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Summary of Proposal HYD1167

TitleMonitoring seasonal variations in reservoir storage using high resolution TerraSAR-X time series data for studying water availability in semi-arid NE Brazil for use in hydrological modeling
Investigator Foerster, Saskia - GFZ Potsdam, Department of Geodesy and Remote Sensing, Remote Sensing section
Team Member
Dr Francke, Till - University of Potsdam, Institute for Earth and Environmental Sciences
SummaryThe aim of the study is to explore the capabilities of multi-temporal high resolution TerraSAR-X data for monitoring and managing water resources in dryland areas that face large water scarcity and erosion problems. The study area in the semi-arid North-East of Brazil is characterized by pronounced wet and dry periods. To ensure water availability during the seven month dry period, more than 150 reservoirs were constructed in the investigated 1000 km² catchment of Bengue. While the few large ones are equipped with water level gauges, in the majority of the smaller remote reservoirs continuous water level measurements are not feasible. However, particularly these remote reservoirs show pronounced seasonal water level variations, which reflect the effect ofwater inflow, consumption and losses and have substantial influence on local water availability and basin-scale water and sediment connectivity. TSX data analysis may provide valuable information on the reservoirs´ bathymetric characteristics and on the spatial and temporal behavior of the hydrological system in terms of water surface area and thus storage variability. Ground-truth data, i.e. water level time series by gauges, extent of reservoir surface areas by GPS and bathymetric surveys by echo-sounding, will be collected parallel to the TSX data acquisition for validation purposes. Interferometric TSX data collected during the dry period will be utilized to derive digital elevation models of fallen dry reservoirs. Based on these DEMs and collected ground-truth data, typical stage-area and stage-volume functions of the reservoirs will be set up. Multi-temporal TSX data will then be utilized to detect reservoir surface area changes over dry and wet periods, while different algorithms based on intensity, texture and contours will be tested for their suitability. These seasonal changes in reservoir surface area will then be related to water levels and volume using the set-up functions. This will allow hydrological model calibration and validation by reconstructing runoff and water retention in reservoirs throughout the catchment as a pre-requisite for predicting and managing water availability for the local population.

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