Overview

This dataset contains daily reservoir operation records (inflow, outflow, storage) for 256 major reservoirs across the Contiguous United States (CONUS) from 1990 to 2019. Related study on real-world changes in reservoir storage and operation has been published in Chen and Cai (2025). Results of trends in storage metric series and operation module application changes are also provided in this resource. For detailed methodology and analysis, please refer to the associated publication.

Key Features

• Data Coverage: 256 reservoirs selected from Li et al. (2023).
• Temporal Span: Minimum of 25 years (starting in 1990, ending in 2014 or later).
• Data Quality:
• Less than 10% missing data.
• Outlier removal for abnormal storage changes.
• Missing values filled using linear interpolation.
• Additional Data: Daily water surface elevation for 217 reservoirs (obtained from ResOpsUS dataset).

Description of Files

readme.md

• The file documenting the metadata for the entire dataset.

readme.html

• The file that can be directly opened with a web browser in case that the readme.md is not well rendered.

Metadata_256_reservoirs.csv

• The file recording the metadata for all 256 reservoirs. Each row records a reservoir and each column specifies the specific attribute. Each column is described below.
• GRanD ID: the unique identifier used for the reservoir.
• Dam name: name of the dam.
• State: the state where the dam is primarily located in.
• Water region: the HUC2 water region where the dam is primarily located in.
• Main use: the primary operation purpose of the dam, defined in the GRanD.
• Studied data range: Temporal span of operation data used for trend analysis.
• Longitude and “Latitude": the coordinate of the dam.
• Main Use: the primary operation purpose of the dam, defined in the GRanD.
• Storage size ratio: reservoir capacity over the annual average inflow.
• Historical maximum storage: the maximum storage (in 10^8 cubic meters) during the available time period (used to estimate reservoir capacity).

Trend_test-storage_metrics.csv

• Results of trend tests for selected annual storage metrics (the annual minimum, 25th, 50th, 75th, and 95th storage) for all reservoirs.
• Trend tests were conducted using the Mann-Kendall (M-K) test and Theil-Sen estimator.
• Refer to Chen and Cai (2025) for detailed methodology and results.

Operation_module_application_frequnecy_changes.csv

• Changes in operation module application frequency for 214 reservoirs (with two or more modules).
• Modules were derived using the Generic Data-driven Reservoir Operation Model (GDROM) as detailed in Li et al. (2023).
• For methodology and analysis, see Chen and Cai (2025).

Processed daily reservoir operation data

• This folder contains the operation record of each reservoir in CSV format, named as “reservoirID.csv”.

• Data Fields

| Field | Description | Unit | |---------------- |------------------------------ |----------| | Time | Date of observation | / | | netinflow | Daily net inflow (in volume) | million cubic meters (MCM) | | storage | Daily reservoir storage | million cubic meters (MCM) | | outflow | Daily outflow (in volume) | million cubic meters (MCM) | | Year | Year of observation | / | | DOY | Day of year | / | | elevation (217 reservoirs) | Water surface elevation | feet |

Note

• Start Date: Data begins on 1989-10-01 to align with the water year (WYs). For some reservoirs, outflow values are missing between 1989-10-01 and 1990-01-01, though storage values are available. Missing values are filled; no gaps remain after 1990-01-01.
• Net Inflow: Given that inflow data is missed for a large portion of reservoirs, we calculate the "net inflow" based on water balance as the inflow volume to the reservoir. Specifically, the mass balance equation is:

$$S_{t+1} = S_t + I_t - R_t + (G_t - L_t)$$

where, $S_t$ is the initial storage at day $t$; $I_t$ is the total inflow to the reservoir during day $t$; $R_t$ is the water volume released during day $t$; $G_t$ represents the total water volume gained other than inflow, such as the precipitation and recharge from adjacent aquifers; $L_t$ denotes the total loss of water from the reservoir during day $t$, such as the loss through seepage and evaporation.

We assume ignorable error in observed storage and release and calculate the “net inflow” from storage and release observations based on the mass balance. The “net inflow” accounts for the total gain and loss of water implicitly and provides the approximate water volume that purely enters the reservoir. The net inflow is used as an input to the GDROM model to analyze module application frequency.

Usage

This dataset is suitable for: - Investigating reservoir operation patterns. - Developing or validating hydrological models.

Related Publications and Dataset

• Chen, Y., & Cai, X. (2025). The storage and operation changes of 256 reservoirs across the contiguous United States. Water Resources Research, 61, e2024WR037372. https://doi.org/10.1029/2024WR037372
• Li, D., Y. Chen, X. Cai, Q. Zhao (2023). Data-driven Reservoir Operation Rules for 450+ Reservoirs in Contiguous United States, HydroShare. https://doi.org/10.4211/hs.63add4d5826a4b21a6546c571bdece10
• Li, D., Chen, Y., Lyu, L., & Cai, X. (2024). Uncovering historical reservoir operation rules and patterns: Insights from 452 large reservoirs in the contiguous United States. Water Resources Research, 60, e2023WR036686. https://doi.org/10.1029/2023WR036686.
• Chen, Y., Li, D., Zhao, Q., & Cai, X. (2022). Developing a generic data-driven reservoir operation model. Advances in Water Resources, 167, 104274. https://www.sciencedirect.com/science/article/abs/pii/S0309170822001397?via%3Dihub