The Shuttle Radar Topography Mission produced the most complete, highest‐resolution digital elevation model of the Earth. The project was a joint endeavor of NASA, the National Geospatial‐Intelligence Agency, and the German and Italian Space Agencies and flew in February 2000. It used dual radar antennas to acquire interferometric radar data, processed to digital topographic data at 1 arc sec resolution. Details of the development, flight operations, data processing, and products are provided for users of this revolutionary data set.

INDEPTH geophysical and geological observations imply that a partially molten midcrustal layer exists beneath southern Tibet. This partially molten layer has been produced by crustal thickening and behaves as a fluid on the time scale of Himalayan deformation. It is confined on the south by the structurally imbricated Indian crust underlying the Tethyan and High Himalaya and is underlain, apparently, by a stiff Indian mantle lid. The results suggest that during Neogene time the underthrusting Indian crust has acted as a plunger, displacing the molten middle crust to the north while at the same time contributing to this layer by melting and ductile flow. Viewed broadly, the Neogene evolution of the Himalaya is essentially a record of the southward extrusion of the partially molten middle crust underlying southern Tibet.

Surface fresh water is essential for life, yet we have surprisingly poor knowledge of the spatial and temporal dynamics of surface freshwater discharge and changes in storage globally. For example, we are unable to answer such basic questions as “What is the spatial and temporal variability of water stored on and near the surface of all continents?” Furthermore, key societal issues, such as the susceptibility of life to flood hazards, cannot be answered with the current global, in situ networks designed to observe river discharge at points but not flood events. The measurements required to answer these hydrologic questions are surface water area, the elevation of the water surface (h), its slope (∂h/∂x), and temporal change (∂h/∂t). Advances in remote sensing hydrology, particularly over the past 10 years and even more recently, have demonstrated that these hydraulic variables can be measured reliably from orbiting platforms. Measurements of inundated area have been used to varying degrees of accuracy as proxies for discharge but are successful only when in situ data are available for calibration; they fail to indicate the dynamic topography of water surfaces. Radar altimeters have a rich, multidecadal history of successfully measuring elevations of the ocean surface and are now also accepted as capable tools for measuring h along orbital profiles crossing freshwater bodies. However, altimeters are profiling tools, which, because of their orbital spacings, miss too many freshwater bodies to be useful hydrologically. High spatial resolution images of ∂h/∂t have been observed with interferometric synthetic aperture radar, but the method requires emergent vegetation to scatter radar pulses back to the receiving antenna. Essentially, existing spaceborne methods have been used to measure components of surface water hydraulics, but none of the technologies can singularly supply the water volume and hydraulic measurements that are needed to accurately model the water cycle and to guide water management practices. Instead, a combined imaging and elevation‐measuring approach is ideal as demonstrated by the Shuttle Radar Topography Mission (SRTM), which collected images of h at a high spatial resolution (∼90 m) thus permitting the calculation of ∂h/∂x. We suggest that a future satellite concept, the Water and Terrestrial Elevation Recovery mission, will improve upon the SRTM design to permit multitemporal mappings of h across the world's wetlands, floodplains, lakes, reservoirs, and rivers.

Abstract. In just the past 5 years, the field of Earth observation has progressed beyond the offerings of conventional space-agency-based platforms to include a plethora of sensing opportunities afforded by CubeSats, unmanned aerial vehicles (UAVs), and smartphone technologies that are being embraced by both for-profit companies and individual researchers. Over the previous decades, space agency efforts have brought forth well-known and immensely useful satellites such as the Landsat series and the Gravity Research and Climate Experiment (GRACE) system, with costs typically of the order of 1 billion dollars per satellite and with concept-to-launch timelines of the order of 2 decades (for new missions). More recently, the proliferation of smartphones has helped to miniaturize sensors and energy requirements, facilitating advances in the use of CubeSats that can be launched by the dozens, while providing ultra-high (3-5 m) resolution sensing of the Earth on a daily basis. Startup companies that did not exist a decade ago now operate more satellites in orbit than any space agency, and at costs that are a mere fraction of traditional satellite missions.With these advances come new space-borne measurements, such as real-time high-definition video for tracking air pollution, storm-cell development, flood propagation, precipitation monitoring, or even for constructing digital surfaces using structure-from-motion techniques. Closer to the surface, measurements from small unmanned drones and tethered balloons have mapped snow depths, floods, and estimated evaporation at sub-metre resolutions, pushing back on spatio-temporal constraints and delivering new process insights. At ground level, precipitation has been measured using signal attenuation between antennae mounted on cell phone towers, while the proliferation of mobile devices has enabled citizen scientists to catalogue photos of environmental conditions, estimate daily average temperatures from battery state, and sense other hydrologically important variables such as channel depths using commercially available wireless devices. Global internet access is being pursued via highaltitude balloons, solar planes, and hundreds of planned satellite launches, providing a means to exploit the "internet of things" as an entirely new measurement domain. Such globalPublished by Copernicus Publications on behalf of the European Geosciences Union. The future of Earth observation in hydrology access will enable real-time collection of data from billions of smartphones or from remote research platforms. This future will produce petabytes of data that can only be accessed via cloud storage and will require new analytical approaches to interpret. The extent to which today's hydrologic models can usefully ingest such massive data volumes is unclear. Nor is it clear whether this deluge of data will be usefully exploited, either because the measurements are superfluous, inconsistent, not accurate enough, or simply because we lack the capacity to process and analyse them. What is apparen...

Surface water elevation profiles for a reach of the Ohio River were produced by the Jet Propulsion Laboratory Instrument Simulator to represent satellite measurements representative of those that would be observed by a wide swath altimeter being considered jointly by U.S. and European space agencies. The Ensemble Kalman filter with a river hydrodynamics model as its dynamical core was used to assimilate the water elevation synthetic observations, and to estimate river discharge. The filter was able to recover water depth and discharge, reducing the discharge RMSE from 23.2% to 10.0% over an 84‐day simulation period, relative to a simulation without assimilation. An autoregressive error model was instrumental in correcting boundary inflows, and increasing the persistence of error reductions between times of observations. The nominal 8‐day satellite overpass produced discharge relative errors of 10.0%, while 16‐day and 32‐day overpass frequencies resulted in errors of 12.1% and 16.9% respectively.

[1] The proposed Surface Water and Ocean Topography (SWOT) mission would provide measurements of water surface elevation (WSE) for characterization of storage change and discharge. River channel bathymetry is a significant source of uncertainty in estimating discharge from WSE measurements, however. In this paper, we demonstrate an ensemble-based data assimilation (DA) methodology for estimating bathymetric depth and slope from WSE measurements and the LISFLOOD-FP hydrodynamic model. We performed two proof-of-concept experiments using synthetically generated SWOT measurements. The experiments demonstrated that bathymetric depth and slope can be estimated to within 3.0 microradians or 50 cm, respectively, using SWOT WSE measurements, within the context of our DA and modeling framework. We found that channel bathymetry estimation accuracy is relatively insensitive to SWOT measurement error, because uncertainty in LISFLOOD-FP inputs (such as channel roughness and upstream boundary conditions) is likely to be of greater magnitude than measurement error.

INDEPTH seismic reflection profiling shows that the decollement beneath which Indian lithosphere underthrusts the Himalaya extends at least 225 kilometers north of the Himalayan deformation front to a depth of approximately 50 kilometers. Prominent reflections appear at depths of 15 to 18 kilometers near where the decollement reflector apparently terminates. These reflections extend north of the Zangbo suture to the Damxung graben of the Tibet Plateau. Some of these reflections have locally anomalous amplitudes (bright spots) and coincident negative polarities implying that they are produced by fluids in the crust. The presence of geothermal activity and high heat flow in the regions of these reflections and the tectonic setting suggest that the bright spots mark granitic magmas derived by partial melting of the tectonically thickened crust.

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