DDD Conference

Space Based Technological Applications for Water Management

Conveners: Sivan Isaacson, Dead Sea & Arava Center, & Dr. Shimrit Maman, BGU

Arid zones are of high desertification risk, thus, water monitoring in such regions is crucial. Any change and decrease in the even now sparse and limited water availability in these regions can lead to a considerable impact on the full ecosystem.
Space-based technology (Earth Observation/Remote Sensing) and geospatial data and their applications possess high potential in water management, particularly in arid regions.
This session will address the use of space technologies for various applications with an emphasis on arid regions. Proposed talks should include current and planned projects/research combining space-based data with water related topics such as flash floods, water management, drought monitoring, water quality as well as other social, economic and ecological water sustainability challenges.

Showing all 5 results

  • Placeholder
    Space Based Technological Applications for Water Management

    Dr. Mason Stahl

    The Seasonal Cycle of Surface Soil Moisture: Global Characterization and Applications to Soil Quality

    Union College, USA

  • Placeholder
    Space Based Technological Applications for Water Management

    Dr. Shirish Ravan

    Space Technologies for Achieving Sustainable Development Goals Specific to Environmental Sustainability and Climate Change

    United Nations Office for Outer Space Affairs, Austria

     

  • Placeholder
    Space Based Technological Applications for Water Management

    Dr. Yael Storz-Peretz

    Flash Flood Forecasting in Arid Regions – Challenges and Opportunities

    Israel Water Authority, Israel

  • Placeholder
    Space Based Technological Applications for Water Management

    Mr. Daniel Kamoun

    Remote Sensing Techniques for Groundwater Measurements in Drylands Subsurface

    Brandeis University, USA

  • Placeholder
    Space Based Technological Applications for Water Management

    Ms. Arti Tiwari

    A Deep Learning Approach for Automatic Identification of Ancient Agricultural Water Harvesting Systems

    Ben Gurion University of the Negev, Israel

Skip to content