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ResORR: A globally scalable and satellite data-driven algorithm for river flow regulation due to reservoir operations

Environmental Modelling & Software, ISSN: 1364-8152, Vol: 176, Page: 106026
2024
  • 2
    Citations
  • 0
    Usage
  • 3
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    2
    • Citation Indexes
      2
  • Captures
    3
  • Mentions
    1
    • News Mentions
      1
      • News
        1

Most Recent News

Investigators at University of Washington Discuss Findings in Information Technology (Resorr: a Globally Scalable and Satellite Data-driven Algorithm for River Flow Regulation Due To Reservoir Operations)

2024 JUN 12 (NewsRx) -- By a News Reporter-Staff News Editor at Ecology Daily News -- A new study on Information Technology is now available.

Article Description

We propose a globally scalable algorithm, ResORR (Reservoir Operations driven River Regulation), to predict regulated river flow and tested it over the heavily regulated basin of the Cumberland River in the US. ResORR was found able to model regulated river flow due to upstream reservoir operations of the Cumberland River. Over a mountainous basin dominated by high rainfall, ResORR was effective in capturing extreme flooding modified by upstream hydropower dam operations. On average, ResORR improved regulated river flow simulation by more than 50% across all performance metrics when compared to a hydrologic model without a regulation module. ResORR is a timely software algorithm for understanding human regulation of surface water as satellite-estimated reservoir state is expected to improve globally with the recently launched Surface Water and Ocean Topography (SWOT) mission.

Bibliographic Details

Pritam Das; Faisal Hossain; Sanchit Minocha; Sarath Suresh; George K. Darkwah; Hyongki Lee; Konstantinos Andreadis; Miguel Laverde-Barajas; Perry Oddo

Elsevier BV

Computer Science; Environmental Science

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