Dataset

Linear Optimal Runoff Aggregate v1.0

Also known as: LORA v1.0
ARC Centre of Excellence for Climate System Science
ARC Centre of Excellence for Climate System Science Data Manager (Managed by) Sanaa Hobeichi (Aggregated by)
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25914/5b612e993d8ea&rft.title=Linear Optimal Runoff Aggregate v1.0&rft.identifier=10.25914/5b612e993d8ea&rft.publisher=ARC Centre of Excellence for Climate System Science&rft.description=No synthesized global gridded runoff product, derived from multiple sources, is available despite such a product being useful to meet the needs of many global water initiatives. We apply an optimal weighting approach to merge runoff estimates from hydrological models constrained with observational streamflow records. The weighting method is based on the ability of the models to match observed streamflow data while accounting for error covariance between the participating products.To address the lack of observed streamflow for many regions, a dissimilarity method was applied to transfer the weights of the participating products to the ungauged basins from the closest gauged basins using dissimilarity between basins in physiographic and climatic characteristics as a proxy for distance. We perform out-of-sample tests to examine the success of the dissimilarity approach and we confirm that the weighted product performs better than its 11 constituents products in a range of metrics. Our resulting synthesized global gridded runoff product is available at monthly time scales, and includes time variant uncertainty, for the period 1980 – 2012 on a 0.5o grid. The synthesized global gridded runoff product broadly agrees with published runoff estimates at many river basins, and represents well the seasonal runoff cycle for most of the globe. The new product, called Linear Optimal Runoff Aggregate (LORA), is a valuable synthesis of existing runoff products and is freely available for download.  &rft.creator=Sanaa Hobeichi&rft.date=2018&rft.relation=10.5194/hess-23-851-2019&rft.coverage=-179.75,-89.75 -179.75,89.75 179.75,89.75 179.75,-89.75 -179.75,-89.75&rft_rights=Access to this dataset is free, the users are free to download this dataset and share it with others and adapt it as long as they credit the dataset owners, provide a link to the license, and if changes were made, indicate it clearly and distribute their contributions under the same license as the original, commercial use is not permitted.&rft_rights=Creative Commons - Attribution - Non Commercial - ShareAlike 4.0 International http://creativecommons.org/licenses/by-nc-sa/4.0/legalcode&rft_subject=Surfacewater Hydrology&rft_subject=Earth Sciences&rft_subject=Physical Geography and Environmental Geoscience&rft_subject=Hydrology&rft_subject=Runoff&rft.type=dataset&rft.language=English Access the data

Licence & Rights:

Non-Commercial Licence view details
CC-BY-NC-SA

Creative Commons - Attribution - Non Commercial - ShareAlike 4.0 International
http://creativecommons.org/licenses/by-nc-sa/4.0/legalcode

Access to this dataset is free, the users are free to download this dataset and share it with others and adapt it as long as they credit the dataset owners, provide a link to the license, and if changes were made, indicate it clearly and distribute their contributions under the same license as the original, commercial use is not permitted.

Access:

Open view details

Dataset is available online via NCI thredds catalogue

Full description

No synthesized global gridded runoff product, derived from multiple sources, is available despite such a product being useful to meet the needs of many global water initiatives. We apply an optimal weighting approach to merge runoff estimates from hydrological models constrained with observational streamflow records. The weighting method is based on the ability of the models to match observed streamflow data while accounting for error covariance between the participating products.To address the lack of observed streamflow for many regions, a dissimilarity method was applied to transfer the weights of the participating products to the ungauged basins from the closest gauged basins using dissimilarity between basins in physiographic and climatic characteristics as a proxy for distance. We perform out-of-sample tests to examine the success of the dissimilarity approach and we confirm that the weighted product performs better than its 11 constituents products in a range of metrics. Our resulting synthesized global gridded runoff product is available at monthly time scales, and includes time variant uncertainty, for the period 1980 – 2012 on a 0.5o grid. The synthesized global gridded runoff product broadly agrees with published runoff estimates at many river basins, and represents well the seasonal runoff cycle for most of the globe. The new product, called Linear Optimal Runoff Aggregate (LORA), is a valuable synthesis of existing runoff products and is freely available for download.

 

Created: 07 2018

Data time period: 1980-01-01 to 2012-12-31

-179.75,-89.75 -179.75,89.75 0,89.75 179.75,89.75 179.75,-89.75 0,-89.75 -179.75,-89.75

0,0

Subjects

User Contributed Tags    

Login to tag this record with meaningful keywords to make it easier to discover

Identifiers