Model:Reservoir

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Reservoir


Metadata

Also known as
Model type Single
Model part of larger framework
Incorporated models or components:
Spatial dimensions 1D
Spatial extent Point-Based
Model domain Hydrology
One-line model description Reservoir: Tools for Analysis, Design, and Operation of Water Supply Storages
Extended model description Measure single reservoir performance using resilience, reliability, and vulnerability metrics; compute storage-yield-reliability relationships; determine no-fail Rippl storage with sequent peak analysis; optimize release decisions using determinisitc and stochastic dynamic programming; evaluate inflow characteristics.
Keywords:

Reservoir, Water storage yield,


First name Sean
Last name Turner
Type of contact Model developer
Institute / Organization Pacific Northwest National Lab
Postal address 1
Postal address 2
Town / City Seattle
Postal code --
State Washington
Country United States
Email address sean.turner@pnnl.gov
Phone
Fax


Supported platforms Unix, Linux, Mac OS, Windows
Other platform
Programming language
Other program language R
Code optimized Single Processor
Multiple processors implemented
Nr of distributed processors
Nr of shared processors
Start year development 2015
Does model development still take place? No
If above answer is no, provide end year model development
Code development status Only maintenance
When did you indicate the 'code development status'? 2020
Model availability As code
Source code availability
(Or provide future intension)
Through web repository
Source web address https://github.com/swd-turner/reservoir
Source csdms web address
Program license type GPL v2
Program license type other
Memory requirements --
Typical run time --


Describe input parameters The Rippl function executes the sequent peak algorithm to determine the no-fail storage for given inflow and release time series. The storage function gives the design storage for a specified timebased reliability and yield. Similarly, the yield function computes yield given the storage capacity. The rrv function returns three reliability measures, relilience, and dimensionless vulnerability for given storage, inflow time series, and target release. Users can assume Standard Operating Policy, or can apply the output of sdp analysis to determine the RRV metrics under different operating objectives. The Hurst function estimates the Hurst coefficient for an annualized inflow time series.
Input format ASCII
Other input format
Describe output parameters The no-fail storage capacity and corresponding storage behaviour time series.
Output format ASCII
Other output format
Pre-processing software needed? No
Describe pre-processing software
Post-processing software needed? No
Describe post-processing software
Visualization software needed? No
If above answer is yes
Other visualization software


Describe processes represented by the model --
Describe key physical parameters and equations --
Describe length scale and resolution constraints --
Describe time scale and resolution constraints --
Describe any numerical limitations and issues --


Describe available calibration data sets
Upload calibration data sets if available:
Describe available test data sets
Upload test data sets if available:
Describe ideal data for testing


Do you have current or future plans for collaborating with other researchers?
Is there a manual available? Yes
Upload manual if available: Media:Reservoir-manual2015.pdf
Model website if any https://cran.r-project.org/web//packages/reservoir/
Model forum / discussion board
Comments


This part will be filled out by CSDMS staff

OpenMI compliant No but possible
BMI compliant No but possible
WMT component No but possible
PyMT component
Is this a data component
Can be coupled with:
Model info
Sean Turner
Nr. of publications: --
Total citations: 0
h-index: --"--" is not a number.
Qrcode Reservoir.png
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Nr. of publications: --
Total citations: 0
h-index: --"--" is not a number.


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Output Files