This site requires Cookies enabled in your browser for login.
WaterNet Home
WaterNet
for
pour le
Canada
Menu
WaterNet
Home
GWFO
Home
Master
List
Data
Centre
Collections
X
Defaults
Select All
Websites
X
Global Water Futures Observatories (GWFO) Global Water Futures (GWF) Global Institute for Water Security (GIWS) International Network of Alpine Research Catchment Hydrology
Legacy Research Programs
X
Changing Cold Regions Network (CCRN) Drought Research Initiative (DRI) International Network of Alpine Research Catchment Hydrology (Legacy Site) Improving Processes & Parameterization for Prediction in Cold Regions Hydrology (IP3) The Mackenzie Global Energy and Water Cycle Experiment (GEWEX) Study (MAGS)
Legacy sites
Map
Utilities
X
Account Settings Metadata Editor Record List Alias List Editor
Data Centre
Data Type Editor
. . .
X
Clear
Select All
Advanced Search
Related items loading ...
Fetching Chart ...
Publication Additional Information Download
Publication Type
Journal Article
Authorship
Zaerpour, M., Papalexiou, S. M., & Nazemi, A.
Title
Informing Stochastic Streamflow Generation by Large-Scale Climate Indices at Single and Multiple Sites
Year
2021
Publication Outlet
Advances in Water Resources, 104037
DOI
https://doi.org/10.1016/j.advwatres.2021.104037
Citation
Zaerpour, M., Papalexiou, S. M., & Nazemi, A. (2021). Informing Stochastic Streamflow Generation by Large-Scale Climate Indices at Single and Multiple Sites. Advances in Water Resources, 104037. https://doi.org/10.1016/j.advwatres.2021.104037
Abstract
Despite the existence of several stochastic streamflow generators, not much attention has been given to representing the impacts of large-scale climate indices on seasonal to interannual streamflow variability. By merging a formal predictor selection scheme with vine copulas, we propose a generic approach to explicitly incorporate large-scale climate indices in ensemble streamflow generation at single and multiple sites and in both short-term prediction and long-term projection modes. The proposed framework is applied at three headwater streams in the Oldman River Basin in southern Alberta, Canada. The results demonstrate higher skills than existing models both in terms of representing intra- and inter-annual variability, as well as accuracy and predictability of streamflow, particularly during high flow seasons. The proposed algorithm presents a globally relevant scheme for the stochastic streamflow generation, where the impacts of large-scale climate indices on streamflow variability across time and space are significant.
Program Affiliations
GWF: Global Water Futures
Publication Stage
Published
Additional Information
Papalexiou, Simon-Michael , Refereed Publications
Download Links
https://doi.org/10.1016/j.advwatres.2021.104037
© 2026 - WaterNet Version 2026-06-01
Global Water Futures Observatories
Powered by
G W F Net
T-2022-12-03-d1VRFMRJ5vUCvLvd239BUYzA Publication 1.0