Surface Water Volume Research Articles

Sharp decline in surface water resources for agriculture and fisheries in the Lower Mekong Basin over 2000-2020

Water resources play a crucial role in the global water cycle and are affected by human activities and climate change. However, the impacts of hydropower infrastructures on the surface water extent and volume cycle are not well known. We used a multi-satellite approach to quantify the surface water storage variations over the 2000–2020 period and relate these variations to climate-induced and anthropogenic factors over the whole basin. Our results highlight that dam operations have strongly modified the water regime of the Mekong River, exhibiting a 55 % decrease in the seasonal cycle amplitude of inundation extent (from 3178 km2 to 1414 km2) and a 70 % decrease in surface water volume (from 1109 km3 to 327 km3) over 2000–2020. In the floodplains of the Lower Mekong Basin, where rice is cultivated, there has been a decline in water residence time by 30 to 50 days. The recent commissioning of big dams (2010 and 2014) has allowed us to choose 2015 as a turning point year. Results show a trend inversion in rice production, from a rise of 40 % between 2000 and 2014 to a decline of 10 % between 2015 and 2020, and a strong reduction in aquaculture growth, from +730 % between 2000 and 2014, to +53 % between 2015 and 2020. All these results show the negative impact of dams on the Mekong basin, causing a 70 % decline in surface water volumes, with major repercussions for agriculture and fisheries over the period 2000–2020. Therefore, new future projects such as the Funan Techo canal in Cambodia, scheduled to start construction at the end of 2024, will particularly affect 1300 km2 of floodplains in the lower Mekong basin, with a reduction in the amount of water received, and other areas will be subjected to flooding. The human, material and economic damage could be catastrophic.

Making waves: How to clean surface water with photogranules

Global surface waters are in a bad ecological and chemical state, which has detrimental effects on entire ecosystems. To prevent further deterioration of ecosystems and ecosystem services, it is vital to minimize environmental pollution and come up with ways to keep surface water healthy and clean. Recently, photogranules have emerged as a promising platform for wastewater treatment to remove organic matter and nutrients with reduced or eliminated mechanical aeration, while also facilitating CO2 capture and production of various bioproducts. Photogranules are microbial aggregates of microalgae, cyanobacteria, and other non-phototrophic organisms that form dense spheroidic granules. Photogranules settle fast and can be easily retained in the treatment system, which allows increased amounts of water and wastewater to be treated. So far, photogranules have only been tested on various “high-strength” wastewaters but they might be an excellent choice for treatment of large volumes of polluted surface water as well. Here, we propose and tested for the first time photogranules on their effectiveness to remove nutrients from polluted surface water at unprecedented low concentrations (3.2 mg/L of nitrogen and 0.12 mg/L of phosphorous) and low hydraulic retention time (HRT = 1.5 h). Photogranules can successfully remove nitrogen (<0.6 mg/L, ∼80 % removal) and phosphorous (<0.01 mg/L, 90–95 % removal) to low levels in sequencing batch operation even without the need for pH control. Subjecting photogranules to surface water treatment conditions drastically changed their morphology. While, under “high-strength” conditions the photogranules were spherical, dense and defined, under polluted surface water conditions photogranules increased their surface area by forming fingers. However, this did not compromise their excellent settling properties. Finally, we discuss the future perspectives of photogranular technology for surface water treatment.

Water Hydrogen-Bond Mediated Layer by Layer Alignment of Lipid Rafts as a Precursor of Intermembrane Processes.

Lipid rafts, which are dynamic nanodomains in the plasma membrane, play a crucial role in intermembrane processes by clustering together and growing in size within the plane of the membrane while also aligning with each other across different membranes. However, the physical origin of layer by layer alignment of lipid rafts remains to be elucidated. Here, by using fluorescence imaging and synchrotron X-ray reflectivity in a phase-separated multilayer system, we find that the alignment of raft-mimicking Lo domains is regulated by the distance between bilayers. Molecular dynamics simulations reveal that the aligned state is energetically preferred when the intermembrane distance is small due to its ability to minimize the volume of surface water, which has fewer water hydrogen bonds (HBs) compared to bulk water. Our results suggest that water HB-driven alignment of lipid rafts plays a role as a precursor of intermembrane processes such as cell-cell fusion, virus entry, and signaling.

Dynamic monitoring of surface area and water volume of reservoirs using satellite imagery, computer vision and deep learning

The development of surface area and estimated volume measurements for water reservoirs using advanced computational techniques has become an increasingly important task for reservoir operation. Thus, the objective of this study is to determine the surface area and estimate the volume of water reservoirs through the segmentation of multispectral satellite images using a Fully Convolutional Neural Network (FCN). This paper introduces a universally applicable framework that utilizes deep convolutional neural networks for segmenting water bodies, particularly focusing on areas in Paraíba State, Northeast Brazil, susceptible to severe droughts. The study utilized Sentinel-2 satellite data obtained from Google Earth Engine for the period between January 2019 and September 2023. The extraction of water surface area from satellite images was achieved using the U-Net model, a deep learning framework based on FCN. The accuracy of water surface area extraction was analyzed using the Intersection-Over-Union (IoU) metric, also known as Jaccard Index. Subsequently, reservoir volumes were calculated using elevation-area-volume curves. The evaluation metrics for the results included root mean square error (RMSE), mean absolute percentage error (MAPE), coefficient of determination (R2), and Pearson correlation coefficient (r). The network demonstrated high accuracy, achieving a 95% IoU on the test set. This methodology was applied to four reservoirs, yielding promising results that closely aligned the monitored reservoir curves derived from satellite imagery with observed field data. The findings of this study are significant for research on semiarid region changes, extending their relevance to a broader understanding of global environmental dynamics. This work not only contributes to the field of remote sensing in hydrology but also offers practical insights for effective water resource management in drought-prone regions.

Quantification of surface water extent and volume in the Inner Niger Delta (IND) over 2000–2022 using multispectral imagery and radar altimetry

Spatio-temporal dynamics of surface water reservoirs at regional and global scales remain poorly understood. Using satellite remote sensing provides a unique opportunity to address this problem. This study aims to (1) quantify the extent and volume of surface water and (2) compare our approach with other datasets. We utilized MODIS-based spectral indices to monitor temporal variations in inundation extent. By interpolating water levels across the surface water extent, we generated water level maps and quantified surface water volume from 2000 to 2022. Evaluation against ICESat-2 data involved 64 comparisons, with approximately 58% showing an R 2 value greater than or equal to 0.5, and 38% were higher than or equal to 0.7. Compared to the flooding model, our method aligns more closely with ICESat-2 data, contrary to the flooding model which tends to overestimate water levels and, consequently, water storage.

A network design approach for citizen science-satellite monitoring of surface water volume changes in Bangladesh

This study introduces a reproducible and integrated framework for gauge network design for tracking surface water availability in a citizen science framework. For identifying the optimal number and location of gauges, the framework uses Monte Carlo simulations. With randomized selection of gauges from an existing high-density network, the framework does not impose a single optimal solution but rather provides a range of optimal solutions, allowing water managers the freedom to select the number of gauges and locations in accordance with their specific needs. Using the methodology, the study revealed how a strategic placement of gauges can potentially improve the estimation of surface water storage variations. The study findings can be used to enhance the assessment of lake products derived from missions such as the Surface Water and Ocean Topography (SWOT).

Development and application of a new water-carbon-economy coupling model (WCECM) for optimal allocation of agricultural water and land resources

The optimal allocation of agricultural water and land resources is of great significance in ensuring sustainable food production and economic benefits of farmers. However, agriculture, as an important carbon cycle ecosystem, has paid limited attention to carbon sequestration in the optimal allocation of water and land resources. Therefore, this study developed a new water-carbon-economy coupling model (WCECM) for optimal allocation of agricultural water and land resources. In this model, the minimum water scarcity, maximum carbon sequestration and maximum economic benefits are taken as the optimization objectives. In addition, surface water volume and groundwater volume and planting area etc. were defined as constraints, respectively. Then, the model was solved using the Non-dominated Sorting Genetic Algorithm III (NSGA-III) and the Entropy-weighted-TOPSIS evaluation method. The developed model was demonstrated in the largest Farm, Youyi Farm, which is one of commercial grain production base in China to analyze the optimization of water and land resources from 2010 to 2019. We found that the new WCECM, based on the simulation of a complex coupled water-carbon-economy system, can realize the optimal allocation of agricultural water and land resources to protect regional water resources, increase carbon sequestration and adjust the agricultural planting structure. In detail, through the multi-objective optimization model, the planting structure and the allocation ratio of surface water and groundwater irrigation water consumption are more suitable for this study area. After the optimization, the area planted with Rice was significantly reduced, the area planted with Maize was increased, and the area planted with Soybean did not change significantly compared with the first two crops. The planting structure has changed from focusing on paddy cultivation to dryland cultivation, with the ratio of Rice area, Maize area and Soybean area being 3:6:1. The water consumption is constrained within manageable limits, with an average annual irrigation water consumption of 2.01 × 108 m3. The amount of carbon sequestered has increased significantly, with an average annual increase of 7.8 × 108 kg. Meanwhile, the optimized economic benefits increased slightly, with a value of ¥2.35 billion. In short, optimization of water and land resources is beneficial for improving farmers' incomes, increasing carbon sequestration in agriculture, and conserving water resources.

INFILTRATION WELLS ECO-DRAINAGE PLANNING AS A FLOOD PREVENTION EFFORT IN BINANGUN SUB-DISTRICT, BLITAR REGENCY

The existence of land use change and loss of water catchment areas causes environmental ecosystems to be disrupted. Previously, green land has changed its function to become a development area which causes an increase in the volume of surface water when it rains because the water is not reabsorbed by the soil. In October 2022, there was a flood in the Binangun sub-district which was caused by the overflow of the drainage canals and rivers due to the large volume of surface water that entered. As an effort to deal with the flooding problem that occurs, planning infiltration wells is an effective solution to reduce the volume of surface water in the Binangun sub-district. Infiltration well planning was carried out with hydrological analysis and design discharge with a rational calculation method. From the analysis, it was found that the planned debit value was 284.61m3/s. The soil permeability value was obtained from the Falling Head soil sample test. The permeability test results of the falling head method obtained soil permeability values ​​in 3 regions namely, North = 0.003094m/s, Middle = 0.002827m/s, South = 0.001525m/s. The planning results showed that the dimensions of the infiltration wells for the Southern region are R=0.5m, L=1.5m, and H=6m with the assumption that the number of design wells is 333 which can reduce the planned discharge in the Binangun sub-district area by 35%. Keywords: Infiltration Wells; Floods; Drainage Planning.

Monitoring monthly variation of Tonle Sap Lake water volume using Sentinel-1 imagery and satellite altimetry data

This work estimates the surface water volume variation of the Cambodian Tonle Sap Lake at a monthly scale from 2015-2022. To achieve this, radar Sentinel-1 imagery was processed using the Google Earth Engine platform to generate backscatter coefficient maps. The Otsu method was utilized to identify the optimal threshold to classify each backscatter coefficient map into water or non-water clusters. Additionally, altimetry data from three satellites (i.e., Sentinel-3, Jason-3, and Jason-CS/Sentinel-6) was processed to estimate Tonle Sap Lake’s water level variation using the AlTiS software. Surface water maps of the lake, derived from MODIS and clear-sky Sentinel-2 imagery, were used to validate the lake’s surface water extent time series, while in situ water level data collected at Prek Kdam station was used to validate the variation of the lake’s water height. Our results estimated that the lake’s open water area varies from 2200 to 6000 km2, while its water level ranges from 3.1 to 10.9 m. Combining the two time series, we estimated that Tonle Sap Lake’s water volume varies between approximately -7.2 and 9.4 km3 month-1, which shows high correlation with the variation of the water volume flowing through Chau Doc and Tan Chau stations (R = 0.9528 after removing the time lag). This study highlights the ability of satellite data for lake monitoring, which is very useful in remote areas where gauge stations are limited or unavailable. Future work aims to test the accuracy of the proposed methodology in other types of environments, particularly in mountainous regions of North Vietnam, where the terrain is very steep.

Pan-Greenland mapping of supraglacial rivers, lakes, and water-filled crevasses in a cool summer (2018) and a warm summer (2019)

The spatiotemporal distribution and variability of surface water remained poorly known at the pan-Greenland scale, and its dominant features (supraglacial rivers, lakes, and water-filled crevasses) were rarely studied collectively. We present pan-GrIS surface water extent and volume for a relatively cool (2018) and a relatively warm (2019) summer, using 10 m resolution Sentinel-2 imagery, a semi-automated multi-scale water extraction algorithm, and the Regional Atmospheric Climate Model (RACMO). While the 10 m resolution of Sentinel-2 imagery prevents inclusion of all water-filled crevasses and narrow rivers, our findings include: (1) strong interannual differences are observed in total surface water area (4903km2 vs. 9988 km2), volume (3.5 km3 vs. 6.8 km3), and mean elevation limit (1407 m a.s.l. vs. 1545 m a.s.l.) in response to a low (cool) (265 Gt/yr) and high (warm) (510 Gt/yr) runoff year; (2) large spatial contrasts in surface water extent, volume, elevation limit, and drainage pattern among the eight major GrIS basins; (3) supraglacial rivers dominate GrIS surface water appearance, accounting for 57%/48% of total surface water area/volume, respectively, over the two years (in contrast, water-filled crevasses and supraglacial lakes account for 33%/32% and 10%/20%, respectively); (4) ratio of remotely sensed water volume to RACMO-simulated cumulative surface runoff declines during the cool (2.6%) vs. the warm (1.8%) year; and from north (4.5%) to south (1.1%) Greenland. In summary, this study reveals strong temporal and spatial differences in GrIS surface water extent, volume, and drainage pattern and raises prospects for improved understanding of pan-Greenland Ice Sheet surface hydrology.

Accurate estimation of surface water volume in tufa lake group using UAV-captured imagery and ANNs

Quantitative acquisition of surface water volume of tufa lake group is significant for protecting the tufa landscapes. Limited by low spatial resolution, satellite remote sensing failed to extract the surface water distribution of small and scattered tufa lakes. In recent years, Unmanned Aerial Vehicle (UAV) remote sensing has been increasingly applied to survey aquatic resources and environments, posing great potential for accurately measuring surface water volume of tufa lake group. In this paper, taking the Shuzheng Lakes in Jiuzhai Valley of China as the study site, we used UAV-captured images and Artificial Neural Network (ANN) models to precisely estimate the surface water volume of the tufa lake group. Digital Surface Model (DSM) and orthomosaic were first generated using aerial triangulation. Next, the two classification networks were trained to separate water from vegetation, and then the water extents of individual tufa lakes were extracted. Subsequently, the water depth map of each tufa lake was retrieved using the transferred shallow and deep bathymetry networks. Lastly, the total surface water volume of tufa lake group was achieved by summing the products of pixel unit area and the water depth of each pixel. As results, the surface water volume of tufa lake group estimated by the optimum model combination was approximately 181,360 m3, and the corresponding R-squared was 0.92. These demonstrated the effectiveness of utilizing UAV-based remote sensing and integrated ANN models to accurately estimate surface water volume of tufa lakes.

Delayed valley incision due to karst capture (Demänová Cave System, Western Carpathians, Slovakia)

Karst systems can control the amount of water flowing on the surface and thus the fluvial erosional efficiency. Here, we used the ages of speleothems from the active cave system to determine the middle Pleistocene history of the entrenchment of the Demänová Valley. By referencing the vertical position of fluvially active and inactive cave passages to the valley bottom, we estimated the deceleration magnitude of the valley incision due to karst drainage through the Demänová Cave System. The well-developed karst system captures a significant volume of surface water and reduces surface erosion. This, in turn, causes a delay in the incision of the valley drained by the caves in comparison to the downstream positions (below the springs of sinking waters), where river-driven erosion dominates. Karst drainage has reduced the erosional efficiency in the inflow part of the Demänová Valley due to a hydraulic gradient among inputs and outputs of allochthonous waters, mostly during the middle and late Pleistocene. The cave level that contains the active underground segment of the Demänovka River, previously dated to ~350 ka, definitely existed earlier than 600 ka. The period from approximately 600 to 395 ± 5 kyr ago was characterized by relatively stable conditions with continuous deposition of flowstones, regardless of the climate episodes, including several glacial–interglacial cycles.

Phytotreatment of water contaminated with waste lubricating oil using Pistia stratiotes

ABSTRACT Auto-mechanic service workshops in Nigeria tend to spill waste lubricating oil into the soil. The waste lubricating oil is washed into nearby streams by runoff leading to water pollution. The current study is aimed at assessing the performance and response of P. stratiotes in the remediation of water contaminated with waste lubricating oil. The contaminated water used for this study is a product of an artificial spillage of surface water and different volumes (30, 60, 90, 120 and 150 mL) of waste lubricating oil. The reduction efficiency, biotranslocation, bioconcentration factor, relative growth rate and the enzymatic and non-enzymatic response of P. stratiotes were determined. The results show that the efficiency of P. stratiotes in improving the quality of the contaminated water increases with an increase in the retention time of P. stratiotes but decreases with an increase in the volume of used lubricating oil. The result also shows an increase in the growth rate of P. stratiotes with increasing retention time but a decrease with an increased volume of used engine oil. The study also shows that P. stratiotes can counteract any effect induced by the pollutants in the contaminated water through antioxidant and non-antioxidant responses.

Evaluation of Chitosans as Coagulants-Flocculants to Improve Sand Filtration for Drinking Water Treatment.

The World Health Organization (WHO) reports that two billion people worldwide lack access to safely managed water sources, including 1.2 billion who already have access to improved water sources. In many countries, household point-of-use (POU) water-treatment options are used to remove or deactivate microorganisms in water, but not all POU technologies meet WHO performance requirements to achieve safe drinking water. To improve the effectiveness of POU technologies, the use of multiple treatment barriers should be used as a way to increase overall treatment performance. The focus of this research is to evaluate multiple barrier treatment using chitosan, an organic coagulant-flocculant, to improve microbial and turbidity reductions in combination with sand filtration. Bench-scale intermittently operated sand filters with 16 cm layers of sands of two different grain sizes representing slow and rapid sand filters were dosed daily over 57 days with microbially spiked surface water volumes corresponding to household use. E. coli bacteria and MS2 coliphage virus reductions were quantified biweekly (N = 17) using culture methods. Bacteria and virus removals were significantly improved over sand filtration without chitosan pretreatment (Wilcoxon Rank-Sum, p &lt; 0.05). When water was pretreated at an optimal chitosan dose of 10 mg/L followed by sand filtration, log10 reductions in bacteria and viruses met the two-star WHO performance level of effectiveness. Microbial and turbidity reductions generally improved over the filter operating period but showed no trends with filtration rates.

Pre-concentration of 218 multiclass pesticide in groundwater samples using MSU-1 mesoporous sorbent

A mesoporous material (MSU-1), prepared in the laboratory, was applied as a solid phase sorbent to pre-concentrate 218 multiclass pesticides in environmental waters. The pesticides present in the sample extracts were determined by ultra-high-performance liquid chromatography coupled with tandem mass spectrometry. The most intense ion was selected as precursor ion. After fragmentation in the collision chamber, the most intense transition (SRM1) was used for quantification and three points were used for identification and confirmation, as established by Directive 96/23/EC. A comprehensive study of the main variables affecting the sorption/desorption of pesticides in the MSU-1 was performed using step-by-step (elution solvent, sample pH and salt content) and multi-response surface (sorbent amount, water volume and solvent elution volume) methodologies, with the optimal values being no addition of NaCl, 100 mg MSU-1 sorbent, 50 mL water sample at pH = 6 and elution of pesticides with 5 mL of acetonitrile. The matrix effect was tested by comparing the slopes of solvent-based and matrix-matched calibration graphs. 80 % of pesticides showed a low matrix effect, and 20 % showed a medium or high matrix effect. Two calibration strategies were tested to correct the matrix effect by adding the pesticide standards before or after the pre-concentration step. The first one corrected for systematic errors due to the low adsorption of pesticides in the MSU-1 and corrected for the matrix effect. The method was validated using blank groundwater samples spiked with 0.1, 0.25 and 0.5 μg/L of all pesticides. Recoveries between 54 and 130 % (RSD ≤ 20 %) were obtained for most pesticides (90 %), while recoveries ≥ 130 % were obtained for 22, 10 and 5 pesticides at 0.1, 0.25 μg/L and 0.5 μg/L, respectively. A monitoring study of thirteen groundwater samples collected in Almería (South of Spain) was performed applying the proposed methodology. Thirty-eight different pesticides were found in the groundwater samples analyzed. However, most of them were found in concentrations below 0.1 µg/L, with imidacloprid, hexaflumuron and oxadixyl being the most frequently detected in 7, 6 and 5 samples, respectively. Only in 5 samples, methiocarb (three samples), pyrethrin I and pytethrin II (one sample) and hezaflumuron (one sample) were found at levels higher than 0.1 μg/L. The method green profile was evaluated using National Environmental Methods Index and analytical Eco-scale assessment tools.

Analysis of the impact of the degree of catchment sealing on the operation of drainage system

With increasing sealing of the catchment surface, the time of outflow of water from the catchment decreases and the volume of surface water flowing out increases. This phenomenon has a negative impact on the water balance of the catchment area, and results in an increase in the frequency of flooding, related to inability of the existing drainage systems to collect the surface waters. This paper presents the results of modeling of hydraulic conditions in a selected part of the storm sewage system. The US EPA’s software SWMM 5 was applied to our studies. Three different rainfall events of various intensity and time and variable sealing degree of the catchment surface were studied in our research. The conducted simulation tests enabled the analysis of the sewage flow rate, the canals filling height as well as assessment of the impact of changing the degree of surface sealing on the amount of rainwater discharged and the frequency of outflows.

Experimental evidence for modulation of slope effect on heterogeneous infiltrating surfaces by run-on

The influence of soil surface gradient on rainfall infiltration and related surface runoff generation are not well understood for representation in hydrologic modeling because of conflicting theoretical formulations and experimental results available in the scientific literature. The main objective of this study is to integrate and extend previous laboratory experiments using artificial rainfall over a laboratory setup with adjustable slope angle (α) and consisting of two adjacent natural bare soils that according to the USDA soil classification were of loam (Soil 1) and sandy loam (Soil 2) type, respectively. Soil 2, placed downstream, was subjected to the run-on process due to the overland flow produced over Soil 1. The slope effects are discussed on the basis of measurements of runoff surface (QS) and deep flow (Qd), both strictly linked to the infiltration rate, supported by a simplified rainfall-runoff model. Our results indicate that at a time close to the end of rainfall period (tre=8 h), for α increasing from 1° to 10°, Qd decreased by about 25% while QS exhibited a corresponding increase in magnitude. In the same slope range, at t → tre the total volume of water collected as deep flow decreased by about 40% for heavy rainfall and up to about 50% for light rainfall. On the other hand, a growth of the total surface water volume occurred such that the total outflow volume was nearly independent of α. The run-on effect is seen to modulate the differences in steady deep flows for different slopes. The above variations became of minor interest between 10° and 15°. The significant differences in the variations of surface and deep flow to changes of slope angle were analyzed and placed in context with those from earlier experiments. The differences are attributed to a different level of interaction between capillary and gravitational effects that should be represented in existing infiltration models, because appreciable values of α characterize most watershed areas and the decrease of infiltration with increasing α over bare soils can imply a greater contribution to the direct runoff and a significant reduction of the groundwater recharge with respect to a flat surface.

Investigating Thermal Controls on the Hyporheic Flux as Evaluated Using Numerical Modeling of Flume-Derived Data

The flux of water through the hyporheic zone (HZ) is controlled by stream bedforms, sinuosity, surface water velocity, local water table, seasonality, and hydraulic conductivity (K) of the bed material. Dependent on both the kinematic viscosity and density of water, K values are a function of temperature. In most studies, changes in temperature have been neglected because of the limited effect either density or viscosity has on K values. However, these variations are important given the role of K in HZ flux, which lead to the hypothesis that flow into the HZ would be more efficient (faster rate and greater depth) under warmer conditions than under cool conditions. To discern how water temperature affects flow depth in the HZ, VS2DHI simulations were created to map flow under both warm and cool thermal conditions. The models employed data collected from a series of varying temperature hydrologic flume tests in which the effects of hyporheic flow altering variables such as sinuosity, surface water velocity and volume, and bed-forms were controlled. Results verify that K values in the HZ were larger under warm conditions generating deeper HZ pathways, while the smaller K values under cool conditions produced shallower pathways. The simulations confirmed a faster speed of frontal movement under warm conditions than cool. Péclet numbers revealed a shallower advective extinction depth under cool conditions as opposed to warm.

Monitoring Lake Volume Variation from Space Using Satellite Observations—A Case Study in Thac Mo Reservoir (Vietnam)

This study estimates monthly variation of surface water volume of Thac Mo hydroelectric reservoir (located in South Vietnam), during the 2016–2021 period. Variation of surface water volume is estimated based on variation of surface water extent, derived from Sentinel-1 observations, and variation of surface water level, derived from Jason-3 altimetry data. Except for drought years in 2019 and 2020, surface water extent of Thac Mo reservoir varies in the range 50–100 km2, while its water level varies in the range 202–217 m. Correlation between these two components is high (R = 0.948), as well as correlation between surface water maps derived from Sentinel-1 and free-cloud Sentinel-2 observations (R = 0.98), and correlation between surface water level derived from Jason-3 altimetry data and from in situ measurement (R = 0.99; RMSE = 0.86 m). We showed that water volume of Thac Mo reservoir varies between −0.3 and 0.4 km3 month−1, and it is in a very good agreement with in situ measurement (R = 0.95; RMSE = 0.0682 km3 month−1). This study highlights the advantages in using different types of satellite observations and data for monitoring variation of lakes’ water storage, which is very important for regional hydrological models. Similar research can be applied to monitor lakes in remote areas where in situ measurements are not available, or cannot be accessed freely.

Bacterial Communities Along Environmental Gradients in Tropical Soda Lakes.

Soda lake environments are known to be variable and can have distinct differences according to geographical location. In this study, we investigated the effects of different environmental conditions of six adjacent soda lakes in the Pantanal biome (Mato Grosso do Sul state, Brazil) on bacterial communities and their functioning using a metagenomic approach combined with flow cytometry and chemical analyses. Ordination analysis using flow cytometry and water chemistry data from two sampling periods (wet and dry) clustered soda lakes into three different profiles: eutrophic turbid (ET), oligotrophic turbid (OT), and clear vegetated oligotrophic (CVO). Analysis of bacterial community composition and functioning corroborated this ordination; the exception was one ET lake, which was similar to one OT lake during the wet season, indicating drastic shifts between seasons. Microbial abundance and diversity increased during the dry period, along with a considerable number of limnological variables, all indicative of a strong effect of the precipitation-evaporation balance in these systems. Cyanobacteria were associated with high electric conductivity, pH, and nutrient availability, whereas Actinobacteria, Alphaproteobacteria, and Betaproteobacteria were correlated with landscape morphology variability (surface water, surface perimeter, and lake volume) and with lower salinity and pH levels. Stress response metabolism was enhanced in OT and ET lakes and underrepresented in CVO lakes. The microbiome dataset of this study can serve as a baseline for restoring impacted soda lakes. Altogether, the results of this study demonstrate the sensitivity of tropical soda lakes to climate change, as slight changes in hydrological regimes might produce drastic shifts in community diversity.