Lake Water Level Changes Research Articles

Enhancing the temporal resolution of water levels from altimetry using D-InSAR: A case study of 10 Swedish Lakes

Lakes provide societies and natural ecosystems with valuable services such as freshwater supply and flood control. Water level changes in lakes reflect their natural responses to climatic and anthropogenic stressors; however, their monitoring is costly due to installation and maintenance requirements. With its advanced hardware and computational capabilities, altimetry has become a popular alternative to conventional in-situ gauging, although subject to the temporal availability of altimetric observations. To further improve the temporal resolution of altimetric measurements, we here combine radar altimetry data with Differential Interferometric Synthetic Aperture Radar (D-InSAR), using ten lakes in Sweden as a testing platform. First, we use Sentinel-1A and Sentinel-1B SAR images to generate consecutive six-day baseline interferograms across 2019. Then, we accumulate the phase change of coherent pixels to construct the time series of InSAR-derived water level anomalies. Finally, we retrieve altimetric observations from Sentinel-3, estimate their mean and standard deviation, and apply them to the D-InSAR standardized anomalies. In this way, we build a water-level time series with more temporal observations. In general, we find a strong agreement between water level estimates from the combination of D-InSAR and Satellite Altimetry (DInSAlt) and in-situ observations in eight lakes (Concordance Correlation Coefficient - CCC >0.8) and moderate agreement in two lakes (CCC >0.57). The applicability of DInSAlt is limited to lakes with suitable conditions for double-bounce scattering, such as the presence of trees or marshes. The accuracy of the water level estimates depends on the quality of the altimetry observations and the lake's width. These findings are important considering the recently launched Surface Water and Ocean Topography (SWOT) satellite, whose capabilities could expand our methodology's geographical applicability and reduce its reliance on ground measurements.

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.

Evaluating D-InSAR performance to detect small water level fluctuations in two small lakes in Sweden

Monitoring lake water level fluctuations is critical for managing water resources, predicting the impacts of climatic change, and preserving ecosystem services lakes provide. However, traditional gauging stations are insufficient to monitor all lakes worldwide due to the large number of existing lakes, the challenges of installation and maintenance, and the remote locations of some. Although satellite altimetry is an alternative for measuring water levels, it cannot monitor small lakes effectively. This study evaluates the potential of Differential Interferometric Synthetic Aperture Radar (D-InSAR) for tracking minor water level changes in small lakes, a method more typically used in wetland studies. We investigate two Swedish lakes using Sentinel-1A and Sentinel-1B data from 2019, generating six-day interferograms and filtering out those with in situ water level changes exceeding one phase cycle. Our results show that D-InSAR can detect small water level changes with Lin’s correlations up to 0.63 and 0.89 and RMSE values of approximately 9 and 4 mm, respectively. These results evidence the potential of future L-band SAR missions with larger wavelengths, such as the NASA-ISRO SAR (NISAR) of the National Aeronautics and Space Administration (NASA) and the Indian Space Research Organisation (ISRO), to track water level changes in lakes and aid water tracking missions such as the SWOT (Surface Water and Ocean Topography).

Altimetry-based ice-marginal lake water level changes in Greenland

Greenland holds over 3300 ice-marginal lakes, serving as natural reservoirs for outflow of meltwater to the ocean. A sudden release of water can largely influence ecosystems, landscape morphology, ice dynamics and cause flood hazards. While large-scale studies of glacial lake outburst floods (GLOFs) have been conducted in many glaciated regions, Greenland remains understudied. Here we use altimetry data to provide the first Greenland-wide inventory of ice-marginal lake water level changes, studying over 1100 lakes from 2003–2023, revealing a diverse range of lake behaviors. Around 60% of the lakes exhibit minimal fluctuations, while 326 lakes have drained, collectively contributing to 541 observed GLOFs from 2008–2022. These GLOFs vary substantially in magnitude and frequency, with the highest concentration observed in the North and Northeast regions. Our results show substantial annual differences in the number of GLOFs with a notable peak in 2019, coinciding with a year marked by extreme runoff. Our method detected a 1200% increase in the number of draining lakes compared to existing historical databases. This highlights a large underreporting of GLOF events and emphasizes the pressing need for a deeper understanding of the mechanisms behind and the consequences of these dramatic events.

Satellite data is revealing long time changes in the world largest lakes

Lakes are a crucial source of drinking water, provide ecological services from fisheries and aquaculture to tourism and are also a critical part of the global carbon cycle. Therefore, it is important to understand how lakes are changing over time. The ESA Ocean Colour Climate Change Initiative (OC-CCI) database allows to study changes in the largest lakes over 1997–2023 period. The Caspian Sea and ten next largest lakes were under investigation. Changes in the phytoplankton biomass (Chl-a), the concentration of particulate matter (bbp(555)), the colored dissolved organic matter, CDOM (adg(412)), and the light diffuse attenuation coefficient in water (Kd(490)) were analyzed. Both increasing and decreasing trends (or no significant trend at all) of studied parameters were observed in these lakes over the study period. In some of the Laurentian Great Lakes the changes in CDOM over the study period were found to be in accordance with the lake water level changes i.e. with the inflow from the catchment. There was difference between the trends of Chl-a and bbp(555) in lakes Michigan and Huron indicating that there may have been shift in phytoplankton community that took place around 2005. The study demonstrated that remote sensing products, like the ones created by ESA OC-CCI, are valuable tools to study behavior of large lakes ecosystems over time.

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

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

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

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

Changes in lake area and water level in response to hydroclimate variations in the source area of the Yellow River: a case study from Lake Ngoring

Changes in lake area and water level in response to hydroclimate variations in the source area of the Yellow River: a case study from Lake Ngoring

Estimation of Coastal Area and Lake Water Level Changes Using High-Resolution Altimetry

Radar satellite altimeters are widely used in offshore areas, whereas they are underutilized in coastal areas due to a number of interference factors. Altimeter satellite data can be used to summarize elevation information at 1 Hz for offshore areas, but for areas close to land, it is more effective to utilize imagery with a resolution of 20 Hz to provide a more detailed representation. The use of highresolution satellite altimeter data is expected to increase the amount of data available for hydrological data such as complex coastlines and small lakes. Therefore, in this study, we investigated the applicability of 20 Hz altimeter data in the Korean Peninsula. First, the accuracy was analyzed by comparing the 20 Hz altimeter data from the Jason-3 satellite with the Ulleungdo tide data. Second, we compared the 20 Hz altimeter data from the Sentinel-3A satellite with the water level data of Soyang Lake to see if it can be applied to land areas. In the case of inland lakes, the water level is estimated to be affected by the discharge volume due to heavy rainfall in summer, and it was determined that the satellite altimeter data can be utilized. Therefore, utilizing the data from this study is expected to improve the accuracy of hydrological analysis in coastal and lake environments.

Monitoring Lake Level Changes in Bosten Lake from 2003-2021 based on Multi-source Satellite Altimetry Data

The investigation of freshwater lake water resource changes in arid regions is crucial for understanding the evolution of regional lake dynamics under climate change, given their value and limited availability. This study aims to overcome the limitations of traditional water level monitoring methods and address the practical need for monitoring water level changes in Lake Bosten, located in the arid and semi-arid regions of China. To this end, we employed ICESat, ICESat-2, and CryoSat-2 altimetry data, as well as Landsat 8-OLI optical remote sensing data, to obtain the water level information for Bosten Lake from 2003 to 2022. We analyzed the temporal variation of the lake level and discussed the response of the lake level to climate and human activities in the context of temperature, precipitation data, and human water use. The water level of Lake Bosten exhibited a decreasing and then increasing trend, with three rising and three falling intervals, respectively. The intra-year variation of the lake water level exhibited bimodal characteristics, and the fluctuation range of water level during abundant water periods was greater than that during dry periods. Finally, we correlated the extracted lake water level with the measured water level at the hydrological station and found a significant positive linear correlation between the observed water level of Bosten Lake based on satellite altimetry and the measured water level at the hydrological station, with an overall correlation coefficient of 0.896 and 0.934 (P &lt; 0.01), indicating high accuracy of the water level results obtained in this study. The dynamics of Lake Bosten are influenced by a combination of climate change, hydrological elements, and human activities, with a relatively weak relationship between climate change and lake volume and a strong influence of human activities. Multi-source altimetry satellites provide a powerful tool for monitoring lake water levels over a long time scale, which is critical for studying lake water level changes and their response to climate and the environment.

Typization of Lakes of the East Antarctica Oases

The urgency of creating a new complex typization of lakes of the East Antarctica oases is dictated not only by the desire to summarize accumulated Antarctic lakes’ data but also by the need to obtain the most informative characteristics of lake hydrological regime in the region for solving a wide applied problems’ range. Features of lake water level changes were used as a criterion in developing the complex typization of lakes of the East Antarctica oases for the first time, in contrast to existing classifications. The study was based on the analysis of literary and archive materials (the Larsemann Hills, the Schirmacher oasis, the Banger Hills, the Molodezhnyi oasis, the Vestfold Hills, and the McMurdo Dry Valleys), as well as our own expeditionary data (field seasons of 2017–2022, the Larsemann Hills). A group of indirect criteria (presence and type of natural dam, position in the cascade, flowage type, etc.) is proposed in addition to a group of direct criteria (duration of the lake filling phase, water level rise, etc. requiring organization of field observations) to obtain a holistic view of the water level regime of lakes. It is important that characteristics of the most indirect criteria can be obtained by visual reconnaissance surveys or by maps and remote sensing data. The identified 4 types (outbursting, tendentious, transit, and tidal) and 8 subtypes of lakes were illustrated by generalized graphs of water level changes, which objectively characterize the features of the lake hydrological regime. The openness of the typization suggests the opportunities for actualization with the accumulation of new scientific knowledge and data.

Synthesis of the ICESat/ICESat-2 and CryoSat-2 observations to reconstruct time series of lake level

ABSTRACT Synthesis of multi-satellite altimetry facilitates the acquisition of long-term changes in lake level but may induce biases due to inconsistent data sources, and thus remains largely unexplored. This study investigates the integrated application of Ice, Cloud, and land Elevation Satellite (ICESat), ICESat-2, and CryoSat-2 missions to provide consecutive lake level series in 2003–2020. The sample comprises 48 lakes in the world with gauge-based or Hydroweb water level data. The CryoSat-2 data are first adjusted to the ICESat-2 height reference based on the mean values of their monthly water level difference during their overlapping period (2018–2020). Then, the corrected CryoSat-2 data are used to link the ICESat and ICESat-2 data. Results show that in the sample lakes, the deviations between CryoSat-2 and ICESat-2 data vary and range from −0.78 m to 0.13 m. The data quality of the synthesized time series is evaluated by comparing against the validation data, with an average R 2 of 0.84. This study shows that CryoSat-2 has the potential of filling the gap between ICESat and ICESat-2. The three altimeters can be expected to integrate effectively for monitoring lake water level changes in the past two decades.

Developing a vine copula model to simulate and predict long serial lake water levels

Lake water level changes show randomness and the complexity of basin hydrological simulation and lake water level response. We constructed a vine copula model to simulate and predict lake water level that incorporated rolling decisions and real-time correction of prediction results. The model was applied to predict the long- and short-term water levels in Erhai Lake on the Yun-gui Plateau, southwest China. The results showed that (1) the predicted daily water levels (with ME=0.02~0.09, RMSE=0.02~0.024, NSE=0.99, and IA=0.99) were more accurate than the predicted monthly water levels (with the ME=0.039~0.444, RMSE=0.194~0.279, NSE=0.913~0.958, and IA=0.977~0.989), and the accuracy of the predictions improved as the number of variables increased. (2) The vine copula model outperformed the back-propagation neural network and support vector regression models, and, of the three model types, gave the best estimate of the nonlinear relationships between the predicted water level and climatic factors, especially in the wet season (May to October). (3) The prediction accuracy of the vine copula model was lower for small sample sizes and when there was a lack of runoff data. By improving the analysis of the model’s errors, the percentages of the relative errors of the prediction accuracy less than 5%, 10%, 15%, and 20% increased to 70%, 83%, 95%, and 98%, respectively.

A Preliminary Analysis of Anthropogenic and Natural Impacts on a Volcanic Lake Ecosystem in Southern Italy by UAV-Based Monitoring.

Lakes play an important role in providing various ecosystem services. However, stressors such as climate change, land use, or land-cover change threaten the ecological functions of lakes. National and international legislations address these threats and establish consistent, long-term monitoring schemes. Remote sensing techniques based on the use of Unmanned Aerial Vehicles (UAV) have recently been demonstrated to provide accurate and low-cost spatio-temporal views for the assessment of the ecological status of aquatic ecosystems and the identification of areas at risk of contamination. Few studies have been carried out so far on the employment of these tools in the monitoring of lakes. Therefore, high-resolution UAV surveys were used to analyse and evaluate natural and anthropogenic impacts on the habitat status of a volcanic lake in a protected area. Five UAV flights took place during a year-long cycle (November 2020 to November 2021) in a volcanic lake located in southern Italy. For each flight performance, an orthomosaic of georeferenced RGB images was obtained, and the different features of interest were monitored and quantified using automated processing in a GIS environment. The UAV images made it possible not only to estimate the flooded shores but also to detect the impact of human-made structures and infrastructures on the lagoon environment. It has been possible to observe how the rapid changes in lake-water level have led to the submersion of about 90.000 m2 of terrain in winter, causing the fragmentation and degradation of habitats, while the connectivity of the natural ecosystem has been threatened by the presence of the road around the lake. The proposed methodology is rather simple and easily replicable by decision makers and local administrators and can be useful for choosing the best restoration interventions.

Dünden Bugüne Beyşehir Gölü (Isparta-Konya, Türkiye) Balıkçılığı ve Durum Analizi

Anadolu plakasının önemli karstik boşalım havzalarından birinde yer alan Beyşehir Gölü 650 km2 yüzey alanı ile Türkiye’nin en büyük tatlısu gölü olmasının yanında; biyo-ekolojik, sosyo-ekonomik ve kültürel yönlerden çok önemli bir sulak alandır. Beyşehir Gölü balıkçılığı üzerine tutulmuş ilk kayıtlar 1910’lara dayanmakla birlikte, balıkçılığa ait ilk bilimsel bulgular 1950’li yıllarda başlamıştır. Gölün balıkçılığı hakkında güvenli verilere ulaşmak oldukça zor olmakla beraber, 1950’lerden günümüze kadar olan süreçte balıkçılık üzerine etkin olan başlıca süreçlerin: i) kullanılan avcılık yöntemi ve av araçları, ii) gölün trofik yapısındaki değişimler, iii) yabancı fauna elemanlarının göle girmesi, iv) gölün su seviyesindeki değişimler, v) balıkçıların sosyo-ekonomik ve bilinç düzeyi, vi) balıkçılık yönetim stratejileri olduğu görülmüştür. Gölde 1950’lerde yaklaşık 3 kg/ha olan av verimi 2021 yılında 13,34 kg/ha olarak belirlenmiştir. Aradan geçen zamanda faunada önemli değişimler olurken, artan av miktarı ile birlikte balıkçı sayısında da önemli bir artış olduğu belirlenmiştir. Günümüzde 14’ü endemik olmak üzere 23 balık türünün yaşadığı ve mezotrofik-ötrofik düzeyde olan gölde, 2010-2021 yılları ortalamasına göre avlanan 669.051 kg balığın %67,41’ini Carassius gibelio (gümüşi havuzbalığı) %20,17’sini Sander lucioperca (sudak) ve %12,42’sini Cyprinus carpio (sazan) oluştururken; 2021 yılındaki avcılık dağılımının ise %75,41’ini gümüşi havuzbalığı, %21,47’sini sudak ve %3,11 kadarını ise sazan oluşturmuştur. Gölde 385 adet balıkçı aktif olarak avcılık yapmakta olup, 2021 yılı verilerine göre balıkçı başına 2.252 kg/yıl ava karşılık 13.790 TL/yıl kazanç elde edilmiştir. Bu çalışmanın diğer bir sonucu olarak, Beyşehir Gölü balıkçılık ekosistemi üzerindeki en büyük etkenin zamansız ve aşırı avcılık olduğu anlaşılmıştır.

Monitoring Shoreline and Land Use/Land Cover Changes in Sandbanks Provincial Park Using Remote Sensing and Climate Data

Climate change-driven forces and anthropogenic interventions have led to considerable changes in coastal zones and shoreline positions, resulting in coastal erosion or sedimentation. Shoreline change detection through cost-effective methods and easy-access data plays a key role in coastal management, where other effective parameters such as land-use/land-cover (LULC) change should be considered. This paper presents a remotely sensed shoreline monitoring in Sandbanks Provincial Park, Ontario, Canada, from 1984 to 2021. The CoastSat toolkit for Python and a multilayer perceptron (MLP) neural network classifier were used for shoreline detection, and an unsupervised change detection framework followed by a postclassification change detection method was implemented for LULC classification and change detection. The study assessed the recent coastal erosion and accretion trends in the region in association with spatiotemporal changes in the total area of the West and East Lakes, the transition between LULC classes, extreme climate events, population growth, and future climate projection scenarios. The results of the study illustrate that the accretion trend apparently can be seen in most parts of the study area since 1984 and is affected by several factors, including lake water-level changes, total annual precipitations, sand movements, and other hydrologic/climatic parameters. Furthermore, the observed LULC changes could be in line with climate change-driven forces and population growth to accelerate the detected accretion trend in the East and West Lakes. In total, the synergistic interaction of the investigated parameters would result in a greater accretion trend along with a lower groundwater table amid even a low carbon scenario. The discussed findings could be beneficial to regional/provincial authorities, policymakers, and environmental advocates for the sustainable development of coastal communities.

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.

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.

Water Level Change Monitoring Based on a New Denoising Algorithm Using Data from Landsat and ICESat-2: A Case Study of Miyun Reservoir in Beijing

Inland lakes or reservoirs are the main surface water resources, related to people’s survival and social development. On-site water level data are critical for water resource management, while satellite laser and remote sensing data are a significant tool for long-term change monitoring. In this study, we took the Miyun Reservoir, the most important source of drinking water in Beijing, as the research area. We used Landsat images and the Ice, Cloud, and Land Elevation Satellite (ICESat-2) for small-scale water level change monitoring and inversion across unrecorded periods. First, we proposed a new two-step denoising method based on local statistics to denoise the ATL03 single photon data from 2018 to 2020, and extracted the effective elevation information of Miyun Reservoir. Second, based on Landsat images from 1984 to 2020, the MNDWI index was used to extract the water area and generated a percentage map of water occurrence. Finally, the water and land boundary elevation were selected from the effective photon elevation information according to the boundary position under each percentage of the water generation percentage graph, the area, and the water level elevation model (A–E model) was established, and the water level values of unrecorded periods were inverted. The denoising results showed that the denoising accuracy of all data is higher than 95%. The area of Miyun Reservoir has changed greatly in the past 37 years, especially in the northeast corner and northern region. The inverted water level elevation had a strong correlation with the measured value, the correlation coefficient reached 0.97, the root mean square error (RMSE) was 0.553 m, and the estimated water level value was highly consistent with the recorded value and fluctuated dramatically from 1984 to 2020. This method complements the traditional water level mapping method, provides a new idea for the monitoring of water level changes in lakes or reservoirs without field records, and also contributes to the timely and effective monitoring and management of global lake and reservoir water level and time changes.

Impacts of lake water change on vegetation development in the retreat area of the Aral Sea

The Aral Sea has been persistently shrinking in past decades, and the influence of the lake water level changes on vegetation in the lake retreat areas is uncertain. In this study, we quantitatively assessed the vegetation development due to relevant hydrological changes in the retreat area of the Aral Sea. The results showed that the normalized difference vegetation index (NDVI) in the retreat area displayed an overall increase from 1986 to 2020. The increasing vegetated area accounted for 84 % of the total area of the South Aral Sea, which was caused by an increase in the exposed lakebed area. However, about 40 % of the area in the North Aral Sea was the increasing vegetated area due to the improved water environment. When the depth to water table (DTW) was larger than 7–8 m, vegetation development was more dependent on precipitation than groundwater. When DTW was less than 7–8 m, groundwater had a more significant impact than precipitation on vegetation development. The negative impacts of groundwater salinity exceed the positive contributions of water supply on vegetation development, which differs to the common understanding under conditions of fresh or brackish groundwater in arid climates. Water level recovery is an effective option for improving vegetation establishment on the exposed seabed; otherwise, the exposed seabed area observed during the period 1990s–2010s in the eastern basin may remain a saline desert for a long period in the future. Finally, an empirical relationship between NDVI and water levels was established, which can be used for lake water level management that considers vegetation development in the retreated area of the Aral Sea.