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.
| 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. (Metadata update) | |
| Published date: | Apr 08, 2022 at 3:31 p.m. | |
| DOI: | 10.4211/hs.ca365ffb1a1f49df8b77e393be965fd8 | |
| Citation: | See how to cite this resource |
| Sharing Status: | Published |
|---|---|
| Views: | 1313 |
| Downloads: | 21 |
| +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
Temporal
| Start Date: | |
|---|---|
| End Date: |
Content
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. |
| Title | Owners | Sharing Status | My Permission |
|---|---|---|---|
| Global Hydropower Simulation Collection | Jia Yi Ng | Discoverable & Shareable | Open Access |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
Comments
There are currently no comments
New Comment