SaWaM - Seasonal Water Resources Management

In the frame of the research initiative Water as a Global Resource (GRoW), and sponsored by the German Federal Ministry of Education and Research (BMBF), the project SaWaM aims at performance analysis of global hydro-meteorological data as decision support for the regional water management in semi-arid regions.

In the frame of the research initiative Water as a Global Resource (GRoW), and sponsored by the German Federal Ministry of Education and Research (BMBF), the project SaWaM aims at performance analysis of global hydro-meteorological data as decision support for the regional water management in semi-arid regions. Major target areas include Karun and Urmia (Iran), Blue Nile and Upper Atbara (Sudan), and Sao Francisco (Brazil) basins. The special focus is on seasonal prediction of water availability, evaluation of the state of the eco-system, and modeling of sediment flow. By the end of this project, SaWaM will introduce an industry mature prototype, which allows to examine and apply all developed products. To ensure the practical applicability of the results, the developed models will also be evaluated over other basins in Ecuador and West Africa. SaWaM is a collaborative research project between Karlsruhe Institute of Technology, University of Potsdam, University of Stuttgart, Technical University of Berlin, University of Marburg, Helmholtz Center for Environmental Research (UFZ), German Research Center for Geosciences (GFZ), Lahmeyer International GmbH, GAF AG, and a variety of regional decision makers.

The reliability of SaWaM’s results is partially governed by how comprehensive the input hydro-meteorological data sets are. Given the significant reduction in the number of gauge stations, however, this information is not ubiquitously available as in situ measurement. Here at GIS, we make use of spaceborne geodetic sensors as an alternative for hydrological monitoring. More specifically, we use satellite altimetry and satellite gravimetry to derive water level and water storage anomaly time series.

The main focus is on radar altimetry which in case of SaWaM’s regions of interest is quite challenging. River networks in semi-arid areas are mostly featured with narrow cross sections. This causes a high degree of heterogeneity of radar reflections inside the altimetry footprint, and consequently, inaccurate water height estimation. The other source of complexity is the poor spatial and temporal data coverage which hinders the time series analysis. By developing appropriate re-trackers and applying multi-mission satellite altimetry, our objective is to compensate for such degrading effects and provide SaWaM with reliable water level information. Moreover, we will look into GRACE and GRACE FO and evaluate their practical use for the purpose of hydrological monitoring within the temporal and spatial resolution which is required for SaWaM.

 

Dieses Bild zeigt Behnia
M.Sc.

Sajedeh Behnia

PhD Student

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