Lake Water Level Research Articles

Daily water‐level forecasting for multiple polish lakes using multiple data‐driven models

AbstractWater level in lakes fluctuates frequently due to the impact of natural and anthropogenic forcing. Frequent fluctuations of water level will impact lake ecosystems, and it is thus of great significance to have a good knowledge of water‐level dynamics in lakes. However, forecasting daily water‐level fluctuation in lake systems remains a tough task due to its non‐linearity and complexity. In this study, two deep data‐driven models, including gated recurrent unit (GRU) and long short‐term memory (LSTM), were coupled with attention mechanism for the forecasting of daily water level in lakes for the first time. Daily water‐level times series in five lowland lakes in Poland were used to evaluate the models. Root mean squared error (RMSE) and mean average error (MAE) were used for the evaluation of model performance. The modelling results were compared with the traditional feed‐forward neural networks (FFNN), GRU, LSTM, and zero‐order forecast. The modelling results showed that sequential deep learning models do not outperform feed‐forward models in all cases. In most cases, LSTM with attention mechanism (average RMSE = 0.88 cm, average MAE = 0.69 cm) outperforms GRU with attention mechanism (average RMSE = 1.00 cm, average MAE = 0.81 cm). However, attention mechanism did not help to improve the accuracy of the GRU and LSTM for most cases. Based on the average performance in different lakes, GRU performs the best among the deep learning models (average RMSE = 0.84 cm, average MAE = 0.66 cm). Zero‐order forecast models perform better than deep learning models for predicting tomorrow (average RMSE = 0.71 cm, average MAE = 0.39 cm), while deep learning models perform better as the horizon of prediction increases.

Conceptual hydrological model-guided SVR approach for monthly lake level reconstruction in the Tibetan Plateau

Study regionTibetan Plateau (TP) Study focusLakes in the TP that are subject to low human activity serve as an important indicator for quantitative assessment of regional climate change. However, previous studies have mainly focused on annual changes in lake area, level, and storage because of limited monitoring stations, and long-term lake level reconstruction at monthly resolution remains challenging. We propose a conceptual hydrological model-guided monthly lake level reconstruction (WBM-SVR) approach that incorporates water balance models (WBMs) and support vector regression (SVR), to improve the training and testing sets compared with SVR alone through consideration of the hydrological process. The WBM-SVR approach integrates WBMs to select input factors, sub-process control equations to quantify the contributions of input factors, empirical parameters to characterize catchment uniqueness, and SVR for water level modelling. New hydrological insights for the regionPhysically guided WBM-SVR is more accurate than SVR in reconstructing monthly lake water levels. WBMs can quantify the hydrological process in the lake catchment area with efficient quasi-physical mechanisms and refine the input–output factors within lake hydrometeorology. The reconstructability, generalization capability, and transferability of WBM-SVR are validated for three different types of lakes (glacier-free inflow lake, glacier-free outflow lake, and glacier-fed inflow lake), and the reconstruction results indicate significant improvements in WBM-SVR compared with SVR. The WBM-SVR approach shows great promise for achieving monthly lake level reconstruction.

Prediction of lake water-level fluctuations using adaptive neuro-fuzzy inference system hybridized with metaheuristic optimization algorithms

Lakes help increase the sustainability of the natural environment and decrease food chain risk, agriculture, ecosystem services, and leisure recreational activities locally and globally. Reliable simulation of monthly lake water levels is still an ongoing demand for multiple environmental and hydro-informatics engineering applications. The current research aims to utilize newly developed hybrid data-intelligence models based on the ensemble adaptive neuro-fuzzy inference system (ANFIS) coupled with metaheuristics algorithms for lake water-level simulation by considering the effect of seasonality on Titicaca Lake water-level fluctuations. The classical ANFIS model was trained using three metaheuristics nature-inspired optimization algorithms, including the genetic algorithm (ANFIS-GA), particle swarm optimizer (ANFIS-PSO), and whale optimization algorithm (ANFIS-WOA). For determining the best set of the input variables, an evolutionary approach based on several lag months has been utilized prior to the lake water-level simulation process using the hybrid models. The proposed hybrid models were investigated for accurately simulating the monthly water levels at Titicaca Lake. The ANFIS-WOA model exhibited the best prediction performance for lake water-level pattern measurement in this study. For the best scenario (the inputs were {X}_{t-1},; {X}_{t-2}, ;{X}_{t-3}, ;{X}_{t-4}, ; {X}_{t-12}) the ANFIS-WOA model attained root mean square error (RMSE approx 0.08 m), mean absolute error (MAE approx 0.06 m), and coefficient of determination (R2approx 0.96). Also, the results showed that long-term seasonal memory for this lake is suitable input for lake water-level models so that the long-term dynamic memory of 1-year time series for lake water-level data is the best input for estimating the water level of Titicaca Lake.

Impact of overgrazing and climate change on the lake ecosystem in arid region

Mongolia's geographical location, extreme climate, fragile ecosystems, agricultural dependence on climate requires adaptation to global climate change and smart usage of natural resources. The water level of most lakes in Mongolia had been steadily increasing from mid-1960s to 1995 and declining from 1996. The purpose of this study is to determine current condition by each ecosystem compartment in and around the Lake Duruutsagaan and to define cause of the lake shrinking and deterioration of ecosystem. The Lake Duruutsagaan ecosystem study was carried out in the following natural elements: climate, hydrology, hydrobiology, forest, soil, pasture, plant species composition, and animals. The lake surface area was slightly decreased by 24.21% from 10.02 km2 in 2003 to 7.59 km2 in 2017. The lake water is highly mineralized, probably due to increases of evaporation of water. Also elevated concentrations of some chemical elements are detected in the lake water, including Phosphorus (22.6 mg L-1) and Arsenic (198 mg L-1). The high concentration of these two elements shown different kind of pollution existed in the lake. Probably, arsenic content in lake water is related to the geological composition of surrounding area, but elevated concentration of P can be attributed to the nutrient pollution due to soil erosion in surrounding area of lake. Species diversity in this lake is limited and only a few species of crustaceans that can tolerate under high salinity and polluted condition are present. All of soil samples have a low content of clay particles (between 2.6-8.5%). According to the soil samples data, pasture land in study area is moderately 80.95%, strongly 7.04% deteriorated due to direct and indirect effects of overgrazing. Especially, natural regeneration is not observed in the forest area. According to the study results, current condition of Lake Duruutsagaan and its surrounding area is indicating the need for some protection and restoration management.

Dry-Season Water Level Shift Induced by Channel Change of the River–Lake System in China’s Largest Freshwater Lake, Poyang Lake

As a large open lake that connects to the middle reaches of Yangtze River, Poyang Lake, China, has experienced dramatic water level changes, especially during the dry periods (November–March) in recent years. For better understanding the shift of dry-season lake level, we quantified the variations induced by channel changes of the river–lake system (CCORLS). Attempts were achieved through establishing two Long Short-Term Memory (LSTM) based water level prediction models, combined hydrological data in the periods of 1956–2000 and 2006–2016. The results indicated that: (1) With reference to earlier (1956–2000) dry periods, the recent (2006–2016) mean water levels had an overall decreasing trend, with values of 0.04–1.26 m across the lake. (2) The response of water level to CCORLS was spatially heterogeneous, triggering a sharp reduction in the central to northern lake, an obvious reduction in the lake outlet, and a relatively smaller reduction in the southern lake. (3) The bottom topography alteration of Poyang Lake made a dominating contribution to decline the lake water levels, while the Yangtze River’s mainstream channel near the lake played a minor role in the decrease of water level. Results shed light on the impact of systematic watercourse changes on the water level of a lake connected a river and enhanced understanding of the characteristics and mechanisms behind the hydrological changes of large freshwater lakes.

A multi-proxy record of palaeoenvironmental and palaeoclimatic conditions during Plio-Pleistocene peat accumulation in the eastern flank of the Isparta Angle: A case study from the Şarkikaraağaç coalfield (Isparta, SW Central Anatolia)

The Şarkikaraağaç coalfield is located in the north-western part of the Lake Beyşehir Basin, which is the most significant graben area in the eastern flank of Isparta Angle, and hosts a 300-Mt coal resource. This study focuses on the first palaeoenvironmental and palaeoclimatic reconstruction of Pliocene and early Pleistocene coal-bearing sequences cored in the two coal exploration wells (SK-1 and SK-2) using coal petrography, mineralogy, faunal (ostracod and mollusk), and floral (palynology and diatom) data from four coal seams (from bottom to top: B, A, X-1, and X-0) with the variable total thickness (1 to 7 m). According to the palynological data, warm and humid climate conditions prevailed during the early Pliocene, and the precursor peats of seams A and B were mainly accumulated under limno-telmatic conditions, with high contributions of herbaceous peat-forming plants. Nevertheless, the co-occurrence of syngenetic carbonate minerals and framboidal pyrites along with calcareous fossil and diatom remains implies neutral to weakly alkaline conditions within palaeomires of these seams. Furthermore, ostracod and gastropod fauna from these seams might imply nutrient-rich shallow water conditions and spring support (e.g., karstic aquifer) into palaeomires. Thus, algal activity within the palaeomires was presumably high, and freshwater algae and diatoms were commonly identified in these seams.With the development of increased uplift ratio of central Taurides and climatic changes towards to late stages of Pliocene and particularly early Pleistocene, the common peat-forming plants within palaeomires and vegetation in the surrounding areas were changed. The increased precipitation caused an elevation of water levels in the study area; hence, the precursor peats of the seam X-1 were accumulated under wet forest mire conditions. This increase also explains the existence of ostracod and mollusk fauna related to river and spring support underlying sequences of the seam X-1. With the ceasing of accumulation of peat of the seam X-1, the climate became drier, and very shallow water conditions have been common. The development of spring support and relatively high precipitation in a short period of time allowed for final peat accumulation (seam X-0) during the early Pleistocene. Nevertheless, this period was followed by the development of relatively colder conditions in the study area, and cold small water conditions were developed during the end of the early Pleistocene. Furthermore, microthermic vegetation was common in the vicinity of the palaeomires during the early Pleistocene. Overall, the peat accumulation and water level of lakes in the study area seem to be controlled by climatic oscillations and uplift of margins of the Lake Beyşehir Basin during the Pliocene to early Pleistocene.

Fuzzy solution of nonlinear Boussinesq equation

Abstract In this paper, the solution of the one-dimensional second-order unsteady nonlinear fuzzy partial differential Boussinesq equation is examined. The physical problem concerns unsteady flow in a semi-infinite unconfined aquifer bordering a lake. In the examined problem, there is a sudden rise and subsequent stabilization of the lake's water level, thus the aquifer is recharging from the lake. The aquifer boundary conditions are considered fuzzy and, therefore, ambiguities are created to the solution of the overall physical problem. Then, the fuzzy problem is translated to a system of crisp boundary value problems. By using a Boltzmann transformation, the crisp problem is transformed into an integro-differential equation and solved with the help of a special numerical method. This method has a simple iterative procedure, which converges rapidly and is proven very accurate in comparison with other analytical methods. Additionally, the algebraic equation estimates very close to the storage coefficient, the flux at the stream-aquifer origin, and the water stored volume with respect to other exact solutions. This method is very useful for practical cases (artificial recharge problems, irrigation, and drainage projects), giving the possibility to decision-makers to take the right decision.

Evidence for increasing influence of atmospheric teleconnections on water levels in the Great Lakes

Understanding the variability and predominant drivers of water level fluctuations in large water bodies is critical for the development of proactive mitigation plans in the nearshore zone. Here, for the first time, we reconstructed the individual and collective influence of the Atlantic Multi-decadal Oscillation, Pacific Decadal Oscillation, region 3.4 of El Niño-Southern Oscillation, and North Atlantic Oscillation on Lake Huron-Michigan’s water budget components, including water levels, over-lake precipitation, evaporation, runoff, and river flow rates over a 115-year period. Conducting wavelet spectral analysis on the reconstructed impact of large-scale climate oscillations revealed the emergence of quasi-periodic and non-stationary fluctuations along with frequency shifts in hydrological variables, highlighting their increasingly stronger signature on water levels after 1980. After removing the atmospheric teleconnection effects, the residual hydrological time series provided evidence of gradual changes in runoff and river flow rates and their relationships with precipitation, reflecting the effects of intensifying anthropogenic activities on the regional water cycle over the past decades. Considering the uncertainty pertaining to the magnitude and frequency of atmospheric teleconnections in a changing climate, the findings of our study can offer a new perspective in our understanding of the drivers of water level variability along the shoreline and/or the navigability of shallow waters in the Great Lakes.

Understanding Water Level Changes in the Great Lakes by an ICA-Based Merging of Multi-Mission Altimetry Measurements

Accurately monitoring spatio-temporal changes in lake water levels is important for studying the impacts of climate change on freshwater resources, and for predicting natural hazards. In this study, we applied multi-mission radar satellite altimetry data from the Laurentian Great Lakes, North America to optimally reconstruct multi-decadal lake-wide spatio-temporal changes of water level. We used the results to study physical processes such as teleconnections of El Niño and southern oscillation (ENSO) episodes over approximately the past three-and-a-half decades (1985–2018). First, we assessed three reconstruction methods, namely the standard empirical orthogonal function (EOF), complex EOF (CEOF), and complex independent component analysis (CICA), to model the lake-wide changes of water level. The performance of these techniques was evaluated using in-situ gauge data, after correcting the Glacial Isostatic Adjustment (GIA) process using a contemporary GIA forward model. While altimeter-measured water level was much less affected by GIA, the averaged gauge-measured water level was found to have increased up to 14 cm over the three decades. Our results indicate that the CICA-reconstructed 35-year lake level was more accurate than the other two techniques. The correlation coefficients between the CICA reconstruction and the in situ water-level data were 0.96, 0.99, 0.97, 0.97, and 0.95, for Lake Superior, Lake Michigan, Lake Huron, Lake Erie, and Lake Ontario, respectively; ~7% higher than the original altimetry data. The root mean squares of errors (RMSE) were 6.07 cm, 4.89 cm, 9.27 cm, 7.71 cm, and 9.88 cm, respectively, for each of the lakes, and ~44% less than differencing with the original altimetry data. Furthermore, the CICA results indicated that the water-level changes in the Great Lakes were significantly correlated with ENSO, with correlation coefficients of 0.5–0.8. The lake levels were ~25 cm higher (~30 cm lower) than normal during EI Niño (La Niña) events.

Modelling of pH changes in alkaline lakes with water transfer from a neutral river

While water transfer from rivers to alkaline lakes has been proposed to solve lake water level drawdown and ecological degradation problems, its effectiveness for achieving ecological goals is often questionable. A sudden pH decline in alkaline lakes due to water transfer is considered likely to harm the lake ecology. However, it remains unclear to what extent water transfer affects alkaline lake pH. Thus, a three-dimensional numerical model coupling a pH calculation method considering the carbonate balance with the MIKE3 hydrodynamic model was developed to predict pH changes in an alkaline lake. Laboratory and field measurements verified the model reliability. The model accurately simulated the mixed-water pH during water transfer, with a root mean square error of 0.03–0.07 and a coefficient of determination of 0.894–0.998. The model was then applied to predict the pH response to water transfer in Lake Chenghai. The results showed that the pH response to water transfer demonstrated spatial and temporal variability, and a low-pH diffusion zone (pH ≤ 9) formed in the northern parts of the lake during annual water transfer; the effects of water transfer on the pH in the lake were cumulative over time, and the average pH in Lake Chenghai after five years decreased by 0.2 units; strong wind and low inflow could effectively reduce the low-pH diffusion area; and daily thermal stratification of the plateau region threatened the low-pH diffusion area control in Lake Chenghai. Our results provide a new reference for formulating ecological water transfer strategies for alkaline lakes and similar water bodies.

Groundwater dynamics of a lake-floodplain system: Role of groundwater flux in lake water storage subject to seasonal inundation

Groundwater behaviors in lake-floodplain systems are dynamic and complex; in particular, the role of groundwater flux in regulating lake water storage subject to strong seasonal variation is not well understood. This study addresses the contribution of groundwater flux in a large floodplain system (Poyang Lake, China), with focus on quantifying the groundwater-lake interactions at multiple time scales in high rainfall (2010) and low rainfall (2011) years using a groundwater flow model (MODFLOW). Simulated results revealed that the unconfined aquifer received approximately 8 % of the annual rainfall as groundwater recharge. Fluctuations in shallow groundwater and lake water level reflected hydraulic synchronization and hysteresis. Additionally, the diurnal variability in the groundwater-lake exchange fluxes was subject to dynamic and bidirectional patterns, and a time lag between the water exchange and rainfall was also found. For 2010 and 2011, the monthly net flux of lake infiltration into groundwater was 1.5–10.0 mm and 0.1–6.0 mm and groundwater exfiltration into lake was 1.3–9.5 mm and 0.4–2.2 mm, respectively, demonstrating a significant variation of the exchange magnitude and direction. In particular, we found that groundwater exfiltration contributed up to 55 % of lake storage change in February of 2011. The outcomes from this study indicate that groundwater can be a major component of the Poyang Lake's water balance, which suggests an important role of groundwater in regulating the lake water storage and perhaps other flood pulse systems.

Interannual and Monthly Variability of Typical Inland Lakes on the Tibetan Plateau Located in Three Different Climatic Zones

Changes in lake water volume can reflect variations in regional hydrometeorology and are a sensitive indicator of regional environmental change. The Tibetan Plateau, referred to as the “Asian Water Tower”, has a large number of lakes. These lakes are in a natural state and are relatively unaffected by human activities. Understanding the changes to lake water volume is a key issue for the study of lake-atmosphere interactions and the effects of lake expansion and contraction on regional climate. By using multisource remote sensing and water level observations, this study systematically analyzed inter-annual changes from 1970 to 2021 of three typical inland lakes basin (Bamu Co-Peng Co basin, Langa Co-Mapum Yumco basin andLongmu Co-Songmuxi Co basin), which are located in different climatic regions of the Tibetan Plateau and monthly changes from 2019 to 2021 of Bamu Co, Langa Co and Longmu Co in the lake area, water level, and water volume. In addition, the study analyzed the response of lakes in different climate regions to climate change from 1979 to 2018. The main conclusions are as follows. (1) From 1970 to 2021, there were similar trends in lake changes between the primary and twin lakes. (2) The changes to lakes in different climatic regions are different: lakes in the monsoon-dominated region showed a significant trend of expansion from 2000 to 2014, but the trend slowed down and stabilized after 2014; lakes in the westerlies-dominated region showed a small expansion trend; lakes in the region affected by both westerlies and the monsoon showed an overall shrinking trend. (3) The monthly variation of lake water volume showed a trend of first increasing and then decreasing, with the largest relative change of lake water volume in August and September. (4) Precipitation is a dominant factor controlling lake variation during the year. (5) Temperature and precipitation are dominant meteorological elements affecting the decadal variation of the lake, and with the warming of the TP, temperature plays an increasingly important role.

Centrifuge modelling of spoil slopes within pit-lake mine reclamations

Pit lakes are a common form of reclamation of areas where open pit mining activities have taken place. The development of these lakes often uses previous overburden materials, or “spoils”, that are readily available. Depending on the local geology, these spoil materials can contain large proportions of high-plasticity clays, which poses challenges in terms of the analysis and design of the sloped banks constructed to form new lakes. This paper describes a study in which geotechnical centrifuge modelling was used to investigate the stability and performance, in terms of accumulated displacements over cycles of lowering and raising the lake water elevation, of slopes constructed with a high-plasticity clay. A “replica-spoil” material was used in the tests to replicate key characteristics of spoil materials from known spoil heaps in Europe. The paper describes the centrifuge models and testing procedure developed for the tests, as well as the challenges encountered with the use of the high-plasticity clay. Two slope angles were tested: a 15 slope to match the typical slopes at a known field site, and a steeper 24 slope. Pore pressures within the slope were measured over several cycles of lake water elevation change. Slope displacements were measured using local transducers placed at the slope crest and toe, as well as using a PIV image analysis technique. The slopes were shown to experience plastic deformations, with displacements accumulating over subsequent cycles of lake water level change. The 24 slope developed slightly larger accumulated displacements than the 15 slope, though neither slope showed signs of ultimate collapse. Results from the centrifuge tests provide invaluable data which can be used for the verification of numerical models considering similar stability scenarios.

Interaction Model of Rainfall, Lake, and Ground Waters

This research intends to build an interaction model between rainfall, lake water, and ground water. The location of research is in the Sentani Lake where is placed in the Jayapura Regency-Papua-Indonesia. Sentani Lake is a lake in the Sentani Watershed. Sentani Lake is located between Jayapura City and Jayapura Regency-Papua Province. The area of Sentani Lake is 9,630 ha with the depth is 75 m over the sea. In the northern of this lake are the Cyclops Mountains (Dafonsero) that separate the Sentani Lake and the Pacific Sea. The Sentani Lake functions as the track of transportation, food source, drinking water source, and tourism. Based on the bathymetry analysis result which is obtained from the River Region Institution of Papua, the Sentani Lake has the smallest elevation from 13.05 mdpl until 71.5 mdpl with a maximum storage capacity of 4.8 milliard m3. The methodology of this research consists of 1) To set and to simulate of Hydrology Model; 2) Analysis of water balance; 3) To set up the hydro-geology model; 4) To simulate the integration of rainfall-lake water- ground water. The interaction model between rainfall and lake waters is built based on the relation between the outlet discharge and the rainfall at 10 points and then is validated at the 5 points of observation data. This model produces the formulation as follows: inflow to the lake from rainfall = 0.067 x rainfall – 5. The interaction model between the lake water level and the ground water level is built based on the value of ground water-level fluctuation and the lake water level at the 10 points, and it is validated at the 6 points of observation data. This model produces the following formulation: fluctuation of ground water level = 0.1529 x fluctuation of lake water level. By combining the ground water and run-off in the Sentani Watershed, it is known as follows: inflow total of lake = base-flow + 0.067 x rainfall – 5.

Community Analysis of Benthic Macroinvertebrates According to Water Level of Lake in Littoral and Profundal Zone

Community Analysis of Benthic Macroinvertebrates According to Water Level of Lake in Littoral and Profundal Zone

Expansion of typical lakes in Xinjiang under the combined effects of climate change and human activities

Lakes are important guarantees of regional economic development and ecological security. Previous studies focused on trends of surface area and water level of lakes in Xinjiang, but paid less attention to nonlinear change and driving mechanisms of lake areas at annual and monthly scales. To address this issue, this study used a remote-sensing Big Data cloud platform and mathematical statistical methods to investigate the change in typical lakes and its attribution in Xinjiang during 1986–2020. The results showed that: 1) there was a significant linear trend in Xinjiang lakes: except for Jili Lake, the plains lakes showed an insignificant (p > 0.1) expansion trend, while the mountain lakes showed an significant expansion trend (p < 0.01). 2) There was a significant nonlinear trend in Xinjiang lakes: most of the plains lakes showed periodicity at 14 and 21 years, however most of the mountain lakes showed periodicity at 17 and 21 years. Most of the mutation trends of plains lakes were not significant, yet the mutation trends of mountain lakes showed significant expansion. 3) Human activities were the dominant factor leading to changes in the plains lakes: among the anthropogenic factors, farmland area, GDP, and population had significant effects on lake area (p < 0.1), and lake expansion was closely related to population and farmland area. Among climatic elements, precipitation mainly affected the changes in plains lakes. 4) Climate change was the dominant factor leading to changes in mountain lakes. The effects of temperature change on mountain lakes were all significantly positive (p < 0.05). In the future, it will be necessary to build lake protection schemes that adapt to climate change and human disturbances. This study can provide an important scientific basis for the rational development and utilization of lakes in Xinjiang.

Comparison of Numerical Methods in Simulating Lake–Groundwater Interactions: Lake Hampen, Western Denmark

The numerical simulation of lake–groundwater interaction dynamics is very challenging, and, thus, only few model codes are available. The present study investigated the performance of a new method, namely, the Sloping Lakebed Method (SLM), in comparison to the widely used MODFLOW lake package (LAK3). Coupled lake–groundwater models based on LAK3 and SLM were developed for Lake Hampen, Denmark. The results showed that both methods had essentially the same accuracy when simulating the lake water level, the groundwater head and the overall water balance. The SLM-based model had the potential to reproduce the change of the lake surface area in a more natural way. Moreover, the vertical discretization of a lake in the SLM is independent of the groundwater model, and, thus, the model grid at the top layers could be considerably coarsened without a loss of model accuracy. This could lead to savings in computational time of approximately 30%.

Evidence of large water-level variations found in deltaic sediments of a tropical deep lake in the karst mountains of the Lacandon forest, Mexico

Lake Tzibaná is one of the largest (1.27 km2) and deepest (Zmax = 52 m) karstic lakes in the UNESCO’s Biosphere Reserve “Nahá-Metzabok” and in the Lacandon Forest, southeastern Mexico. It archives sediments from multiple sources and the inflowing Nahá River forms deltaic deposits. In 2019, the water level in Lake Tzibaná declined by ~ 15 m, persisting for 4 months and exposing the Nahá River Delta. A geophysical profile on the exposed delta revealed an accumulation of ~ 20 m of such deposits. Three sediment outcrops from an inactive channel in the Nahá River Delta, which ranged in height from 0.6 to 1.43 m, were sampled and a multi-proxy analysis of biological remains and geochemical variables was conducted. Four facies were observed: (1) massive-coarse sand, (2) fine sand, (3) dark leaf litter and (4) massive silty clay, each characterized by specific microcrustacean, testate amoebae and diatom taxa. Six dark leaf litter horizons were radiocarbon dated and revealed a complex depositional history including inverted ages making the establishment of an age model difficult. Nevertheless, past lake-level changes and the formation of the four facies match three characteristic water-level stages, which can also be observed on recent satellite images: (1) Massive-coarse sand deposits, with compositional and sedimentological characteristics of a shoreline environment and fluvial lateral banks, were formed during large-magnitude reductions in the lake level, similar to the one in 2019, (2) Interbedded layers of fine sand and dark leaf litter, currently found in low-energy fluvial environments, were formed during shorter and less pronounced decrease intervals, and (3) Massive silty clay, with distinctive microorganisms from low-energy lacustrine environments, is deposited during high water-level stages, when the delta is covered by water. Our findings illustrate how hydrological changes alter sedimentary dynamics in deltaic areas of lakes. Despite the complexity of their depositional processes, deltaic records can serve as a complementary source of paleolimnological information to records from distal zones due to their sensitivity to variations in water level, especially during extreme and prolonged desiccation events. Future research should attempt to combine evidences from deltaic and sediment sequences from deeper zones of Lake Tzibaná to reconstruct water-level variations during the entire Holocene. Understanding past lake-level reductions is not only relevant for the local indigenous communities but also crucial for the conservation of this ecosystem of international importance.

Neurocomputing intelligence models for lakes water level forecasting: a comprehensive review

Neurocomputing intelligence models for lakes water level forecasting: a comprehensive review

The Spatiotemporal Change of Xiao Qaidam Lake from 1990 to 2020 and Its Potential Hazards

In the climatic context of warming and humidification in Northwest China, most lakes in Qinghai Province experienced a rising water level and expanding area, inundating grassland and infrastructure around lakes, and even extreme events such as lake outburst floods. Based on Landsat TM/ETM+/OLI and GF PMS images, lake water level data, SRTM digital elevation model (DEM), GlobeLand30 and meteorological data used in this study, we analyzed the area change of Xiao Qaidam Lake in Qaidam Basin with its causes, factors and potential hazards. The results show that the area of Xiao Qaidam Lake increased by 60.42 km2 (85.43%) from 1990 to 2020, which can be roughly divided into three stages: fluctuation decline in 1990–2001 (−1.89 km2/a); relatively stable in 2002–2014; and rapid expansion in 2015–2020 (8.54 km2/a). In 2020, the water level and water volume of Xiao Qaidam Lake increased by 3.62 m and 0.39 km3, respectively, compared with 2015, resulting in the inundation of an area of 54.55 km2 of grassland around the lake and a direct threat to the Liuge and Dexiao Expressways. Both the increase in annual precipitation (12.63 mm/10a) and the decrease in potential evapotranspiration (−13.38 mm/10a) since 1990 are the main reasons for the rapid expansion of Xiao Qaidam Lake, and the increasing trend of climate warming and humidification will lead to the continuous expansion of Xiao Qaidam Lake in the next decades. According to the water volume growth rate from 2015 to 2020, it is predicted that by 2024 the area and water level of Xiao Qaidam Lake will reach 154 km2 and 3180 m, respectively, and part of Liuge and Dexiao Expressways will be submerged. Therefore, it is urgent to strengthen the monitoring of Xiao Qaidam Lake and formulate corresponding disaster prevention and reduction measures.