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Virtual Special Issue: Hydrological Extremes in a Changing Environment: Modelling and Attribution Analysis


The International Symposium of Hydrological Sciences and High-efficiency Water Resources Utilization under the Changing Environment (ISHW 2019) was held in Wuhan, China, from October 24 - 26th, 2019. It was co-organized by the School of Water Resources and Hydropower Engineering, and the State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University. The symposium was sponsored by the 111 Project “Evolution Mechanism and Adaptive Strategies of Hydrological and Water Resources System under the Changing Environment” of the Ministry of Education of China and the Research Council of Norway (FRINATEK Project 274310).

The ISHW 2019 brought together over 300 participants from more than 30 universities, institutions, and enterprises around the world to address the issues related to hydrological sciences and water resources management under the changing environment. In this symposium, a wide variety of cutting-edge topics centered around (1) Sponge City; (2) Water Resources Management; (3) Frequency Analysis of Nonstationary Hydrological Extremes; (4) Ecohydrology; (5) Climate Change; (6) Information Technology (IT) and Artificial Intelligence (AI) in Hydrology and Water Resources.

This Special Issue publishes selected papers related to climate change and hydrological extremes, i.e. droughts and floods, which are globally important natural hazards with associated costly impacts on society and the environment. Floods and droughts result from the superposition of different processes at various space and time scales: physical processes in the atmosphere, catchments, the river systems and anthropogenic activities. However, the characteristics of hydrological extremes have been altered due to climate change and variability, such that approaches for their detection, attribution and frequency of occurrence need to be revisited as they are no longer stationary processes.

This Special Issue of Hydrological Extremes in a Changing Environment: Modelling and Attribution Analysis includes 8 papers. All the papers collectively reflect hydrological extreme issues under the changing environment.

The Guest Editors would like to acknowledge the invaluable contributions of all the anonymous reviewers, and the consistently helpful guidance and support of Emma Gulseven at IWA Publishing and the Emeritus Editor-in-Chief, Professor Chong-Yu Xu.


Editorial: Hydrological extremes in a changing environment: modeling and attribution analysis

Yanlai Zhou, Cosmo Ngongondo, Nils Roar Sælthun

Hydrology Research



Design flood estimation with varying record lengths in Norway under stationarity and nonstationarity scenarios

Lei Yan, Lihua Xiong, Gusong Ruan, Mengjie Zhang, Chong-Yu Xu

Hydrology Research (1 December 2021) 52 (6): 1596–1614.




Decline in net primary productivity caused by severe droughts: evidence from the Pearl River basin in China

Yuliang Zhou, Ping Zhou

Hydrology Research (1 December 2021) 52 (6): 1559–1576.




Copula-based modeling of hydraulic structures using a nonlinear reservoir model

Qiaofeng Tan, Yunze Mao, Xin Wen, Tian Jin, Ziyu Ding, Zhenni Wang

Hydrology Research (1 December 2021) 52 (6): 1577–1595.




Hydro-environmental response to the inter-basin water resource development in the middle and lower Han River, China

Junhong Zhang, Liquan Guo, Tao Huang, Dongdong Zhang, Zhimin Deng, Linshuang Liu, Tao Yan

Hydrology Research (1 January 2022) 53 (1): 141–155.




Probabilistic interval estimation of design floods under non-stationary conditions by an integrated approach

Yanlai Zhou, Shenglian Guo, Chong-Yu Xu, Lihua Xiong, Hua Chen, Cosmo Ngongondo, Lu Li

Hydrology Research (1 February 2022) 53 (2): 259–278.




Propagation dynamics and causes of hydrological drought in response to meteorological drought at seasonal timescales

Lan Ma, Qiang Huang, Shengzhi Huang, Dengfeng Liu, Guoyong Leng, Lu Wang, Pei Li

Hydrology Research (1 January 2022) 53 (1): 193–205.




Evaluation of a multisite weather generator on precipitation simulation in the Yangtze river basin

Yu Li, Xin-Min Zeng, Jiali Guo

Hydrology Research (1 January 2022) 53 (1): 206–220.




Improving BP artificial neural network model to predict the SPI in arid regions: a case study in Northern Shaanxi, China

Li Shaoxuan, Xie Jiancang, Yang Xue, Xue Ruihua, Zhao Peiyuan

Hydrology Research (1 March 2022) 53 (3): 419–440.



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