Zukunftslabor Wasser - RiverSnap

Led by:  Prof. Dr.-Ing. Torsten Schlurmann; Dr.-Ing. Mario Welzel
E-Mail:  schlurmann@lufi.uni-hannover.de
Team:  Dr. Armin Moghimi
Year:  2023
Funding:  Zukunftslabor Wasser Niedersachsen
Duration:  2023-2026 (First Phase)

Water is the basis of all life and must therefore be protected as a valuable resource. In order to guarantee the distribution of water during increasing periods of drought and to be prepared for extreme situations such as flooding, coordinated measures by politics and industry are required. They should be supported by further research based on modern water management methods. Digitization is essential for this. That is why the Lower Saxony Ministry of Science and Culture and the Volkswagen Foundation are funding the new Future Lab Water at the Center for Digital Innovations Lower Saxony (ZDIN). With a funding volume of 3.7 million euros, the digitalization of water management is to be further researched and made applicable at an excellent scientific level within five years. The project consortium of the Future Laboratory Water includes, among others, the disciplines of water management, hydraulic engineering, hydrology, coastal engineering, environmental systems science, computer science, sensor technology as well as planning and political sciences. Geographically, the applicant institutions cover the state of Lower Saxony from the coast to the inland to the Harz low mountain region. At the Ludwig Franzius Institute, a contribution to the project is made with the initiative "RiverSnap":The estimation of river hydrological parameters is crucial for various water-related management and planning activities, such as water allocation, flood forecasting, environmental management, infrastructure design, and climate change assessment. Remote sensing image processing can be a valuable tool in this process due to its non-intrusive data collection, large-scale coverage, high temporal resolution, multispectral information, automation and efficiency, integration with other data sources, and decision support capabilities. RiverSnap is a local citizen science project to record and estimate some hydrological parameters, like water level (stage), river course (erosion/deposition of the river), and vegetation. The project have two objectives which are link together. First, the goal of this project is to provide a simple and appropriate platform for scientists, community members and people to snap images/videos of a river from a fixed position using their smartphones and share the images via social media with us. On the other hand, this project aim to develop and implement robust, smart, cost-effective, efficient Artificial intelligence (AI)-based approaches for extraction riverine hydrologic parameters/features from these images/videos. It will expected that, RiverSnap can enhance the accuracy, efficiency, and effectiveness of river parameter estimation, leading to improved water resources management and decision-making. The results of the RiverSnap can also use to predict these parameters for future time.