Checking for non-preferred file/folder path names (may take a long time depending on the number of files/folders) ...

This resource contains some files/folders that have non-preferred characters in their name. Show non-conforming files/folders.

This resource contains content types with files that need to be updated to match with metadata changes. Show content type files that need updating.

Global Hydropower Simulation - Forecast_2022

Authors:
Owners:		This resource does not have an owner who is an active HydroShare user. Contact CUAHSI (help@cuahsi.org) for information on this resource.
Type:	Resource
Storage:	The size of this resource is 285.9 MB
Created:	Dec 22, 2020 at 2:03 a.m.
Last updated:	May 31, 2022 at 1:27 a.m.
DOI:	10.4211/hs.ca365ffb1a1f49df8b77e393be965fd8
Citation:	See how to cite this resource

Sharing Status:	Published
Views:	961
Downloads:	17
+1 Votes:	Be the first one to this.
Comments:	No comments (yet)

Abstract

This resource contains the hydropower time series for 735 headwater hydropower dams operating under 3 different schemes – control rules, forecast-informed operations with perfect forecast, and forecast informed operations with deterministic forecast. The deterministic streamflow forecasts depend on seven drivers, that is, four large scale climate drivers— El Niño Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), and Atlantic Multidecadal Oscillation (AMO)—and three variables accounting for local processes—lagged inflow, snowfall, and soil moisture.

Start exploring the data by downloading the Rdata together with the open_file.R script. You will be able to find monthly-resolution time series outputs of our simulation, including the hydropower production, storage level, and water releases for each dam.

Subject Keywords

Coverage

Spatial

Coordinate System/Geographic Projection:

WGS 84 EPSG:4326

Coordinate Units:

Decimal degrees

North Latitude

68.8154°

East Longitude

176.7896°

South Latitude

-45.8796°

West Longitude

-125.5871°

Temporal

Start Date:
End Date:

Content

Learn more about the BagIt download

Select a file to see file type metadata.

Related Resources

This resource is referenced by

Lee, D., Ng, J. Y., Galelli, S., & Block, P. (2022). Unfolding the relationship between seasonal forecast skill and value in hydropower production: a global analysis. Hydrology and Earth System Sciences, 26(9), 2431-2448.

This resource belongs to the following collections:

Title	Owners	Sharing Status	My Permission
Global Hydropower Simulation Collection	Jia Yi Ng	Discoverable & Shareable	Open Access

How to Cite

Lee, D., J. Y. Ng, S. Galelli, P. Block (2022). Global Hydropower Simulation - Forecast_2022, HydroShare, https://doi.org/10.4211/hs.ca365ffb1a1f49df8b77e393be965fd8

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/

Comments

There are currently no comments