Lake Water Depth Research Articles

Holocene hydroclimate variability reconstructed from Lake Pangodi sediments in Estonia

Long-term hydroclimate variability recorded in lake sediments from Estonia provide information about environmental changes in northern Europe during the Holocene. Lake Pangodi is a semi-closed basin lake in southern Estonia with a large surface area to volume ratio, making it sensitive to effective moisture balance (precipitation minus evapotranspiration), which is recorded as changes in the lake level. Here we conducted a ground penetrating radar (GPR) survey, sedimentological analyses, radiometric dating and lake level modeling study to identify periods of lake-level high- and low-stands. The radiocarbon-dated sedimentary stratigraphic features on our radargram support the model results, suggesting that Lake Pangodi formed at ∼12.8 ka. The water levels were likely variable during the early Holocene, and the comparison of Lake Pangodi sediment facies and the lake level model show relatively stable lake water depth between ∼9.8 ka and ∼2.4 ka, and an increase towards modern. A notable reduction in lake levels occurred between ∼8.2 and ∼7.7 ka, likely due to a significantly reduced precipitation-evaporation balance. Our middle Holocene reconstruction suggests water column depths nearly 2.0 m lower than modern. This aligns with the results from studies conducted in the Baltic region, yet contrasts those from Scandinavia, suggesting different hydroclimate driving mechanisms during the Holocene variations in hydrogeological regimes. Our model detected the most abrupt rise of 1.7 m in water levels between ∼1.5 and ∼1.3 ka. This study highlights the need to develop proxies from single lake basins combining multiple methods for a better spatiotemporal resolution of paleo-hydrological changes.

Quantifying the functional genes of C, N, P, and S cycling in a deep lake: Depth patterns and drivers

Microbial functional composition is important for biogeochemical cycles, and is usually constrained by taxonomic species pool and natural environmental gradients. However, the distribution of functional genes in deep lakes and the driving factors remains elusive. Here, we quantified the abundance of 71 functional genes relevant to carbon degradation, carbon fixation, methane metabolism, nitrogen cycling, phosphorus cycling, and sulfur cycling in 38 sediments along the water depth ranging from 0 to 90 m in Lugu Lake, China, using Quantitative Microbial Ecology Chip (QMEC) and then explored their water-depth diversity pattern and abiotic and biotic drivers. Functional gene diversity showed a hump-shaped pattern along the depth and peaked at around 50 m which is the low boundary of thermocline layer. There were specific environmental preferences among functional gene subgroups such as nitrogen and sulfur cycling genes preferring to deeper and shallow waters, respectively. The dissimilarity of total functional genes increased with water depth distance indicating a distance-decay relationship. There was a congruence between functional and taxonomic composition by showing the positive correlations between the compositions of functional genes and bacteria or archaea. This phenomenon is consistently observed for the six functional gene subgroups, and the congruence strength was highest for nitrogen cycling while lowest for sulfur cycling. Compared to abiotic factors, biotic factors were more relevant to the functional gene diversity and composition. Biotic factors explained 28.5 % of the variance of functional gene diversity, while water depth and other environmental factors such as water total phosphorus and sediment carbon explained 4.2 % and 3.8 %, respectively. For functional gene composition, biotic factors accounted for 25.2 % of the variance, whereas water depth and other environmental factors contributed to 0.7 % and 4.4 %, respectively. Among all explanatory variables for function genes, bacterial composition had the highest contribution, which was further supported by showing its direct effects of 1.45 and 0.86 on functional diversity and composition, respectively. This study for the first time quantified the microbial functional genes along water depth in deep lakes and provided a more comprehensive understanding of the functional dynamics in microbial communities within aquatic ecosystems.

A Persistent Coast Mode of Precipitation in Southeast China Over the Last Millennium

AbstractInstrumental data set have revealed several summer precipitation patterns in eastern China, being summarized as “tripole,” “dipole” and “coast” modes. The former two have been found to persist at different time scales, leaving the latter unclear in geological records. Here we present 1300‐year hydroclimate records in a tropical maar lake in the southern coast of China using archeal lipid GDGTs, which can reflect lower water redox conditions largely regulated by lake water depth. The down‐core GDGTs reveal a relatively drier condition during the medieval climate anomaly compared to the Little Ice Age, in‐phase with other records in southeast coast of China but opposite to the inland region, hence demonstrating a persistent “coast” mode in eastern China. The thermal state of equatorial Pacific is suggested to play an important role in shaping the “coast” mode by modulating the location and strength of the western Pacific subtropical high and tropical typhoons.

Spatiotemporal lakes surface area changes over 35 years and potential causes in the Central Rift Valley, Ethiopia

Study RegionCentral Rift Valley (CRV) region, Ethiopia. Study FocusThe study aims to investigate the spatiotemporal change in lake water surface extents over 35 years (1986–2020) and identify potential causes. Three alternative multispectral water indices—Normalized Difference Water Index (NDWI), Automatic Water Extraction Index (AWEI), and Modified Normalized Difference Water Index (MNDWI)—derived from Landsat sensors (TM, ETM+, OLI) were utilized to extract and analyze the lake surface area. The Mann-Kendall correlation was applied to examine whether hydro-meteorological and anthropogenic variables are possible causes for changes. New Hydrological Insights for the RegionMNDWI outperforms other indices with over 96 % accuracy in mapping lake surface area. Lake Abiyata experienced the most significant reduction in surface area from 1986 to 2020 (>50 %), followed by Lake Ziway (<2 %) while Lake Langano remained relatively stable. This significant reduction positively correlates to alterations in lake water depth (R2=0.92). Factors such as increased temperature, evaporation, and water abstraction for soda ash production negatively correlated with lake surface area, while inflow from Bulbula River and mean annual rainfall showed positive correlations. Abiyata Lake's decrease in surface area is primarily attributed to water abstraction for soda-ash manufacturing and incoming river flow. If the current trends in water abstraction from the Lake and income water diversion continue, there is a high possibility that Lake Abiyata will change into a terminal lake shortly.

Multidimensional water level and water quality response to severe drought in Xingyun Lake

Drought stress has a significant impact on the quality and quantity of lake water. Understanding this impact is crucial for preventing water security risks and pollution recovery. However, there is a lack of systemic understanding of how drought affects water quality and quantity, and how they change in multiple dimensions. This manuscript established a synthesized methodology with the principles to judge the applicability and three steps of application to detect the change in water quality and water level under severe drought in Xingyun Lake, China. Results show that (1) The water level and water quality of Xingyun Lake have a synchronous and evident response to drought during 2009–2014. The rainfall during 2008–2015 declined by 22.9 % to normal, and the inundated area and lake water depth in 2012 decreased by 10.50 % from 2002 to 1.38 m to the average depth, respectively. The pollution index climbed above 1.21 after 2008, fluctuating around 1.42. (2) Under drought, the water quality indicators significantly changed in the terms of the overall feature, trend, eigenvalue, and morphological characteristics. The water quality indicators of Set2008-2015 are significantly different from set2000-2007 and not in the groups of set1994-2000. The morphological characteristics of water quality indicators in set2008-2015 differs significantly from that in set2000-2007 shown by the minimum, maximum, median, quartiles, and extreme values. (3) Although NH3–N showed no significant change, the water quality deteriorated in the physical, chemical, and biological aspects. The TP, IMN, and BOD5 changed more evidently than DO and NH3–N. (4) Water quality grade and indicator concentration deteriorated significantly and sharply under severe drought and are threatened deeply by TP and TN. The synthesized methodology is scientifically constructed and canbe employed in the characteristics cognition of water quality and water level to severe drought in and out of this research. And the intervention time and various regulating measures for pollution degradation and water quality recovery canbe constructed based on the multi-dimensional analysis of water quality change under drought evolution.

Long-term Satellite-derived Bathymetry of Arctic Supraglacial Lake from ICESat-2 and Sentinel-2

Abstract. The polar ice sheets serve as natural thermostats, regulating Earth’s temperatures. The Greenland Ice Sheet (GrIS), the second-largest ice sheet, is a critical indicator of climate change and global warming. Estimating the volume of supraglacial lakes on the GrIS, which is directly linked to the extent of melting in the Arctic ice sheet, requires information on both lake area and water depth. Conventional bathymetric methods (i.e., airborne bathymetric LiDAR, shipborne echo-sounder) are commonly used for accurate water depth measurement. However, polar supraglacial lakes face challenging conditions, leading to uncertainties in their spatial and temporal distribution. To overcome the limitations, this study combines Sentinel-2 and ICESat-2 (Ice, Cloud, and Land Elevation Satellite-2) to estimate bathymetry and detect changes in lake volume on the GrIS from 2019 to 2023. Firstly, Sentinel-2 images were pre-processed, and ICESat-2 single-photon LiDAR points were extracted using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) method, followed by the bathymetric corrections as the training data. Subsequently, three bathymetry models (i.e., log-linear, log-ratio, and BP (Back Propagation) neural network) were constructed using Sentinel-2 images and ICESat-2 data. Lastly, the highresolution ArcticDEM (Arctic Digital Elevation Model) was used as the validation data to assess the satellite-derived bathymetry accuracy. In this study, the log-ratio model yielded the best results with the R2, RMSE, and MAE of 0.92, 0.79 m (lower than 10% of the maximum depth), and 0.62 m. The results demonstrate the feasibility of the integrated active and passive remote sensing approach for bathymetry in Arctic supraglacial lakes.

Influence of hydrological features on CO2 and CH4 concentrations in the surface water of lakes, Southwest China: A seasonal and mixing regime analysis

Due to the large spatiotemporal variability in the processes controlling carbon emissions from lakes, estimates of global lake carbon emission remain uncertain. Identifying the most reliable predictors of CO2 and CH4 concentrations across different hydrological features can enhance the accuracy of carbon emission estimates locally and globally. Here, we used data from 71 lakes in Southwest China varying in surface area (0.01‒702.4 km2), mean depth (< 1‒89.6 m), and climate to analyze differences in CO2 and CH4 concentrations and their driving mechanisms between the dry and rainy seasons and between different mixing regimes. The results showed that the average concentrations of CO2 and CH4 in the rainy season were 23.9 ± 18.8 μmol L−1 and 2.5 ± 4.9 μmol L−1, respectively, which were significantly higher than in the dry season (10.5 ± 10.3 μmol L−1 and 1.8 ± 4.2 μmol L−1, respectively). The average concentrations of CO2 and CH4 at the vertically mixed sites were 24.1 ± 21.8 μmol L−1 and 2.6 ± 5.4 μmol L−1, being higher than those at the stratified sites (14.8 ± 13.4 μmol L−1 and 1.7 ± 3.5 μmol L−1, respectively). Moreover, the environmental factors were divided into four categories, i.e., system productivity (represented by the contents of total nitrogen, total phosphorus, chlorophyll a and dissolved organic matter), physicochemical factors (water temperature, Secchi disk depth, dissolved oxygen and pH value), lake morphology (lake area, water depth and drainage ratio), and geoclimatic factors (altitude, wind speed, precipitation and land-use intensity). In addition to the regression and variance partitioning analyses between the concentrations of CO2 and CH4 and environmental factors, the cascading effects of environmental factors on CO2 and CH4 concentrations were further elucidated under four distinct hydrological scenarios, indicating the different driving mechanisms between the scenarios. Lake morphology and geoclimatic factors were the main direct drivers of the carbon concentrations during the rainy season, while they indirectly affected the carbon concentrations via influencing physicochemical factors and further system productivity during the dry season; although lake morphology and geoclimatic factors directly contributed to the carbon concentrations at the vertically mixed and stratified sites, the direct effect of system productivity was only observed at the stratified sites. Our results emphasize that, when estimating carbon emissions from lakes at broad spatial scales, it is essential to consider the influence of precipitation-related seasons and lake mixing regimes.

High-resolution insights of physical properties of water columns of lakes at the Larsemann Hills, East Antarctica

During the Austral summer of 2022, a study was conducted to investigate the physical properties of six lakes in the Larsemann Hills, East Antarctica. The lake water column's key properties, viz. temperature, salinity, density, fluorescence, and depth, were examined using a CTD profiler to establish a high-resolution description of their variations and identify the factors influencing intra and inter-lake variations. The results indicated that the shallow lakes LH14, LH04, and Discussion were well mixed. Lakes LH04 and LH14 on Stornes were affected by salinity, likely sea spray. In contrast, the deeper lakes, namely Nella, Cameron and Progress, were primarily driven by temperature and density dynamics. The hydrological characteristics of Cameron and Progress were notably impacted by their proximity to the ice sheet, while Nella was influenced by the presence of a partial lake ice cover. The lake depth, geographical location and presence of ice cover in the catchment significantly influenced temperature and salinity variations within the lakes. Deep lakes may be more sensitive to changes in temperature and density as compared to shallow lakes and could potentially affect other physical lake parameters. This baseline information is a valuable reference for future investigations on these lakes and similar environments.

Geochemical, sedimentological and microbial diversity in two thermokarst lakes of far Eastern Siberia

Thermokarst lakes are important conduits for organic carbon sequestration, soil organic matter (soil-OM) decomposition and release of atmospheric greenhouse gases in the Arctic. They can be classified as either floating-ice lakes, which sustain a zone of unfrozen sediment (talik) at the lakebed year-round, or as bedfast-ice lakes, which freeze all the way to the lakebed in winter. Another key characteristic of thermokarst lakes are their eroding shorelines, depending on the surrounding landscape, they can play a major role in supplying the lakebeds with sediment and OM. These differences in winter ice regime and eroding shorelines are key factors which determine the quantity and quality of OM in thermokarst lake sediments. We used an array of physical, geochemical, and microbiological tools to identify the differences in the environmental conditions, sedimentary characteristics, carbon stocks and microbial community compositions in the sediments of a bedfast-ice and a floating-ice lake in Far East Siberia with different eroding shorelines. Our data show strong differences across most of the measured parameters between the two lakes. For example, the floating-ice lake contains considerably lower amounts of sediment organic matter and dissolved organic carbon, both of which also appear to be more degraded in comparison to the bedfast-ice lake, based on their stable carbon isotope composition (δ13C). We also document clear differences in the microbial community composition, for both archaea and bacteria. We identified the lake water depth (bedfast-ice vs. floating-ice) and shoreline erosion to be the two most likely main drivers of the sedimentary, microbial and biogeochemical diversity in thermokarst lakes. With ongoing climate warming, it is likely that an increasing number of lakes will shift from a bedfast- to a floating-ice state, and that increasing levels of shoreline erosion will supply the lakes with sediments. Yet, still little is known about the physical, biogeochemical and microbial differences in the sediments of these lake types and how different eroding shorelines impact these lake systems.

Suspended sediment deposition and sediment yields at Lake Peters, northeast Brooks Range, Alaska: Fluvial‐ and lake‐based approaches

AbstractLake‐based studies can provide seasonal‐ to millennial‐scale records of sediment yield to improve our understanding of catchment‐scale sediment transfer and complement shorter fluvial‐based sediment transport studies. In this study, sediment accumulation rates at 40 coring locations in Lake Peters, Brooks Range, Alaska, over ca. 42 years, calculated using fallout radionuclides and sediment density patterns, were spatially modelled based on distance from the primary inflow and lake water depth. We estimated mean interdecadal specific sediment yield (Mg km−2 year−1) using the spatially modelled sediment accumulation rates and compared that result to fluvial‐based sediment delivery for 2015–2016 open‐channel seasons, as well as to yields reported for other Arctic catchments. Using the lake‐based method, mean yield to Lake Peters between ca. 1973 and 2015 was 52 ± 12 Mg km−2 year−1, which is comparable with fluvial‐based modelling results of 33 (20–60) Mg km−2 year−1 in 2015 and 79 (50–140) Mg km−2 year−1 in 2016 (95% confidence intervals), respectively. Although 2016 was a year of above average sedimentation, the last extreme depositional event probably occurred between ca. 1970 and 1976 when a basal layer of fine sand was deposited in a broadly distributed, relatively thick and coarse bed, which we used for lake‐wide correlation. The dual lacustrine–fluvial method approach permits study of within‐lake and catchment‐scale processes. Within Lake Peters, sedimentation patterns show decreasing fluxes down‐lake, sediment bypassing near the primary inflow, the influence of secondary inflows and littoral redistribution, and a focusing effect in the deep proximal basin. At the watershed scale, sediment yield is largely driven by intense summer rainfall and strong seasonal hydroclimatic variability. This research informs paleo‐environmental reconstruction and environmental system modelling in Arctic lake catchments.

Using 222Rn temporal and spatial distributions to estimate the groundwater discharge rate and associated nutrient fluxes into high salinity lakes in Badain Jaran Desert, Northwest China.

Groundwater is the main source of water and salt recharge for to lakes in arid regions. Quantifying the groundwater discharge and its nutrient input is important in the evolution of lake environments in the Badain Jaran Desert (BJD), Northwest China. In this study, ten BJD lakes were sampled for 222Rn in April and September 2021, and the 222Rn mass balance model was used to quantify the groundwater discharge rates and derived nutrient fluxes to these lakes. The results showed that the 222Rn activity and the groundwater recharge rate of lake water both present a positively correlated with lake water depth. The hot points of high 222Rn activity in the lake water were consistent with the locations of groundwater discharge areas. According to the 222Rn temporal and spatial distributions, the mean groundwater recharge rates for the ten lakes in April and September were 5.4 ± 0.6 and 7.7 ± 1 mm/d, respectively, and the annual mean groundwater discharge rates varied between 1.1 ± 0.2 and 14.6 ± 1.6 mm/d, with a mean of 7 ± 0.9 mm/d. Given that all the perennial lakes in the BJD have the same groundwater recharge rate as the mean recharge rate of the ten studied lakes, the annual mean groundwater recharge amount received by the lakes in the entire BJD is (5.6 ± 0.7) × 107 m3/a. According to the groundwater recharge amount, the inputs of dissolved inorganic nitrogen, dissolved inorganic phosphorus, dissolved inorganic silicon, total nitrogen, and total phosphorus to the BJD lakes from groundwater were (4.7 ± 0.6) × 105, (3.8 ± 0.5) × 104, (7.9 ± 1) × 105, (7.2 ± 0.9) × 105, (2.5 ± 0.3) × 104 kg/a, respectively. This study provides a reference for quantifying of groundwater discharge rates into salt lakes in other arid regions.

Multiple kernel fusion: A novel approach for lake water depth modeling

Multiple kernel fusion (MKF) refers to the task of combining multiple sources of information in the Hilbert space for improved performance. Very often the combined kernel is formed as a linear composition of multiple base kernels where the combination weights are learned from the data. As the first application of an MKF approach in hydrological modeling, lake water depth as one of the pivot factors in the reservoir analysis is simulated by considering different hydro-meteorological variables. The role of each individual input parameter is initially investigated by applying a kernel regression approach. We then illustrate the utility of an MKF formalism which learns kernel combination of weights to yield an optimal composition for kernel regression. A set of 40-year data collected from 27 groundwater and streamflow stations and 7 meteorological stations for precipitation and evaporation parameters in the vicinity of Lake Urmia are utilized for model development. Both visual and quantitative statistical performance criteria illustrate a superior performance for the MKF approach compared to kernel ridge regression (KRR), the support vector regression (SVR), back propagation neural network (BPNN) and auto regressive (AR) models. More specifically, while each individual input parameter fails to provide an accurate prediction for lake water depth modeling, an optimal combination of all input parameters incorporating the groundwater level, streamflow, precipitation and evaporation via a multiple kernel learning approach enhances the predictive performance of the model accuracy in the multiple scenarios. The promising results (RMSE = 0.098 m; R2 = 0.987; NSE = 0.986) may motivate the application of a MKF approach towards solving alternative and complex hydrological problems.

Simulating the water δ18O of a small open lake in the East Asian monsoon region based on hydrologic and isotope mass-balance models

Hydrologic and isotope mass-balance models (MBMs) are useful tools for the simulation and quantitative interpretation of lake water δ18O (δL). Such studies of small, open lakes are important because δL may show large responses to weather-driven hydrological variability. A δL sequence was simulated for three-year and five-day interval data from Taozi Lake, a small, open lake in Changsha, in the East Asian monsoon region of China. The MBMs performed well, with the optimal model explaining 90% of the observed δL variability. However, it was necessary to parameterize the precipitation input by increasing the lake water depth during heavy precipitation events to capture the observed sharp decreases in δL. We found that the MBMs using air temperature and the equilibrated atmospheric vapor δ18O (δA) produced a more negative δL compared to the model using the surface water temperature and the observed δA, and that the equilibrated δA was somewhat arbitrary, which introduced a large error in the model output. A sensitivity test highlighted the importance of the seasonal variability of hydrometeorological and isotopic variables to reproduce the observed δL variability. Additionally, the simulated average δL showed a similar pattern of variation to the meteorological variables shifted by different ratios, but for the relative humidity, there was only a narrow window within which a realistic δL series could be reproduced. Our results show that a realistic MBM can be established based on long-term observations, with implications for studies of hydrologic processes and paleoclimate reconstruction.

Spatial Patterns and Quantification of Lacustrine Groundwater Discharge Determined Based on 222Rn

AbstractLacustrine groundwater discharge (LGD) is of great importance to the hydrological cycle and the eco‐environment of lakes. LGD is often characterized by large spatial variability, but the spatial patterns of LGD have rarely been quantified, particularly at large whole‐lake scales. This study presents quantitative estimation of the spatial patterns of LGD in an oxbow lake in the central Yangtze River Basins by a segmented application of 222Rn mass balance model. The results show that the LGD rates in all points ranged from 10.05 to 197.25 mm/d, with an average of 61.23 mm/d. Larger LGD rates were not only occurring in the lakeshore area, but also in the lake center. The high LGD rate in the lake center area here was likely a result of a direct connection between the water‐rich confined aquifer and the lake. Sensitivity analysis of the 222Rn mass balance show that lake water 222Rn concentration, groundwater concentration, wind speed and water depth were sensitive parameters, which were important parameters in controlling the quantitative results of LGD. The average LGD rate uncertainty and percentage were 28.45 mm/d and 49.20%. This study thus provides a solution in quantifying the spatial patterns of LGD lakes.

Fast multi-output relevance vector regression for joint groundwater and lake water depth modeling

Fast multi-output relevance vector regression (FMRVR) algorithm is developed for simultaneous estimation of groundwater and lake water depth for the first time in this study. The FMRVR is a multi-output regression analysis technique which can simultaneously predict multiple outputs for a multi-dimensional input. The data used in this study is collected from 34 stations located in the lake Urmia basin over a 40-year time period. The performance of the FMRVR model is examined in contrast to the support vector regression (SVR) and multi-linear regression (MLR) benchmarks. Results reveal that FMRVR is able to generate more accurate estimation for groundwater and lake water depth with coefficient of determination (R2) of 0.856 and 0.992 and root mean square error (RMSE) of 0.857 and 0.083, respectively. The outperformance of FMRVR can be linked to its capability for a joint estimation of multiple relevant outputs by taking into account possible correlations among the outputs.

Distribution, potential sources, and response to water depth of archaeal tetraethers in Tibetan Plateau lake sediments

The Tibetan Plateau (TP) is an area of focus for assessing global change and regional responses due to its sensitivity to climate change on different timescales. Its widely distributed lakes are ideal for research. Paleo-lake-level records from this region can provide insights into potential climate connections and help predict future hydrological trends. However, the applicability of the existing archaeal tetraether-based lake-level proxies in this region remains unclear, thereby hindering the advancement of paleoclimate research in this area. Here, we investigated the archaeal ethers in 108 surface sediment samples from 83 lakes and 22 surrounding soils on the TP to explore their distribution, sources, and environmental controlling factors. The majority of archaeal tetraethers in lake sediments are produced in situ, with allochthonous origin being secondary. Nitrososphaeria (previously called Thaumarchaeota) could serve as the main biological sources in both lakes and soils, and other archaea (such as methanogenic archaea) may also contribute to those in lakes. Of the examined environmental variables, the lake water depth was the dominant factor affecting the distributions of the archaeal tetraethers in the studied lakes. The %Cren and %OH-GDGTs indices were confirmed to be potential lake-level proxies. Moreover, the Cren/Cren’ ratio may be a novel lake-level proxy due to its good response to water depth. Furthermore, %Cren, %OH-GDGTs, and the Cren/Cren’ ratio may be affected by the nutrient status and Dissolved Oxygen (DO) concentration of the lake; so, these lake-level proxies need to be used with caution in lakes with relatively high nutrient statuses. The results of this study provide a reference for improving our understanding of tetraether distribution patterns and for the reconstruction of paleo-lake levels.

Late miocene evolution of the Paleo-Danube Delta (Vienna Basin, Austria)

The first deltas of the Paleo-Danube formed around 11.5 Ma ago along the northwestern margin of the Vienna Basin, during a lowstand of Lake Pannon. We present a detailed description of the depositional architecture of five individual lobes of these deltas in the Austrian part of the central Vienna Basin based on the integration of 3D seismic surveys and well-log data, covering an area of about 600 km2. Based on geometry, steep clinoforms and the development of beach ridges, the delta is classified as mostly river-dominated with significant influence of wave-reworking processes. The development and shifts of individual lobes suggest a stepwise northward movement of the delta system, which is discussed in relation to a stepwise activity of regional fault systems. True vertical depth measurements between topset and bottomset deposits document a decrease of lake water depth from about 180 m during the early phase of delta formation at 11.5 Ma down to about 100 m during its mature phase. A major lake level rise of Lake Pannon around 11.3 Ma caused the flooding of the margins of the Vienna Basin, resulting in back stepping of fluvial deposits into the North Alpine Foreland Basin, which led to the termination of delta deposition in the study area. The Paleo-Danube delta of the Vienna Basin is comparable in many ways to the Holocene to modern Danube delta, located in the Black Sea. Size, sediment volume and speed of progradation of the lobes, however, indicate, that this primeval delta was distinctly smaller than its modern successor and had a much smaller sediment load.

Quantitative reconstruction of consecutive paleolake-level fluctuations by the groundwater recharged lake in the desert hinterland: A case study in the Badain Jaran Desert, Northwestern China

Quantitative reconstruction of consecutive paleolake-level fluctuations may help reconstruct lake evolution during the Holocene. However, the reconstruction of a groundwater recharged lake in a desert hinterland is challenging. In this study, 23 samples of lake bottom sediments were obtained from eight groundwater recharged lakes in the hinterland of the Badian Jaran Desert in northwest China to establish models between the grain size component and lake level. Our results showed that the four grain size components of the sediments could be separated using the Weibull function. The first two fine grain components (W1 and W2) were deposited in the atmospheric dust. The two coarser components (W3 and W4) could be interpreted as sediments transported by wind from the surrounding sand dunes, while W3 was subsequently redistributed by lake waves. Changes in the lake water depth could be expressed by the W1 and W2 component contents, as well as the modal size of W3. Using the above models, unmixing grain size components of the lake sediment obtained from the ZZH section located in a seasonal lake (Zhunzhahan Jaran Lake) in the desert hinterland were used to quantitatively reconstruct the lake-level fluctuations during the Holocene. The lake level frequently fluctuated between 3.82 and 9.21 m during 10.6–8.6 cal kyr BP, slightly fluctuated between 3.41 and 5.26 m during 8.6–4.7 cal kyr BP, and markedly declined from 6.09 m to 4.46 m during 4.7–3.5 cal kyr BP. Lake-level changes in the hinterland of the Badian Jaran Desert did not correspond to the effective moisture changes during the early Holocene. Instead, the rise in lake level during the early Holocene would have resulted from the input of groundwater from the meltwater in the mountains of the recharge area. The data reveal new methods for quantitatively reconstructing consecutive paleolake-level fluctuations by groundwater recharged lakes in the desert hinterland.

Distribution of antibiotics in lake water-groundwater - Sediment system in Chenhu Lake area

Antibiotics pollution in lakes has been widely reported worldwide, however rare studies were concerned about antibiotics distribution in lake water - groundwater - sediment system. Here, a total of 22 antibiotics and 4 sulfonamides metabolites were detected in lake water, sediments, and different depth of groundwater surrounding Chenhu Lake during the wet and dry seasons. N4-acetylsulfonamides (Ac-SAs), fluoroquinolones (FQs), and tetracyclines (TCs) were the main groups of antibiotics in the study area. In the whole lake environment, there were more types of antibiotics in the aquatic environments than in the sediments, and the antibiotics distribution was closely related to geographical location. Specifically, the average concentration of antibiotics in groundwater decreased with an increase in sampling site distance from the lake. All antibiotics, except oxytetracycline (OTC), showed a significant decline during the dry season that could be due to the implementation of lake conservation policies, which significantly helped reducing lake pollution. There were obvious differences in the distribution of antibiotics in distinct sedimentary environments. In the surface sediments, the antibiotics content in the reclamation and the perennially flooded areas was higher than in the lakeshore area. The hydraulic interactions in the perennial flooded area facilitated the deep migration of antibiotics into lake sediments. Correlation analysis revealed a good relevance between the distribution of antibiotics in lake water and groundwater. Redundancy analysis shows that dissolved oxygen and temperature were the main factors affecting the distribution of antibiotics.

Ecosystem functioning is linked to microbial evenness and community composition along depth gradient in a semiarid lake

Lake level or water depth are key physical variables known to respond dramatically to climate change, especially in arid regions, and their fluctuations exert substantial influences on lake biodiversity and ecosystem functioning. However, it is unclear how multiple ecosystem functions (i.e., ecosystem multifunctionality, EMF) respond to changes in water depth and how aquatic community attributes, such as species richness, evenness and community compositions, are linked to EMF along water depth gradients. Lake Hulun, a representative of semiarid-region lake in China, has experienced serious lake area shrinkage over the past 20 years. Here, we explored the water-depth patterns of three microbial taxonomic groups of bacteria, archaea and fungi and nine ecosystem functions related to nutrient cycling in Lake Hulun. We further examined the relative importance of different community attributes on EMF variations. We found that the community compositions of bacteria, archaea and fungi showed consistent water-depth decay patterns, and EMF and most individual ecosystem functions involved in C, N, P and S cycling increased with water depth. Further, EMF was predominantly mediated by microbial evenness and community composition, but not species richness, as predicted by the traditional theory of biodiversity-ecosystem functioning relationships. In addition, water depth indirectly affected the relationships between the microbial community and EMF via sediment nutrient contents. These findings indicate that the water depth changes under climate change could substantially alter ecosystem structure and functioning in arid regions. We further emphasize the necessity of including multiple community attributes in biodiversity-EMF relationship research to clarify the biotic and abiotic forces underlying EMF variations.