Evaporative water loss of 1.42 million global lakes

Multivariate extremes in lakes

Extreme within-lake conditions have the potential to exert detrimental effects on lakes. Here we use satellite observations to investigate how the occurrence of multiple types of extremes, notably algal blooms, lake heatwaves, and low lake levels, have varied in 2724 lakes since the 1980s. Our study, which focuses on bloom-affected lakes, suggests that 75% of studied lakes have experienced a concurrent increase in at least two of the extremes considered (27% defined as having a notable increase), with 25% experiencing an increase in frequency of all three extremes (5% had a notable increase). The greatest increases in the frequency of these extremes were found in regions that have experienced increases in agricultural fertilizer use, lake warming, and a decline in water availability. As extremes in lakes become more common, understanding their impacts must be a primary focus of future studies and they must be carefully considered in future risk assessments.

Global WaterPack - The development of global surface water over the past 20 years at daily temporal resolution

Open surface water across the globe is essential for many life forms and is an important source for human settlements, agriculture, and industry. The presence and variation in time and space is influenced by different natural conditions (e.g. climate, topography, geology) and human use (e.g. irrigation, flood protection). The information on the spatial and temporal distribution of open surface water is fundamental for many disciplines and is also required as an essential parameter for hydrological and climatological modelling. Here, we present a dataset derived from satellite earth observation, which is based on more than 6.3 million single MODIS products with a volume of approx. 300 TB. The resulting dataset reflects the situation of open surface water on a global scale for each day over the time period from 2003 to 2022 at a spatial resolution of 250 m. The dataset enables the analysis of the development of lake and reservoir surface areas, freezing cycles, and inundation areas.

Biotic and Abiotic Regulations of Carbon Fixation into Lacustrine Sediments with Different Nutrient Levels

Lake sediments play a critical role in organic carbon (OC) conservation. However, the biogeochemical processes of the C cycle in lake ecosystems remain limitedly understood. In this study, Fe fractions and OC fractions, including total OC (TOC) and OC associated with iron oxides (TOCFeO), were measured for sediments from a eutrophic lake in China. The abundance and composition of bacterial communities encoding genes cbbL and cbbM were obtained by using high-throughput sequencing. We found that autochthonous algae with a low C/N ratio together with δ13C values predominantly contributed to the OC burial in sediments rather than terrigenous input. TOCFeO served as an important C sink deposited in the sediments. A significantly positive correlation (r = 0.92, p < 0.001) suggested the remarkable regulation of complexed FeO (Fep) on fixed TOC fractions, and the Fe redox shift triggered the loss of deposited OC. It should be noted that a significant correlation was not found between the absolute abundance of C-associating genera and TOC, as well as TOCFeO, and overlying water. Some rare genera, including Acidovora and Thiobacillus, served as keystone species and had a higher connected degree than the genera with high absolute abundance. These investigations synthetically concluded that the absolute abundance of functional genes did not dominate CO2 fixation into the sediments via photosynthesis catalyzed by the C-associating RuBisCO enzyme. That is, rare genera, together with high-abundance genera, control the C association and fixation in the sediments.

Profiling dynamics of the Southeast Asia's largest lake, Tonle Sap Lake

Lakes, as vital components of the Earth's ecosystem with crucial roles in global biogeochemical cycles, are experiencing pervasive and irreparable worldwide losses due to natural factors and intensive anthropogenic interferences. In this study, we investigated the long-term dynamic patterns of the Tonle Sap Lake, the largest freshwater lake in the Mekong River Basin, using a series of hydrological data and remote sensing images between 2000 and 2020. Our findings revealed a significant decline in the annual average water level of the lake by approximately 2.1 m over 20 years, accompanied by an annual average reduction in surface area of about 1400 km2. The Tonle Sap Lake exhibited episodic declines in water level and surface area, characterized by the absence of flooding during the flood season and increasing aridity during the dry season. Furthermore, the shoreline of the lake has significantly advanced towards the lake in the northwestern and southern regions during the dry season, primarily due to sedimentation-induced shallowing of the lake edge depth and decreased water levels. In contrast, lake shorelines in the eastern region remained relatively stable due to the constructed embankments for the protection of the cultivated farmland. While the seasonal fluctuations of the Tonle Sap Lake are regulated by regional precipitation in the Mekong River Basin, the prolonged shrinking of the lake can be mainly ascribed to intensive anthropogenic activities. The interception of dams along the upper Mekong River has resulted in a decrease in the inflow to Tonle Sap Lake, exacerbating its shrinkage. Moreover, there are minor impacts from agricultural land expansion and irrigation on the lake. This study highlights the driving forces behind the evolution of Tonle Sap Lake, providing valuable information for lake managers to develop strategies aimed at conserving and restoring the ecological integrity of the Tonle Sap Lake.

Using Knowledge-Guided Machine Learning To Assess Patterns of Areal Change in Waterbodies across the Contiguous United States

Lake and reservoir surface areas are an important proxy for freshwater availability. Advancements in machine learning (ML) techniques and increased accessibility of remote sensing data products have enabled the analysis of waterbody surface area dynamics on broad spatial scales. However, interpreting the ML results remains a challenge. While ML provides important tools for identifying patterns, the resultant models do not include mechanisms. Thus, the "black-box" nature of ML techniques often lacks ecological meaning. Using ML, we characterized temporal patterns in lake and reservoir surface area change from 1984 to 2016 for 103,930 waterbodies in the contiguous United States. We then employed knowledge-guided machine learning (KGML) to classify all waterbodies into seven ecologically interpretable groups representing distinct patterns of surface area change over time. Many waterbodies were classified as having "no change" (43%), whereas the remaining 57% of waterbodies fell into other groups representing both linear and nonlinear patterns. This analysis demonstrates the potential of KGML not only for identifying ecologically relevant patterns of change across time but also for unraveling complex processes that underpin those changes.

Assessing size shifts amidst a warming climate in lakes recharged by the Asian Water Tower through satellite imagery

Recent studies indicate that the Asian Water Tower (AWT) is at risk due to climate change, which can negatively impact water and food security in Asia. However, there is a lack of comprehensive information on lakes' spatial and temporal changes in this region. This information is crucial for understanding the risk magnitude and designing strategies. To fill this research gap, we analyzed 89,480 Landsat images from 1977 ± 2 to 2020 ± 2 to investigate the changes in the size of lakes recharged by the AWT. Our findings showed that out of the 209 lakes larger than 50 km2, 176 (84 %) grew during the wet season and 167 (81 %) during the dry season. 74 % of expanded lakes are located in the Inner Tibetan Plateau (TP) and Tarim basins. The lakes that shrank are found mainly in the Helmand, Indus, and Yangtze basins. Over the entire period, the area of shrinkage (55,077.028 km2 in wet season, 53,986.796 km2 in dry) markedly exceeded expansion (13,000.267 km2 in wet, 11,038.805 km2 in dry), with the drastic decline of the Aral Sea being a major contributor to shrinkage, accounting for 90 % of the total loss. From 1990 ± 2 to 2020 ± 2, alpine lakes mostly expanded, plain lakes mostly shrank, with the opposite trend from 1977 ± 2 to 1990 ± 2. Glacial loss and permafrost thawing under global warming in the Inner TP, Tarim Interior, Syr Darya, and Mekong basins were strongly correlated with lake expansion. However, permafrost discontinuities may prevent significant growth of lakes in the Indus and Ganges basins despite increased recharge. Our findings point to the prominence of the risk the lakes recharged by AWT face. Taking immediate action to manage these risks and adaptation is crucial as the AWT retreats and lake recharges are slowed.

Transitioning from MODIS to VIIRS Global Water Reservoir Product

Reservoirs play a crucial role in regulating water availability and enhancing water security. Here, we develop NASA's Visible Infrared Imaging Radiometer Suite (VIIRS) based Global Water Reservoir (GWR) product, consisting of measurements of reservoir area, elevation, storage, evaporation rate, and evaporation loss for 164 large global reservoirs. The dataset is available at 8-day and monthly temporal resolutions. Since the Moderate Resolution Imaging Spectroradiometer (MODIS) is close to the end of its life, we further evaluated the consistency between MODIS and VIIRS-based GWR to ensure continuity to the 20+ year MODIS GWR product. Independent assessment of VIIRS reservoir storage (8-day) retrievals against in-situ measurements shows an average of R2 = 0.84, RMSE = 0.47 km3, and NRMSE = 16.45%. The evaporation rate has an average of R2 = 0.56, RMSE = 1.32 mm/day, and NRMSE = 28.14%. Furthermore, results show good consistency (R2 ≥ 0.90) between the VIIRS and MODIS-based product components, confirming that long-term data continuity can be achieved. This dataset can provide valuable insights for long-term trend analysis, hydrological modeling, and understanding hydroclimatic extremes in the context of reservoirs.

National-scale remotely sensed lake trophic state from 1984 through 2020

Lake trophic state is a key ecosystem property that integrates a lake's physical, chemical, and biological processes. Despite the importance of trophic state as a gauge of lake water quality, standardized and machine-readable observations are uncommon. Remote sensing presents an opportunity to detect and analyze lake trophic state with reproducible, robust methods across time and space. We used Landsat surface reflectance data to create the first compendium of annual lake trophic state for 55,662 lakes of at least 10 ha in area throughout the contiguous United States from 1984 through 2020. The dataset was constructed with FAIR data principles (Findable, Accessible, Interoperable, and Reproducible) in mind, where data are publicly available, relational keys from parent datasets are retained, and all data wrangling and modeling routines are scripted for future reuse. Together, this resource offers critical data to address basic and applied research questions about lake water quality at a suite of spatial and temporal scales.

Evaporation from the hypersaline Aral Sea in Central Asia

The Aral Sea, once the world's fourth largest lake, has shrunk by 91 % in area and 95 % in volume since 1960s. The shrinkage has resulted in a notable increase in water salinity, which may affect the surface evaporation. Despite previous studies, the hydrological consequences of salinity in the Aral Sea have often been overlooked. In this study, we investigated the impact of water surface salinity on evaporation by employing a water activity-based Penman salinity equation, and we explored its effects on the water balance of the Aral Sea. We established an empirical relationship between the water activity and water salinity. The results indicated that the evaporation rates were overestimated when salinity effects were excluded from evaporation estimations in Aral Sea, especially for the hypersaline South Aral Sea. During the period from 2000 to 2020, the evaporation of a 16 km3 water volume could have been overestimated if the salinity effects were ignored. When calculated from updated evaporation and the lake water balance, the inflow from the middle reaches to the Aral Sea showed significant deviations from the existing data sources. We emphasize that, the observed runoff at stations is higher than our estimated inflow.

Spatiotemporal lake area changes influenced by climate change over 40 years in the Korean Peninsula

Water resources in lakes of the Korean Peninsula play a significant role in society and ecosystems in both South and North Korea. This study characterized spatiotemporal changes in the lake area during the dry season (March-May) in the Korean Peninsula over the last 40 years. The satellite images (Landsat 5-9) were used to derive annual areas of 975 lakes during the dry season from 1984 to 2023. Our analysis indicated that the MNDWI is the optimal remote sensing-based index for delineating lake areas in the Korean Peninsula, with an overall accuracy of 92.3%. Based on the selected index, the total lake areas of the dry seasons have increased from 1070.7 km2 in 1984 to 1659.3 km2 in 2023, mainly due to newly constructed dam reservoirs. While the detailed changes in lake area vary, we found divergent results based on their sizes. The large lakes (> 10 km2) showed their area increased by 0.0473 km2 (0.1%) every year and have more influences from climate change. On the contrary, the small lakes (≤ 10 km2) have area decreases by 0.0006-0.006 km2 (0.15-0.5%) every year and have less influence from climate change. This study shows that the spatiotemporal lake area changes are determined by either climate change or human activity.

Gene co-expression networks unravel the molecular responses of freshwater hydrophytes to combined stress of salinity and cadmium

Salinization in freshwater lakes is becoming a serious global environmental problem, especially in lakes of plateaus such as south-western plateau of China. However, limited information is available about the molecular response of freshwater hydrophytes to salinity under multiple stress. In the present study, a weighted gene co-expression network (WGCNA) was used to identify the modules of co-expressed genes in the physiological and biochemical indicators of Pistia stratiotes to determine its molecular response to salinity (NaCl) alone and when combined with cadmium (Cd). The physiological and biochemical indicators showed that P. stratiotes improved its salt tolerance by enhancing photosynthetic abilities, reducing oxidative stress, and inducing osmoprotectant generation. Morever, addition of NaCl reduced the Cd accumulation in P. stratiotes. Transcriptome and WGCNA analysis revealed that the pathways of alpha-linolenic acid metabolism, ribosomal, flavonoid biosynthesis, and phenylpropanoid biosynthesis were significantly enriched in both treatments. Genes associated with photosynthesis-antenna proteins, nitrogen metabolism, and the acid cycle pathways were only expressed under salinity stress alone, while the proteasome pathway was only significantly enriched in the combined salinity and Cd treatment. Our findings provide novel insights into the effects of salinization on aquatic plants in freshwater ecosystems and the management of aquatic ecosystems under global change.

Remotely sensed terrestrial open water evaporation

Terrestrial open water evaporation is difficult to measure both in situ and remotely yet is critical for understanding changes in reservoirs, lakes, and inland seas from human management and climatically altered hydrological cycling. Multiple satellite missions and data systems (e.g., ECOSTRESS, OpenET) now operationally produce evapotranspiration (ET), but the open water evaporation data produced over millions of water bodies are algorithmically produced differently than the main ET data and are often overlooked in evaluation. Here, we evaluated the open water evaporation algorithm, AquaSEBS, used by ECOSTRESS and OpenET against 19 in situ open water evaporation sites from around the world using MODIS and Landsat data, making this one of the largest open water evaporation validations to date. Overall, our remotely sensed open water evaporation retrieval captured some variability and magnitude in the in situ data when controlling for high wind events (instantaneous: r2 = 0.71; bias = 13% of mean; RMSE = 38% of mean). Much of the instantaneous uncertainty was due to high wind events (u > mean daily 7.5 m·s-1) when the open water evaporation process shifts from radiatively-controlled to atmospherically-controlled; not accounting for high wind events decreases instantaneous accuracy significantly (r2 = 0.47; bias = 36% of mean; RMSE = 62% of mean). However, this sensitivity minimizes with temporal integration (e.g., daily RMSE = 1.2-1.5 mm·day-1). To benchmark AquaSEBS, we ran a suite of 11 machine learning models, but found that they did not significantly improve on the process-based formulation of AquaSEBS suggesting that the remaining error is from a combination of the in situ evaporation measurements, forcing data, and/or scaling mismatch; the machine learning models were able to predict error well in and of itself (r2 = 0.74). Our results provide confidence in the remotely sensed open water evaporation data, though not without uncertainty, and a foundation by which current and future missions may build such operational data.

Satellites reveal widespread decline in global lake water storage

Climate change and human activities increasingly threaten lakes that store 87% of Earth's liquid surface fresh water. Yet, recent trends and drivers of lake volume change remain largely unknown globally. Here, we analyze the 1972 largest global lakes using three decades of satellite observations, climate data, and hydrologic models, finding statistically significant storage declines for 53% of these water bodies over the period 1992-2020. The net volume loss in natural lakes is largely attributable to climate warming, increasing evaporative demand, and human water consumption, whereas sedimentation dominates storage losses in reservoirs. We estimate that roughly one-quarter of the world's population resides in a basin of a drying lake, underscoring the necessity of incorporating climate change and sedimentation impacts into sustainable water resources management.

Hydrological Controls on Dissolved Organic Matter Composition throughout the Aquatic Continuum of the Watershed of Selin Co, the Largest Lake on the Tibetan Plateau

Alpine river and lake systems on the Tibetan Plateau are highly sensitive indicators and amplifiers of global climate change and important components of the carbon cycle. Dissolved organic matter (DOM) encompasses organic carbon in aquatic systems, yet knowledge about DOM variation throughout the river-lake aquatic continuum within alpine regions is limited. We used optical spectroscopy, ultrahigh-resolution mass spectrometry (Fourier transform ion cyclotron resonance mass spectrometry), and stable water isotopic measurements to evaluate linkages between DOM composition and hydrological connection. We investigated glacial influences on DOM composition throughout the watershed of Selin Co, including upstream glacier-fed rivers and downstream-linked lakes. We found that the dissolved organic carbon concentration increased, whereas specific ultraviolet absorbance (SUVA₂₅₄) decreased along the river-lake continuum. Relative to rivers, the downstream lakes had low relative abundances of polyphenolic and condensed aromatic compounds and humic-like substances but increased relative abundances of aliphatics and protein-like compounds. SUVA₂₅₄ decreased while protein-like components increased with enriched stable water isotope δ²H-H₂O, indicating that DOM aromaticity declined while autochthonous production increased along the flow paths. Glacier meltwater contributed to elevated relative abundances of aliphatic and protein-like compounds in headwater streams, while increased relative abundances of aromatics and humic-like DOM were found in glacier-fed lakes than downstream lakes. We conclude that changes in hydrological conditions, including glacier melt driven by a warming climate, will significantly alter DOM composition and potentially their biogeochemical function in surface waters on the Tibetan Plateau.

Association between temperature variability and global meningitis incidence

BACKGROUND

Meningitis can cause devastating epidemics and is susceptible to climate change. It is unclear how temperature variability, an indicator of climate change, is associated with meningitis incidence.

METHODS

We used global meningitis incidence data along with meteorological and demographic data over 1990-2019 to identify the association between temperature variability and meningitis. We also employed future (2020-2100) climate data to predict meningitis incidence under different emission levels (SSPs: Shared Socioeconomic Pathways).

RESULTS

We found that the mean temperature variability increased by almost 3 folds in the past 30 years. The largest changes occurred in Australasia, Tropical Latin America, and Central Sub-Saharan Africa. With a logarithmic unit increase in temperature variability, the overall global meningitis risk increases by 4.8 %. Australasia, Central Sub-Saharan Africa, and High-income North America are the most at-risk regions. Higher statistical differences were identified in males, children, and the elderly population. Compared to high-emission (SSP585) scenario, we predicted a median reduction of 85.8 % in meningitis incidence globally under the low-emission (SSP126) climate change scenario by 2100.

CONCLUSION

Our study provides evidence for temperature variability being in association with meningitis incidence, which suggests that global actions are urgently needed to address climate change and to prevent meningitis occurrence.