Model:Reservoir

Reservoir

Also known as
Model type	Single
Model part of larger framework
Note on status model
Date note status model

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,

Name	Sean 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/
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Authors

Sean Turner

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