Sadri, Sara

Senior Scientist

Profile
Selected Publications
  • Sara Sadri
    INSTITUTE:
    UNU-FLORES
    OFFICE:
    UNU-FLORES, Ammonstrasse 74, Dresden, 01067, Germany
    E-MAIL:
    sadri@unu.edu
    NATIONALITY:
    Canada, Iran

    Research Interests

    • Agricultural Development & Geo-information for Agriculture & Natural Resources
    • Impacts of natural factors and human activities on water resources
    • Remote sensing and GIS
    • Soil Hydrology

    Education

    • PhD, Civil Engineering, University of Waterloo, Canada (2010)
    • MSc, Biosystems Engineering, University of Manitoba, Canada (2005)
    • BSc, Agricultural and Irrigation Engineering, University of Tehran, Iran (2002)

    Appointments

    • Research Scientist, Natural Resources Canada
    • Research Scientist, Global Institute for Water Security, Canada
    • Associate Professional Specialist and Postdoc, Princeton University

    Biographical Statement

    Sara Sadri is a Senior Scientist at UNU-FLORES working primarily on advancing the Resource Nexus AID programme. She is a hydrologist in remote sensing and statistics; Sara focuses on water and food insecurity issues. Additionally, she works to find solutions to anthropogenic and climate change-induced drought within the water-energy-society nexus. Sara is passionate about the growing need to establish real-time online tools to support the achievement of the SDGs, especially in regions where the water security of communities is under threat. She aims to connect and collaborate with stakeholders, communities, and policymakers and utilise renewable energy approaches and affordable technologies to design and build case-based solutions to pressing environmental concerns.

    Further Information

    Google Scholar

  • Articles

    • Sh. Wang, D. Mondal, S. Sadri, Ch. K. Roy, J. S. Famiglietti, K. A. Schneider (2022) SET-STAT-MAP:
      Extending Parallel Sets for Visualizing Mixed Data. IEEE 15th Pacific Visualization Symposium
      (PacificVis), #7610 (Accepted, In Press).
    • S. Sadri, J. S. Famiglietti, M. Pan, H. Beck, A. A. Berg, E. F. Wood (2022) FarmCan: a physical,
      statistical, and machine learning model to forecast crop water deficit for farms. Hydrology and Earth
      System Sciences (HESS), Vol. 26(20), 5373-5390.
    • N. Vergopolan, N. W. Chaney, M. Pan, J. Sheffield, H. Beck, C. Ferguson, L. Torres-Rojas, S. Sadri, E.
      F. Wood (2021) Satellite-based Soil Moisture at 30-m Resolution Reveals the Drivers of Spatial Variability
      Across the US. Nature Scientific Data, #8:264.
    • S. Sadri, M. Pan, Y. Wada, N. Vergopolan, J. Sheffield, J. S. Famiglietti, Y. Kerr, E. F. Wood (2020). A
      Global Near-Real-Time Soil Moisture Index Monitor for Food Security Using Integrated SMOS and SMAP.
      Remote Sensing of Environment, 246, 111864.
    • S. Sadri, E. F. Wood, M. Pan (2018). Developing a Drought Monitoring Index for the Contiguous U.S.
      Using SMAP. Hydrol. Earth Syst. Sci., 22, 6611–6626.

    Conference Proceedings

    • L. Xu, J. S. Famiglietti, D. Ferris, X. Huggins, Ch. Mohan, S. Sadri, P. Sanyal, J. S. Wong (2022) From
      Coarse Resolution to Realistic Resolution: GRACE as a Science Communication and Policymaking Tool
      for Sustainable Groundwater Management. EGU General Assembly, Vienna, Austria, 2327 May 2022,
      EGU22-10542
    • N. Vergopolan, N. W. Chaney, H. Beck, M. Pan, S. Sadri, J. Sheffield, E. F. Wood (2020).
      Hyper-resolution Land Surface Modeling Enables Hydrologically Consistent 30-m SMAP-based Soil
      Moisture Retrievals Over Continental Scales. American Geophysical Union, Fall Meeting 2020, San
      Francisco, U.S.A. #A041-0002
    • S. Sadri, M. Pan, J. Famiglietti, E. F. Wood, H. Beck, N. Vergopolan, A. Berg (2019). Water Resources
      Optimization and Irrigation Advisory Based on Farm-Level Remote Sensing and Crop Water Demand.
      American Geophysical Union, Fall Meeting 2020, San Francisco, U.S.A. #H046-05

    Thesis

    • S. Sadri (2010). Frequency Analysis of Drought Using Stochastic and Soft Computing Techniques.
    • S. Sadri (2005). Aerobic Treatment of Landfill Leachate Using a Submerged Membrane Bioreactor