Summary

NEW ! The SSSI volume 55 on Remote Sensing and Water Resources is now available (see publication page)

In recent years, remote sensing techniques have demonstrated their capability to monitor components of the water balance of large river basins on time scales ranging from months to decades. For example, satellite altimetry is routinely used for systematic monitoring of water levels of large rivers, lakes and floodplains. If combined with satellite imagery, it provides surface water volume variations. Passive and active microwave sensors offer important information on soil moisture (e.g., the SMOS mission) as well as wetlands and snowpack. Space gravity missions (e.g., the GRACE mission) offer for the first time, the possibility of directly measuring spatio-temporal variations of the total vertically integrated terrestrial water storage. When combined with other space observations (e.g., from satellite altimetry and SMOS) or model estimates of surface waters and soil moisture, space gravity data can measure groundwater storage variations. The purpose of this workshop is to bring together scientists interested in land hydrology, water resources and the global water cycle either from observations or hydrological models –or both-. Two main issues will be addressed:

(1) promote the use in combination of space observations for monitoring water storage changes in river basins worldwide

(2) use the space data in hydrological modeling either through data assimilation or as external constraints.

An important perspective for the latter topic is to account as far as possible for direct anthropogenic forcing on land hydrology (e.g., ground water depletion; dam building on rivers, crop irrigation, change in land use and agricultural practices, etc.) using a variety of remote sensing and other information. Such a new generation of hydrological models will be of great interest for water management objectives. They might also be used for projecting future water resources under different climate and anthropogenic forcing scenarios.

 

Last update: September 15, 2016