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<p>Reservoir operation plays a central role in water management, satisfying diverse human demands and simultaneously influencing hydrologic processes. Yet for most reservoirs, the lack of complete daily operation records and realistic operation rules constrains their representation in large-scale hydrological models. To address this, we present <b>GDROM v2</b>, a nationwide dataset of 2,017 reservoirs across the Contiguous United States (CONUS), building upon the original GDROM of 452 reservoirs. GDROM v2 provides (1) daily time series of inflow, release, and storage variables, integrated through data fusion of existing datasets and reconstructed estimates; (2) operation rules adopted from original GDROM for data-rich reservoirs and derived for data-limited reservoirs using transfer learning. Validation results show that the reconstructed variable time series reasonably agree with observations; derived operation rules outperform existing benchmark models across diverse data availability conditions. GDROM v2, publicly available <i>via</i> an open-data platform (Hydroshare.org), offers the largest collection of reservoir operation variables time series and realistic operation rules across the CONUS, providing a useful resource for hydrological modeling and water management studies.</p>

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GDROM v2: An Inventory of Operation Variables Time Series and Rules for 2,017 Large Reservoirs across the CONUS

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月28日

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  • Zihan Zheng,
  • Ximing Cai,
  • Linshui Zhang,
  • James Li,
  • Yanan Chen

摘要

Reservoir operation plays a central role in water management, satisfying diverse human demands and simultaneously influencing hydrologic processes. Yet for most reservoirs, the lack of complete daily operation records and realistic operation rules constrains their representation in large-scale hydrological models. To address this, we present GDROM v2, a nationwide dataset of 2,017 reservoirs across the Contiguous United States (CONUS), building upon the original GDROM of 452 reservoirs. GDROM v2 provides (1) daily time series of inflow, release, and storage variables, integrated through data fusion of existing datasets and reconstructed estimates; (2) operation rules adopted from original GDROM for data-rich reservoirs and derived for data-limited reservoirs using transfer learning. Validation results show that the reconstructed variable time series reasonably agree with observations; derived operation rules outperform existing benchmark models across diverse data availability conditions. GDROM v2, publicly available via an open-data platform (Hydroshare.org), offers the largest collection of reservoir operation variables time series and realistic operation rules across the CONUS, providing a useful resource for hydrological modeling and water management studies.