Drought Forecast and Water Management System for the semi-arid region of the state of Ceara, Brazil
Final Report Abstract
The aim of the current project was to develop an operational drought forecast and water management system (DFMS) prototype for the state of Ceará. Instead, as proposed, of integrating all outcomes into the existing water management information system of FUNCEME (SIGA), it was decided that each application should be developed as a stand alone component that could be flexibly applied to different ends, as well as to serve inputs for downstream models and applications. The main reason for this deviation to the proposal was the release in production of the Copernicus science hub API by the European space agency. This API was not available by the time the proposal was written and unleashed enormous possibilities when combined with innovative methodologies for bathymetric survey of small reservoirs from satellite. This required developing new monitoring approaches to make use of this novel data set instead of using obsolete approximations of available water storage in small reservoirs. The project was divided into four main work packages, which aimed to operationalize WASA-SED, setup of the DFMS, geovisualization, and stakeholder consultation and dissemination. The mentioned deviation of the project proposal occurred mainly in WP2, i.e. setup of the DFMS. The main outcome of this project was the implementation of an engine and a web application for historical and forecasted hydro-meteorological variables relevant for water management in semi-arid regions. The web application and its engine are updated monthly and integrate a long chain of modeling and data processing, from a global circulation model to reservoir storage prediction. The setup of the drought forecasting system required a great effort of data integration from different sources: meteorological monitoring network, APIs, regional forecast data, hydrological monitoring networks. The application engine runs monthly and updates both monitoring and forecast databases. Another important outcome of this project was the development of tools for monitoring water storage in micro and small reservoirs from satellite data. An important step to achieve this was the development and deployment of a software that enables the bathymetric surveying of thousands of micro and small reservoirs from SAR imagery with only limited computer interaction. Finally, reservoir inflows were forecasted with the hydrological model WASA-SED. The model setup was integrated within the forecasting workflow, but to date it was not possible to integrate the results in the above mentioned web application.
Publications
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(2018). “Seasonal drought prediction for semiarid northeastern Brazil: verification of six hydro-meteorological forecast products”. In: Hydrology and Earth System Sciences 22.9, pp. 5041–5056
Delgado, José Miguel, Sebastian Voss, Gerd Bürger, Klaus Vormoor, Aline Murawski, José Marcelo Rodrigues Pereira, Eduardo Martins, Francisco Vasconcelos Júnior, and Till Francke
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(2019). “Assessment of the geometry and volumes of small surface water reservoirs by remote sensing in a semi-arid region with high reservoir density”. In: Hydrological Sciences Journal 64.1, pp. 66–79
Pereira, Bruno, Pedro Medeiros, Till Francke, Geraldo Ramalho, Saskia Foerster, and José Carlos De Araújo
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(2019). “Seasonal drought prediction for semiarid northeast Brazil: what is the added value of a process-based hydrological model?” In: Hydrology and Earth System Sciences 23.4, pp. 1951–1971
Pilz, Tobias, José Miguel Delgado, Sebastian Voss, Klaus Vormoor, Till Francke, Alexandre Cunha Costa, Eduardo Martins, and Axel Bronstert
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(2019). “The Climate Data Toolbox for MATLAB”. In: Geochemistry, Geophysics, Geosystems 20.7, pp. 3774–3781
Greene, Chad A., Kaustubh Thirumalai, Kelly A. Kearney, José Miguel Delgado, Wolfgang Schwanghart, Natalie S. Wolfenbarger, Kristen M. Thyng, David E. Gwyther, Alex S. Gardner, and Donald D. Blankenship
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“Mapping regional surface water volume variation in reservoirs in northeastern Brazil during 2009-2017 using high-resolution satellite images”. In: Science of the Total Environment 789, p. 147711
Zhang, S., S. Foerster, PAH Medeiros, JC. de Araújo, Z. Duan, A. Bronstert, and B. Waske
