential Ecological Risk Index (PERI).Changes in land use/cover around the Sultan Marshlands affected heavy metal distribution of the soils except for Cd. Among all land use/cover types, Fe concentration was the highest in the soils, while Cd concentration was the lowest. Soils in Southern Marshland exhibited higher average concentrations of Cr, Fe, Zn, Co, Cu, and Ni compared to other land uses/covers. Farmlands and rangelands had higher concentrations of Cd, As and Pb. Land use/cover was ranked based on the total heavy metal load in the following order in terms of average values: Southern Marshland > Scrubland > Farmland > Rangeland > Northern Marshland > Dry Lake. According to Cf, the soils in the Dry Lake were exposed to considerable levels of As contamination. Based on PLI, half of the soil sampling points in the Southern Marshland soils showed a degradation in environmental quality. Er indicated that all land uses moderately polluted with Cd. According to the average PERI, all soils under different land use/cover types were categorized as having a low ecological risk. It was believed that heavy metals originated from both natural and human activities. To ensure the sustainability of the ecosystem and to mitigate the risk of heavy metal pollution entering the food chain, it is recommended to manage farming and mining activities and land use habits.

Using Knowledge-Guided Machine Learning To Assess Patterns of Areal Change in Waterbodies across the Contiguous United States.

Lake and reservoir surface areas are an important proxy for freshwater availability. Advancements in machine learning (ML) techniques and increased accessibility of remote sensing data products have enabled the analysis of waterbody surface area dynamics on broad spatial scales. However, interpreting the ML results remains a challenge. While ML provides important tools for identifying patterns, the resultant models do not include mechanisms. Thus, the "black-box" nature of ML techniques often lacks ecological meaning. Using ML, we characterized temporal patterns in lake and reservoir surface area change from 1984 to 2016 for 103,930 waterbodies in the contiguous United States. We then employed knowledge-guided machine learning (KGML) to classify all waterbodies into seven ecologically interpretable groups representing distinct patterns of surface area change over time. Many waterbodies were classified as having "no change" (43%), whereas the remaining 57% of waterbodies fell into other groups representing both linear and nonlinear patterns. This analysis demonstrates the potential of KGML not only for identifying ecologically relevant patterns of change across time but also for unraveling complex processes that underpin those changes.

Effect of sodium dodecyl sulfate (SDS) on microbial community structure and function in lake–terrestrial ecotones: A simulation experiment

Even a low concentration of sodium dodecyl sulfate (SDS), a widely used bactericidal surfactant, can significantly change the species, quantity and genetic functions of microorganism communities in natural waters. Lake–terrestrial ecotones are areas where microorganisms are highly active, and they are also the lake areas most vulnerable to SDS pollution. Because microorganisms are very sensitive to environmental changes, their activities vary greatly among lakes and laboratories, so it is difficult to simulate their real dynamics using small-scale experiments. To study the interaction between SDS and microorganisms in a lake–terrestrial ecotone, a large artificial simulation device was used to analyse microbial community structure, phospholipid fatty acid (PLFA) content, gene function and ability to degrade SDS in a lake–terrestrial ecotone contaminated with SDS. The results showed that (1) the period from 2 to 4 days after the beginning of the experiment was the key stage for the biodegradation of SDS. The biodegradation cycle of SDS in the natural environment is shorter than that in small-scale experimental setups, and more than 90% of SDS was removed within 4 days in the simulation device. (2) Low-level SDS pollution (≤ 6 mg/L) has different effects on different types of lacustrine microorganisms. The presence of SDS can lead to a significant decrease in microbial diversity and biomass in lake–terrestrial ecotones with a high density of aquatic plants, but the opposite is true in ecosystems with degraded aquatic plant communities. (3) After SDS pollution occurred, pollution-resistant bacteria such as Chitinophaga and Flavobacterium became dominant. The relative abundance of carbon cycle functional genes increased rapidly in microorganisms, while the relative abundance of nitrogen cycle functional genes decreased. These changes were not readily reverse even after 20 days, although the communities recovered to a certain extent.

Velocity variations and hydrological drainage at Baltoro Glacier, Pakistan

Abstract. Glacial meltwater directly influences glacier dynamics. However, in the case of debris-covered glaciers, the drivers of glacier velocity and the influence of supraglacial lakes have not yet been sufficiently analysed and understood. We present a spatio-temporal analysis of key glacier characteristics for Baltoro Glacier in the Karakoram from October 2016 to September 2022 based on Earth observation data and climate parameters extracted from the High Asia Refined analysis (HAR) data set. For the glacier variables, we used surface velocity, supraglacial lake extent, melt of snow and ice, and proglacial run-off index. For climate variables, we focused on air temperature and precipitation. The surface velocity of Baltoro Glacier was characterized by a spring speed-up, summer peak, and fall speed-up with a relative increase in summer of 0.2–0.3 m d−1 (75 %–100 %) in relation to winter velocities, triggered by the onset of or an increase in basal sliding. Snow and ice melt have the largest impact on the spring speed-up, summer velocity peak, and the transition from inefficient to efficient subglacial drainage. The melt covered up to 64 % (353 km2) of the entirety (debris-covered and debris-free) of Baltoro Glacier and reached up to 4700 m a.s.l. during the first melt peak and up to 5600 m a.s.l. during summer. The temporal delay between the initial peak of seasonal melt and the first relative velocity maximum decreases downglacier. Drainage from supraglacial lakes (3.6–5.9 km2) contributed to the fall speed-up, which showed a 0.1–0.2 m d−1 (20 %–30 %) lower magnitude compared to the summer velocity peak. Most of the run-off can be attributed to the melt of snow and ice. However, from mid-June onward, the lakes play an increasing role, even though their contribution is estimated to be only about half of that of the melt. The observed increase in summer air temperatures leads to a greater extent of melt, as well as to a rise in the number and total area of supraglacial lakes. This tendency is expected to intensify in a future warming climate.

GEA-MSNet: A Novel Model for Segmenting Remote Sensing Images of Lakes Based on the Global Efficient Attention Module and Multi-Scale Feature Extraction

The decrease in lake area has garnered significant attention within the global ecological community, prompting extensive research in remote sensing and computer vision to accurately segment lake areas from satellite images. However, existing image segmentation models suffer from poor generalization performance, the imprecise depiction of water body edges, and the inadequate inclusion of water body segmentation information. To address these limitations and improve the accuracy of water body segmentation in remote sensing images, we propose a novel GEA-MSNet segmentation model. Our model incorporates a global efficient attention module (GEA) and multi-scale feature fusion to enhance the precision of water body delineation. By emphasizing global semantic information, our GEA-MSNet effectively learns image features from remote sensing data, enabling the accurate detection and segmentation of water bodies. This study makes three key contributions: firstly, we introduce the GEA module within the encode framework to aggregate shallow feature semantics for the improved classification accuracy of lake pixels; secondly, we employ a multi-scale feature fusion structure during decoding to expand the acceptance domain for feature extraction while prioritizing water body features in images; thirdly, extensive experiments are conducted on both scene classification datasets and Tibetan Plateau lake datasets with ablation experiments validating the effectiveness of our proposed GEA module and multi-scale feature fusion structure. Ultimately, our GEA-MSNet model demonstrates exceptional performance across multiple datasets with an average intersection ratio union (mIoU) improved to 75.49%, recall enhanced to 83.79%, pixel accuracy (PA) reaching 90.21%, and the f1-score significantly elevated to 83.25%.

Blinded by the light: does heat or light enhance wild mosquito (Diptera: Culicidae) attraction to CO2-baited traps in the Great Salt Lake area?

The New Jersey Light Trap has been among the earliest trap models used for mosquito surveillance in the United States. This trap was modernized in the 1950s to the miniature CDC light trap, with the addition of CO2 following soon after. The incandescent light has the tendency to attract nontarget insects, as well as losing a substantial portion of their energy as heat. Few studies have delineated whether heat or light in isolation make a difference in field collections using the former traps within the United States. Our study focused on isolating heat and light variables by using incandescent bulbs, light emitting diode (LED) bulbs, and electric heating patches affixed to a base model CO2 trap as designed at the Salt Lake City Mosquito Abatement District. Sites were selected in the urban and suburban foothills and canyons of the Wasatch Mountain front, industrial areas near the Salt Lake City International Airport, and rural wetlands in the marshes outlying the Great Salt Lake. Five traps were replicated within each sector during the summer and fall summer seasons. Collections were composed of Aedes dorsalis (Meigen), Culex pipiens L., Culex tarsalis Coquillett, and Culiseta inornata (Williston). Composition changes were a result of seasonal, rather than spatial, shifts. The results showed that LED light traps depressed collections of key species. Otherwise, there were negligible differences in collections among incandescent, heat film, and base model traps. In the Intermountain West, the miniature CDC trap is reliable enough to make programmatic decisions even if light usage varies by district.

Deriving high-accuracy lake water-level changes from multi-source satellite datasets

ABSTRACT Satellite data have exhibited a great potential to track lake water-level changes. By integrating multi-source satellite datasets (i.e., Ice, Cloud and land Elevation Satellite-2 (ICESat-2) lidar datasets, Landsat imagery, and Global Surface Water Dataset (GSWD)), we proposed a method to track annual water-level changes of Lake Mead, USA over 1984–2018. Specifically, we first extracted ICESat-2 profiles as elevation information. Second, we used Landsat imagery to extract annual lake boundaries and calculate lake areas. Third, we constructed the relationship between elevations and inundation frequencies provided by the GSWD for ICESat-2 points, and applied it to extract annual water levels by using inundation frequency of Landsat derived lake boundaries. Finally, we created the relationship between lake water level and lake areas via a cubic polynomial model to refine the annual lake water levels. Our water level results agreed well with the in-situ data (R 2 = 0.99, p < 0.01, RMSE = 0.64 m). Our results showed that the ICESat-2 data performed well in providing accurate elevation information around the shore of lake. Using satellite datasets, our proposed method has the potential to derive water levels for water bodies worldwide in the future.

Environmental factors controlling seasonal and spatial variability of zooplankton in thermokarst lakes along a permafrost gradient of Western Siberia

Humic thermokarst lakes of permafrost peatlands in Western Siberia Lowland (WSL) are major environmental controllers of carbon and nutrient storage in inland waters and greenhouse gases emissions to the atmosphere in the subarctic. In contrast to sizable former research devoted to hydrochemical and hydrobiological (phytoplankton) composition, zooplankton communities of these thermokarst lakes and thaw ponds remain poorly understood, especially along the latitudinal gradient, which is a perfect predictor of permafrost zones. To fill this gap, 69 thermokarst lakes of the WSL were sampled using unprecedented spatial coverage, from continuous to sporadic permafrost zone, in order to assess zooplankton (Cladocera, Copepoda, Rotifera) diversity and abundance across three main open water physiological seasons (spring, summer and autumn). We aimed at assessing the relationship of environmental factors (water column hydrochemistry, nutrients, and phytoplankton parameters) with the abundance and diversity of zooplankton. A total of 74 zooplankton species and taxa were detected, with an average eight taxa per lake/pond. Species richness increased towards the north and reached the maximum in the continuous permafrost zone with 13 species found in this zone only. In contrast, the number of species per waterbody decreased towards the north, which was mainly associated with a decrease in the number of cladocerans. Abundance and diversity of specific zooplankton groups strongly varied across the seasons and permafrost zones. Among the main environmental controllers, Redundancy Analysis revealed that water temperature, lake area, depth, pH, Dissolved Inorganic and Organic Carbon and CO2 concentrations were closely related to zooplankton abundance. Cladocerans were positively related to water temperature during all seasons. Copepods were positively related to depth and lake water pH in all seasons. Rotifers were related to different factors in each season, but were most strongly associated with DOC, depth, CH4, phytoplankton and cladoceran abundance. Under climate warming scenario, considering water temperature increase and permafrost boundary shift northward, one can expect an increase in the diversity and abundance of cladocerans towards the north which can lead to partial disappearance of copepods, especially rare calanoid species.

Winter/Spring Runoff Is Earlier, More Protracted, and Increasing in Volume in the Laurentian Great Lakes Basin

AbstractWinter/spring runoff has changed in streams worldwide due to climate change, particularly in temperate areas where winter/spring streamflow depends on snowmelt. Such changes potentially affect receiving waters through altered nutrient loading and mixing patterns. The Laurentian Great Lakes are an important freshwater resource and have experienced a myriad of impacts due to climate change. We analyzed 70 years of stream gauge data in the Great Lakes Basin to test for changes in timing, duration, and amount of winter/spring runoff during the period 1950–2019. We found strong evidence for earlier runoff in each of the Great Lakes except Lake Erie, protracted winter/spring runoff throughout the Great Lakes Basin, and a higher runoff depth during the winter‐spring period over time for all watersheds except Lake Superior. Lake Ontario had the greatest change in the date by which 50% of the Jan–May runoff had been discharged (6 days earlier from 1950 to 2019). For winter/spring runoff duration, the most extreme change was observed in Lake Erie (increase of 19 days), and for runoff depth, the greatest change was in the Lake Huron Basin (increase of 3.3 cm). Results were similar for natural and impacted streams. Our results demonstrate dramatic changes in runoff patterns over the last seven decades in the Great Lakes Basin concomitant with previously published changes in precipitation and snowpack. Shifts toward earlier, more protracted, and more voluminous runoff likely change nutrient loading and mixing patterns that influence primary producers, particularly in the nearshore areas of the Great Lakes.

Trend analysis of hydro-climatic variables in the Great Lakes Depression region of Mongolia

Abstract Arid and semi-arid regions are the first to be affected by hydro-climatic changes. The Great Lakes Depression Basin in western Mongolia is the most notable example of such a region. Therefore, analyzing hydro-climatic changes in the Great Lakes Depression region is essential for future climate, hydrological, eco-hydrological processes, and ecosystem studies in similar areas and basins. In this study, Mann–Kendall (MK), innovative trend analysis method (ITAM), and Sen's slope estimator test (SSET) were used to determine the interrelationship between climate and river discharge changes and lake water level changes through statistical analysis. During the last 30 years, the air temperature has increased by 1.2 °C (Z = 1.16). Total annual precipitation decreased by 23.44 mm, resulting in 134.16 mm (Z = −0.79). The river discharge of the major rivers, such as Khovd River (Z = −3.51) and Zavkhan River (Z = −6.01), has significantly decreased. In Uvs (Z = 0.30) and Khyargas (Z = 2.03) lakes, the water level has also dropped. This study confirms that the increase in air temperature in the depression area of the Great Lakes reduces the amount of precipitation, and the decrease in precipitation affects the decrease in river discharge, which further affects the water level of the inflowing lakes.

Gökpınar Baraj Gölü (Batı Anadolu, Türkiye)’ndeki Egzotik Güneş Levreği Popülasyonunun (Lepomis gibbosus) Biyo-Ekolojik Özellikleri Üzerine Bir Araştırma

This study was conducted to determine some bioecological characteristics of Lepomis gibbosus (L. 1758), commonly known as pumpkinseed sunfish, which spreads in Gökpınar Dam Lake (GDL) in Denizli Province. The fish samples were captured with an experimental seine net and multimesh gillnet from May 2019 to April 2020. During the samplings, certain physicochemical parameters of GDL were measured, habitat utilization, relations to environmental variables, feeding habits and interspecific interactions with other fishes of L. gibbosus individuals were observed. It is observed that GDL provides a suitable habitat for L. gibbosus in terms of water quality and other ecological requirements. A total of 1005 L. gibbosus individuals, consisting of 302 females, 605 males, and 98 juveniles, were sampled throughout the study, and biometric studies were conducted. In the population males were found to be dominant. The averages were determined as follows; total length as 5.82±2.09 cm (2.46-11.34), weight as 4.94±4.67g (0.20- 34.65), and condition factor as 1.71±0.24. The ages were determined between 0+ to II+and Age-length relationship (VBGE) was estimated as L_(t=) 19,85(1-e^(-0,2744(t+0,272) ) ) Spawning occurs between April and June in individuals at the age of I+. It has been observed that the species exhibits good growth rates in this habitat, displays opportunistic omnivorous feeding behavior, preys on another invasive alien species, Gambusia holbrooki, present in the lake, and competes with the same species for habitat sharing. It has been determined that L. gibbosus has formed a self-sustaining population in GDL, but it utilizes a limited lake area as its habitat. In conclusion, GDL is considered as a hydrologically unstable and highly variable habitat. L. gibbosus population of GDL exhibits significant similarities in terms of bioecological characteristics with populations that spread outside its natural spreading area. As L.gibbosus is an exotic fish and might be have invasive traits, it is necessary to monitor of the population regularly, and control measures should be taken to prevent its spread to other inland water bodies.

Ecological Regeneration of Wetland: Case Study of Kanwar Lake, Begusarai

The wetlands are the partially water-submerged environments that are highly productive, and support fauna and flora species in significant numbers that are dependent for their survival on the organic production of wetlands. Kanwar Lake is situated about 22 kilometers to the northwest of Begusarai. The Gandak River, a tributary of the Ganges, meanders across the area, creating the largest oxbow lake in Asia. It is a natural body of water that is significant on many different levels, including ecological, floral, faunal, geomorphological, and zoological. In 1989, the state government of Bihar designated Kanwar as a protected area for avian species. It has been considered a Ramsar site since 1987, but the wetland was not one of the 13 designated sites. In 1984, the lake’s area was 6,786 hectares (ha), but by 2004, it had shrunk to 6,043.825 ha. Only 2,032 hectares remained of the original lake area by 2012. Wealthy farmers and locals have rapidly colonized the lake bed. Lake biodiversity has declined as weeds have grown across the wetland. Widespread deforestation, overgrazing, unsustainable agricultural methods and over-exploitation of biomass for wood, fodder, and timber have stripped the land of its natural vegetative cover and exacerbated erosion. The research deals with the ecological study of the area and how urbanization has caused impacts on it. It focuses on how this has caused the deterioration of the lake and the measures for restoring the lake ecology, safeguarding the trend of urbanization. After analyzing the major key issues and analyzing the issues at the edge of the lake and around the Manjhaul, some of the major findings conclude that there is a need for stormwater management of the whole city, restoration of Kanwar wetland, and industrial control around the lake.

Investigating the microclimate impacts of blue–green space development in the urban–rural fringe using the WRF-UCM model

Blue–green spaces in the urban–rural fringe (URF) can help restrain endless urban sprawl and urban warming; however, the climate impact of these spaces has not been examined. Based on spatial transformation characteristics within the identified URF areas in Wuhan from 2000 to 2020, this study used the WRF-UCM model to observe microclimate impacts of different development modes and lake reduction in URF blue–green spaces. 1) Urban sprawl increased the average air temperature at 2 m (T2) by 0.82 °C and increased the 10-m wind speed (WS10) by 0.16 m/s in the city centre area. 2) The non-built-up areas (GW_CT) development mode reduced T2, with a maximum hourly cooling effect of 0.13 °C, and the open high-rise (GW_HR) and large low-rise (GW_LL) development modes increased the average nighttime T2 (with maximum hourly warming of 0.22 °C and 0.12 °C, respectively) as well as the WS10. 3) When built-up land expanded outwards and encroached on more than 25.89% of the lake area, the T2 and WS10 at the city centre significantly changed (0.17 °C and 0.1 m/s increased). This paper demonstrates the importance of conducting climate impact assessments for peri-urban blue-green space development.

Impacts of Climate Change and Human Activity on Lakes around the Depression of Great Lakes in Mongolia

The western region of Mongolia is characterized by an arid climate and a fragile ecological environment. It is a sensitive zone in response to global climate change and one of the major sources of dust globally. This region is home to numerous lakes, and their dynamic changes not only reflect global climate variations but also have implications for the global ecological environment quality. In this study, Landsat images were used as the data source, and Google Earth Engine (GEE) was employed to extract lakes with an area larger than 1 km2 from 1992 to 2021. The spatiotemporal characteristics of lake water area (LWA) changes were analyzed, and a structural equation model was applied to attribute the lake changes. The results indicate an overall trend of increasing lake area followed by a decrease in the study area. Specifically, lakes in the provinces of Khovd and Gobi-Altai exhibited a decreasing trend followed by an increasing trend, while lakes in the provinces of Uvs and Zavkhan showed an increasing trend followed by a decreasing trend. Three typical types of lakes, namely, alpine lakes, throughflow lakes, and terminal lakes, all exhibited a trend of increasing area followed by a decrease. The analysis of driving forces behind lake area changes reveals that climate change and human activities primarily exert indirect influences on the lake area changes in each province. Specifically, climate change and human activities lead to changes in soil moisture, which have a significant explanatory power for lake area changes. Regarding the typical types of lakes, climate change serves as the primary driving force for alpine lakes, while human activities are the main driving forces for throughflow lakes and terminal lakes.

INGRESSION OF THE KARANGATIAN SEA INTO THE MANYCH DEPRESSION (LATE PLEISTOCENE)

The work presents the results of paleogeographic study, including facies-lithological, malacofaunistic and luminescence analyses, of three boreholes core drilled in the central part of the Manych Depression, which made it possible to determine the time and stages of the existence of the Karangatian ingressive bay in the Manych Depression, and to correlate the latter with phases of the Karangatian transgression identified earlier on the basis of luminescence dating. Based on the results of the study it was found that: 1) the Karangatian Sea penetrated into the Manych Depression during the second phase of transgression in the time interval of ~120-110 ka years ago (MIS 5e-d). The salinity of the bay in the area of the modern Manych-Gudilo Lake reached 20-22‰; 2) the inflow of water of the Hyrcanian transgression of the Caspian into the bay in the central part of the Manych Depression took place 110-105 ka years ago, which corresponds to the third phase of the Karangatian transgression (MIS 5c). The brackish Caspian waters desalinated the Karangatian Bay in the area of the modern Manych-Gudilo Lake down to 14‰ and below; 3) the waters of the Karangatian Sea finally left the Manych Depression about 105 ka years ago (MIS 5c).

Beyond the ice: decoding Lake Mertzbakher’s response to global climate shifts

This study addresses the critical problem of understanding the changing dynamics of glacier meltwater in Lake Mertzbakher, a challenge heightened by ongoing global climate change. Employing the innovative method of the Google Earth Engine (GEE) platform, this research meticulously extracted surface water data at 60 time points during the years 2000, 2005, 2010, 2015, and 2021. This approach represents a significant advancement over previous methods by offering more frequent and precise data analysis. We incorporated meteorological factors such as temperature and precipitation to assess their influence on the monthly changes in the glacier lake area. Our findings indicate a pronounced outburst in July, leading to a substantial decrease in the lake’s area, which reaches its lowest in September. Through detailed partial regression analysis, we established a hierarchy of meteorological influences on the lake’s area, identifying minimum temperature (r = 0.245), mean temperature (r = −0.239), precipitation (r = 0.228), radiation (r = 0.154), and maximum temperature (r = 0.128) as key factors. Additionally, our use of a structural equation model unveiled the most impactful elements, with mean temperature (r = −3.320), minimum temperature (r = 2.870), radiation (r = 0.480), and precipitation (r = 0.470) leading the effects. These insights mark a substantial contribution to our understanding of glacier lake dynamics, offering crucial data for predicting and managing glacier lake floods. This study’s novel methodology and comprehensive analysis underscore its significance in enhancing disaster prevention and preparedness strategies amidst the challenges of global climate change.

Durability Performance of Basalt Fiber-Reinforced Concrete Subjected to Sulfate-Magnesium Combined Attack.

In salt lake areas, cast-in situ concrete structures are subjected to long-term corrosion by sulfate and magnesium ions. The properties of concrete can be improved by adding materials like basalt fiber (BF). To investigate the degradation process and mechanism of cast-in situ concrete with premixed BF under the dual corrosion of sulfate and magnesium salts, concrete with a content of BF ranging from 0 to 0.5% was prepared. Specimens were subjected to different internal and external corrosion conditions and immersed for 180 days. Dimension, mass, and appearance changes at different immersion times were recorded. The compressive and flexural strength of the specimens were tested and continually observed throughout the immersion time. Mineral and microstructural changes at different immersion times were determined by the XRD, TG, and SEM analysis methods. Results indicated that external sulfate-internal magnesium combined attack had a significant negative effect on the early strength. The compressive and flexural strength of the corroded specimens decreased by 17.2% and 14.1%, respectively, compared to the control group at 28 days. The premixed magnesium ions caused the decomposition of the C-S-H gel, resulting in severe spalling and lower mechanical properties after immersing for a long time. As the BF can inhibit crack development, the properties of the concrete premixed with BF were improved. Specimens exhibited superior performance at a BF content of 0.5%, resulting in a 16.2% increase in flexural strength. This paper serves as a valuable reference for the application of basalt fiber-reinforced concrete under the challenging conditions of sulfate-magnesium combined attack.