Lake Level Research Articles

Forecasting Lake Nokoué Water Levels Using Long Short-Term Memory Network

The forecasting of hydrological flows (rainfall depth or rainfall discharge) is becoming increasingly important in the management of hydrological risks such as floods. In this study, the Long Short-Term Memory (LSTM) network, a state-of-the-art algorithm dedicated to time series, is applied to predict the daily water level of Lake Nokoué in Benin. This paper aims to provide an effective and reliable method to enable the reproduction of the future daily water level of Lake Nokoué, which is influenced by a combination of two phenomena: rainfall and river flow (runoff from the Ouémé River, the Sô River, the Porto-Novo lagoon, and the Atlantic Ocean). Performance analysis based on the forecasting horizon indicates that LSTM can predict the water level of Lake Nokoué up to a forecast horizon of t + 10 days. Performance metrics such as Root Mean Square Error (RMSE), coefficient of correlation (R2), Nash–Sutcliffe Efficiency (NSE), and Mean Absolute Error (MAE) agree on a forecast horizon of up to t + 3 days. The values of these metrics remain stable for forecast horizons of t + 1 day, t + 2 days, and t + 3 days. The values of R2 and NSE are greater than 0.97 during the training and testing phases in the Lake Nokoué basin. Based on the evaluation indices used to assess the model’s performance for the appropriate forecast horizon of water level in the Lake Nokoué basin, the forecast horizon of t + 3 days is chosen for predicting future daily water levels.

A 14,000‐Year Sediment Record of Mercury Accumulation and Isotopic Signatures From Lake Malaya Chabyda (Siberia)

AbstractEurasian permafrost soils contain large amounts of organic carbon (OC) and mercury (Hg), sequestered by vegetation during past and present interglacial periods. Lake sediment archives may help understand past OC and Hg dynamics and how they interact with climate‐related variables. We investigated Hg accumulation, OC dynamics, and Hg and OC stable isotopes in a 14,000‐year sediment record from Lake Malaya Chabyda (Central Yakutia, Russia). Sediment Hg was correlated to OC (p value < 0.01), with lower OC and Hg accumulation rates (OCAR, HgAR) during the cold Younger Dryas (YD, 12,900–11,700 cal BP), when the lake level was low. Elevated sediment Δ200Hg (0.05‰ ± 0.11‰), representing dominant HgII deposition, and low δ13C, indicates low lake primary productivity during the YD. During the early Holocene, Δ200Hg and Δ199Hg decreased, while δ13C, δ202Hg, OCAR, and HgAR increased, suggesting enhanced algal primary productivity in deeper, more turbid waters. From 4,100 cal BP to present, Hg/OC ratios and HgAR increased at constant OCAR, indicating an additional Hg source to the lake. Analysis of Hg isotopes suggests direct Hg0 uptake into lake waters, potentially driven by primary production and efficient Hg burial. Our observations suggest that the gradual climate warming since the Last Glacial Termination and into the early Holocene led to enhanced OC and Hg burial in northern lakes and watersheds. Late Holocene enhanced Hg burial, but not OC, is possibly related to a renewed increase in lake primary productivity. Continued global warming may lead to further Hg sequestration in northern aquatic ecosystems.

Vegetation, temperature, and Indian Summer Monsoon evolution over the past 4400 years revealed by a pollen record from Drigo Co on the southern Qinghai-Tibet Plateau

Understanding the changes in temperature and precipitation on the southern Qinghai-Tibet Plateau (QTP), which is influenced by the Indian Summer Monsoon (ISM), is crucial for predicting possible future changes in the regional ecological environment under ongoing climate change. However, due to the lack of well-dated, high-resolution paleoclimate records, the trends of temperature and ISM precipitation on the southern QTP since the mid-Holocene are poorly understood. We present a high-resolution pollen record from Dirgo Co, on the southern QTP, spanning the past 4400 years. The decrease in the pollen ratio of Artemisia to Cyperaceae (A/Cy) indicates a downward shift of altitudinal vegetation belts in the Drigo Co area over the past 4400 years, suggesting falling temperatures; and decreases in tree pollen percentages indicate the gradual weakening of the ISM. Our pollen record also indicates five cold phases with the near-simultaneous weakening of the monsoon, during: 4300–4100 cal yr BP, 3600–3400 cal yr BP, 2800–2600 cal yr BP, 1600–1400 cal yr BP, and 700–100 cal yr BP, and these climate anomalies were also recorded elsewhere on the QTP. We suggest that the changes in temperature and ISM intensity on the southern QTP over the past 4400 years were modulated by changes in summer insolation and solar activity. These changes affected the sea surface temperature (SST) over the tropical Pacific and Indian Ocean regions, and they were linked to a positive phase of the El Niño/Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), which weakened the ISM intensity in the Drigo Co area. Additionally, due to increased evaporation related to high temperatures, combined with intensified grazing activities over the past ∼200 years, the lake level has fallen, and the vegetation cover has decreased. As global temperatures continue to rise, the alpine steppe in the Drigo Co area may increase and the vegetation density may gradually decrease, and at the same time the regional ecological environment may gradually deteriorate.

Risk assessment of a glacial lake with abruptly slowing expansion, Jiongpu, Southeastern Tibet

The expansion of potentially hazardous glacial lakes is a symptom of global warming during this interglacial period. A pertinent example is the Jiongpu glacial lake in southeastern Tibet, the area of which has expanded approximately fivefold in the last half-century. However, recently, the glacier tongue has retreated to a high steep slope, and the rate of retreat of the glacier and expansion of the lake have temporarily slowed. The risk of a glacier tongue landslide after glacier detachment and subsequent glacial lake outburst flood (GLOF) needs to be assessed. In this study, we employed a combination of unmanned aerial vehicle (UAV), sonar, geological radar, remote sensing, field investigation, sampling, drilling, and dating techniques to determine the critical parameters of potential GLOFs, including glacier tongue geometry, lake bathymetry, and moraine dam geometry and composition. Utilizing empirical models and multiphase flow models, we identified the most hazardous triggers and simulated the processes of a glacier tongue landslide into the lake, moraine dam overtopping by a displacement wave, and subsequent flood evolution. The results showed that the most hazardous trigger in volume is a glacier tongue landslide, accounting for 58.29 % of all triggers associated with potential GLOFs. Lapped by the largest glacier tongue landslide impulse wave, the moraine dam would not fail because the minimum safety factor is approximately 1.66 ± 0.7 according to empirical methods and geological slope simulation. However, overtopping would occur, resulting in a peak discharge of approximately 9740 ± 4137 m3/s at the moraine dam based on r.avaflow calculations. The flood would reach the densely populated Jinling township and inundate approximately 46 ± 4.55 % of the houses according to HEC-RAS. Reducing the water level of the glacial lake represents an effective strategy for mitigating potential losses. This concise, physics-based method effectively assesses GLOF triggers and processes and can be applied to risk assessments of other expanding glacial lakes.

Paleoenvironmental reconstruction of Lake Van and Lake Erçek over the last millennium using varved sediments (Eastern Türkiye)

Detailed lithological and geochemical studies of the bottom sediments were conducted based on the original sampling of brackish adjacent lakes: Lake Van and Lake Erçek in Eastern Anatolia, Türkiye. Seasonal variations in the accumulation of weather-driven element content were determined using high-resolution Synchrotron Radiation X-Ray Fluorescence (SR-XRF) analysis of the annual layers in the solid prepare. The results were utilized to approximate the regional paleo-temperature of both lakes and the water level of Lake Van. Visual counting of the varve as well as annual oscillation of measured geochemical series was employed to create a time scale. The element content series were synchronized with recent changes in external climatic environments and lake water level fluctuations. Subsequently, the geochemical series were transformed into climate units, using calibration on synchronous meteorological data. Finally, the original quantitative reconstruction of the regional climate variations was performed over the last millennium period with annual time resolution; for Lake Erçek (840 years ago) and Lake Van (1300 years ago). It was revealed that the sediments of these adjacent lakes (Lake Van and Lake Erçek), located 30 km apart from each other, provided synchronous responses to regional environmental changes, which confirmed the reliability of the reconstructions.

A Fuller Great Salt Lake Would Likely Narrow an Environmental Health Gap

Pacific Islander and Hispanic residents of Salt Lake City would benefit most from higher lake levels and reduced dust pollution.

Considerations in designing climate change assessments for complex, non-linear hydrological systems

Bias correction of climate model simulations is vital to allow climate change impacts to be assessed for water resources systems. However, there has been limited research to date on the implications of system non-linearity on bias correction approaches. Here we bias correct regional climate model simulations of precipitation and evapotranspiration and use the output to force hydrological and water balance models of five small, interconnected lakes located south west of Sydney. We show that substantial, non-linear storage within the lakes amplifies biases that are not evident when the climate forcing or even the hydrological model simulations are evaluated using daily distributions of the climate variables and streamflow.The non-linearity in the stage-storage relationships of the lakes means that each lake responds differently to the same climate forcings. For example, ensemble mean projections for one lake suggest increases in water level across the full distribution of lake levels, whilst other lakes are projected to have decreasing water levels up to the median of the distribution, but increases during wetter conditions. These differences are explained by the varying influence of potential evapotranspiration increases depending on the surface area of the lakes at different depths. Using bottom up climate change assessments, we further explore these non-linear responses of the lakes to different climate forcings. We show that bottom up climate change assessments can provide information on the relative role of potential evapotranspiration changes compared to precipitation changes, providing more guidance to ecosystem managers than just using bias corrected climate model simulations alone. The paper discusses opportunities for future work to improve representation of climate attributes important for storage dominated water resource and natural ecosystems

Hydroformer: Frequency Domain Enhanced Multi‐Attention Transformer for Monthly Lake Level Reconstruction With Low Data Input Requirements

AbstractLake level changes are critical indicators of hydrological balance and climate change, yet long‐term monthly lake level reconstruction is challenging with incomplete or short‐term data. Data‐driven models, while promising, struggle with nonstationary lake level changes and complex dependencies on meteorological factors, limiting their applicability. Here, we introduce the Hydroformer, a frequency domain enhanced multi‐attention Transformer model designed for monthly lake level reconstruction, utilizing reanalysis data. This model features two innovative mechanisms: (a) Frequency‐Enhanced Attention (FEA) for capturing long‐term temporal dependence, and (b) Causality‐based Cross‐dimensional Attention (CCA) to elucidate how specific meteorological factors influence lake level. Seasonal and trend patterns of catchment meteorological factors and lake level are initially identified by a time series decomposition block, then independently learned and refined within the model. Tested across 50 lakes globally, the Hydroformer excelled in reconstruction periods ranging from half to three times the training‐test length. The model exhibited good performance even when training data missing rates were below 50%, particularly in lakes with significant seasonal fluctuations. The Hydroformer demonstrated robust generalization across lakes of varying sizes, from 10.11 to 18,135 km2, with median values for R2, MAE, MSE, and RMSE at 0.813, 0.313, 0.215, and 0.4, respectively. Furthermore, the Hydroformer outperformed data‐driven models, improving MSE by 29.2% and MAE by 24.4% compared to the next best model, the FEDformer. Our method proposes a novel approach for reconstructing long‐term water level changes and managing lake resources under climate change.

How marine incursions affect the sedimentary environment and the quality of source rocks in the Upper Cretaceous Songliao Basin, NE China

The linkage between marine incursions and lacustrine petroleum source rock deposition has been studied worldwide. A variety of interpretations have been suggested to explain the influence of marine incursions on the quality of source rocks in the Upper Cretaceous Qingshankou Formation (K2qn), Songliao Basin. In this study, high-resolution of geochemical and sedimentary results of two drilled wells from the K2qn were presented to improve the understanding on this issue. 117 samples from Well GY8HC of the Qijia-Gulong Sag (brief as Gulong Sag) and 251 samples from Well ZY1 of the Sanzhao Sag, the Central Depression of the basin were analyzed to establish the evolution of paleoenvironment and the influence of marine incursions on organic matter enrichment in the two sags. All the evidence suggests that marine incursions have a positive effect on the quality of member 1 of the K2qn source rocks (K2qn1) in the Sanzhao Sag, which was probably due to the rising lake level and increasing salinity of the watermasses. The enhanced salinities could have inhibited lake overturn and oxygenation of bottom water, and thus created a favorable condition for the preservation of organic matter. In contrast, the K2qn1 source rock in the Gulong Sag was less affected by marine incursions, which is likely due to the Daqing placanticline blocking two sags. The lake water in the Gulong Sag was characterized as fresh-brackish with less mixing of seawater. Petrographic observation suggests that organic matter in the Gulong source rocks was mainly derived from lacustrine algal and microsporinite. This research provides novel insights into the linkage between marine incursions and the depositional environment during the formation of K2qn1 in the Songliao Basin.

Active remote sensing data and dispersal processes improve predictions for an invasive aquatic plant during a climatic extreme in Great Lakes coastal wetlands

Invasive aquatic plants pose a significant threat to coastal wetlands. Predicting suitable habitat for invasive aquatic plants in uninvaded yet vulnerable wetlands remains a critical task to prevent further harm to these ecosystems. The integration of remote sensing and geospatial data into species distribution models (SDMs) can help predict where new invasions are likely to occur by generating spatial outputs of habitat suitability. The objective of this study was to assess the efficacy of utilizing active remote sensing datasets (synthetic aperture radar (SAR) and light detection and ranging (LiDAR) with multispectral imagery and other geospatial data in predicting the potential distribution of an invasive aquatic plant based on its biophysical habitat requirements and dispersal dynamics. We also considered a climatic extreme (lake water levels) during the study period to investigate how these predictions may change between years. We compiled a time series of 1628 field records on the occurrence of Hydrocharis morsus-ranae (European frogbit; EFB) with nine remote sensing and geospatial layers as predictors to train and assess the predictive capacity of random forest models to generate habitat suitability in Great Lakes coastal wetlands in northern Michigan, USA. We found that SAR and LiDAR data were useful as proxies for key biophysical characteristics of EFB habitat (emergent vegetation and water depth), and that a vegetation index calculated from spectral imagery was one of the most important predictors of EFB occurrence. Our SDM using all predictors yielded the highest mean overall accuracy of 88.3% and a true skill statistic of 75.7%. Two of the most important predictors of EFB occurrence were dispersal-related: 1) distance to the nearest known EFB population (m), and 2) distance to nearest public boat launch (m). The area of highly suitable habitat (pixels assigned ≥0.8 probability) was 74% larger during a climatically extreme high water-level year compared to an average year. Our findings demonstrate that active remote sensing can be integrated into SDM workflows as proxies for important drivers of invasive species expansion that are difficult to measure in other ways. Moreover, the importance of a proxy variable for endogenous dispersal (distance to nearest known population) in these SDMs indicates that EFB is currently spreading, and thereby less influenced by within-site dynamics such as interspecific competition. Lastly, we found that extreme climatic conditions can dramatically change this species’ niche, and therefore we recommend that future studies include dynamic climate conditions in SDMs to more accurately forecast the spread during early invasion stages.

Health Risk of Heavy Metals in Drinking Water Sources of Water-Carrying Lakes Affected by Retreating Polder: A Case Study of Luoma Lake

Heavy metal pollution is a critical issue affecting the safety of drinking water sources. However, the impact of human activities on heavy metal risk levels in water-carrying lakes remains unclear. This study aims to explore the risk mechanisms of heavy metals in Luoma Lake, an important water-carrying lake for the South-to-North Water Diversion Project. We explored the spatial and temporal differences in the distribution of heavy metals in Lake Luoma using methods such as the heavy metal pollution index (HPI) and assessed the risk variations using a health assessment model. The results indicated that heavy metal concentrations in water-carrying lakes generally decreased during the dry season, with Mn and Zn levels decreasing by 89.3% and 56.2%, respectively. The comprehensive score of HPI decreased by 13.16% following the retreating polder compared to the control area (Non-retreating polder area). Furthermore, the HPI at the drinking water intake was lower, which is closely associated with the elevated dissolved oxygen (DO) and oxidation–reduction potential (ORP) resulting from water diversion. The annual average health risk across the entire lake was not significant, with higher levels observed in the control area. The annual non-carcinogenic risk levels of Mn, Ni, Cu, Zn, and Pb range from 10−13 to 10−9, which are considered negligible risk levels. Notably, the carcinogenic risk posed by arsenic (As) through the drinking pathway reached 10−5 a−1, exceeding the maximum levels recommended by certain organizations. These findings provide a critical foundation for managing heavy metals in water-carrying drinking water sources.

Outburst floods and their impact on Chinese Neolithic cultures during the 4.2 ka BP event: Evidence from Dayeze Lake in the lower reaches of the Yellow River

Abrupt climate fluctuations between 4.2 and 3.5 ka BP, and in particular the 4.2 ka BP event, exerted a profound impact on the global ancient civilizations. However, hydroclimatic conditions within the Asian Summer Monsoon (ASM) regions during this event remain uncertain. Here we report a multi-proxy analysis of a sediment core obtained from Dayeze Lake in the lower reaches of the Yellow River in monsoonal China, to elucidate the hydroclimatic variabilities over the past 4.2 ka. Core intervals (4.2–3.5, 1.1–0.6 cal ka BP) containing high levels of sand fraction, low-frequency magnetic susceptibility and zirconium, and low levels of organic matter and calcium oxide, reflect outburst floods from the Yellow River. This is supported by the widespread fluvial deposits and slackwater deposits preserved in archaeological sites and loess-paleosol profiles from the middle and lower reaches of the Yellow River. In contrast, various climate records, such as lake level, pollen, and tree ring data, from the marginal regions of the ASM reflect widespread droughts during the same time period. This finding highlights the significant spatial heterogeneity of hydroclimate within ASM regions associated with the 4.2 ka BP event, which may be related to migrations of the monsoonal rain belt and the West Pacific subtropical high, as well as frequent El Niño–Southern Oscillation events. Referring to archaeological data, we conclude that the decline and collapse of Chinese Neolithic cultures were related to a pattern of droughts in the marginal regions of the ASM and floods in the middle and lower reaches of the Yellow River.

A hybrid data-driven approach to analyze the drivers of lake level dynamics

A hybrid data-driven approach to analyze the drivers of lake level dynamics

Causes and consequences of natural and anthropogenically induced late Holocene hydrological variations on the largest freshwater system in the Lesser Caucasus (Lake Sevan, Armenia)

Although Lake Sevan is the largest freshwater reservoir in the Caucasus, no paleohydrological or paleoenvironmental investigations have been carried out on profundal sediments so far. Here we present high-resolution sedimentological results from a 141 cm-long sediment core covering the past 4870+190/-245 cal a BP. The chronology is based on a combination of 137Cs/210Pb and radiocarbon dating supported by paleomagnetic secular variation stratigraphy, providing new inclination and declination data for the Caucasus. The time frame covered by this sequence is characterized by a long-term lake level rising trend superimposed by smaller-scale hydrological variations which is in agreement with the rest of the Lake Sevan basin. In the presented sedimentary sequence, the superimposed hydrological variations seem to be coherent with the Hallstatt and Eddy cycles.A distinct shift towards wetter conditions is observed between 2500 and 2000 cal a BP resulting in a very high lake level. An artificial lake level drop of about 20 m in the 20th century led to anoxic conditions similar to the ones during a low lake level at 4870+190/-245 cal a BP. This study shows that under natural conditions Lake Sevan was able to recover from this oxygen deficit when the lake level increased, implying that this would also happen to the artificially lowered lake today if the lake level were raised.

Mobilization of phosphorus in sediments of eutrophic lakes induced by elevated sulfate levels

Elevated sulfate levels in eutrophic lakes have been observed to induce the release of endogenous phosphorus. While previous studies have predominantly examined its impact on iron-bound phosphorus (FeP), the influence on organic phosphorus (OP), a crucial active phosphorus component in sediments, remains poorly understood. In this study, mesocosms were established with lactate supplementation and varying sulfate concentrations to explore sulfate reduction and its impacts on phosphorus mobilization in freshwater sediments. Lactate addition induced hypoxia and provided substrates, thereby stimulating sulfate reduction with a decline of sulfate levels, an increase of sulfide concentrations, and fluctuations of sulfate-reducing bacteria. Meanwhile, concentrations of total dissolved phosphorus and phosphate were dramatically promoted during lactate decomposition, with a higher sulfate concentration associated with greater phosphorus elevation, correlating with the decrease of total phosphorus in sediment. The increase in phosphorus of the overlying water was partly attributed to FeP release from the sediment, confirmed by a decrease in its sediment content. FeP release was ascribed to dissimilatory reduction of iron oxides or chemical reduction mediated by sulfides in anoxic sediments, leading to the desorption and subsequent release of phosphorus. Evidences included the proliferation of iron-reducing bacteria, a decrease in Fe(II) concentrations in sediment pore- water, and the continuous accumulation of solid iron sulfides in surface sediments. Furthermore, OP mineralization in sediment also contributed to the increase in phosphorus in water columns, confirmed by a reduction in its content and the abundance of fermentation bacteria in surface sediment. Notably, the decrease in OP content accounted for >80 % of the total phosphorus reduction in surface sediment in the end. Thus, sulfur cycling plays a critical role in iron and phosphorus cycling, significantly stimulating not only the mobilization of FeP but also OP in sediments, with OP mineralization potentially being the primary contributor to endogenous phosphorus release.

Invasive-Weed-Optimization-Based Extreme Learning Machine for Prediction of Lake Water Level Using Major Atmospheric–Oceanic Climate Scenarios

Fresh water lakes are vulnerable assets that need to be protected against manmade/natural challenges like climate change and anthropogenesis activities. This study addresses the predictability of the lake water level changes based on the knowledge acquired directly from the climate data. Two fresh water lakes named Lake Iznik and Uluabat, located in Turkey, are addressed. Time series of the lake water levels during October 1990–September 2019 at a monthly scale, along with the corresponding anomalies of 24 Large-Scale Atmospheric–Oceanic Oscillations (LSAOOs) from around the globe, are used in the analysis. The relationship between variables and the structure of the models are initially acquired based on the significance of the dependence between climate indices and lake water levels with consideration of the significance of the Spearman rank-order coefficient. Then, the time series are divided into training (80%) and testing (20%) sets. The Extreme Learning Method (ELM), enhanced with the genetic algorithm (ELM-GA) and Invasive Weed Optimization (ELM-IWO), is then used in the predictive models. Based on the results, Lake Uluabat showed a stronger teleconnection with LSAOOs, while the ELM-GA for Lake Iznik and ELM-IWA for Lake Uluabat depicted the best performance in the prediction of lake water levels. Comparison of the enhanced ELM-IWO to the corresponding ELM-GA illustrates that the ELM-IWO reveals more acceptable results owing to its flexible nature.

A sedimentary DNA perspective about the influence of environmental and food‐web changes on the microbial eukaryotic community of Lake Biwa

Abstract The impacts of environmental change on Lake Biwa have been explored for decades, with water monitoring and palaeolimnological studies revealing how environmental forcing, including climate warming, eutrophication, water level manipulation and human manipulation of fish populations, has influenced the food web of Lake Biwa. However, these studies have rarely accounted for microbial food‐web components. This knowledge gap is mostly due to the lack of time series spanning more than a couple of decades, coupled with the high taxonomical expertise required to identify organisms belonging to very diverse groups. The use of a sedimentary DNA approach allows for the reconstruction of past changes in the diversity, composition and structure of the microbial eukaryotic community of aquatic systems. The application of 18S metabarcoding has been proven successful to describe the response of unicellular eukaryotes (protists) and aquatic fungi in lake ecosystems, encompassing a large taxonomic and functional diversity such as phototrophs, heterotrophs and mixotrophs. We applied 18S metabarcoding to 31 sediment core samples from Lake Biwa, spanning the past 100 years and explored the response of microbial eukaryotic communities to changes in multiple environmental stressors, including nutrient levels, lake water level, climate, as well as fish and zooplankton biomass for the period 1973–2010. We found that the manipulation of the water level and changes in fish community composition were the primary factors impacting (indirectly) the structure of the lake microbial eukaryotic community with minor, but significant, effects of climate warming and phosphorus levels. Co‐occurrence network analysis highlighted the potential food web impacts on the microbial eukaryotic community, suggesting that organisms from this compartment were impacted by both bottom‐up and top‐down processes.

Soil Genesis of Alluvial Parent Material in the Qinghai Lake Basin (NE Qinghai–Tibet Plateau) Revealed Using Optically Stimulated Luminescence Dating

Alluvial parent material soil is an important soil type found on the Qinghai–Tibet Plateau (QTP) in China. However, due to the limited age data for alluvial soils, the relationship between alluvial geomorphological processes and soil pedogenic processes remains unclear. In this study, three representative alluvial parent material profiles on the Buha River alluvial plain in the Qinghai Lake Basin, northeast QTP, were analyzed using the optical luminescence (OSL) dating method. Combined with physical and chemical analyses of the soil, we further analyzed the pedogenic process of alluvial soil. The alluvial parent material of the Buha alluvial plain predominately yielded ages between 11.9 and 9.1 ka, indicating that the alluvial soil began to form during the early Holocene. The development of the alluvial soil on the first-order terrace presents characteristics of entisol with multiple burial episodes, mainly between 8.5 and 4.0 ka, responding to the warm and humid middle Holocene and high lake levels.

Evolution and morphological diversity of the genus Diploneis (Bacillariophyta) in Lake Malawi, with description of six new species

ABSTRACT Lake Malawi, one of the world’s oldest and most important freshwater systems, harbours a remarkable biotic diversity partly due to variable fluctuations in climate and lake level. Over time, these fluctuations have contributed to the emergence and development of different ecological niches and microhabitats that have facilitated diversification within the lake. Despite our extensive knowledge of different animal groups, the evolutionary history of species-rich diatom groups in Africa and, particularly, in Lake Malawi has yet to be studied. Here, we used a combination of morphological, molecular, and paleontological data to assess the species richness and evolutionary processes of the diatom genus Diploneis in this lake. The comprehensive dataset revealed four putative new endemic species from modern and two apparently extinct Diploneis species from the fossil record of the lake, described here as new to science. Morphological analyses showed that all these new species exhibit remarkable differences and unique morphological patterns that were recently discovered in Diploneis species from nearby Lake Tanganyika. Molecular phylogenetic analyses revealed that the four new species now living in Lake Malawi are nested within a clade of Lake Tanganyika Diploneis species but do not form a monophyletic group. This suggests that the new Lake Malawi Diploneis species are derived from one or more Tanganyikan ancestors and that more than one colonization event probably occurred. However, further analyses are needed to elucidate their origin.

Attribution of hydrological droughts in large river-connected lakes: Insights from an explainable machine learning model

Large lakes play an important role in water resource supply, regional climate regulation, and ecosystem support, but they face threats from frequent extreme drought events, necessitating an understanding of the mechanisms behind these events. In this study, we developed an explainable machine learning (ML) model that combines the Bayesian optimized (BO) long short-term memory (LSTM) model and the integrated gradients (IG) interpretation method to simulate and explain lake water level variations. In addition, the hydrological drought trends and extreme drought events in Poyang Lake from 1960 to 2022 were identified using the standardized water level index (SWI) and run theory. The analysis revealed that the frequency of hydrological droughts in Poyang Lake increased from 1960 to 2022, especially in the autumn after 2003. By selecting the flows of the catchment and the Yangtze River as the input features, the BO-LSTM model accurately predicted the water level of Poyang Lake. The IG method was then used to interpret the prediction results from three aspects: the importance ranking of the input features, their roles in the seasonal drought trends, and their roles in extreme drought events. The results indicate that (1) the most influential factor affecting the water level of Poyang Lake was the inflow of the Ganjiang River in the catchment. (2) The increase in the lake outflow caused by the Yangtze River's draining effect was the reason for the intensification of the autumn drought in Poyang Lake. (3) The extreme hydrological drought events were primarily caused by low catchment inflows. Overall, this research provides a new approach that balances prediction accuracy with interpretability for predicting and understanding the hydrological processes in large river-connected lakes. Moreover, this method was also applied to the attribution analysis of hydrological drought in Poyang Lake, providing theoretical support for regional water resource management.