Seasonal Hydropower Planning for Data‐Scarce Regions Using Multimodel Ensemble Forecasts, Remote Sensing Data, and Stochastic Programming-Reference-Cited by-同舟云学术

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Seasonal Hydropower Planning for Data‐Scarce Regions Using Multimodel Ensemble Forecasts, Remote Sensing Data, and Stochastic Programming

Published:2019-11 Issue:11 Volume:55 Page:8583-8607
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Resour. Res.

Author:

Koppa Akash¹^ORCID,Gebremichael Mekonnen¹,Zambon Renato C.²^ORCID,Yeh William W.‐G.¹^ORCID,Hopson Thomas M.³^ORCID

Affiliation:

1. Department of Civil and Environmental Engineering University of California, Los Angeles Los Angeles CA USA

2. Department of Hydraulic and Environmental Engineering University of Sao Paulo Brazil

3. National Center for Atmospheric Research Boulder CO USA

Funder

National Aeronautics and Space Administration

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2019WR025228

Reference86 articles.

1. Decision Support System for Optimizing Reservoir Operations Using Ensemble Streamflow Predictions

2. Dual assimilation of satellite soil moisture to improve streamflow prediction in data-scarce catchments

3. Value of long-term streamflow forecasts to reservoir operations for water supply in snow-dominated river catchments

4. A Model Predicting Stomatal Conductance and its Contribution to the Control of Photosynthesis under Different Environmental Conditions

5. Optimization of Large-Scale Hydropower System Operations

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