Lakes are integrators of environmental change occurring at both the regional and global scale. They present a wide range of behavior on a variety of timescales (cyclic and secular) depending on their morphology and climate conditions. Lakes play a crucial role in retaining and stocking water, and because of the significant global environmental changes occurring at several anthropocentric levels, the necessity to monitor all morphodynamic characteristics [e.g., water level, surface (water contour) and volume] has increased substantially. Satellite altimetry and imagery are now widely used together to calculate lake and reservoir water storage changes worldwide. However, strategies and algorithms to calculate these characteristics are not straightforward, and specific approaches need to be developed. We present a review of some of these methodologies by using lakes over the Tibetan Plateau to illustrate some critical aspects and issues (technical and scientific) linked to the observation of climate change impact on surface waters from remote sensing data. Many authors have measured water variation using the limited remote sensing measurements available over short time periods, even though the time series are probably too short to directly link these results with climate change. Indeed, there are many processes and factors, like the influence of lake morphology, that are beyond observation and are still uncertain. The time response for lakes to reach a new state of equilibrium is a key aspect that is often neglected in current literature. Observations over a long period of time, including maintaining a constellation of comprehensive and complementary satellite missions with service continuity over decades, are therefore necessary especially when the ground gauge network is too limited. In addition, the design of future satellite missions with new instrumental concepts (e.g., SAR, SARin, Ka band altimetry, Ka interferometry) will also be suitable for complete monitoring of continental waters.

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Glaciers are one of the terrestrial essential climate variables (ECVs) as they respond very sensitively to climate change. A key driver of their response is the glacier surface mass balance that is typically derived from field measurements. It deserves to be quantified over long time scales to better understand the accumulation and ablation processes at the glacier surface and their relationships with inter-annual changes in meteorological conditions and long-term climate changes. Glaciers with in situ monitoring of surface mass balance are scarce at the global scale, and satellite remote sensing provides a powerful tool to increase the number of monitored glaciers. In this study, we present a review of three optical remote sensing methods developed to quantify seasonal and annual glacier surface mass balances. These methodologies rely on the multitemporal monitoring of the end-of-summer snow line for the equilibrium-line altitude (ELA) method, the annual cycle of glacier surface albedo for the albedo method and the mapping of the regional snow cover at the seasonal scale for the snow-map method. Together with a presentation of each method, an application is illustrated. The ELA method shows promising results to quantify annual surface mass balance and to reconstruct multi-decadal time series. The other two methods currently need a calibration on the basis of existing in situ data; however, a generalization of these methods (without calibration) could be achieved. The two latter methods show satisfying results at the annual and seasonal scales, particularly for the summer surface mass balance in the case of the albedo method and for the winter surface mass balance in the case of the snow-map method. The limits of each method (e.g., cloud coverage, debris-covered glaciers, monsoon-regime and cold glaciers), their complementarities and the future challenges (e.g., automating of the satellite images processing, generalization of the methods needing calibration) are also discussed.