Analytical Models for Multipath and Switch Leakage for the SWOT Interferometer

The volume variability and the hydrological functioning of the thousands of lakes in the Sahelian region are poorly known. The recently launched Surface Water and Ocean Topography (SWOT) mission carrying a wide-swath Ka-band radar interferometer offers new opportunities for large-scale monitoring of lake dynamics, and overcomes the spatial coverage limitations of the nadir altimeters. Here, we evaluate the performance of two SWOT data products, namely the PIXel Cloud (PIXC) and the Lake Single Pass (LakeSP), over sixteen small and medium-sized lakes in the Central Sahel. For both products, Water Surface Elevations (WSEs) are in excellent agreement with in-situ data on two lakes, with 1-σ errors (68th percentile of absolute errors) between 0.06 and 0.11 m, consistently with the mission science requirements. When compared to Sentinel-3 WSE, the PIXC product shows better results than LakeSP, with 1- σ differences of 0.16 m and 0.32 m, respectively. SWOT LakeSP Water Surface Area (WSA) estimates show a general overestimation with a median bias of 17.2% compared to Sentinel2 measurements. SWOT pixel classification errors are found to affect both products, especially for LakeSP. Elevation-area relationships derived from combined SWOT PIXC and Sentinel-2 compare well with in-situ (RMSEs below 0.28 m), highlighting the capabilities of SWOT for monitoring lake volume changes once complemented by external water masks. Finally, annual water level amplitude estimates of more than 600 lakes of different sizes are derived using SWOT PIXC, emphasizing the spatial coverage potential of SWOT.

The proposed surface water and ocean topography (SWOT) mission aims at observing short scale ocean topography with an unprecedented resolution and accuracy. Its main proposed sensor is a radar interferometer, so a major source of topography error is the roll angle: the relative positions of SWOT’s antennas must be known within a few micrometers. Because reaching SWOT’s stringent requirements with onboard roll values is challenging, we carried out simulations as a contingency strategy (i.e., to be ready if roll is larger than anticipated) that could be used with ground-based data. We revisit the empirical calibration algorithms with additional solving methods (e.g., based on orbit sub-cycle) and more sophisticated performance assessments with spectral decompositions. We also explore the link between the performance of four calibration methods and the attributes of their respective calibration zones: size and geometry (e.g., crossover diamonds), temporal variability (e.g., how many days between overlapping SWOT images). In general, the so-called direct method (using a single SWOT image) yields better coverage and smaller calibrated roll residuals because the full extent of the swath can be used for calibration, but this method makes an extensive use of the external nadir constellation to separate roll from oceanic variability, and it is more prone to leakages from oceanic variability on roll (i.e., true topography signal is more likely to be corrupted if it is misinterpreted as roll) and inaccurate modeling of the true topography spectrum. For SWOT’s baseline orbit (21 days repeat and 10.9 days sub-cycle), three other methods are found to be complementary with the direct method: swath crossovers, external nadir crossovers, and sub-cycle overlaps are shown to provide an additional calibration capability, albeit with complex latitude-varying coverage and performance. The main asset of using three or four methods concurrently is to minimize systematic leakages from oceanic variability or measurement errors, by maximizing overlap zones and by minimizing the temporal variability with one-day to three-day image differences. To that extent, SWOT’s proposed “contingency orbit” is an attractive risk reduction asset: the one-day sub-cycle overlaps of adjoining swaths would provide a good, continuous, and self-sufficient (no need for external nadirs) calibration scheme. The benefit is however essentially located at mid to high-latitudes and it is substantial only for wavelengths longer than 100 km.

Lakes are among the most prevalent and predominant water repositories on the Earth's land surface. A primary objective of the Surface Water and Ocean Topography (SWOT) satellite mission is to monitor surface water elevation, area, and storage change in lakes globally. To meet this objective, prior information on lakes, such as locations and benchmark extents, is required to organize SWOT's KaRIn observations for computing lake storage variation over time. Here, we present the SWOT mission Prior Lake Database (PLD) to fulfill this requirement. This paper emphasizes the development of the “operational PLD,” which consists of (a) a high‐resolution mask encompassing approximately 6 million lakes and reservoirs that meet the minimum size criterion of 1 ha, as defined in SWOT’s lake observation science goals, and (b) multiple operational auxiliaries that support the lake mask in generating SWOT's standard lake vector data products. We built the prior lake mask by harmonizing the UCLA Circa‐2015 Global Lake Dataset and several state‐of‐the‐art reservoir databases. Operational auxiliaries were produced from multi‐theme geospatial data to provide essential information for PLD functionality, including lake catchments and influence areas, ice phenology, relationship with SWOT prior rivers, and spatiotemporal coverage by SWOT overpasses. Globally, over three quarters of the prior lakes are smaller than 10 ha. About 97% of the lakes, constituting half of the global lake area, are fully observed at least once per orbit cycle. The PLD will be recursively improved throughout the mission lifetime and serves as a critical framework for organizing, processing, and interpreting SWOT observations over lacustrine environments with fundamental significance to lake system science.

Even though altimetry has redefined our understanding of global rivers and lakes, the sparse temporal sampling of altimeters is often a cause of concern for many applications. This study explores the efficiency of temporal sampling offered by the recently launched Surface Water and Ocean Topography (SWOT) mission for hydrological applications over India. In particular, two research hypotheses are being investigated, namely a). Potential of SWOT data for enhancing flood mapping capabilities across India and b) Impact of SWOT-based discharges for calibrating a hydrological model calibration. Toward answering the first hypothesis, we considered a hypothetical launch date for SWOT, generating overpass data based on the mission's spatiotemporal orbital configuration. These overpass data were then compared with flood-affected areas identified in the Indian Flood Inventory (IFI) data to assess SWOT's potential for flood mapping. Results show that the spatio-temporal resolution of SWOT facilitates the monitoring of diverse proportions of Indian districts based on the cycle. More specifically, 0.67%, 15.79%, 29.24%, 45.54%, and 8.06% of Indian districts have one, two, three, four, and more than four observations per SWOT cycle (~21 days), respectively. To evaluate the second hypothesis, namely, the feasibility of SWOT discharge in hydrological model calibration, we created proxy-SWOT data by sampling in-situ data in accordance with the SWOT orbit configuration. Subsequently, errors were introduced into the in-situ gauge data based on recommendations from the SWOT science team. Results are presented over selected case study region of the Mahanadi river basin in India.

This study presents an evaluation of the Surface Water and Ocean Topography (SWOT) mission for monitoring riverine hydrodynamics, using the Po River (Northern Italy) as a test case. Given the recent launch of SWOT, its application to river hydraulics remains relatively unexplored and requires thorough validation against in-situ observations and specially, physically based models. We assess SWOT Water Surface Elevation (WSE), water surface slope, and recently released discharge products during the science phase, by comparing them with gauge measurements and hydrodynamic simulations over a ~300 km reach of the Po River, including the delta section (a coupled 1D/2D HEC-RAS model is employed to dynamically simulate river hydraulics).The analysis integrates multiple SWOT products, including the Level-2 High-Rate Pixel Cloud (SWOT_L2_HR_PIXC) and Level-2 River Single-Pass Vector Product (SWOT_L2_HR_RiverSP - RiverSP), explicitly accounting for quality flags and performance under different flow regimes.Results highlight the critical importance of quality-aware filtering for reliable use of SWOT observations. Good- and degraded-flagged WSE data generally show strong agreement with both in-situ measurements and model simulations, whereas suspect and bad flagged observations exhibit significantly larger discrepancies, with deviations reaching several meters. The analysis also reveals spatial patterns in SWOT performance linked to geophysical and orbital factors.Comparison of RiverSP WSE node data against 10 in-situ stations shows biases up to ~10 cm for good and degraded data, with mean Kling–Gupta Efficiency (KGE) values of 0.92 and 0.82 for high-flow and low-flow regimes, respectively. Across all 114 analysed SWOT passes (each representing a longitudinal river WSE profile), on average, 68% of node observations per pass, are flagged as good or degraded, while 12 passes contain no usable data. Nevertheless, approximately 82% of the profiles show high agreement with the hydrodynamic model (KGE ≥ 0.8), highlighting the strong performance of SWOT in reproducing river WSE profiles. Profile-based comparisons also reveal orbit-dependent performance variability among different SWOT passes.To address data limitations and improve spatial coverage, complementary Pixel Cloud products are leveraged for their higher spatial resolution, although these require extensive preprocessing, including spatial filtering and noise/outlier removal.The study further explores the spatial and temporal performance of SWOT observations in relation to (i) distance from nadir track, (ii) satellite pass orientation, (iii) river planform geometry (e.g. straight vs. meandering reaches), and (iv) flow regime (e.g. rising limb, peak, recession, low flow). Although based on a single case study, the results illustrate both the potential and current limitations of SWOT products for riverine applications. The findings emphasize the importance of integrating quality-controlled satellite observations with physically based hydrodynamic models to support operational hydrology, long-term monitoring, and decision-making for flood and drought risk mitigation in inland-to-coastal environments. The proposed methodology is readily transferable to other river systems for inter-basin comparative analyses under diverse hydraulic conditions.

The Surface Water and Ocean Topography (SWOT) altimeter will perform a continuous global water survey with unprecedented resolution and accuracy across its 3-year mission. After being launched on December 16th 2022 with a SpaceX Falcon 9 rocket from Vandenberg in California, it was successfully commissioned followed by a Calibration and Validation (Cal/Val) phase that lasted approximately between April and July 2023. During this period, numerous in-situ measurements were performed across the globe to assess the altimeter’s performance. Airborne Light Detection And Ranging (LiDAR) campaigns were conducted off the coasts of Normandy, France as part of other measurements in this region. We carried out 4 different missions, 2 in May and 2 in June, using a Leica ALS 60 airborne sensor aboard 2 different planes, a Piper Navajo and a Swearingen Fairchild Merlin. The flight plans were designed below the SWOT Ka-band Radar Interferometer (KaRIn) along and across the 1-day fast sampling ground track. Ground Control Points (GCP) were acquired under the LiDAR coverage, close to the city of Cherbourg. The plane’s trajectory was processed using CNES GINS software, using the integer Precise Point Positioning (iPPP) mode, resulting in centimetric antenna phase positioning. LiDAR data were calibrated using the GCPs with a millimetric average accuracy. First results between SWOT data and airborne LiDAR indicate very good consistency. Indeed, the differences between the SWOT LR 2 km pre-cal product and LiDAR data, averaged over a similar 2 km grid, gives centimetric standard deviation.

Bogotá, the capital of Colombia, relies on one of the largest and most complex urban water supply systems in the country. Drinking water is primarily sourced from high-altitude reservoirs located within the Chingaza National Park, situated in the Andean páramo ecosystems surrounding the metropolitan area. Beginning in late 2023 and continuing into 2024, severe drought conditions linked to the El Niño phenomenon led to historically low storage levels in the Chingaza system. As a consequence, in April 2024, Bogotá implemented water rationing for the first time in recent decades.In this context, this study evaluates the potential of satellite-based observations to support reservoir monitoring and water resources management in Bogotá. We analyze water surface elevation (WSE) and water surface area (WSA) for the Chuza and San Rafael reservoirs—both part of the Chingaza system—by integrating in situ observations with products from the Surface Water and Ocean Topography (SWOT) mission and Sentinel-2 imagery.First, WSE estimates from SWOT Level-2 products (LakeSP and Raster) were validated against observed WSE between September 2023 and February 2026. Over the same period, WSA derived from SWOT and Sentinel-2 was validated against in situ WSA estimated from reservoir hypsometric curves.Results show an excellent agreement between SWOT LakeSP WSE and observations for the Chuza reservoir, with a Pearson correlation coefficient of 0.9934. In contrast, performance for the San Rafael was substantially lower, with a correlation of 0.5971 and a systematic negative bias of −8.83 m, indicating reduced accuracy of SWOT-derived WSE in this smaller reservoir. Similar patterns were observed for the SWOT Raster product with moderate correlation for Chuza (0.7138), and large discrepancies for San Rafael. In contrast, WSA time series derived from the Normalized Difference Water Index (NDWI) from Sentinel-2 exhibited acceptable performance for San Rafael, with a correlation of 0.8535 and a bias of −0.37 km², and 0.6207 correlation and -0.61 km² bias for the Chuza reservoir.Overall, the results demonstrate the strong potential of SWOT and Sentinel-2 products for monitoring strategic water supply reservoirs in the Colombian Andes, while also highlighting pronounced performance differences linked to reservoir size, shape and surrounding topography. The findings emphasize the usefulness of these satellite products for hydrological applications in the Colombian Andes but also underscore challenges such as persistent cloud cover and the need for more robust algorithms that integrate the high precision of SWOT with complementary datasets to improve area estimation.

The 29 July 2025, M w 8.8 Kamchatka earthquake caused a major tsunami in the west Pacific Ocean. We use the sea surface height measurements from the recently launched wide-swath satellite altimeter, Surface Water and Ocean Topography (SWOT) mission, to extract the tsunami signal. The ascending pass (P0267) of SWOT mission captured the perturbation on the ocean surface in two-dimensions after about 70 min. The tsunami signal sampled by SWOT has a peak amplitude of 0.7 m spread across a horizontal distance of ∼250 km. We compare the tsunami signal extracted from SWOT with the wave fields simulated using the seafloor deformation computed from co-seismic fault slip model. SWOT observations could capture major features of the simulated wave field with a correlation coefficient (r) of 0.77. Our results suggest that rapid, two-dimensional imaging of tsunami waves by SWOT could improve both earthquake source estimation and tsunami wave predictions, which are important for the mitigation of tsunami-related hazards.

Evaluating SWOT water level information using a large scale hydrology simulator: A case study over India

SWOT is a pathfinder mission using new technology to address transformative questions on energy and water of the Earth System in a warming climate.  The excess heat energy entering the Earth system as a result of the greenhouse effect is largely stored in water, and changes in the water cycle and water resources have profound effects on life on Earth.             SWOT is a next generation radar altimeter that uses synthetic aperture radar interferometry to measure the elevation of water surface over both continents and oceans in two dimensions with a radar footprint 1000 times smaller than that of a conventional altimeter. SWOT will cover the world between 78N and 78S every 21 days, leaving only small gaps comprising <5% of Earth’s surface.  More than 90% of the heat from global warming since the industrial revolution has been absorbed and stored in the ocean.  A major part of this process takes place in the ocean on scales too small to be observed from space in the past.  SWOT will improve the two-dimensional spatial resolution of sea surface height from present 200 km to 20 km to address the processes of heat uptake from the atmosphere. In a warming climate earth’s water cycle is accelerating, making it difficult to track and manage water resources as well as predicting floods and droughts.  The areal extent of surface water on land can be observed by conventional spaceborne sensors, but the volume of surface water in lakes and rivers will be surveyed by SWOT from space for the first time.  The numbers of rivers and lakes to be surveyed by SWOT are orders of magnitude more than the present observations. The high-resolution data of SWOT near the coasts will allow us to study sea level variations in unprecedented detail. Storm surge and other impacts like salt water intrusion and river diversion will be exacerbated by the continuing sea level rise.  SWOT data will help improve models to monitor and forecast these impacts. After nearly 20 years’ development, SWOT was launched on December 16, 2022 as a joint mission of NASA and the French Space Agency, CNES, with contributions from the Canadian Space Agency and the UK Space Agency. The satellite system was fully deployed within a week of launch and is in a 3-month phase of engineering checkout.  A 3-month calibration and validation phase will start afterwards in the one-day repeat initial orbit, which will transition into a 21-day repeat orbit during the science phase of the mission in mid 2023.  The release of SWOT data to the public for evaluation is expected to take place 10 months after launch.  The status of the mission at the end of April will be reported by this presentation.

The Surface Water and Ocean Topography (SWOT) mission is primarily designed to measure Sea Surface Height in two dimensions at an unprecedented resolution thanks to its innovative Ka-band radar interferometer KaRIn. In addition to the topography measurements derived from the phase difference between the images acquired at each of the two antennas separated by 10 meters, KaRIn can also provide information about the sea state, by exploiting the measured power in each of the SAR images and the interferometric correlation between both acquisition channels.This last quantity, sometimes referred to as interferometric coherence, is directly affected by the presence of surface waves. This provides a fantastic opportunity to measure, for the first time at a global scale, Significant Wave Height at kilometric resolutions (well below the reach of nadir altimeters) and in two dimensions. This, however, requires estimating all other sources of decorrelation of instrumental origin with an exquisite precision to avoid misinterpreting instrumental effects as geophysical signals.In this talk, I will briefly describe how the interferometric acquisitions by KaRIn are calibrated and processed to obtain SWH maps in 2D at various km-scale resolutions (typically 2x2 km or 5x5 km), and discuss how the accuracy at which we need to estimate all the other sources of decorrelation varies with cross-track distance and actual SWH to highlight the most challenging regimes for the inversion. I will then present comparisons between the KaRIn two-dimensional SWH measurements and several independent sets of validation data, including data from SWOT’s nadir altimeter, from the SAR nadir altimeter on-board Sentinel-3, from MASS’s lidar, and from in-situ data. I will finish by discussing various physical features that can be observed in the retrieved SWH fields to illustrate that the high resolution and the two-dimensional character of SWOT measurements really open the door to the quantitative study of the processes that contribute to sea-state variations at small scales.

The upcoming Surface Water and Ocean Topography (SWOT) mission will measure water surface heights and widths for rivers wider than 100 m. At its native resolution, SWOT height errors are expected to be on the order of meters, which prevent the calculation of water surface slopes and the use of slope‐dependent discharge equations. To mitigate height and width errors, the high‐resolution measurements will be grouped into reaches (∼5 to 15 km), where slope and discharge are estimated. We describe three automated river segmentation strategies for defining optimum reaches for discharge estimation: (1) arbitrary lengths, (2) identification of hydraulic controls, and (3) sinuosity. We test our methodologies on 9 and 14 simulated SWOT overpasses over the Sacramento and the Po Rivers, respectively, which we compare against hydraulic models of each river. Our results show that generally, height, width, and slope errors decrease with increasing reach length. However, the hydraulic controls and the sinuosity methods led to better slopes and often height errors that were either smaller or comparable to those of arbitrary reaches of compatible sizes. Estimated discharge errors caused by the propagation of height, width, and slope errors through the discharge equation were often smaller for sinuosity (on average 8.5% for the Sacramento and 6.9% for the Po) and hydraulic control (Sacramento: 7.3% and Po: 5.9%) reaches than for arbitrary reaches of comparable lengths (Sacramento: 8.6% and Po: 7.8%). This analysis suggests that reach definition methods that preserve the hydraulic properties of the river network may lead to better discharge estimates.

Exploring the potential of SWOT mission for reservoir monitoring in Mahanadi basin

Surface Water and Ocean Topography (SWOT) is a future wide-swath radar altimetry mission. The main instrument is the Ka-band radar interferometer (KaRIn). It provides interferometric radar images that will be processed to obtain water elevation estimates worldwide. Due to the specific geometric and radiometric characteristics of KaRIn/SWOT, the phase-to-height conversion is one of the most critical processing steps. We propose methods to estimate water heights without using classical approaches based on spatial phase unwrapping and control points. Results obtained on the simulated SWOT data are shown.

This study investigates the occurrence of surface elevation oscillations, known as seiches, at the atoll scale. We show that the innovative Ka‐band Radar Interferometer (KaRIn) onboard the Surface Water Ocean Topography (SWOT) satellite makes it possible to visualize seiche‐like structures within lagoons of French Polynesia. This ability to capture two‐dimensional sea surface undulations of low amplitude (on the order of a few centimeters) in relatively small water bodies (less than 80 km in length) is unprecedented in satellite altimetry, and opens new avenues of research into these events and their contribution to coastal erosion and flooding. Our study combines sea surface height observations from SWOT with in situ measurements conducted in the Raroia lagoon and theoretical calculations based on an eigenvalue model. These three complementary approaches—satellite remote sensing, in situ data, and theoretical modeling—allow us to investigate both the spatial and spectral properties of seiches in atoll islands.