T3 (Theme 3)
Session Details
| Moderator: | Lars Ribbe & Bilal Ahmed Al-Saeedi |
| Date/Time: | 09.10.2024, 11:30 – 13:00 |
| Location: | Margarete-Bieber-Saal |
Description
This session focuses on the critical intersection of land-use changes and climate variability, and their far-reaching effects on water resources and ecosystem services. Presenters showcase innovative, data-driven methodologies and models designed to assess hydrological responses, forecast extreme weather events, and guide sustainable water management in diverse environments. From Andean watersheds to urban centers and transboundary catchments, this session highlights regional case studies and advanced approaches for addressing the challenges posed by environmental change. Participants will gain a deeper understanding of how spatial decision-making tools, ecosystem service assessments, and climate data analysis can support adaptive management strategies for mitigating the impacts of land-use and climate shifts on water resources.
The studies presented in this session (1) assess how land-use changes and climate variability affect runoff and hydrological processes in the Andean region, (2) explorer the use of machine learning for predicting flash floods and enhancing urban resilience to extreme weather events, (3) use ecosystem service assessments to enhance spatial decision-making for sustainable management in transboundary water system, (4) evaluate river health in the face of changing land-use patterns and climate, and (5) analyze long-term temperature trends and climate variability using global climate datasets to inform urban water management strategies.
Speakers
| Time | ID | Name | Title |
| 11:30 - 11:35 | --- | Moderator | Welcome & Introduction |
| 11:35 - 11:50 | 75 | Danny Daniel Saavedra Ore | Assessment of land use and climate changes impacts on hydrological responses in a Peruvian Andean watershed in the context of the MERESE |
| 11:50 - 12:05 | 84 | Paul Muñoz | Leveraging data-driven technologies for flash flood forecasting and urban water management resilience |
| 12:05 - 12:20 | 258 | Alicia Correa | Advancing spatial decision-making in a transboundary catchment through multidimensional ecosystem services assessment |
| 12:20 - 12:35 | 532 | Triambak Baghel | A methodology for assessing the impact of climate and land use change on River Health: An application to the Songkhram River in Northeast Thailand |
| 12:35 - 12:50 | 552 | Juan Diego Giraldo-Osorio | Long-term change, and climate variability, of extreme temperature in Bogotá-Colombia: results from ERA5-Land data |
| 12:50 - 13:00 | --- | All | Group Discussion & Closing |
Session Details
| Moderator: |
Alexandra Nauditt & Lars Ribbe |
| Date/Time: | 10.10.2024, 11:30 – 13:00 |
| Location: | Margarete-Bieber-Saal |
Description
This session explores cutting-edge, data-driven approaches that deepen the understanding of hydrological systems and processes. Using advanced techniques such as machine learning, remote sensing, and geostatistical methods, the session explores applications ranging from glacier mass balance estimations to rainfall evaluation and runoff prediction in various regions of the world. By utilizing free open-source data, satellite imagery, and algorithms, these studies offer key insights into water resource management, climate resilience, and sustainable development. Attendees gain a comprehensive view of how technological innovation is transforming the way we monitor, model, and enhance water availability and management in diverse ecosystems.
The studies presented in this session (1) examine the use of satellite imagery and open-source data to estimate glacier mass balance, (2) use remote sensing and machine learning to estimate ecosystem productivity, (3) assess the accuracy of satellite rainfall estimates and their applications for improving hydrological modeling and water resource management, (4) apply machine learning and neural networks to analyze runoff factors in flood-prone regions, and (5) merging precipitation datasets through machine learning and geostatistical approaches to create a more accurate representation of rainfall patterns.
Speakers
| Time | ID | Name | Title |
| 11:30 - 11:35 | --- | Moderator | Welcome & Introduction |
| 11:35 - 11:50 | 82 | Ailin Sol Ortone Lois | Mass balance estimations of Patagonian glaciers using free open sources |
| 11:50 - 12:05 | 342 | Cindy Urgilés | Gross Primary Productivity estimation through remote sensing and machine learning techniques in the high Andean Region of Ecuador |
| 12:05 - 12:20 | 353 | Cristian Diaz Moscote | Evaluation of Satellite Rainfall Estimates in the Magdalena Grande Region, Northern Colombia |
| 12:20 - 12:35 | 376 | Asib Ahmed | Synergistic Approach with Machine Learning and Recurrent Neural Network to Identify Potential Factors of Runoff on a Spatiotemporal Basis for managing water resources in flood-prone region of Bangladesh |
| 12:35 - 12:50 | 509 | Bilal Ahmed Al-Saeedi | An optimized representation of precipitation in Jordan: Merging gridded precipitation products and ground-based measurements using machine learning and geostatistical approaches |
| 12:50 - 13:00 | --- | All | Group Discussion & Closing |
Session Details
| Moderator: | Björn Weeser & Fabia Codalli |
| Date/Time: | 11.10.2024, 11:30 – 13:00 |
| Location: | Margarete-Bieber-Saal |
Description
This session highlights the importance of community-driven initiatives and nature-based solutions in advancing water sustainability and resilience. Presenters will demonstrate how citizen science and local participation can effectively bridge data gaps, inform decision-making, and empower communities to address pressing water challenges. In addition, the session showcases cutting-edge applications of geospatial technologies and machine learning to optimize water use in regions facing scarcity. From groundwater monitoring to rainfall tracking, these studies demonstrate the power of combining community efforts with technology and nature-based interventions to enhance water management practices in diverse settings, from semi-arid regions in India to the Galapagos Islands.
The studies presented in this session (1) show how citizen science initiatives are helping to monitor and manage groundwater resources, (2) evaluate the use of nature-based solutions to enhance water recharge and improve water quality, (3) apply geospatial data and machine learning to optimize water use in semi-arid regions, (4) highlight a community-centric approach to rainfall monitoring that improves urban water security by addressing critical data gaps through citizen engagement, and (5) investigate the impacts of El Niño using citizen-generated data, enhancing understanding of climate variability and its effects on water resources.
Speaker
| Time | ID | Name | Title |
| 11:30 - 11:35 | --- | Moderator | Welcome & Introduction |
| 11:35 - 11:50 | 175 | Heriberto Gonzalez Sanchez | Groundwater and Citizen-Science: Making Visible the Invisible |
| 11:50 - 12:05 | 271 | Antonio Cardona | Assessing the Potential of Nature-Based Solutions as Interventions for Catchment Management: Calera Aquifer, Zacatecas, Mexico |
| 12:05 - 12:20 | 361 | Aariz Ahmed | Achieving Sustainable Water Use in Semi-Arid Regions in India Using Geospatial and ML Methods |
| 12:20 - 12:35 | 399 | Salman Khan | Bridging Data Gaps for Informed Decision-Making: Community-Centric Rainfall Monitoring for Improved Urban Water Security |
| 12:35 - 12:50 | 410 | Maria Lorena Orellana Samaniego | Analyzing the 2023-2024 El Niño Event in the Galapagos Islands Using Data from the DARWIN Citizen Science Program |
| 12:50 - 13:00 | --- | All | Group Discussion & Closing |