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Hydrology Research Special Issue on

Hydrological Extremes in a Changing Environment: Modelling and Attribution Analysis

 

 

Hydrological extremes, i.e. droughts and floods, 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. For more accurate estimation of hydrological extremes under nonstationary and uncertain conditions, there is a need for holistic assessments. Time-frequency analysis, hydrological modeling, physical-cause analysis, multivariate statistical analysis and uncertainty analysis are powerful tools for detecting, attributing and making frequency analysis of nonstationary hydrological extremes in a changing climate. Both non-stationarity and uncertainty of frequency analysis of extreme hydrological events should be integrated to reveal the possible operational alternatives to the assumption of stationarity in hydrological extremes frequency analysis. This Special Issue aims to promote innovative research advances in the detection, attribution and frequency analysis of nonstationary hydrological extremes through novel techniques.

 

Guest Editors:

  • Nils Roar Sælthun (University of Oslo, Norway)
  • Cosmo Ngongondo (University of Malawi, Malawi)
  • Yanlai Zhou (University of Oslo, Norway)

 

 

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

Yanlai Zhou; Cosmo Ngongondo; Nils Roar Sælthun

Hydrology Research (1st July 2022) 53 (7): iii–v.

DOI: https://doi.org/10.2166/nh.2022.101

 

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 (1st March 2022) 53 (3): 419-440.

DOI: https://doi.org/10.2166/nh.2022.115

 

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

Yu Li; Xin-Min Zeng; Jiali Guo

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

DOI: https://doi.org/10.2166/nh.2021.040

 

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 (1st January 2022) 53 (1): 193-205.

DOI: https://doi.org/10.2166/nh.2021.006

 

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 (1st December 2021) 52 (6): 1577-1595.

DOI: https://doi.org/10.2166/nh.2021.178

 

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 (1st December 2021) 52 (6): 1596-1614.

DOI: https://doi.org/10.2166/nh.2021.026

 

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 (1st January 2022) 53 (2): 141-155.

DOI: https://doi.org/10.2166/nh.2021.090

 

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

Yuliang Zhou; Ping Zhou

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

DOI: https://doi.org/10.2166/nh.2021.061

 

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 (1st February 2022) 53 (2): 259-278.

DOI: https://doi.org/10.2166/nh.2021.007

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