Data for: Water system simulation modeling with hydropower optimization and environmental flows: An example with Pywr
Rheinheimer, David et al. (2022), Data for: Water system simulation modeling with hydropower optimization and environmental flows: An example with Pywr, Dryad, Dataset, https://doi.org/10.5061/dryad.x0k6djhn8
This dataset was used in the CenSierraPywr model created for the project "Optimizing Hydropower Operations While Sustaining Ecosystem Functions in a Changing Climate", for the California Energy Commission. Specifically, this data is to support reproducibility of the article describing the basic methods (Rheinheimer et al., in review). The model was built in Pywr, an open-source, linear programming-based Python package for modeling basin-scale water systems in the Central Sierra Nevada, California. Here, we focus on the Stanislaus and Upper San Joaquin River basins as they have high elevation hydropower typically operated to maximize revenue. CenSierraPywr consists of daily water allocations that include both hydroeconomic drivers for hydropower and more advanced environmental flows. Piecewise linear electricity prices from simulated hourly price data are used to drive discretionary hydropower, while environmental flows include the addition of ramping rates. Hydrological inputs include runoff data at the sub-basin level, based on the historical (1950 to 2011) daily gridded (1/16 degree) runoff data generated by the Variable Infiltration Capacity (VIC) hydrologic model developed by Livneh et al. (2013), forced with observed meteorological data and bias-corrected using local gauge data. All data inputs for reproducibility of CenSierraPywr for the Stanislaus and Upper San Joaquin Rivers are included, including original and preprocessed electricity and hydrological data and management-related data specific to certain hydropower projects or facilities.
Electricity prices were derived from a custom-developed dataset described at: https://datadryad.org/stash/dataset/doi:10.6071%2FM3295P
Electricity prices were linearized using the pwlf Python package, using five (5) pieces.
Runoff data was based on the historical (1950 to 2011) daily gridded (1/16 degree) runoff data generated by the Variable Infiltration Capacity (VIC) hydrologic model developed by Livneh et al. (2013), forced with observed meteorological data and bias-corrected using local gauge data. Development of the historical data is further described at: https://datadryad.org/stash/dataset/doi:10.6071%2FM3609B
Runoff was converted to relevant derivatives, such as aggregated runoff and water year types, using a variety of Python-based preprocessing scripts available from and further described at: https://github.com/vicelab/cen-sierra-pywr. Hydropower project-specific water year types were developed following the logic described in hydropower licenses issued by the Federal Energy Regulatory Commission (FERC).
Management-related data (e.g., flood control curves, storage-elevation curves, urban and agricultural demands, hydropower project-specific water year type classifications), were derived from a variety of related publicly available data sources, FERC licenses, U.S. Army Corps of Engineers Water Control Manuals, and observed data.
For use with CenSierraPywr, all data in the main data.zip file should be downloaded and extracted to the main data folder used for CenSierraPywr. This data folder should be specified in an environment variable called "SIERRA_DATA_PATH". The existing folder structure within the data.zip file should not be altered.
U.S. Department of Energy, Award: DE-IA0000018
California Energy Commission, Award: CEC 300-15-004