Lake Storage Research Articles

СОСТОЯНИЕ КАРБОНАТНО-КАЛЬЦИЕВОГО РАВНОВЕСИЯ КАЗАХСТАНСКОЙ ЧАСТИ БАССЕЙНА РЕКИ ЕРТИС

The materials of our own studies of the carbonate-calcium equilibrium in the Kazakh part of the Ertis river basin, conducted in July 2023, are presented. It has been established that the rivers and lakes of the Ertis basin differ in the state of carbonate-calcium equilibrium. This difference is due to a number of factors: carbonate alkalinity, total mineralization, pH value, water temperature, which in turn depend on the physical and geographical conditions of the region. The Kara Ertis River, its tributaries and Ertis itself in all areas have water unsaturated with calcium carbonate, containing aggressive CO2 in concentrations (0.02...5.50 mg/dm3), which do not pose a danger to concrete structures on Portland cement. The amount of supersaturation of CaCO3 water in rivers ranges from 0.03...0.92. In the isolated lakes Orlovskoye, Kurkol and Eski Ertis, an excess of the main equilibrium indicators was noted compared to rivers, the water in them becomes supersaturated with calcium carbonate by an average of 1.16...5.82 times. The water of the Balkyldak wastewater storage lake does not contain aggressive CO2, however, according to the content of normalized magnesium ions, chloride and sulfate ions, the water shows an aggressive effect on the cement stone of hydraulic structures of varying degrees.

Iron as a precursor of aggregation and vector of organic carbon to sediments in a boreal lake

AbstractWhile organic matter (OM) interactions in the water column prevent iron (Fe) precipitation and sedimentation, Fe also acts as a precursor of aggregation and a vector of OM to sediments. This study aims to characterize Fe–OM interactions to understand the role of Fe in promoting aggregation and transport of OM. Samples of Fe and OM were collected from water, settling material, and sediment along a gradient starting from the inlet and continuing offshore within a boreal lake. Fe speciation was determined using X-ray absorption spectroscopy (XAS), and the chemical composition of OM was assessed using Diffuse reflectance infrared Fourier transform spectroscopy (DRIFT IR) and Nuclear magnetic resonance spectroscopy (NMR). The results show a decrease in Fe and OM concentrations in the water column with increasing distance from the inlet. Winter sampling revealed a shift in Fe speciation from dominance of organically complexed Fe to an increase in Fe(oxy)hydroxide, accompanied by a loss of aromatic and carboxylate function of OM. Summer sampling revealed no significant changes along the gradient, with Fe(oxy)hydroxide and carbohydrates dominating the water phase. Interestingly, settling particles and surface sediments were dominated by Fe(oxy)hydroxides and aliphatic OM. We propose that phototransformation may be an important process that influences the interaction between Fe and OM and, as a consequence, their fate along the spatial gradient. Our study suggests a photochemically induced loss of carboxylate groups, reflected by an increased carbohydrate-to-carboxylate ratio along the gradient, particularly in winter, and generally lower levels during summer. Loss of carboxylate function promotes the formation of Fe(oxy)hydroxides, which in turn, facilitates the aggregation and sinking of OM, particularly aliphatic components. These insights contribute to a broader understanding of carbon cycling and storage in lakes. Future studies should assess the significance of photochemical processes to OM burial and it how may change given trends in Fe and OM in northern regions.

Substantial increase of organic carbon storage in Chinese lakes

Previous studies typically assumed a constant total organic carbon (OC) storage in the lake water column, neglecting its significant variability within a changing world. Based on extensive field data and satellite monitoring techniques, we demonstrate considerable spatiotemporal variability in OC concentration and storage for 24,366 Chinese lakes during 1984–2023. Here we show that dissolved OC concentration is high in northwest saline lakes and particulate OC concentration is high in southeast eutrophic lakes. Along with increasing OC concentration and water volume, dissolved and particulate OC storage increase by 44.6% and 33.5%, respectively. Intensified human activities, water input, and wind disturbance are the key drivers for increasing OC storage. Moreover, higher OC storage further leads to an 11.0% increase in nationwide OC burial and a decrease in carbon emissions from 71.1% of northwest lakes. Similar changes are occurring globally, which suggests that lakes are playing an increasingly important role in carbon sequestration.

Hydrogen storage with gravel and pipes in lakes and reservoirs

Climate change is projected to have substantial economic, social, and environmental impacts worldwide. Currently, the leading solutions for hydrogen storage are in salt caverns, and depleted natural gas reservoirs. However, the required geological formations are limited to certain regions. To increase alternatives for hydrogen storage, this paper proposes storing hydrogen in pipes filled with gravel in lakes, hydropower, and pumped hydro storage reservoirs. Hydrogen is insoluble in water, non-toxic, and does not threaten aquatic life. Results show the levelized cost of hydrogen storage to be 0.17 USD kg−1 at 200 m depth, which is competitive with other large scale hydrogen storage options. Storing hydrogen in lakes, hydropower, and pumped hydro storage reservoirs increases the alternatives for storing hydrogen and might support the development of a hydrogen economy in the future. The global potential for hydrogen storage in reservoirs and lakes is 3 and 12 PWh, respectively. Hydrogen storage in lakes and reservoirs can support the development of a hydrogen economy in the future by providing abundant and cheap hydrogen storage.

Migration of On-Premises Database to Cloud and Perform Explanatory Analytics on Sales Data

This paper explores the migration of an industrial company's sales database from its servers to the cloud using Microsoft Azure, emphasizing three unique aspects of the process. First, it integrates the Delta Lake format within Azure Data Lake Storage Gen2, which is critical for maintaining multiple versions of data securely and ensuring ACID compliance. Second, the paper addresses significant adoption challenges such as data security, recovery, and vendor lock-in. It provides practical advice and strategic insights to help organizations navigate the complexities of cloud migration. Third, it offers a comparative analysis of two cloud storage methods—serverless and dedicated pool storage. This analysis evaluates their performance, cost-effectiveness, and suitability for different workload sizes, providing valuable insights for selecting the optimal storage strategy. Overall, this study contributes to a deeper understanding of cloud migrations, emphasizing practical applications and strategic decision-making necessary for enhancing operational efficiency and effective data management in cloud environments.

Spatio-temporal variations and multi-scale correlations of climate, water, land, and vegetation resources over the past four decades in the Heihe River Basin

Study regionHeihe River Basin (HRB), Northwest China. Study focusThe study proposes an analytical scheme to identify trend, periodicity, and scale-correlation in climate, water, land, and vegetation resources over the past four decades using multivariate remote sensing data. New hydrological insights for the regionHeat and precipitation resources in the HRB have increased at rates of 14.27℃ yr−1 and 1.26 mm yr−1, respectively. The glacier area has decreased by 47.47 %. Additionally, the increase in upstream precipitation (2.82 mm yr−1) and glacier meltwater effectively replenishes runoff, soil water, and groundwater. The implementation of the ecological water diversion project (EWDP) in 2000 has contributed to enhancing runoff and lake storage capacity. The 9.28 % increase in vegetation cover (including cropland, forest, grassland, and shrubland) indicates an improvement in the hydrothermal conditions of the HRB. Additionally, the magnitude and direction of interactions among various natural resources vary across multiple spatial scales and time scales. The effect of hydrothermal coupling on vegetation is more prominent at the interdecadal scale. Vegetation growth in the upstream area is primarily influenced by thermal condition, while moisture plays a significant role in the midstream and downstream areas. Knowledge from this study contributes to the informed allocation of natural resources and offer policymakers valuable insights to enhance eco-environmental sustainability.

Understanding the environmental drivers of summer dissolved carbon in lakes on the Qinghai-Tibetan Plateau

How environmental factors affecting dissolved carbon remains unclear in lakes on the Qinghai-Tibetan Plateau (QTP), which limits the understanding of the lake carbon cycle. In this study, 60 lakes on the QTP in summer were investigated to clarify the variation in dissolved carbon, estimate dissolved carbon storage, and reveal how environmental factors affect the variation in dissolved carbon. The average dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) contents of 60 lakes on the QTP in summer were 12.78 mg/L and 103.66 mg/L, respectively. Salinity and total nitrogen were the important drivers of variations in DIC and DOC, respectively. Lake salinity and temperature were reduced only when precipitation was >50 mm, thus affecting the variations in lake dissolved carbon. Importantly, the elevation and area of the lake also significantly affected the variation in lake dissolved carbon. The total storage amounts of DOC and DIC in the 60 lakes on the QTP in summer were 58.94 Tg and 6.22 Tg, respectively. Lake area was the most direct factor influencing dissolved carbon storage in lakes on the QTP. Moreover, the TN and pH of the lake water also affected the DOC and DIC storage in the lakes, respectively. Interestingly, the lake pH at 9.1 was an important turning point that caused variations in lake DIC storage. Surprisingly, we found that rivers were able to transport 30 % of the DIC into QTP lakes and were the main source of DIC in the lakes in summer. The findings of this study clarify the sources of dissolved carbon and its drivers and improve our understanding of the carbon cycling processes in the lake system on the QTP.

A large-scale hydrological and hydrodynamic coupled model for flow routing in the Yangtze-Dongting system

In lowland alluvial river systems consisting of mainstream, distributaries, and floodplain lakes, the flow dynamics are characterized by changing backwater effects and seasonal water storage and release, and the bed morphology is unstable due to frequent sediment deposition and erosion. Hence, models that can accurately and efficiently simulate hydraulic interactions with low topographic data demands are required for such water systems. In this study, we present a coupled flow routing model for the Yangtze River-Dongting Lake system by coupling a 1D hydrodynamic model for the mainstream with hydrological models for distributaries and the lake. A new approach is proposed to generate a set of rating curves to represent the combined impacts of the inflow and outlet stage on the lake storage volume, thereby an innovative hydrological routing method fully considering backwater effects is established. Additionally, an implicit fully coupled algorithm is presented to integrate the hydrodynamic and hydrological models, which demonstrates ideal numerical stability and high computational efficiency. The coupled model is applied to flow routing in the Yangtze-Dongting system, with the Nash-Sutcliffe efficiency coefficients above 0.960, and most of the mean absolute error below 0.4 m (1000 m3/s) for stage (discharge). The model is also used to evaluate the impact of topographic changes during 1998–2016 on the flow process. The results indicate that the mainstream stage has decreased notably, while the reduction of the storage capacity of the lake is not yet remarkable. For the model proposed in this paper, only hydrological data and mainstream topographic data are necessary during model development, calibration, and application. In the context of continuous channel/lake bed adjustment in the middle reach of the Yangtze River Basin, the coupled model provides an effective tool for quantitatively evaluating the hydrological regime and flood process of a river system at a full scale.

Leveraging AI with Databricks and Azure Data Lake Storage

The integration of artificial intelligence (AI) with cloud-based analytics platforms has revolutionized data processing and decision-making. This research article explores the synergies between AI, Databricks, and Azure Data Lake Storage (ADLS), showcasing how organizations can harness AI capabilities to enhance data analytics workflows. Through a comprehensive analysis of real- world use cases, scalability assessments, performance optimizations, and cost efficiency evaluations, we demonstrate the transformative impact of AI-driven analytics on business outcomes.

Submerged Surface Area and Water Storage Volume of Hamrin Dam Lake Using Contour Lines

The predictions and warnings from drying up lakes and rivers are increasing nowadays, especially in Iraq, due to climatic changes and water flow reduction from neighboring countries. Consequently, this paper deals with monitoring the changes in submerged surface areas and Hamrin dam lake storage volume from December 2011 to the end of 2022. Hamrin Lake supplies Diyala province, Iraq, with irrigation water. Multitemporal satellite images were acquired from google earth pro and Earth Observation (EO) browsers. Triangular Irregular Network (TIN) layers generated contour lines through the ArcGIS environment. Volumes were calculated using the end area method. The results show that the water storage volume reached 1.8 billion cubic meters (bcm) in December 2016 and decreased to 12 million cubic meters in December 2021. Hamrin Lake lost 99% and 98% of its capacity relative to the normal water storage volume in 2021 and 2022, respectively. At normal storage, the maximum water volume of Hamrin Lake is about 3 bcm. The scarcity of irrigation water from Hamrin Lake causes decreasing agricultural areas, desertification, and people migrating to other regions.

СОВРЕМЕННАЯ ГИДРОХИМИЧЕСКАЯ ХАРАКТЕРИСТИКА ВОДНЫХ ОБЪЕКТОВ КАЗАХСТАНСКОЙ ЧАСТИ БАССЕЙНА Р. ЕРТИС

The article presents materials from our own research on the study of the distribution of the mineralization, ionic composition, hardness, dissolved gases and pH values in various components of the river ecosystem of the Kazakhstan part of the Ertis river basin in the summer of 2023. It has been established that the water of the Black Ertis river is ranked in terms of mineralization to ultra-fresh, the value of total hardness – to soft, the content and ratio of the main ions - to the carbonate class, calcium group, the second type. Within the Pavlodar region, the concentration of the main salt-forming ions in the water of the Ertis River increases on average by 1.7...2.4 times, the water becomes fresh, the Alekin water index remains CCaII throughout the entire flow. The mineralization of water in the floodplain lakes Orlovskoye, Staritsa, Kurkol differs little from the water of the river Irtysh. The value of all studied indicators in the water of the Ertis River, its tributaries and lakes does not exceed the maximum permissible concentration. The water of all studied water bodies, with the exception of the storage lake Balkyldak, in terms of the content of standardized main ions and mineralization, belongs to quality class 1, is suitable for all types of water use and corresponds to “very good” quality. The wastewater storage tank Balkyldak has water of high salinity (19.42 g/dm3), very hard, highly metamorphosed sodium chloride composition of the third type and it can be recommended for the extraction of bischofite, halite and gypsum.

Joint optimal operation of the South-to-North Water Diversion Project considering the evenness of water deficit

Abstract. Inter-basin water transfer projects are the main measure to address the water deficit crisis caused by uneven distribution of water resources. The current water transfer operation mainly tends to be present in areas with small water transfer costs and is prone to encounter the problem of spatial and temporal imbalances in water allocation. To address these issues, this paper defines a water deficit evenness index (WDEI), aimed at minimizing regional differences in water scarcity and sharing the pressure of water scarcity as a social demand objective. This index is incorporated into a joint optimization model for the Jiangsu section of the South-to-North Water Diversion Project (J-SNWDP), which comprises both the ecological objective of the total water deficit (TWD) and the economic objective of the pumping water (PW). Further, the Nondominated Sorting Genetic Algorithm III (NSGA-III) and multi-attribute decision-making were applied to solve the model and obtain an optimal operation strategy. The results showed the following: (1) the WDEI defined in this paper can mitigate the synchronized water scarcity in certain water users. In typical normal years (wet year and dry year), the WDEI shows a reduction of 94.2 % (81.8 %, 76.7 %) compared to the historical operation strategy. (2) The optimized operation strategy can significantly reduce TWD and PW by 82.06% (37.69 %, 52.36 %) and 45.13 % (3.25 %, 21.51 %) compared with the historical values, respectively, which can improve the water supply satisfaction and reduce the project cost. At the same time, the lake storage capacity of the optimal operation strategy performs well, and the water transfer efficiency of the river is significantly improved. (3) In this paper, targeted optimal operation strategies and potential ways to secure the project tasks are proposed for different natural flow. Overall, it is of great significance to study the water supply equity in the J-SNWDP to alleviate the concentrated water deficit in Jiangsu Province and other similar regions.

Integrated Hydrological Modeling for Watershed Analysis, Flood Prediction, and Mitigation Using Meteorological and Morphometric Data, SCS-CN, HEC-HMS/RAS, and QGIS

Flooding is a natural disaster with extensive impacts. Desert regions face altered flooding patterns owing to climate change, water scarcity, regulations, and rising water demands. This study assessed and predicted flash flood hazards by calculating discharge volume, peak flow, flood depth, and velocity using the Hydrologic Engineering Centre-River Analysis System and Hydrologic Modelling System (HEC-HMS and HEC-RAS) software. We employed meteorological and morphological data analyses, incorporating the soil conservation service (SCS) curve number method for precipitation losses and the SCS-Hydrograph for runoff transformation. The model was applied to two drainage basins (An-Nawayah and Al-Rashrash) in southeastern Cairo, Egypt, which recently encountered several destructive floods. The applied model revealed that 25-, 50-, and 100-year storms produced runoff volumes of 2461.8 × 103, 4299.6 × 103, and 5204.5 × 103 m3 for An-Nawayah and 6212 × 103, 8129.4 × 103, and 10,330.6 × 103 m3 for Al-Rashrash, respectively. Flood risk levels, categorised as high (35.6%), extreme (21.9%), and medium (21.12%) were assessed in low- and very-low-hazard areas. The study highlighted that the areas closer to the Nile River mouth faced greater flood impacts from torrential rain. Our findings demonstrate the effectiveness of these methods in assessing and predicting flood risk. As a mitigation measure, this study recommends the construction of five 10 m high dams to create storage lakes. This integrated approach can be applied to flood risk assessment and mitigation in comparable regions.

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.

Remote sensing retrieval and driving analysis of phytoplankton density in the large storage freshwater lake: A study based on random forest and Landsat-8 OLI

Remote sensing monitoring of seasonal changes in phytoplankton density and analyses of the driving factors of phytoplankton densities are necessary for assessing the health of aquatic ecosystems, controlling lake eutrophication, and formulating ecological restoration policies. Building upon the satellite-ground synchronization experiment that involves the in situ aquatic ecological monitoring conducted in Nansi Lake, which is the largest storage lake situated along the eastern route of the South-to-North Water Diversion Project, we developed a phytoplankton density retrieval model utilizing the random forest (RF) method and Landsat-8 OLI data. On this basis, we mapped the seasonal fluctuations and spatial disparities in the phytoplankton densities from 2013 to 2023. Subsequently, we conducted a detailed analysis of the driving factors and considered both the natural and anthropogenic aspects. The results indicate that (1) the RF model, when utilizing three band combinations, yielded favorable results with R2, RMSE and MAE values of 0.67, 1.31 × 106 cells/L and 1.18 × 106 cells/L, respectively. (2) The phytoplankton densities exhibited both seasonal and spatial variations, with higher concentrations in summer and autumn than in spring and winter. Significantly, the northwestern region of Zhaoyang Lake and the southeastern region of Weishan Lake had substantially greater phytoplankton densities than did the other areas. Furthermore, overarching upward trends were observed from 2013 to 2023, reflecting an annual rate of increase of 3.32%. (3) An analysis of the causal factors indicated that temperatures and gross agricultural production levels are the primary drivers influencing the seasonal variations and distributions of phytoplankton densities. In the future, we will delve into the potential of deep learning and utilize various satellite sensors to explore the intricacies of phytoplankton monitoring, as well as the complex mechanisms that influence aquatic ecological health.

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).

Mapping particulate organic carbon in lakes across China using OLCI/Sentinel-3 imagery

Remote sensing monitoring of particulate organic carbon (POC) concentration is essential for understanding phytoplankton productivity, carbon storage, and water quality in global lakes. Some algorithms have been proposed, but only for regional eutrophic lakes. Based on in-situ data (N = 1269) in 49 lakes across China, we developed a blended POC algorithm by distinguishing Type-I and Type-II waters. Compared to Type-I, Type-II waters had higher reflectance peak around 560 nm (>0.0125 sr−1) and mean POC (4.65 ± 4.11 vs. 2.66 ± 3.37 mg/L). Furthermore, because POC was highly related to algal production (r = 0.85), a three-band index (R2 = 0.65) and the phytoplankton fluorescence peak height (R2 = 0.63) were adopted to estimate POC in Type-I and Type-II waters, respectively. The novel algorithm got a mean absolute percent difference (MAPD) of 35.93 % and outperformed three state-of-the-art formulas with MAPD values of 40.56–76.42 %. Then, the novel algorithm was applied to OLCI/Sentinel-3 imagery, and we first obtained a national map of POC in 450 Chinese lakes (> 20 km2), which presented an apparent spatial pattern of “low in the west and high in the east”. In brief, water classification should be considered when remotely monitoring lake POC concentration over a large area. Moreover, a process-oriented method is required when calculating water column POC storage from satellite-derived POC concentrations in type-II waters. Our results contribute substantially to advancing the dynamic observation of the lake carbon cycle using satellite data.

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

Lake water budgets are sensitive to climate change and human activities and have been undergoing rapid changes worldwide over the past few decades. Satellite altimeters greatly promote the large-scale monitoring of lake level and storage variations. However, limited spatiotemporal coverage of the existing individual altimeters prevents long-term and spatially seamless observations on global lakes. These limitations are partially surmounted by the gridded digital elevation model (DEM) data, which can facilitate spatially contiguous measurements of lake bathymetry exposed at the low-level period. The high-resolution SRTM DEM has been widely used for estimating lake level variations due to its early collection time and reliable data quality, while how many lakes worldwide and to what extent of the newly inundated areas can be monitored based on SRTM DEM remains unexplored. Here, we conduct a quasi-global investigation of SRTM DEM regarding its capability of mapping inundated-area bathymetry and estimating lake storage variations. After generating a global-scale lake inventory (122,444 lakes below 60°N, >1 km2) representing the maximum water inundation extents between 1984 and 2020, the feasibility of mapping lake inundated-area bathymetry was evaluated by comparing the maximum inundated area with the waterbody extent derived from SRTM DEM and analyzing the characteristics of interannual and seasonal variability of each lake. Results show that the maximum exposed lake bathymetries from the SRTM DEM data cover an area of 372,986 km2, accounting for 15.95% of the maximum water area of our investigated lakes. Climate-driven lake expansions or human-induced reservoir impoundments after 2000 (the SRTM mission period) are the main contributors to the higher availability of SRTM DEM-based bathymetry mapping on the Tibetan Plateau, India, eastern China, and Amazon Plains. As the newly launched Surface Water and Ocean Topography (SWOT) mission is anticipated to monitor lake water budget variation at an unprecedented resolution, this study provides a base map for supplementing inundated bathymetry information. The joint use of SRTM and SWOT-based observations will extend the time and space extents of lake-level measurements, thereby enhancing our understanding of lake dynamics at a longer timescale.

Impacts of acid deposition and lake browning on long-term organic carbon storage in Canadian northern forest lakes

Impacts of acid deposition and lake browning on long-term organic carbon storage in Canadian northern forest lakes

Human or climate? Differentiating the anthropogenic and climatic drivers of lake storage changes on spatial perspective via remote sensing data

Lakes are an essential part of the terrestrial water system in which storage changes are controlled by water balance and human impact. Although there are some attempts to define storage changes on a global scale, examination of spatial relations is poorly quantified. In this study, therefore, lake storage changes have been investigated using remote-sensing-derived data around the globe. Hence, 372 artificial/natural lakes were obtained, covering between 1992 and 2019. Watersheds belong to river was extracted via HydroSHED data. Based on watershed, dominant climate types were determined via Köppen-Geiger classification. Similarly, the areal average CRU TS v.4.05 monthly gridded precipitation time series and human footprint data based on watersheds were obtained to understand the drivers of lake storage changes. The nonparametric Mann-Kendall and Sen's slope trend analyses were applied to the lake storage change and precipiation values in order to determine long-term increases and decreases. A bivariate map was constructed between storage changes trend vs precipitation trend and human footprint to reveal the drivers of lake storage changes in terms of spatial aspects. The trend analysis and bivariate map results show that North America, the East African Highlands, and the Tibet plateau are important increasing hotspots, where precipitation is a significant driver for storage oscillations, except for the Tibet plateau. Besides, the Brazilian Highlands, Pacific Mountain System, and Intermontane of conterminous USA are other decreasing hotspots in which human footprint and decreasing precipitation collectively affect these changes. Furthermore, results clearly show that anthropogenic influence is low in the northern and mountainous areas, and storage changes have a linear relationship with precipitation. In contrast, intense human climate interaction influences lake changes in plains areas and arid/temperate climates.