Search Results (49)

The Surface Water and Ocean Topography (SWOT) satellite mission, jointly developed by NASA and several international collaboration agencies, aims to achieve high-resolution two-dimensional observations of global surface water. Equipped with the advanced Ka-band radar interferometer (KaRIn), it significantly enhances the ability to monitor surface water and provides a new data source for obtaining large-scale water surface elevation (WSE) data at high temporal and spatial resolution. However, the accuracy and applicability of its scientific data products for inland water bodies still require validation. This study obtained three scientific data products from the SWOT satellite between August 2023 and December 2024: the Level 2 KaRIn high-rate river single-pass vector product (L2_HR_RiverSP), the Level 2 KaRIn high-rate lake single-pass vector product (L2_HR_LakeSP), and the Level 2 KaRIn high-rate water mask pixel cloud product (L2_HR_PIXC). These were compared with in situ water level data to validate their accuracy in retrieving inland water levels across eight different regions in the middle and lower reaches of the Yangtze River (MLRYR) and to evaluate the applicability of each product. The experimental results show the following: (1) The inversion accuracy of L2_HR_RiverSP and L2_HR_LakeSP varies significantly across different regions. In some areas, the extracted WSE aligns closely with the in situ water level trend, with a coefficient of determination ($R^2$) exceeding 0.9, while in other areas, the $R^2$ is lower (less than 0.8), and the error compared to in situ water levels is larger (with Root Mean Square Error (RMSE) greater than 1.0 m). (2) This study proposes a combined denoising method based on the Interquartile Range (IQR) and Adaptive Statistical Outlier Removal (ASOR). Compared to the L2_HR_RiverSP and L2_HR_LakeSP products, the L2_HR_PIXC product, after denoising, shows significant improvements in all accuracy metrics for water level inversion, with $R^2$ greater than 0.85, Mean Absolute Error (MAE) less than 0.4 m, and RMSE less than 0.5 m. Overall, the SWOT satellite demonstrates the capability to monitor inland water bodies with high precision, especially through the L2_HR_PIXC product, which shows broader application potential and will play an important role in global water dynamics monitoring and refined water resource management research. Full article

This study evaluates the performance of the ICESat-2 ATL13 altimetry product for estimating water levels in 182 Canadian lakes by integrating satellite-derived observations with in situ gauge measurements and applying spatial filtering using the HydroLAKES dataset. The analysis compares ATL13-derived lake surface elevations with hydrometric data from national monitoring stations, providing a robust framework for assessing measurement accuracy. Statistical metrics—including root mean square error (RMSE), mean absolute error (MAE), and mean bias error (MBE)—are employed to quantify discrepancies between the datasets. Importantly, the application of HydroLAKES-based filtering reduces the mean RMSE from 1.53 m to 1.40 m, and the further exclusion of high-error lakes lowers it to 0.96 m. Larger and deeper lakes exhibit lower error margins, while smaller lakes with complex shorelines show greater variability. Regression analysis confirms the excellent agreement between satellite and gauge measurements (R² = 0.9999; Pearson’s r = 0.9999, n = 182 lakes, p < 0.0001). Temporal trends reveal declining water levels in 134 lakes and increasing levels in 48 lakes from 2018 to 2024, potentially reflecting climatic variability and human influence. These findings highlight the potential utility of ICESat-2 ATL13 altimetry for large-scale inland water monitoring when combined with spatial filtering techniques such as HydroLAKES. Full article

Inland lakes and reservoirs are critical components of global freshwater resources. However, traditional water level monitoring stations are costly to establish and maintain, particularly in remote areas. As an alternative, satellite altimetry has become a key tool for lake water level monitoring. Nevertheless, conventional radar altimetry techniques face accuracy limitations when monitoring small water bodies. The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), equipped with a single-photon counting lidar system, offers enhanced precision and a smaller ground footprint, making it more suitable for small-scale water body monitoring. However, the water level data obtained from the ICESat-2 ATL13 inland water surface height product are limited in quantity, while the lake water level accuracy derived from the ATL08 product is relatively low. To overcome these challenges, this study proposes a Spatial Distribution-Based Hierarchical Clustering for Photon-Counting Laser altimeter (SD-HCPLA) for enhanced water level extraction, validated through experiments conducted at the Danjiangkou Reservoir. The proposed method first employs Landsat 8/9 imagery and the Normalized Difference Water Index (NDWI) to generate a water mask, which is then used to filter ATL03 photon data within the water body boundaries. Subsequently, a Minimum Spanning Tree (MST) is constructed by traversing all photon points, where the vertical distance between adjacent photons replaces the traditional Euclidean distance as the edge length, thereby facilitating the clustering and denoising of the point cloud data. The SD-HCPLA algorithm successfully obtained 41 days of valid water level data for the Danjiangkou Reservoir, achieving a correlation coefficient of 0.99 and an average error of 0.14 m. Compared with ATL08 and ATL13, the SD-HCPLA method yields higher data availability and improved accuracy in water level estimation. Furthermore, the proposed algorithm was applied to extract water level data for five lakes and reservoirs in Hubei Province from 2018 to 2023. The temporal variations and inter-correlations of water levels were analyzed, providing valuable insights for regional ecological environment monitoring and water resource management. Full article

Total nitrogen (TN) and total phosphorus (TP) are essential indicators for assessing water quality. This study systematically analyzes the spatial and temporal distribution of TN and TP in China’s surface waters and examines the influence of natural factors and human activities on their concentrations. Utilizing data from 1387 monitoring sites (2020–2021) and employing K-means clustering and geographically weighted regression (GWR), we found that the national average concentrations were 3.89 mg/L for TN and 0.096 mg/L for TP. Spatially, higher TN and TP levels were observed in northern regions, coastal areas, and plains compared with southern, inland, and mountainous areas. Notably, TN concentrations reached up to 29.49 mg/L in the Haihe River basin and related plains, while TP peaked at 0.497 mg/L in the southeastern Shandong and northern Jiangsu coastal zones. Temporally, TN levels were approximately 50% higher in winter than summer, whereas TP levels were about 40% higher in summer. Key influencing factors included rainfall, elevation, fertilizer use, and population density, with spatial heterogeneity observed. Rainfall was the primary factor for TN change and the secondary factor for TP change. Soil type positively correlates with TN and TP changes, affecting non-point source pollution. Human activities such as land use, fertilizer application and population density had a significant effect on the nitrogen and phosphorus concentrations, while woodland had a significant impact on the improvement of water quality. The geographically weighted regression analysis showed spatial heterogeneity in the effects of each factor on TN and TP concentrations, and the best fit was at the watershed scale. The findings highlight the need for enhanced control of agricultural runoff, improved sewage treatment, and region-specific management strategies to inform effective water environment policies in China. Full article

The Surface Water and Ocean Topography (SWOT) mission was launched on 16 December 2022 to measure water levels over both open ocean and inland waters. To achieve these objectives, the SWOT Payload contains an innovative Ka-band radar interferometer, called KaRIn, completed with a nadir altimeter called POSEIDON-3C that was switched on a month after launch and a few days before KaRIn. POSEIDON-3C measurements provide a link between large-scale phenomena and high resolution. The POSEIDON-3C design is based on POSEIDON-3B, its predecessor on board JASON-3. It is also a dual-frequency radar altimeter operating in C- and Ku-bands, but with some improvements to enhance its performance. Even though it is a Low Resolution Mode altimeter, its performance over open ocean, inland waters and coastal zones are indeed excellent. This paper first describes the POSEIDON-3C design and its modes with a focus on its new features and the Digital Elevation Model that drives its open-loop tracking mode. Then, we assess the in-flight performances of the altimeter from an instrumental point of view. For that purpose, special and routine calibrations have been realized. They show the good performance and stability of the radar. In-flight assessments thus provide confidence when it comes to ensuring excellent altimeter measurement stability throughout the mission duration. Full article

The SWOT satellite, carrying the KaRIN first wide-swath onboard altimeter, was launched in December 2022, and has now delivered more than a year of surface water elevation data over the ocean and inland lakes/rivers. These data are affected by systematic errors which constitute the dominant part of the error budget at scales larger than a few thousands of kilometers. Some strategies for their estimation and calibration were explored during the pre-launch studies with performance estimations. Now, based on the real data, we propose in this study to assess the systematic error budget with statistical methods relying on spectral and co-spectral analysis. From this assessment, suggesting very low error levels (below requirements), we propose the implementation of the calibration algorithms at Level-2 and Level-3 with a few minor adjustments justified by the error spectra. The calibrated products are then validated with usual CalVal metrics. Full article

Coal mining activity contributes to energy security and employment occupation, but is associated with environmental deterioration. Coal combustion leads to GHG emissions, while coal mining results in the generation of saline effluents. These effluents are discharged in inland surface waters, applying significant pressure on their quality, with a negative impact on aquatic life and the economy of a region. This study includes water samples that were analyzed in order to investigate the organic compounds, heavy metals, and other physicochemical parameters. Biological monitoring was done according to the Water Framework Directive methodology. The results from an aquatic area in Southern Poland, which indirectly receives coal mine effluents, indicate elevated salinity with excessive chlorides, sulfates, and sodium ions. The water quality of another non-polluted aquatic area was also assessed to examine the impact of indirect coal mine wastewater discharge on this area. The high salinity levels hinder the use of river water for drinking, agricultural, or industrial purposes. The results obtained show high pressure on the ecological status of streams and rivers that receive mine effluents, and on the density and diversity of aquatic invertebrates. This pressure is clearly visible in the structure of benthic communities and in invertebrate diversity. It also contributes to the appearance of invasive species and increasing water salinity. Limiting discharges of mine water transporting large loads of saline substances would reduce the negative impact on the quality of river waters and biological life. Full article

High waves and surges associated with storms pose threats to the coastal communities around the Great Lakes. Numerical wave models, such as WAVEWATCHIII, are commonly used to predict the wave height and direction for the Great Lakes. These predictions help determine risks and threats associated with storm events. To verify the reliability and accuracy of the wave model outputs, it is essential to compare them with observed wave conditions (e.g., significant wave height), many of which come from buoys. However, in the Great Lakes, most of the buoys are retrieved before those lakes are frozen; therefore, winter wave measurements remain a gap in the Great Lakes’ data. To fill the data gap, we utilize data from the Inland Water Surface Height product of the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) as complements. In this study, the data quality of ICESat-2 is evaluated by comparing with wave conditions from buoy observations in the Great Lakes. Then, we evaluate the model quality of NOAA’s Great Lakes Waves-Unstructured Forecast System version 2.0 (GLWUv2) by comparing its retrospective forecast simulations for significant wave height with the significant wave height data from ICESat-2, as well as data from a drifting Spotter buoy that was experimentally deployed in the Great Lakes. The study indicates that the wave measurements obtained from ICESat-2 align closely with the in situ buoy observations, displaying a root-mean-square error (RMSE) of 0.191 m, a scatter index (SI) of 0.46, and a correlation coefficient of 0.890. Further evaluation suggests that the GLWUv2 tends to overestimate the wave conditions in high wave events during winter. The statistics show that the RMSE in 0–0.8 m waves is 0.257 m, while the RMSE in waves higher than 1.5 m is 0.899 m. Full article

Southwestern Peru has an arid climate typical of subtropical west coasts bordering cold ocean currents. Mountain runoff is barely able to sustain urban needs and motivates this research. Using high-resolution satellite reanalysis products, the meso-scale climate and weather variability are explored via point-to-field regression. A time series spanning 1970–2022 of Tacna area (18 S, 70.2 W, 570 m) rainfall, potential evaporation, wind, and weather parameters were evaluated for thermodynamic and kinematic features. Although sea breezes draw marine air inland, they simultaneously generate low-level divergence and subsidence aloft. Potential evaporation in early summer causes water deficits that are rarely offset by late summer runoff from the Andes Mountains. Winter (May–September) showers from passing cold fronts are more frequent during El Niño. Warming of the tropical east Pacific accelerates subtropical westerly winds that lift over the coastal plains. Quasi-stationary Rossby wave patterns amplify transient troughs at 70 W, but the winter showers rarely exceed 4 mm/day due to low-level stability from negative heat fluxes over cool seawater offshore. Two winter wet spells were studied using satellite and surface data (July 2002, July 2009). Light showers were prominent in elevations from 400 to 900 m. An early summer dry spell was considered (November 2020), wherein southeast winds, coastal upwelling, and low dewpoint temperatures coincided with La Niña conditions. A rain-gauge transect showed that summer convection stays east of the Andes escarpment and seldom benefits the coastal plains. Thus, water resources in Tacna are strained beyond the carrying capacity. Full article

Efficient water resource management in glacier- and snow-dominated basins requires accurate estimates of the snow water equivalent (SWE) in late winter and spring and melt onset timing and intensity. To understand the high spatio-temporal variability of snow and glacier ablation, a spatially distributed energy balance model combining satellite-based retrievals of albedo and snow cover was applied. Incoming short-wave energy, contributing to daily estimates of melt energy, was constrained by remotely sensed surface albedo for snow-covered surfaces. Fractional snow cover was used for non-glaciated areas, as it provides estimates of snow cover for each pixel to better constrain snow melt. Thus, available daily estimates of melt energy in a given area were the product of the possible melt energy and the fractional snow cover of the area or pixel for non-glaciated areas. This provided daily estimates of melt water to determine seasonal snow and glacier ablation in Iceland for the period 2000–2019. Observations from snow pits on land and glacier summer mass balance were used for evaluation, and observations from land and glacier-based automatic weather stations were used to evaluate model inputs for the energy balance model. The results show that the interannual SWE variability was generally high both for seasonal snow and glaciers. For seasonal snow, the largest SWE (>1000 mm) was found in mountainous and alpine areas close to the coast, notably in the East- and Westfjords, Tröllaskaga, and in the vicinity of glacier margins. Lower SWE values were observed in the central highlands, flatter inland areas, and at lower elevations. For glaciers, more SWE (glacier ablation) was associated with lower glacier elevations while less melt was observed at higher elevations. For the impurity-rich bare-ice areas that are exposed annually, observed SWE was more than 3000 mm. Full article

Satellite altimetry has been proven to measure water levels in lakes and rivers effectively. The Sentinel-3A satellite is equipped with a dual-frequency synthetic aperture radar altimeter (SRAL), which allows for inland water levels to be measured with higher precision and improved spatial resolution. However, in regions at middle and high latitudes, where many lakes are covered by ice during the winter, the non-uniformity of the altimeter footprint can substantially impact the accuracy of water level estimates, resulting in abnormal readings when applying standard SRAL synthetic aperture radar (SAR) waveform retracking algorithms (retrackers). In this study, a modified method is proposed to determine the current surface type of lakes, analyzing changes in backscattering coefficients and brightness temperature. This method aligns with ground station observations and ensures consistent surface type classification. Additionally, a dual-threshold algorithm that addresses the limitations of the original bimodal algorithm by identifying multiple peaks without needing elevation correction is introduced. This innovative approach significantly enhances the precision of equivalent water level measurements for ice-covered lakes. The study retrieves and compares the water level data of nine North American lakes covered by ice from 2016–2019 using the dual-threshold and the SAMOSA-3 algorithm with in situ data. For Lake Athabasca, Cedar Lake, Great Slave Lake, Lake Winnipeg, and Lake Erie, the root mean square error (RMSE) of SAMOSA-3 is 39.58 cm, 46.18 cm, 45.75 cm, 42.64 cm, and 6.89 cm, respectively. However, the dual-threshold algorithm achieves an RMSE of 6.75 cm, 9.47 cm, 5.90 cm, 7.67 cm, and 5.01 cm, respectively, representing a decrease of 75%, 79%, 87%, 82%, and 27%, respectively, compared to SAMOSA-3. The dual-threshold algorithm can accurately estimate water levels in ice-covered lakes during winter. It offers a promising prospect for achieving long-term, continuous, and high-precision water level measurements for middle- and high-latitude lakes. Full article

Sea-level rise in Benin coastal zones leads to risks of erosion and flooding, which have significant consequences on the socio-economic life of the local population. In this paper, erosion, flood risk, and greenhouse gas sequestration resulting from sea-level rise in the coastal zone of the Benin coast were assessed with the Sea Level Affecting Marshes Model (SLAMM) using ArcGIS Pro 3.1 tools. The input features used were the Digital Elevation Map (DEM), the National Wetland Inventory (NWI) categories, and the slope of each cell. National Wetland Inventory (NWI) categories were then created using Support Vector Machines (SVMs), a supervised machine learning technique. The research simulated the effects of a 1.468 m sea-level rise in the study area from 2021 to 2090, considering wetland types, marsh accretion, wave erosion, and surface elevation changes. The largest land cover increases were observed in Estuarine Open Water and Open Ocean, expanding by approximately 106.2 hectares across different sea-level rise scenarios (RCP 8.5_Upper Limit). These gains were counterbalanced by losses of approximately 106.2 hectares in Inland Open Water, Ocean Beaches, Mangroves, Regularly Flooded Marsh, Swamp, Undeveloped, and Developed Dryland. Notably, Estuarine Open Water (97.7 hectares) and Open Ocean (8.5 hectares) experienced the most significant expansion, indicating submergence and saltwater intrusion by 2090 due to sea-level rise. The largest reductions occurred in less tidally influenced categories like Inland Open Water (−81.4 hectares), Ocean Beach (−7.9 hectares), Swamp (−5.1 hectares), Regularly Flooded Marsh (−4.6 hectares), and Undeveloped Dryland (−2.9 hectares). As the sea-level rises by 1.468 m, these categories are expected to be notably diminished, with Estuarine Open Water and Open Ocean becoming dominant. Erosion and flooding in the coastal zone are projected to have severe adverse impacts, including a gradual decline in greenhouse gas sequestration capacity. The outputs of this research will aid coastal management organizations in evaluating the consequences of sea-level rise and identifying areas with high mitigation requirements. Full article

The Copernicus Sentinel-3 Surface Topography Mission (STM) Land Altimetry provides valuable surface elevation information over inland waters, sea ice, and land ice, thanks to its synthetic aperture radar (SAR) altimeter and its orbit that covers high-latitude polar regions. To ensure that these measurements are reliable and to maximise the return on investment, adequate validation of the geophysical retrieval methods, processing algorithms, and corrections must be performed using independent observations. The EU-ESA project St3TART (started July 2021) aims to generalise the concept of Fiducial Reference Measurements (FRMs) for the Copernicus Sentinel-3 STM. This work has gathered existing data, made new observations during field campaigns, and ensured that these observations meet the criteria of FRM standards so that they can be used to validate Sentinel-3 STM Land Altimetry products operationally. A roadmap for the operational provision of the FRM, including the definition, consolidation, and identification of the most relevant and cost-effective methods and protocols to be maintained, supported, or implemented, has been developed. The roadmap includes guidelines for SI traceability, definitions of FRM measurement procedures, processing methods, and uncertainty budget estimations. Full article

The interferometric imaging radar altimeter (InIRA), mounted on the Tiangong-2 space laboratory, utilizes a small incidence and a short interferometric baseline to achieve altimetry for wide swathes of ocean surface topography and inland water surface elevation. To obtain a high-precision digital elevation model (DEM), calibration of the interferometric system parameters is necessary. Because InIRA utilizes the small-incidence interference system design, serious coupling occurs between the interferometric parameters. Commonly used interferometric calibration methods tend to fall into the local optimal solution for InIRA. Because evolutionary algorithms have a stronger robustness and global search ability, they are better suited to handling the solution space structure under the coupling of complex interferometric parameters. This article establishes an interferometric calibration optimization model for InIRA by utilizing the relative flatness of the lake surface as an inequality constraint. Furthermore, an adaptive penalty coefficient constraint evolutionary algorithm is designed to solve the model. The proposed method was tested on actual InIRA data, and the results indicate that it efficiently adjusts interferometric parameters, enhancing the precision of measurements for Qinghai Lake elevation. Full article

While many studies have been conducted regarding wind-driven Ka-band scattering on the ocean and sea surfaces, few have identified the impacts of Ka-band scattering on small inland water bodies, and fewer have identified the influence of wind on coherence over water. These previous studies have been limited in spatial scale, covering only large water bodies >25 km². The recently launched Surface Water and Ocean Topography (SWOT) mission is the first Ka-band InSAR satellite designed for mapping water surface elevations and open water areas for rivers as narrow as 100 m and lakes as small as 0.0625 km². Because measurements of these types are novel, there remains some uncertainty about expected backscatter amplitudes given wind-driven water surface roughness variability. A previous study using the airborne complement to SWOT, AirSWOT, found that low backscatter and low coherence values were indicative of higher errors in the water surface elevation products, recommending minimum thresholds for backscatter and coherence for filtering the data to increase the accuracy of averaged data for lakes and rivers. We determined that the global average wind speed over lakes is 4 m/s, and after comparing AirSWOT backscatter and coherence data with ERA-5 wind speeds, we found that the minimum required speed to retrieve high backscatter and coherence is 3 m/s. We examined 11,072 lakes across Canada and Alaska, with sizes ranging from 350 m² to 156 km², significantly smaller than what could be measured with previous Ka-band instruments in orbit. We found that small lakes (0.0625–0.25 km²) have significantly lower backscatter (3–5 dB) and 0.20–0.25 lower coherence than larger lakes (>1 km²). These results suggest that approximately 75% of SWOT observable lake areas around the globe will have consistently high-accuracy water surface elevations, though seasonal wind variability should remain an important consideration. Despite very small lakes presenting lower average backscatter and coherence, this study asserts that SWOT will be able to accurately resolve the water surface elevations and water surface extents for significantly smaller water bodies than have been previously recorded from satellite altimeters. This study additionally lays the foundation for future high-resolution inland water wind speed studies using SWOT data, when the data become available, as the relationships between wind speed and Ka-band backscatter reflect those of traditional scatterometers designed for oceanic studies. Full article