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G. T. Aronica
and
B. Bonaccorso

1. Introduction In recent years, an increasing attention has been paid to hydropower generation, since it is a renewable, efficient, and reliable source of energy, as well as an asset to reduce the atmospheric concentrations of greenhouse gases resulting from human activities. At the same time, however, hydropower is among the most vulnerable industries to global warming, because water resources are closely linked to climate changes. Indeed, the effects of climate change on water availability

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Divya Upadhyay
,
Sudhanshu Dixit
, and
Udit Bhatia

1. Introduction Sustaining an optimal reservoir operation under various uncertainties is challenging in changing climate scenarios for hydropower production. The increasing population, urbanization, and industrialization raise the demand for the energy consumption of fossil fuels, water, material, and available natural resources, which further poses the issue of energy security and a clean environment ( Madlener and Sunak 2011 ; Saraswat and Digalwar 2021 ). The large energy requirement

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Adrien Pierre
,
Daniel F. Nadeau
,
Antoine Thiboult
,
Alain N. Rousseau
,
François Anctil
,
Charles P. Deblois
,
Maud Demarty
,
Pierre-Erik Isabelle
, and
Alain Tremblay

inputs/outputs to reservoirs, as well as water levels for the benefit of climate modeling. Hydropower reservoirs differ from lakes in that their water level and residence time are largely controlled by human intervention over the course of the year. As a result, their thermal regime can also differ substantially from that of a natural lake. For example, fluctuations in reservoir temperature profiles can be triggered by internal currents resulting from turbine operation, thereby attenuating thermal

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Nathalie Voisin
,
Alan F. Hamlet
,
L. Phil Graham
,
David W. Pierce
,
Tim P. Barnett
, and
Dennis P. Lettenmaier

1. Introduction and background a. Energy terms and units A discussion of terms and units used throughout the paper is warranted given the many different terms that are used to describe energy-related variables. In a strict physical definition, power and energy are related by time (i.e., energy production is power integrated with respect to time). However, in common usage, “hydropower generation” and “electrical power” are terms that are often used to describe energy production or energy demand

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Zhangkang Shu
,
Jianyun Zhang
,
Junliang Jin
,
Lin Wang
,
Guoqing Wang
,
Jie Wang
,
Zhouliang Sun
,
Ji Liu
,
Yanli Liu
,
Ruimin He
,
Cuishan Liu
, and
Zhenxin Bao

-real-time precipitation estimates during 2010 extreme flood event in Swat River Basin, Hindukush region . Adv. Meteor. , 2016 , 1 – 8 , https://doi.org/10.1155/2016/2604980 . 10.1155/2016/2604980 Bai , L. , C. Shi , L. Li , Y. Yang , and J. Wu , 2018 : Accuracy of CHIRPS satellite-rainfall products over mainland China . Remote Sens. , 10 , 362 , https://doi.org/10.3390/rs10030362 . 10.3390/rs10030362 Block , P. , 2011 : Tailoring seasonal climate forecasts for hydropower operations . Hydrol

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Wei Li
,
Jie Chen
,
Lu Li
,
Hua Chen
,
Bingyi Liu
,
Chong-Yu Xu
, and
Xiangquan Li

various bias correction strategies may result in slightly different results. For a complete evaluation, other bias correction methods and distributed hydrological models should be used in further studies. Acknowledgments This work was partially supported by the State Key Laboratory of Water Resources and Hydropower Engineering Science funding (2017SWG02), the National Natural Science Foundation of China (Grant 51779176, 51525902, 51539009), the Thousand Youth Talents Plan from the Organization

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Jun Li
,
Zhaoli Wang
,
Xushu Wu
,
Chong-Yu Xu
,
Shenglian Guo
, and
Xiaohong Chen

timely warnings of drought disasters. Acknowledgments We appreciate the China Meteo-rological Administration and the National Inventory of the Forest Ministry of China. The research was funded by the China Postdoctoral Science Foundation (2019M662919), the Visiting Researcher Fund Program of State Key Laboratory of Water Resources and Hydropower Engineering Science (Wuhan University, 2019SWG03) the Fundamental Research Funds for the Central Universities (2019JQ06), and the National Natural Science

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Allan Frei
,
Rajith Mukundan
,
Jie Chen
,
Rakesh K. Gelda
,
Emmet M. Owens
,
Jordan Gass
, and
Arun Ravindranath

work is supported by the New York City Department of Environmental Protection Climate Change Integrated Modeling Project (Frei, Mukundan, Gelda, Owens, Gass, Ravindranath), the Institute for Sustainable Cities at Hunter College (Frei, Ravindranath), and the State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan, China (Chen). Thanks to Cloe Mueller for bibliographic support. Data availability statement. All datasets used in this analysis are publicly available as

Open access
Yanchen Zheng
,
Jianzhu Li
,
Lixin Dong
,
Youtong Rong
,
Aiqing Kang
, and
Ping Feng

Design Flood of Water Resources and Hydropower Projects . Chinese Water Resources and Hydropower Press, 80 pp . Mishra , S. K. , M. K. Jain , R. P. Pandey , and V. P. Singh , 2003 : Evaluation of AMC-dependent SCS-CN-based models using large data of small watersheds . Water Energy Int. , 60 , 13 – 23 . Mishra , S. K. , R. K. Sahu , T. I. Eldho , and M. K. Jain , 2006 : An improved Ia-S relation incorporating antecedent moisture in SCS-CN methodology . Water Resour. Manage

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Yu-Kun Hou
,
Hua Chen
,
Chong-Yu Xu
,
Jie Chen
, and
Sheng-Lian Guo

Abstract

Statistical downscaling is useful for managing scale and resolution problems in outputs from global climate models (GCMs) for climate change impact studies. To improve downscaling of precipitation occurrence, this study proposes a revised regression-based statistical downscaling method that couples a support vector classifier (SVC) and first-order two-state Markov chain to generate the occurrence and a support vector regression (SVR) to simulate the amount. The proposed method is compared to the Statistical Downscaling Model (SDSM) for reproducing the temporal and quantitative distribution of observed precipitation using 10 meteorological indicators. Two types of calibration and validation methods were compared. The first method used sequential split sampling of calibration and validation periods, while the second used odd years for calibration and even years for validation. The proposed coupled approach outperformed the other methods in downscaling daily precipitation in all study periods using both calibration methods. Using odd years for calibration and even years for validation can reduce the influence of possible climate change–induced nonstationary data series. The study shows that it is necessary to combine different types of precipitation state classifiers with a method of regression or distribution to improve the performance of traditional statistical downscaling. These methods were applied to simulate future precipitation change from 2031 to 2100 with the CMIP5 climate variables. The results indicated increasing tendencies in both mean and maximum future precipitation predicted using all the downscaling methods evaluated. However, the proposed method is an at-site statistical downscaling method, and therefore this method will need to be modified for extension into a multisite domain.

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