Radar altimetry provides unique information on water stages of inland hydro-systems. In this study, the performance of seven altimetry missions, among the most commonly used in land hydrology (i.e., European Remote-Sensing Satellite-2 (ERS-2), ENVIronment SATellite (ENVISAT), Satellite with Argos and ALtika (SARAL), Jason-1, Jason-2, Jason-3 and Sentinel-3A), are assessed using records from a dense in situ network composed of 19 gauge stations in the Inner Niger Delta (IND) from 1995 to 2017. Results show an overall very good agreement between altimetry-based and in situ water levels with correlation coefficient (R) greater than 0.8 in 80% of the cases and Root Mean Square Error (RMSE) lower than 0.4 m in 48% of cases. Better agreement is found for the recently launched missions such as SARAL, Jason-3 and Sentinel-3A than for former missions, indicating the advance of the use of the Ka-band for SARAL and of the Synthetic-aperture Radar (SAR) mode for Sentinel-3A. Cross-correlation analysis performed between water levels from the same altimetry mission leads to time-lags between the upstream and the downstream part of the Inner Niger Delta of around two months that can be related to the time residence of water in the drainage area.

Quantification of surface water storage in extensive floodplains and their dynamics are crucial for a better understanding of global hydrological and biogeochemical cycles. In this study, we present estimates of both surface water extent and storage combining multi-mission remotely sensed observations and their temporal evolution over more than 15 years in the Mackenzie Delta. The Mackenzie Delta is located in the northwest of Canada and is the second largest delta in the Arctic Ocean. The delta is frozen from October to May and the recurrent ice break-up provokes an increase in the river's flows. Thus, this phenomenon causes intensive floods along the delta every year, with dramatic environmental impacts. In this study, the dynamics of surface water extent and volume are analysed from 2000 to 2015 by combining multi-satellite information from MODIS multispectral images at 500 m spatial resolution and river stages derived from ERS-2 (1995–2003), ENVISAT (2002–2010) and SARAL (since 2013) altimetry data. The surface water extent (permanent water and flooded area) peaked in June with an area of 9600 km² (±200 km²) on average, representing approximately 70 % of the delta's total surface. Altimetry-based water levels exhibit annual amplitudes ranging from 4 m in the downstream part to more than 10 m in the upstream part of the Mackenzie Delta. A high overall correlation between the satellite-derived and in situ water heights (R > 0.84) is found for the three altimetry missions. Finally, using altimetry-based water levels and MODIS-derived surface water extents, maps of interpolated water heights over the surface water extents are produced. Results indicate a high variability of the water height magnitude that can reach 10 m compared to the lowest water height in the upstream part of the delta during the flood peak in June. Furthermore, the total surface water volume is estimated and shows an annual variation of approximately 8.5 km³ during the whole study period, with a maximum of 14.4 km³ observed in 2006. The good agreement between the total surface water volume retrievals and in situ river discharges (R= 0.66) allows for validation of this innovative multi-mission approach and highlights the high potential to study the surface water extent dynamics.

Spatial resolution is the main instrumental requirement for the multi-spectral optical space missions that address the scientific issues of marine coastal systems. This spatial resolution should be at least decametric. Aquatic color data processing associated with these environments requires specific atmospheric corrections (AC) suitable for the spectral characteristics of high spatial resolution sensors (HRS) as well as the high range of atmospheric and marine optical properties. The objective of the present study is to develop and demonstrate the potential of a ground-based AC approach adaptable to any HRS for regional monitoring and security of littoral systems. The in Situ-based Atmospheric CORrection (SACOR) algorithm is based on simulations provided by a Successive Order of Scattering code (SOS), which is constrained by a simple regional aerosol particle model (RAM). This RAM is defined from the mixture of a standard tropospheric and maritime aerosol type. The RAM is derived from the following two processes. The first process involved the analysis of a 6-year data set composed of aerosol optical and microphysical properties acquired through the ground-based PHOTONS/AERONET network located at Arcachon (France). The second process was related to aerosol climatology using the NOAA hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model. Results show that aerosols have a bimodal particle size distribution regardless of the season and are mainly represented by a mixed coastal continental type. Furthermore, the results indicate that aerosols originate from both the Atlantic Ocean (53.6%) and Continental Europe (46.4%). Based on these results, absorbing biomass burning, urban-industrial and desert dust particles have not been considered although they represent on average 19% of the occurrences. This represents the main current limitation of the RAM. An assessment of the performances of SACOR is then performed by inter-comparing the water-leaving reflectance ( ${\rho }_w$ ) retrievals with three different AC methods (ACOLITE, MACCS and 6SV using three different standard aerosol types) using match-ups (N = 8) composed of Landsat-8/Operational Land Imager (OLI) scenes and field radiometric measurements. Results indicate consistency with the SWIR-based ACOLITE method, which shows the best performance, except in the green channel where SACOR matches well with the in-situ data (relative error of 7%). In conclusion, the study demonstrates the high potential of the SACOR approach for the retrieval of ${\rho }_w$ . In the future, the method could be improved by using an adaptive aerosol model, which may select the most relevant local aerosol model following the origin of the atmospheric air mass, and could be applied to the latest HRS (Sentinel-2/MSI, SPOT6-7, Pleiades 1A-1B).

Ephemeral rivers are characterized by brief episodic flood events, which recharge subterraean alluvial aquifers that sustain humans, riparian vegetation, and wildlife in the hyper-arid Namib Desert. Yet we only have a poor understanding of the dynamics and feedback mechanisms in these hydrological systems as arid and semi-arid zones are typically poorly equipped with reliable in situ monitoring stations to provide necessary information. The main objective of our study is to show the potential of satellite data to monitor the dynamics of ephemeral rivers, such as the Kuiseb located in Namibia, since remotesensing offers the advantage of adapted spatial and temporal resolutions. For this study, multi-spectral imagery (Sentinel-2), Synthetic Aperture Radar (SAR, Sentinel-1), and SAR interferometry (Sentinel-1) data were used to produce Normalized Difference Vegetation Index (NDVI) maps, backscattering maps (as σ₀), and interferograms, respectively. These parameters provide information on the hydrologic and vegetation dynamics of the river. Strong variations in NDVI, σ₀, and interferograms are observed during March–April 2017 and June–July 2018 in a tributary of the Kuiseb in the central Namib Desert. In those years, rain events caused the reactivation of the tributary. However, during a major flood in 2021, when no rain occured, no variations in NDVI were detected in this tributary, unlike the σ₀ and interferogram anomalies after the flood. Thus, these variations cannot be explained by rains, which were non-existent during this period, but seem to be linked to the dynamics of the aquifer of the Kuiseb River, wherein floods recharge the alluvial aquifers and the rising water table levels produce a signal that is measurable by satellite radar sensors. All these results present a preliminary work that might be used by water resource managers to automate the processing and methods used to create an ephemeral river monitoring tool.