University of Illinois Urbana-Champaign

Using GIS and RS-PRODUCTS to develop a geo-referenced inventory for reservoirs in the CONUS

Zhang, Linshui

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https://hdl.handle.net/2142/127416

Description

Title
Using GIS and RS-PRODUCTS to develop a geo-referenced inventory for reservoirs in the CONUS
Author(s)
Zhang, Linshui
Issue Date
2024-12-13
Director of Research (if dissertation) or Advisor (if thesis)
Cai, Ximing
Department of Study
Civil & Environmental Eng
Discipline
Civil Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
  • GIS
  • RS-Products
  • Hydrological Modeling
  • Reservoir Inflow and Outflow Simulation
Abstract
Reservoir operation models have evolved to address diverse hydrological conditions, yet challenges persist for reservoirs with limited or no historical data. This study extends the Generic Data-Driven Reservoir Operation Model (GDROM) to improve its scalability and applicability for data-limited and no-data reservoirs. By leveraging streamflow data from upstream and downstream gauge stations of a reservoir, the proposed method adopts a geospatial matching algorithm to identify the inflow and outflow of a reservoir and develop data inventory for many reservoirs with limited historical operation records. Historical records from data-rich reservoirs are used to validate the framework's robustness. For no-data reservoirs, spatially matched streamflow data and proxy-based methods provide a scalable solution to estimate reservoir inflow and outflow for reservoirs with limited data or no data. The results of this work will enable the simulation of reservoir operation dynamics and effective integration reservoirs into large-scale hydrological models. The framework’s adaptability across diverse operational scales and flow regimes enhances the application of GDROMs across the CONUS regions.
Graduation Semester
2024-12
Type of Resource
Thesis
Handle URL
https://hdl.handle.net/2142/127416
Copyright and License Information
Copyright 2024 Linshui Zhang

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