Data from: Characterizing watershed responses and reservoir operational flexibilities: Analyses to support forecast informed reservoir operations (FIRO) planning and assessments
Data files
Abstract
Recent advances in weather forecast skill provide opportunities to manage reservoirs more flexibly using strategies such as Forecast-Informed Reservoir Operations (FIRO). This is especially critical as changes in climate, population, and land use make balancing use of reservoirs to minimize flood risks and maximize water availability more challenging. FIRO viability is contingent on the ability to forecast reservoir inflows with sufficient accuracy and lead time that storage and releases downstream can be maintained at safe levels. In this study, we develop a transferable approach for gaining early insights into potential challenges and opportunities for FIRO by 1) identifying key factors that mediate precipitation-runoff generation, and 2) characterizing how the timing and magnitude of reservoir inflows relate to the amount of space available for storage and the ability to safely release water without causing downstream flooding. The buffering capacity of the reservoir to accommodate inflows is quantified as an operational flexibility metric, which can help to inform streamflow forecast lead time requirements. Using historical hydrologic and meteorologic data and an automated baseflow separation routine, we assessed operational flexibility at 32 reservoirs in California and western Nevada. We demonstrate that operational flexibility varies regionally, with less flexibility in snow-dominated basins, where the amount of water that can be released from reservoirs is more limited relative to those in rain-dominated basins where FIRO pilot studies have been conducted. A warming climate will further challenge this flexibility, indicating that FIRO efforts in snow-dominated basins will likely need to be coupled with other adaptation strategies.
Dataset DOI: 10.5061/dryad.n5tb2rc84
Description of the data and file structure
Data and code for Albano et al. (2026) Characterizing Watershed Responses and Reservoir Operational Flexibilities: Analyses to Support Forecast Informed Reservoir Operations (FIRO) Planning and Assessments. Water Resources Research 10.1029/2025WR042131
Please cite the above study if you use these data or code.
Please reach out to Christine.albano@dri.edu with any questions
Files and variables
File: code.zip
Description:
Files
- MATLAB files
- MAIN_RUNNER_DMCA = code to run DMCA analysis
- R Files
- '1DMCA_output_create_events' = compiles DMCA outputs and creates precipitation and streamflow event attributes
- '2DMCA_output_create_metrics' = relate event attributes to reservoir storage and outlet capacities
- '3DMCA_output_PCA' = calculate averages of top 10% events and input into principal components analysis
Instructions for R files
- Put the parent directory in your preferred location on your computer and set the working directory accordingly
- Run the scripts in sequential order (i.e., 1,2,3). We have included all input and output data, so any of these scripts should run individually and provide the data used to generate figures.
File: data.zip
Description:
BaseflowSeparationGraphics - This directory contains graphics showing the baseflow separation at each site for the top 10% precipitation and streamflow events. Areadme.pptx contains additional detail on how to interpret these graphics
DMCAInputData = This directory contains input data to the DMCA routine. There is one file for each site for precipitation (PrecipitationData) and streamflow (InflowData), labeled by DAM_ID, which can be cross-referenced to the reservoir name in the SiteCharacteristicsData/SiteList_Final.csv.
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Inflow data were converted to UTC (8-hour adjustment) by calculating a weighted average between Day X and Day X+1 to better correspond with the day units of the precipitation data.
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Column headings are as follows: Year, Month, Day, Hour, Minute, Second, with the last column containing either streamflow normalized to basin area in mm/day(InflowData), or precipitation in mm/day (PrecipitationData)
DMCAOutputData = This directory contains outputs from the DMCA routine (code available here: https://github.com/giuliagiani/DMCA-ESR). There are three files for each site labeled by DAM_ID, which can be cross-referenced to the reservoir name in the SiteList_Final.csv in the SiteCharacteristicsData/ directory. Files are labeled and contain data as follows:
fullts – 22 columns – see (Giani et al., 2022) for additional information
- timestep id
- p=precipitation in mm/hour
- q=total streamflow in mm/hour
- bq=baseflow in mm/hour
- year
- month
- day
- hour
- minute
- second
- porig=precipitation in mm/day
- year
- month
- day
- hour
- minute
- second
- qorig=total streamflow in mm/day
- bqorig=baseflow in mm/day
- fluct_rain_Tr= precipitation fluctuation
- fluct_flow_Tr=streamflow fluctuation
- fluct_bivariate_Tr=product of precipitation and streamflow fluctuations
durvol – columns correspond to events; 5 rows of data
- qpratio = runoff ratio (quickflow /precipitation depths)
- qvol=quickflow depth (mm) (difference between qorig and bqorig)
- pvol=precipitation depth (mm)
- durq=streamflow duration (days)
- durp=precipitation duration (days)
teststart– columns correspond to events; 4 rows of data
- startq=start timestep of streamflow event
- startp=start timestep of precipitation event
- endq=end timestep of streamflow event
- endp=end timestep of precipitation event
EventMetrics – this directory contains summarized data outputs
- DMCAeventscompiled.csv contains output from code/1DMCA_output_create_events.R; see this file to interpret column headings
- Eventmetrics.csv contains output from code/2DMCA_output_create_metrics.R; see this file to interpret column headings
SiteCharacteristicsData – this directory contains site-specific information
- FIROBasinsv10.shp – watershed boundaries used to spatially average meteorological data and convert streamflow from volume to depth units
- wldas_wshed_aves_final.csv – daily watershed averages of select WLDAS (Erlingis et al., 2021) variables -- 8 columns
- date
- sq=runoff in mm/day
- sm=antecedent soil moisture % volume
- sb=baseflow in mm/day
- smlt=snowmelt in mm/day
- rainf= rainfall in mm/day
- snowf= snowfall in mm/day
- DAM_ID
- storage_allsites_acft.csv – 6 columns
- year
- month
- day
- storageacft – daily occupied reservoir storage in acre-feet
- DAM_ID
- date
- SiteList_Final.csv – 13 columns
- DAM_ID corresponding with those from (Steyaert et al., 2022), as applicable
- DAM_NAME
- STATUS – of FIRO assessment, as applicable
- SITE_ID – corresponding USGS gaging station, as applicable
- HUC6 – HUC 6 watershed the dam is located in
- NIDID – National Inventory of Dams identifier
- grosspoolstorage – Gross pool storage in acre-feet
- maxfloodspace– Maximum flood storage in acre-feet
- maxrelease – Maximum release capacity in cfs
- downchannelcap – Downstream channel capacity in cfs
- NIDusstor – sum of “NID storage” from National Inventory of dams (U.S. Army Corps of Engineers, 2022) for all reservoirs within the upstream watershed, in acre-feet
- NIDNormalusstor - sum of “Normal storage” from National Inventory of dams (U.S. Army Corps of Engineers, 2022) for all reservoirs within the upstream watershed, in acre-feet
- Primary Purpose – Dam primary purpose from National Inventory of Dams (U.S. Army Corps of Engineers, 2022)
Code/software
The scripts provided can be run in R and MATLAB
Access information
Data were derived from the following sources:
Erlingis, J. M., Rodell, M., Peters-Lidard, C. D., Li, B., Kumar, S. V., Famiglietti, J. S., et al. (2021). A High-Resolution Land Data Assimilation System Optimized for the Western United States. JAWRA Journal of the American Water Resources Association, 57(5), 692–710. https://doi.org/10.1111/1752-1688.12910
Giani, G., Tarasova, L., Woods, R. A., & Rico-Ramirez, M. A. (2022). An Objective Time-Series-Analysis Method for Rainfall-Runoff Event Identification. Water Resources Research, 58(2), e2021WR031283. https://doi.org/10.1029/2021WR031283
Pierce, D. W., Su, L., Cayan, D. R., Risser, M. D., Livneh, B., & Lettenmaier, D. P. (2021). An extreme-preserving long-term gridded daily precipitation data set for the conterminous United States. Journal of Hydrometeorology. https://doi.org/10.1175/JHM-D-20-0212.1
Steyaert, J. C., Condon, L. E., W. D. Turner, S., & Voisin, N. (2022). ResOpsUS, a dataset of historical reservoir operations in the contiguous United States. Scientific Data, 9(1), 34. https://doi.org/10.1038/s41597-022-01134-7
U.S. Army Corps of Engineers. (2022). National Inventory of Dams - California and Nevada (Version Accessed May 5, 2022) [Data set]. https://nid.sec.usace.army.mil/#/dams/search/sy=@stateKey:CA&viewType=map&resultsType=dams&advanced=false&hideList=false&eventSystem=false; https://nid.sec.usace.army.mil/#/dams/search/sy=@stateKey:NV&viewType=map&resultsType=dams&advanced=false&hideList=false&eventSystem=false: https://nid.sec.usace.army.mil/#/.
