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A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water and Climate Change".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 11748

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Special Issue Editors

Prof. Dr. Wenchuan Wang

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Guest Editor

College of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Interests: watershed hydrological models; hydrological forecasting under changing environment; data preprocessing techniques; hybrid intelligent computing; climate change; modelling hydrological processes
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Zhongkai Feng

E-Mail Website
Guest Editor

College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
Interests: reservoir operation; hydrological forecasting; water resources management; artificial intelligence; engineering optimization
Special Issues, Collections and Topics in MDPI journals

Dr. Mingwei Ma

E-Mail Website
Guest Editor

North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Interests: climate change; extreme hydrological event; land surface process; multivariate statistics; uncertainty and risk analysis; hydrological modelling under changing environment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Due to the influences of climate changes and human activities, extreme climate events have made obvious changes to hydrological process and the temporal-spatial distribution of water resources over the past several decades. These unexpected changes are affecting many aspects of human society, such as water supply, power generation, environmental protection, and economic development. In some countries, the growing rainfall has sharply increased the flood risk and many people have to move from their hometown to safe areas during the flood seasons; in some regions, the risks of water resources shortage and drought are becoming more and more serious and a great deal of manpower and material are required in order to guarantee the daily necessities represented by water. In this context, many scientists and engineers are assessing the impact of climate change on watershed hydrological process for a better understanding of the possible hydrological process response and to make reasonable scheduling schemes and policies under the changing environment.

This Special Issue aims to provide an opportunity for scholars to share their latest research findings related to climatic change, hydrological processes, and other related topics. In this Special Issue, high-quality research papers in the following themes are invited (not an exhaustive list):

Watershed hydrological models;
Hydrological process response;
Flood warning and risk analysis;
Hydrological forecasting and simulation;
Extreme hydrological and climate events;
Impact of climate changes on hydrological processes;
Smart water resources management and planning;
Downscaling and modeling using global climate model data;
Adaptive reservoir operation under the changing environment;
Extreme hydrometeorological events;
Dynamical mechanisms associated with hydrometeorological processes;
New approaches/methods/models for hydrological processes;
Relevant case studies and applications.

Prof. Dr. Wenchuan Wang
Prof. Dr. Zhongkai Feng
Dr. Mingwei Ma
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

climate change
hydrological forecasting
climatic and hydrologic models
artificial intelligence
hydrological processes
uncertainty and risk
hydrological models
flood risk response

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Published Papers (7 papers)

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Editorial

Jump to: Research

3 pages, 169 KiB

Open AccessEditorial

Climate Changes and Hydrological Processes

by Wenchuan Wang, Zhongkai Feng and Mingwei Ma

Water 2022, 14(23), 3922; https://doi.org/10.3390/w14233922 - 2 Dec 2022

Cited by 4 | Viewed by 1789

Abstract

Due to the influences of climate changes and human activities, extreme climate events have made obvious changes to the hydrological process and the temporal-spatial distribution of water resources over the past several decades [...] Full article

(This article belongs to the Special Issue Climate Changes and Hydrological Processes)

Research

Jump to: Editorial

21 pages, 4923 KiB

Open AccessArticle

Simulation of the Water Storage Capacity of Siling Co Lake on the Tibetan Plateau and Its Hydrological Response to Climate Change

by Yuanzhi Tang, Junjun Huo, Dejun Zhu and Zhe Yuan

Water 2022, 14(19), 3175; https://doi.org/10.3390/w14193175 - 9 Oct 2022

Cited by 5 | Viewed by 2180

Abstract

Due to their special geographical locations and environments, plateau lakes play a key role in maintaining regional water balance, but lake water storage changes are upsetting this balance. Based on data from lakes on the Tibetan Plateau (TP), this study used the Spatial Processes in Hydrology (SPHY) model to simulate the runoff process in the Siling Co basin from 2000 to 2016 and estimated the changes in water storage of Siling Co and the contribution of each component of runoff into the lake. The results showed that the water storage capacity of Siling Co has increased by 1.2 billion m³/yr, and the lake area continues to expand; declines in precipitation have significantly reduced baseflow (BF), rainfall runoff (RR), and snow runoff (SR), while temperature increases have raised glacier runoff (GR). The simulated average runoff showed that BF, GF, RR, and SR contribute 24%, 22%, 16%, and 38%, respectively, of the flow into Siling Co. Based on hypothetical climate change scenarios and two Shared Socioeconomic Pathways (SSP1-2.6 and SSP3-7.0) from the MRI-ESM2-0 GCMs, this study estimated that a 10% increase in precipitation could lead to a 28% increase in total runoff, while a 1 °C increase in temperature could lead to a 10% decrease in runoff. The average runoff depth of the basin is expected to increase by 30–39 mm, since the temperature and precipitation may increase significantly from 2020 to 2050. The intensification of glacial melting caused by the increase in temperature continues, posing a greater challenge to many water resources management problems caused by the expansion of lakes. Full article

(This article belongs to the Special Issue Climate Changes and Hydrological Processes)

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18 pages, 3415 KiB

Open AccessArticle

Analysis of Hydrologic Drought Frequency Using Multivariate Copulas in Shaying River Basin

by Jianqin Ma, Bifeng Cui, Xiuping Hao, Pengfei He, Lei Liu and Zhirui Song

Water 2022, 14(8), 1306; https://doi.org/10.3390/w14081306 - 17 Apr 2022

Cited by 7 | Viewed by 2625

Abstract

Droughts, considered one of the most dangerous and costly water cycle expressions, always occurs over a certain region, lasting several weeks or months, and involving multiple variables. In this work, a multivariate approach was used for the statistical characterization of hydrological droughts in Shaying River Basin with data from 1959–2008. The standard runoff index (SRI) and the run theory were employed to defined hydrological drought character variables (duration, severity, and intensity peak). Then, a multivariate joint probability analysis with four symmetric and corresponding asymmetric Archimedean Copulas was presented; and the multivariate frequency analysis with the joint return periods (

T_{a n d}

and

T_{o r}

) were estimated. The results showed that the hydrological droughts have a severity of 4.79 and 5.09, and the drought intensity peak is of 1.35 and 1.50 in Zhoukou station and Luohe station, respectively; the rank correlation coefficients τ are more than 0.5, which means multivariate copulas can effectively describe the joint frequency distributions among multivariate variables. Drought risk shows a spatial variation: the downstream observed at Zhoukou station is characterized by a higher multivariate drought risk. In general, multivariate copulas provide a reliable method when constructing a comprehensive drought index and evaluating multivariate drought characteristics. Thus, this paper can provide useful indications for the multi-dimensional droughts’ risks assessment in Shaying River Basin. Full article

(This article belongs to the Special Issue Climate Changes and Hydrological Processes)

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14 pages, 1877 KiB

Open AccessArticle

Analysis of the Relative Importance of the Main Hydrological Processes at Different Temporal Scales in Watersheds of South-Central Chile

by Yelena Medina, Enrique Muñoz, Robert Clasing and José Luis Arumí

Water 2022, 14(5), 807; https://doi.org/10.3390/w14050807 - 4 Mar 2022

Cited by 3 | Viewed by 2645

Abstract

In Chile in recent years, changes in precipitation and temperatures have been reported that could affect water resource management and planning. One way of facing these changes is studying and understanding the behavior of hydrological processes at a regional scale and their different temporal scales. Therefore, the objective of this study is to analyze the importance of the hydrological processes of the HBV model at different temporal scales and for different hydrological regimes. To this end, 88 watersheds located in south-central Chile were analyzed using time-varying sensitivity analysis at five different temporal scales (1 month, 3 months, 6 months, 1 year, and 5 years). The results show that the model detects the temporality of the most important hydrological processes. In watersheds with a pluvial regime, the greater the temporal scale, the greater the importance of soil water accumulation processes and the lower the importance of surface runoff processes. By contrast, in watersheds with a nival regime, at greater temporal scales, groundwater accumulation and release processes take on greater importance, and soil water release processes are less important. Full article

(This article belongs to the Special Issue Climate Changes and Hydrological Processes)

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22 pages, 14626 KiB

Open AccessArticle

Future Climate-Driven Runoff Change in the Large River Basins in Eastern Siberia and the Far East Using Process-Based Hydrological Models

by Andrey Kalugin

Water 2022, 14(4), 609; https://doi.org/10.3390/w14040609 - 17 Feb 2022

Cited by 11 | Viewed by 2057

Abstract

The main goal of this study was to obtain new results on the physically based future hydrological consequences of climate change in the Amur, Lena, and Selenga River basins by using data from an ensemble of global climate (general circulation) models (GCMs) as boundary conditions in spatially distributed, process-based runoff formation models. This approach provides a basis for a more detailed comparison of the sensitivity of hydrological systems of neighboring large river basins in Eastern Siberia and the Far East. The greatest increases in annual flow are predicted for the Lena River under Representative Concentration Pathway (RCP) 2.6 and RCP 6.0 by the middle and end of the 21st century and for the Selenga River under RCP 6.0 by the end of the 21st century, while the Amur flow anomalies are close to zero. During the 21st century, the greatest relative changes in river flow are predicted for the spring flood, especially for the Lena and Selenga, under both scenarios. The summer–autumn and winter runoff of the Amur River has a negative change of up to 8% for the two RCPs, and, on the contrary, the anomalies are positive for the Lena and Selenga. Evaluating runoff variations between RCPs, we noted high summer–autumn and winter runoff changes for the Amur River under RCP 6.0 for the future period, a significant increase in anomalies of the spring and winter runoff of the Lena under RCP 6.0 by the end of the 21st century, and a greater prevalence of summer–autumn and winter runoff increase for the Selenga River under RCP 2.6 during the 21st century, but it is especially pronounced by its end. Full article

(This article belongs to the Special Issue Climate Changes and Hydrological Processes)

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21 pages, 4262 KiB

Open AccessArticle

Variation of Runoff and Runoff Components of the Upper Shule River in the Northeastern Qinghai–Tibet Plateau under Climate Change

by Jinkui Wu, Hongyuan Li, Jiaxin Zhou, Shuya Tai and Xueliang Wang

Water 2021, 13(23), 3357; https://doi.org/10.3390/w13233357 - 26 Nov 2021

Cited by 23 | Viewed by 2993

Abstract

Quantifying the impact of climate change on hydrologic features is essential for the scientific planning, management and sustainable use of water resources in Northwest China. Based on hydrometeorological data and glacier inventory data, the Spatial Processes in Hydrology (SPHY) model was used to simulate the changes of hydrologic processes in the Upper Shule River (USR) from 1971 to 2020, and variations of runoff and runoff components were quantitatively analyzed using the simulations and observations. The results showed that the glacier area has decreased by 21.8% with a reduction rate of 2.06 km²/a. Significant increasing trends in rainfall runoff, glacier runoff (GR) and baseflow indicate there has been a consistent increase in total runoff due to increasing rainfall and glacier melting. The baseflow has made the largest contribution to total runoff, followed by GR, rainfall runoff and snow runoff, with mean annual contributions of 38%, 28%, 18% and 16%, respectively. The annual contribution of glacier and snow runoff to the total runoff shows a decreasing trend with decreasing glacier area and increasing temperature. Any increase of total runoff in the future will depend on an increase of rainfall, which will exacerbate the impact of drought and flood disasters. Full article

(This article belongs to the Special Issue Climate Changes and Hydrological Processes)

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24 pages, 4398 KiB

Open AccessEditor’s ChoiceArticle

A Comparison of BPNN, GMDH, and ARIMA for Monthly Rainfall Forecasting Based on Wavelet Packet Decomposition

by Wenchuan Wang, Yujin Du, Kwokwing Chau, Haitao Chen, Changjun Liu and Qiang Ma

Water 2021, 13(20), 2871; https://doi.org/10.3390/w13202871 - 14 Oct 2021

Cited by 34 | Viewed by 3201

Abstract

Accurate rainfall forecasting in watersheds is of indispensable importance for predicting streamflow and flash floods. This paper investigates the accuracy of several forecasting technologies based on Wavelet Packet Decomposition (WPD) in monthly rainfall forecasting. First, WPD decomposes the observed monthly rainfall data into several subcomponents. Then, three data-based models, namely Back-propagation Neural Network (BPNN) model, group method of data handing (GMDH) model, and autoregressive integrated moving average (ARIMA) model, are utilized to complete the prediction of the decomposed monthly rainfall series, respectively. Finally, the ensemble prediction result of the model is formulated by summing the outputs of all submodules. Meanwhile, these six models are employed for benchmark comparison to study the prediction performance of these conjunction methods, which are BPNN, WPD-BPNN, GMDH, WPD-GMDH, ARIMA, and WPD-ARIMA models. The paper takes monthly data from Luoning and Zuoyu stations in Luoyang city of China as the case study. The performance of these conjunction methods is tested by four quantitative indexes. Results show that WPD can efficiently improve the forecasting accuracy and the proposed WPD-BPNN model can achieve better prediction results. It is concluded that the hybrid forecast model is a very efficient tool to improve the accuracy of mid- and long-term rainfall forecasting. Full article

(This article belongs to the Special Issue Climate Changes and Hydrological Processes)

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