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Atmosphere
Special Issues
The Hydrologic Cycle in a Changing Climate
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The Hydrologic Cycle in a Changing Climate

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Climatology".

Deadline for manuscript submissions: closed (30 November 2024) | Viewed by 8677

Special Issue Editors

Dr. Diana Meilutytė-Lukauskienė

E-Mail Website
Guest Editor
1. Laboratory of Hydrology, Lithuanian Energy Institute, Breslaujos St. 3, LT-44403 Kaunas, Lithuania
2. Department of Physics, Mathematics and Biophysics, Faculty of Medicine, Lithuanian University of Health Sciences, Eiveniu Str. 4, LT-44307 Kaunas, Lithuania
Interests: climate change; extreme hydrological phenomena; low flow indices; hydromorphology; droughts; spring floods
Special Issues, Collections and Topics in MDPI journals
Dr. Vytautas Akstinas

E-Mail Website
Guest Editor
Laboratory of Hydrology, Lithuanian Energy Institute, Breslaujos St. 3, LT-44403 Kaunas, Lithuania
Interests: climatology; climate change; teleconnection patterns; hydrometeorological phenomena; catchment hydrology; hydrological modelling; spring floods
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The hydrological cycle is the continuous movement of water in the Earth's hydrosphere. It is continuous process that consists of atmospheric, surface, and groundwater movement. The changing climate directly affects the drivers and components of the hydrological cycle (evapotranspiration, water vapor concentrations, clouds, air temperature, precipitation patterns, surface runoff, stream flow patterns, etc.).

The climate crisis has led to an increase in average global temperatures and an increase in high-temperature-related extreme events such as heat waves. Higher temperatures are also predicted to change the geographic distribution of climate zones. Higher temperatures accelerate evaporation, which increases the risk of severe drought in one region and causes unexpected flooding in another due to transported moisture. Already, as the climate changes, droughts are becoming more frequent and longer lasting in many regions of the World. Drought is an unusual and temporary lack of water resulting from insufficient rainfall and increased evaporation (due to high temperatures). Conversely, over the last century, an increase in evaporation and precipitation is intensifying the hydrological cycle. This is an undesirable consequence of global warming, as higher temperatures encourage evaporation, i.e., the evaporation from the land surface and sea is transporting the moisture as rain and snow to inland areas. Additionally, warmer air can hold more water vapor which can cause risk of heavy rainfall, extreme flooding, etc. Another example of changes in the hydrological cycle is the retreat of glaciers when the water supplied by solid precipitation is not sufficient to replenish the ice lost by melting or sublimation.

In this Special Issue, we invite all colleagues to contribute papers on new insights into any type of process of the hydrologic cycle, its response to climate change, interactions between its components, and many more topics. Research related to any aspect of observations or modelling of the hydrological cycle is welcome, including new or interdisciplinary approaches, feedback processes, various hydro-meteorological phenomena, the human role in the hydrologic cycle, or other topics that improve our understanding about changes in the hydrologic cycle. Review papers will also be considered.

Dr. Diana Meilutytė-Lukauskienė
Dr. Vytautas Akstinas
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. Atmosphere is an international peer-reviewed open access monthly 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 2400 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
  • hydrologic cycle
  • droughts
  • flooding
  • water resourece management
  • river runoff

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Published Papers (6 papers)

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Research

23 pages, 26773 KiB  
Article
Suitability of CMIP6 Models Considering Statistical Downscaling Based on GloH2O and E-OBS Dataset in River Basin Districts of the Southeastern Baltic Sea Basin
by Vytautas Akstinas, Karolina Gurjazkaitė, Diana Meilutytė-Lukauskienė and Darius Jakimavičius
Atmosphere 2025, 16(2), 229; https://doi.org/10.3390/atmos16020229 - 18 Feb 2025
Viewed by 488
Abstract
Climate projections based on global climate models (GCMs) are generally subject to large uncertainties, as the models only reflect the local climate in the past to a limited extent. Statistical downscaling is the most cost-effective approach to identify the systematic biases of the [...] Read more.
Climate projections based on global climate models (GCMs) are generally subject to large uncertainties, as the models only reflect the local climate in the past to a limited extent. Statistical downscaling is the most cost-effective approach to identify the systematic biases of the GCMs from the past and eliminate them in the projections. This study seeks to evaluate the effectiveness of GCMs in capturing local climatic characteristics at the river basin district scale by applying gridded statistical downscaling techniques using global and regional datasets. The historical observational datasets E-OBS and GloH2O were selected to downscale the raw data of 17 GCMs from ~1° grid cells to 0.25° resolution. E-OBS is a regional dataset supported by a dense network of meteorological stations in Europe, while GloH2O is a global dataset covering all continents. The results show that the suitability of the GCMs varies depending on the selected parameter. The statistical downscaling revealed the advantages of the performance of E-OBS in representing local climate characteristics during the historical period and emphasized the crucial role of regional datasets for good climate depiction. Such an approach provides the possibility to assess the relative performance of GCMs based on the high-resolution observational and reanalysis datasets, while generating statistically downscaled datasets for the best ranked GCMs. The strategies used in this study can help to identify the most appropriate models to assemble the right ensemble of GCMs for specific studies. Full article
(This article belongs to the Special Issue The Hydrologic Cycle in a Changing Climate)
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19 pages, 5659 KiB  
Article
Advanced Soft Computing Techniques for Monthly Streamflow Prediction in Seasonal Rivers
by Mohammed Achite, Okan Mert Katipoğlu, Veysi Kartal, Metin Sarıgöl, Muhammad Jehanzaib and Enes Gül
Atmosphere 2025, 16(1), 106; https://doi.org/10.3390/atmos16010106 - 19 Jan 2025
Viewed by 833
Abstract
The rising incidence of droughts in specific global regions in recent years, primarily attributed to global warming, has markedly increased the demand for reliable and accurate streamflow estimation. Streamflow estimation is essential for the effective management and utilization of water resources, as well [...] Read more.
The rising incidence of droughts in specific global regions in recent years, primarily attributed to global warming, has markedly increased the demand for reliable and accurate streamflow estimation. Streamflow estimation is essential for the effective management and utilization of water resources, as well as for the design of hydraulic infrastructure. Furthermore, research on streamflow estimation has gained heightened importance because water is essential not only for the survival of all living organisms but also for determining the quality of life on Earth. In this study, advanced soft computing techniques, including long short-term memory (LSTM), convolutional neural network–recurrent neural network (CNN-RNN), and group method of data handling (GMDH) algorithms, were employed to forecast monthly streamflow time series at two different stations in the Wadi Mina basin. The performance of each technique was evaluated using statistical criteria such as mean square error (MSE), mean bias error (MBE), mean absolute error (MAE), and the correlation coefficient (R). The results of this study demonstrated that the GMDH algorithm produced the most accurate forecasts at the Sidi AEK Djillali station, with metrics of MSE: 0.132, MAE: 0.185, MBE: −0.008, and R: 0.636. Similarly, the CNN-RNN algorithm achieved the best performance at the Kef Mehboula station, with metrics of MSE: 0.298, MAE: 0.335, MBE: −0.018, and R: 0.597. Full article
(This article belongs to the Special Issue The Hydrologic Cycle in a Changing Climate)
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16 pages, 2272 KiB  
Article
Attribution Identification of Runoff Changes Based on the Budyko Elasticity Coefficient Method: A Case Study of the Middle and Upper Reaches of the Jinghe River in the Yellow River Basin
by Xueliang Wang, Haolin Li, Weidong Huang, Lemin Wei, Junfeng Liu and Rensheng Chen
Atmosphere 2025, 16(1), 6; https://doi.org/10.3390/atmos16010006 - 25 Dec 2024
Cited by 1 | Viewed by 534
Abstract
The impacts of climate change and human activities on water resources are a complex and integrated process and a key factor for effective water resource management in semi-arid regions, especially in relation to the Jinghe River basin (JRB), a major tributary of the [...] Read more.
The impacts of climate change and human activities on water resources are a complex and integrated process and a key factor for effective water resource management in semi-arid regions, especially in relation to the Jinghe River basin (JRB), a major tributary of the Yellow River basin. The Sen’s slope estimator and the Mann–Kendall test (M–K test) are implemented to examine the spatial and temporal trends of the hydrological factors, while the elasticity coefficient method based on Budyko’s theory of hydrothermal coupling is employed to quantify the degree of runoff response to the various influencing factors, from 1971 to 2020. The results reveal that the runoff at Pingliang (PL), Jingchuan (JC), and Yangjiaping (YJP) hydrological stations shows an obvious and gradual decreasing trend during the study period, with a sudden change in about 1986, while precipitation shows a fluctuating and increasing trend alongside a potential evapotranspiration-induced fluctuating and decreasing trend. Compared to the previous period, a change of −29%, in relative terms, in the runoff at the YJP hydrological station is observed. The interaction of human activities and climate change in the watershed contributes to the sharp decrease in runoff, with precipitation, potential evapotranspiration, and human activities accounting for −14.3%, −15.1%, and 70.6% of the causes of the change in runoff, respectively. Human activities (e.g., construction of water conservancy projects), precipitation, and potential evapotranspiration are the main factors contributing to the change in runoff. Full article
(This article belongs to the Special Issue The Hydrologic Cycle in a Changing Climate)
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23 pages, 6044 KiB  
Article
Changes in Magnitude and Shifts in Timing of the Latvian River Annual Flood Peaks
by Elga Apsīte, Didzis Elferts, Jānis Lapinskis, Agrita Briede and Līga Klints
Atmosphere 2024, 15(9), 1139; https://doi.org/10.3390/atmos15091139 - 20 Sep 2024
Cited by 1 | Viewed by 1202
Abstract
Climate change is expected to significantly impact temperature and precipitation, as well as snow accumulations and melt in mid-latitudes, including in the Baltic region, ultimately affecting the quantity and seasonal distribution of streamflow. This study aims to investigate the changes in the magnitude [...] Read more.
Climate change is expected to significantly impact temperature and precipitation, as well as snow accumulations and melt in mid-latitudes, including in the Baltic region, ultimately affecting the quantity and seasonal distribution of streamflow. This study aims to investigate the changes in the magnitude and timing of annual maximum discharge for 30 hydrological monitoring stations across Latvia from 1950/51 to 2021/22. Circular statistics and linear mixed effects models were applied to identify the strength of seasonality and timing. Trend analysis of the magnitude and timing of flood peaks were performed by using the Theil–Sen method and Mann–Kendall test. We analyzed regional significance of trends across different hydrological regions and country using the Walker test. Results indicate strong seasonality in annual flood peaks in catchments, with a single peak occurring in spring in the study sub-period of 1950/51–1986/87. Flood seasonality has changed over recent decades (i.e., 1987/88–2021/22) and is seen as a decrease in spring maximum discharge and increase in winter flood peaks. Alterations in annual flood occurrence also point towards a shift in flow regime from snowmelt dominated to mixed snow–rainfall dominated, with consistent changes towards the earlier timing of the flood peak, with a more or less pronounced gradation from west to east. Analysis shows that a significant trend of decrease in the magnitude and timing of annual maximum discharge was detected. Full article
(This article belongs to the Special Issue The Hydrologic Cycle in a Changing Climate)
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21 pages, 14988 KiB  
Article
An Analysis of Extreme Rainfall Events in Cambodia
by Sytharith Pen, Saeed Rad, Liheang Ban, Sokhorng Brang, Panha Nuth and Lin Liao
Atmosphere 2024, 15(8), 1017; https://doi.org/10.3390/atmos15081017 - 22 Aug 2024
Viewed by 2066
Abstract
Extreme rainfall, also known as heavy rainfall or intense precipitation, is a weather event characterized by a significant amount of rainfall within a short period. This study analyzes the trends in extreme precipitation indices at 17 stations in four main regions in Cambodia—the [...] Read more.
Extreme rainfall, also known as heavy rainfall or intense precipitation, is a weather event characterized by a significant amount of rainfall within a short period. This study analyzes the trends in extreme precipitation indices at 17 stations in four main regions in Cambodia—the Tonle Sap, coastal, Mekong Delta, and Upper Mekong regions—between 1991 and 2021. Analyzing the data with RClimDex v1.9 reveals diverse spatial and temporal variations. The statistical analysis of the extreme rainfall indices in Cambodia from 1991 to 2021 reveals significant trends. In the Tonle Sap region, consecutive dry days (CDDs) increased at most stations, except Battabang, Kampong Thmar, and Pursat, while consecutive wet days (CWDs) increased at most stations. These trends align with rising temperatures and reduced forest cover. In the coastal region, particularly at the Krong Khemarak Phummin station, most rainfall indices increased, with a slope value of 89.94 mm/year. The extreme rainfall indices max. 1-day precipitation (RX1day) and max. 5-day precipitation (RX5day) also increased, suggesting higher precipitation on days exceeding the 95th (R95p) and 99th percentiles (R99p). The Kampot station showed a significant increase in CDDs, indicating a heightened drought risk. In the Mekong Delta, the Prey Veng station recorded a decrease in the CDDs slope value by −4.892 days/year, indicating potential drought risks. The Stung Treng station, which is the only station in Upper Mekong, showed a decreasing trend in CDDs with a slope value of −1.183 days/year, indicating a risk of extreme events. These findings underscore the complex interplay between climate change, land use, and rainfall patterns in Cambodia. Full article
(This article belongs to the Special Issue The Hydrologic Cycle in a Changing Climate)
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26 pages, 21173 KiB  
Article
Application of Shannon Entropy in Assessing Changes in Precipitation Conditions and Temperature Based on Long-Term Sequences Using the Bootstrap Method
by Bernard Twaróg
Atmosphere 2024, 15(8), 898; https://doi.org/10.3390/atmos15080898 - 27 Jul 2024
Cited by 2 | Viewed by 2177
Abstract
This study delves into the application of Shannon entropy to analyze the long-term variability in climate data, specifically focusing on precipitation and temperature. By employing data from 1901 to 2010 across 377 catchments worldwide, we investigated the dynamics of climate variables using the [...] Read more.
This study delves into the application of Shannon entropy to analyze the long-term variability in climate data, specifically focusing on precipitation and temperature. By employing data from 1901 to 2010 across 377 catchments worldwide, we investigated the dynamics of climate variables using the generalized extreme value (GEV) distribution and Shannon entropy measures. The methodology hinged on the robust bootstrap technique to accommodate the inherent uncertainties in climatic data, enhancing the reliability of our entropy estimates. Our analysis revealed significant trends in entropy values, suggesting variations in the unpredictability and complexity of climate behavior over the past century. These trends were critically assessed using non-parametric tests to discern the underlying patterns and potential shifts in climate extremes. The results underscore the profound implications of entropy trends in understanding climate variability and aiding the prediction of future climatic conditions. This research not only confirms the utility of Shannon entropy in climatological studies but also highlights its potential in enhancing our understanding of complex and chaotic climate systems. The study’s findings are vital for developing adaptive strategies in response to the evolving nature of climate extremes, thus contributing to more informed decision-making in environmental management and policy formulation. Full article
(This article belongs to the Special Issue The Hydrologic Cycle in a Changing Climate)
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