Lake Water Storage Research Articles

Methane emissions from thermokarst lakes must emphasize the ice-melting impact on the Tibetan Plateau

Thermokarst lakes, serving as significant sources of methane (CH4), play a crucial role in affecting the feedback of permafrost carbon cycle to global warming. However, accurately assessing CH4 emissions from these lakes remains challenging due to limited observations during lake ice melting periods. In this study, by integrating field surveys with machine learning modeling, we offer a comprehensive assessment of present and future CH4 emissions from thermokarst lakes on the Tibetan Plateau. Our results reveal that the previously underestimated CH4 release from lake ice bubble and water storage during ice melting periods is 11.2 ± 1.6 Gg C of CH4, accounting for 17 ± 4% of the annual total release from lakes. Despite thermokarst lakes cover only 0.2% of the permafrost area, they annually emit 65.5 ± 10.0 Gg C of CH4, which offsets 6.4% of the net carbon sink in alpine grasslands on the plateau. Considering the loss of lake ice, the expansion of thermokarst lakes is projected to lead to 1.1–1.2 folds increase in CH4 emissions by 2100. Our study allows foreseeing future CH4 emissions from the rapid expanding thermokarst lakes and sheds new lights on processes controlling the carbon-climate feedback in alpine permafrost ecosystems.

A mathematical model to improve water storage of glacial lake prediction towards addressing glacial lake outburst floods

Abstract. Moraine-dammed glacial lakes (MDLs) are not only vital sources of freshwater but also a hazard to mountain communities if they drain in sudden glacial lake outburst floods (GLOFs). Accurately measuring the water storage of these lakes is crucial to ensure sustainable use and safeguard mountain communities downstream. However, thousands of glacial lakes still lack a robust estimate of their water storages because bathymetric surveys in remote regions are difficult and expensive. Here we geometrically approximate the shape and depths of moraine-dammed lakes and provide a cost-effective model to improve lake water storage estimation. Our model uses the outline and the terrain surrounding a glacier lake as input data, assuming a parabolic lake bottom and constant hillslope angles. We initially validate our model using data from four newly surveyed glacial lakes on the Qinghai–Tibet Plateau. Subsequently, we incorporate data from 40 additional measured lakes as a sample set to compare and evaluate the model's performance against other existing models. Our model overcomes the autocorrelation issue inherent in earlier area/depth–water storage relationships and incorporates an automated calculation process based on the topography and geometrical parameters specific to moraine-dammed lakes. Compared to other models, our model achieved the lowest average relative error of approximately 14 % when analyzing a dataset of 44 observed lakes, surpassing the > 44 % average relative error from alternative models. Finally, the model is used to calculate the water storage change in moraine-dammed lakes in the past 30 years in High-mountain Asia. The model has been proven to be robust and can be utilized to update the water storage of lake water for conducting further management of glacial lakes with the potential for outburst floods in the world.

Monitoring long-term water storage of lakes and reservoirs in arid ungauged basin based on underwater topography derived from multi-source satellite data.

Monitoring long-term water storage of lakes and reservoirs in arid ungauged basin based on underwater topography derived from multi-source satellite data.

Geospatial perspective for monitoring SDG 6.6.1 based on spatial and temporal analysis of lake water storage variations in Dongting Lake, China

Geospatial perspective for monitoring SDG 6.6.1 based on spatial and temporal analysis of lake water storage variations in Dongting Lake, China

Using hydrological modeling and satellite observations to elucidate subsurface and surface hydrological responses to the extreme drought

Using hydrological modeling and satellite observations to elucidate subsurface and surface hydrological responses to the extreme drought

Reconstructing Tibetan Plateau lake bathymetry using ICESat-2 photon-counting laser altimetry

Reconstructing Tibetan Plateau lake bathymetry using ICESat-2 photon-counting laser altimetry

Lake water storage changes and their cause analysis in Mongolia

Lake is an important water resources in Mongolia, which has undergone a large variation in past decades. However, it is still challenging to monitor long-term changes in lake water storage (LWS) due to the lack of lake level monitoring and long-term satellite altimetry data for Mongolian lakes. According to the Advanced Land Observing Satellite Digital Elevation Model (ALOS DEM) and the Joint Research Centre (JRC) dataset, we estimated the LWS changes of 55 Mongolian lakes (> 10 km2) from 1991 to 2020. The results showed that the LWS increased by 40.24 km3 from 1991 to 1997, especially for northwestern Mongolia with 31.47 km3. However, the LWS decreased by 32.44 km3 from 1998 to 2010, and the lakes in the northwestern and southern decreased by 20.24 km3 (62%) and 7.38 km3 (23%), respectively, and then the LWS continued to decrease by 10.22 km3 from 2011 to 2020. The precipitation was the primary cause of lake change, which could explain 45.13% of LWS change based on Generalized Linear Model, followed by temperature (26.33%) and irrigated area (16.72%). Analyzing the changing characteristic and driving mechanisms of LWS can provide a scientific basis for local water resources management and planning.

Dynamic Monitoring of Poyang Lake Water Area and Storage Changes from 2002 to 2022 via Remote Sensing and Satellite Gravimetry Techniques

The monitoring of Poyang Lake water area and storage changes using remote sensing and satellite gravimetry techniques is valuable for maintaining regional water resource security and addressing the challenges of global climate change. In this study, remote sensing datasets from Landsat images (Landsat 5, 7, 8 and 9) and three Gravity Recovery and Climate Experiment (GRACE) and Gravity Follow-on (GRACE-FO) mascon solutions were jointly used to evaluate the water area and storage changes in response to global and regional climate changes. The results showed that seasonal characteristics existed in the terrestrial water storage (TWS) and water area changes of Poyang Lake, with nearly no significant long-term trend, for the period from April 2002 to December 2022. Poyang Lake exhibited the largest water area in June and July every year and then demonstrated a downward trend, with relatively smaller water areas in January and November, confirmed by the estimated TWS changes. For the flood (August 2010) and drought (September 2022) events, the water area changes are 3032 km2 and 813.18 km2, with those estimated TWS changes 17.37 cm and −17.46 cm, respectively. The maximum and minimum Poyang Lake area differences exceeded 2700 km2. The estimated terrestrial water storage changes in Poyang Lake derived from the three GRACE/GRACE-FO mascon solutions agreed well, with all correlation coefficients higher than 0.92. There was a significant positive correlation higher than 0.75 between the area and TWS changes derived from the two independent monitoring techniques. Therefore, it is reasonable to conclude that combined remote sensing with satellite gravimetric techniques can better interpret the response of Poyang Lake to climate change from the aspects of water area and TWS changes more efficiently.

Significant contribution of the Tianshan lakes to their water storage and water resources

Significant contribution of the Tianshan lakes to their water storage and water resources

Application of One-Dimensional Hydrodynamic Coupling Model in Complex River Channels: Taking the Yongding River as an Example

River conditions are complex and affected by human activities. Various hydraulic structures change the longitudinal slope and cross-sectional shape of the riverbed, which has a significant impact on the simulation of water-head evolution. With continuous population growth, the hydrological characteristics of the Yongding River Basin have undergone significant changes. Too little or too much water discharge may be insufficient to meet downstream ecological needs or lead to the wastage of water resources, respectively. It is necessary to consider whether the total flow in each key section can achieve the expected value under different discharge flows. Therefore, a reliable computer model is needed to simulate the evolution of the water head and changes in the water level and flow under different flow rates to achieve efficient water resource allocation. A one-dimensional hydrodynamic coupling model based on the Saint-Venant equations was established for the Yongding River Basin. Different coupling methods were employed to calibrate the coupling model parameters, using centralised water replenishment data for the autumn of 2022, and the simulation results were verified using centralised water replenishment data for the spring of 2023. The maximum error of the water-head arrival time between different river sections was 4 h, and the maximum error of the water-head arrival time from the Guanting Reservoir to each key cross-section was 6 h. The maximum flow error was less than 5 m3/s, and the changing trend of the flow over time was consistent with the measured data. The model effectively solved the problem of low accuracy of the water level and flow calculation results when using the traditional one-dimensional hydrodynamic model to simulate the flow movement of complex river channels in the Yongding River. The output results of the model include the time when the water head arrives at the key section, the change process of the water level and flow of each section, the change process of the water storage of lakes and gravel pits, and the change process of the total flow and water surface area of the key section. This paper reports data that support the development of an ecological water compensation scheme for the Yongding River.

Diverse response of shallow lake water levels to decadal weather patterns in a heterogeneous glacial Boreal Plains landscape

AbstractTo examine the relative controls of landscape and climate on spatial variability, we measured water level dynamics of shallow lakes over two decades that represent both the heterogeneity of surficial geology classifications, and thus the potential range in surface and groundwater connectivity, and the long‐term weather patterns of the Boreal Plain hydrogeoclimatic setting. Large ranges in shallow lakes water levels (between 0.25 and 2 m) were observed corresponding to extremes in precipitation relative to the long‐term mean precipitation over the study period. We found low concurrence in water level dynamics among four detailed study lakes that received the same meteorological weather signal, but were located in different surficial geology texture classifications that incorporated important landscape parameters associated with lake water balance and storage. Surficial geology classification alone did not, however, distinguish between different ranges in lake water level measured in a broader synoptic survey of 26 lakes across the region. Thus, simple surficial geology classifications cannot alone be applied to classify Boreal Plain lake water level dynamics and other controls, notably landscape position, must also be considered. We further show that inter‐annual variability in lake water levels was significantly greater than seasonal variability in this hydrogeoclimatic setting. This emphasizes the need for studies of sufficient length to capture weather extremes that include periods of wetting and drying, and demonstrates how observed magnitudes of water level variability, and lake function, can be an artefact of study length and initiation date. These findings provide a foundation to test and calibrate conceptual understanding of the wider controls of lake water levels to form holistic frameworks to mitigate ecological and societal impacts due to hydrological changes under climate and anthropogenic disturbance within and between hydrogeoclimatic settings.

2018–2022年青海省主要湖泊蓄水量时空变化数据集

Qinghai Province is an important ecological function area, which is located in the inland of Northwest China. Qinghai Province is abundant in the total amount of water resource, but the spatial-temporal distribution of water resource in Qinghai Province is extremely uneven. Moreover, due to the factors such as climate and geographical environment, most lakes lack monitoring for a long time. As a significant carrier of surface water resource, lakes are important indicators for studying the impact of climate change and human activities on the water cycle process. The domestic GF-1 and GF-6 satellites have the ability to observe the earth repeatedly for a period of 2 days by collaborating, thus the surface water area can be obtained at high frequency. A high-precision surface water level can be acquired by ICESat-2, which has centimeter-level height measurement accuracy. The water area derived from GF-1/6 and water level derived from ICESat-2 were adopted to build the models for monitoring spatial-temporal variation of water storage of lakes in Qinghai Province. We developed a dataset of spatial-temporal variation of lake water storage in Qinghai Province during 2018–2022 via the models. The monitoring accuracy of the dataset had been verified with an overall accuracy better than 93%, which meets the needs of remote sensing monitoring of spatial-temporal variation of lake water storage. The dataset contains a total of 60 monthly storage variation of 33 lakes an area of more than 30 km2 in Qinghai Province during 2018–2022. These lakes are mainly distributed in the west, north and southeast of Qinghai Province. The dataset can provide basic data support for lake, hydrological and climate change process monitoring, dynamic evaluation of water resources, and optimization of water resources management and scheduling in Qinghai Province.

Predicting Future Lake Water Storage Changes on the Tibetan Plateau under Different Climate Change Scenarios

The variation of lake water storage is an important indicator for studying both climate change and ecological environment changes. Previous studies have mainly focused on the lake storage changes in recent decades, and predicting future lake storage changes on the Tibetan Plateau under climate change scenarios remains a crucial gap. We addressed this gap by establishing prediction models for water storage changes in nine lakes using historical water storage and climate data from the past 29 years and predicting the water storage changes for the next 80 years under three scenarios based on Phase 6 of the Coupled Model Intercomparison Project (CMIP6) data. The Quantile-mapping (QM) method was applied to correct the precipitation data of CMIP6 with assimilated data. The results indicated that the prediction model performed well, with high correlation (R2 > 0.7 for the training set) and low mean absolute error (MSE < 0.1 km3). The results suggest that most lakes will experience a slight increase in water storage until 2050, followed by a rapid rise until 2100 under all three SSP (Shared Socioeconomic Pathways) scenarios, including SSP126, SSP245, and SSP585. By the end of the century, the total projected increase in lake water storage is estimated to be 189.676 ± 16.266 km3, 191.762 ± 10.683 km3, and 186.212 ± 6.441 km3 until 2100, respectively.

GloLakes: water storage dynamics for 27 000 lakes globally from 1984 to present derived from satellite altimetry and optical imaging

Abstract. Measuring the spatiotemporal dynamics of lake and reservoir water storage is fundamental for assessing the influence of climate variability and anthropogenic activities on water quantity and quality. Previous studies estimated relative water volume changes for lakes where both satellite-derived extent and radar altimetry data are available. This approach is limited to only a few hundred lakes worldwide and cannot estimate absolute (i.e. total volume) water storage. We increased the number of measured lakes by a factor of 300 by using high-resolution Landsat and Sentinel-2 optical remote sensing and ICESat-2 laser altimetry, in addition to radar altimetry from the Topex/Poseidon; Jason-1, Jason-2 and Jason-3; and Sentinel-3 and Sentinel-6 instruments. Historical time series (1984–2020) of water storage could be derived for more than 170 000 lakes globally with a surface area of at least 1 km2, representing 99 % of the total volume of all water stored in lakes and reservoirs globally. Specifically, absolute lake volumes are estimated based on topographic characteristics and lake properties that can be observed by remote sensing. In addition to that, we also generated relative lake volume changes solely based on satellite-derived heights and extents if both were available. Within this dataset, we investigated how many lakes can be measured in near real time (2020–current) in basins worldwide. We developed an automated workflow for near-real-time global lake monitoring of more than 27 000 lakes. The GloLakes historical and near-real-time lake storage dynamics data from 1984 to current are publicly available through https://doi.org/10.25914/K8ZF-6G46 (Hou et al., 2022c) and a web-based data explorer (http://www.globalwater.online, last access: 12 December 2023).

A dataset of lake level changes in China between 2002 and 2023 using multi-altimeter data

ABSTRACT Lake water levels are an important indicator of water balance and water cycles, and are essential for climate and environmental change studies and water resource evaluation. Currently, lake level measurements are scarce or inconsistent throughout the country, and traditional gauge measurements of many lakes are not feasible, so satellite altimetry is a vital alternative to gauge lake levels. However, the accuracy and sampling frequency of lake level time series are usually low because of time and space coverage limitations; therefore, it is necessary to utilize multi-altimeter data to monitor lake levels and obtain lake level changes over long time series. In this study, we extracted the water level changes in 988 lakes (>10 km2) in China between 2002 and 2023 based on ICESat/-2, Cryosat-2, Jason-1/2/3, and Sentinel-3A/3B altimetry data using waveform retracking, lake level extraction, lake level time series construction, the fusion of multi-altimeter lake level time series, and outlier removal. A total of 55% of the lakes in this dataset have been monitored for more than 10 years, and 34% have more than 12 times the annual average water level monitoring. At the same time, in situ data from 21 lakes were used for validation, and the average root mean square error (RMSE) for each of the datasets of ICESat/-2, Cryosat-2, Jason-1/2/3, and Sentinel-3A/3B versus the in situ lake levels are 0.223 m, 0.163 m, 0.207 m, 0.596 m, 0.295 m, 0.275 m, 0.243 m, and 0.317 m, respectively, and the mean RMSE of the fused lake levels reaches 0.332 m. During the monitoring period, the water levels in Chinese lakes generally increased. The overall annual average rate of change at the 20 and 10-year scales was 0.123 m/a and 0.151 m/a, respectively, among which the overall water levels in large lakes increased significantly. The lakes with a faster rate of decline in the water level were primarily small. The water storage in each lake region in China shows an upward trend, with the most significant increase in the Tibetan Plateau region, where the average annual water level change rate has remained above 0.15 m/a over the past two decades. This dataset has high spatiotemporal coverage and accuracy and can support the estimation of changes in lake water storage, analysis of lake level trends, plateau flooding, and the relationship between lake ecosystems and water resources.

Calculation of Bosten Lake Water Storage Based on Multiple Source Remote Sensing Imagery

Calculation of Bosten Lake Water Storage Based on Multiple Source Remote Sensing Imagery

Characterizing the Water Storage Variation of Kusai Lake by Constructing Time Series from Multisource Remote Sensing Data

In September 2011, Zhuonai Lake (ZL) in the northeast of Hoh Xil (HX) on the Qinghai–Tibet Plateau (QTP) broke out. The outburst event seriously changed the environmental hydraulics in this region. Due to the insufficient temporal resolution of observations, it is challenging to assess the impact of this event on short-period variations of water volumes in three lakes downstream of ZL. Combining multisource remote sensing data, we constructed long and high-temporal-resolution time series for the lake level, area, and lake water storage (LWS) of Kusai Lake (KL) to characterize the variabilities before and after the outburst. The water level, area, and LWS time series contain 1051 samples from 1990 to 2022, with uncertainties of 0.16 m, 2.5 km2, and 0.016 km3, respectively. The accuracies verified using the Database for Hydrological Time Series of Inland Waters (DAHITI) are 0.26 m, 2.64 km2, and 0.08 km3 for water level, area, and LWS, respectively. We characterized the LWS variations during the past 30 years based on the high temporal resolution LWS time series. Before the outburst, the 1-year and 3.5-year variations dominated the LWS time series, and there was no obvious semi-annual signal. After the outburst, the 3.5-year variation disappeared, and a strong semi-annual oscillation was observed. From 2012 to 2015, the periodic LWS variations in KL were disturbed by the ZL outburst and the subsequent outflow of KL led by the outburst. Regular cyclic signals have been restored since 2016, with an amplified annual fluctuation. By analysis, precipitation, evaporation, and glacier area change are excluded as driving factors of the pattern change in LWS variations of KL. It can be concluded that the altered recharge pattern of KL triggered by the outburst directly resulted in the observed changes in TWS behavior. For the first time, we identified the periodic patterns of LWS variations of KL during the past 30 years and revealed that the ZL outburst event significantly influenced these patterns. This finding contributes to the comprehensive understanding of the effects of the ZL outburst on downstream lake dynamics. Furthermore, the presented procedure for constructing long and high-resolution time series of LWS allows for monitoring and characterizing the short-period variabilities of Tibetan lakes that lack hydrological data.

Mapping inundated bathymetry for estimating lake water storage changes from SRTM DEM: A global investigation

Mapping inundated bathymetry for estimating lake water storage changes from SRTM DEM: A global investigation

Lake Evaporation and Its Effects on Basin Evapotranspiration and Lake Water Storage on the Inner Tibetan Plateau

AbstractEffects of lake evaporation (EW) on basin evapotranspiration (ETB) and lake water storage change (LWSC) at lake‐basin scale have never been reported for most basins on the inner Tibetan Plateau (IB). In this study, EW of 118 large lakes in 95 closed lake‐basins were estimated, and its effects on ETB and LWSC over 2001–2018 were examined using a derivative‐guided framework from the aspects of EW amount, rate, trend slope and inter‐annual variability. We found that EW amount has a high effect (17%) on regional ETB amount compared to the average lake area ratio (α) (∼5%), and the effect has increased significantly (2%/10 a). The spatial pattern of the effect is mainly controlled by α, and the increasing trend of α (0.6%/10 a) also dominated the increasing trend in regional ETB rate (0.30 mm/a) though with large spatial heterogeneity. Variance in α and EW rate have a minor effect (∼3%) on ETB variance, especially for the basins with lower α. The combination of quasi lake inflow (RL, 41%) and lake surface precipitation (PW, 16%) offset the depletion of EW (−43%), resulting in the surplus of regional lake water (LWSC > 0). The increase in EW mount, which is mainly from lake area expansion (90%), caused a decreasing trend in LWSC (i.e., slower growth rate) with a contribution of −59%. This suggests a negative feedback between lake area expansion and EW amount in the IB, and the feedback may continue with the predicted area increases.

Estimation and attribution of water storage changes in regulated lakes based on Budyko’s supply–demand framework

Study regionLake Dianchi, southwest China Study focusUnderstanding changes in lake water storage (LWS) and its attribution to climate change and human activities is essential for adaptive management of water resources in regulated lakes. Although altimetric measurements, whether ground- or satellite-based, can reproduce LWS dynamics, they do not provide sufficient information on why LWS is changing. Neither the water balance method nor detailed hydrological modeling can capture exactly LWS change in most regulated lakes largely because of the scarcity of water output observations. Here, a simple water balance model, following Budyko’s supply–demand framework, was proposed to estimate LWS change in regulated lakes without the need for water output information. The elasticity of LWS was theoretically derived from the Budyko-type model to attribute LWS change to its main driving factors. New hydrological insights for the regionApplication of the proposed model to the Lake Dianchi for the period 1964–2022 indicated that the model accurately captured the variations of annual LWS in Lake Dianchi with a relative root mean square error of 4.23%, and correlation coefficient of 0.77. The attribution results suggested that lake regulation strategies were the chief determinant of LWS change in Lake Dianchi, while water transfer had a limited contribution. This study suggests that complex hydrological behavior in regulated lakes can be explored using Budyko's supply–demand framework with a low requirement for data.