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Water
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Hydrological Extremes and Water Resources Research
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Hydrological Extremes and Water Resources Research

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

Deadline for manuscript submissions: closed (30 July 2023) | Viewed by 9635

Special Issue Editors

Dr. Ali Torabi Haghighi

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Guest Editor
Water, Energy and Environmental Engineering, Faculty of Technology, University of Oulu, 90014 Oulu, Finland
Interests: rivers; environmental engineering; civil engineering; hydrology; water resources engineering; hydrological modeling;hydraulics; climate change; environment; water quality
Special Issues, Collections and Topics in MDPI journals
Dr. Epari Ritesh Patro

E-Mail Website
Guest Editor
Water, Energy, and Environmental Engineering Research Unit, University of Oulu, 90014 Oulu, Finland
Interests: hydrology; environmental science; hydropower; energy market
Special Issues, Collections and Topics in MDPI journals
Dr. Ali Danandeh Mehr

E-Mail Website
Guest Editor
Civil Engineering Department, Antalya Bilim University, Antalya 07190, Turkey
Interests: stochastic hydrology; hydroinformatics; algorithms; water resources systems
Dr. AliAkbar Hekmatzadeh

E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, Shiraz University of Technology, Modarres Boulevard 71557-13876, Iran
Interests: water and wastewater treatment; groundwater and surface water modeling; hydraulic structures; soft computing

Special Issue Information

Dear Colleagues,

Heavy precipitations and heatwaves, along with increasing temperature at continental, regional, and basin scales, are exacerbated by global climate change. Subsequently, the frequency and severity of hydrological extremes such as droughts, floods, cyclones, and hurricanes have increased remarkably in recent years. The simultaneous, coincident, or successive occurrence of such extreme events in a region can exacerbate already adverse impacts compared to one extreme individual event. Such extreme events could have long-lasting consequences on society, the natural environment, and ecosystems.

Hydrological extremes have triggered many scientific and technical investigations, which have introduced a wide variety of structural solutions.  Although such solutions have contributed to achieving a safer condition for the territory, we note that coping with natural hazards still represents a living topic for society. Another limitation in current water resource research is that specific tools to cope with possible unexpected events are still lacking. Moreover, know-how regarding risk management of an extreme hydrological event is still based on static planning of emergencies, i.e., a method based on scenarios formulated before the event.

A bottom-up and top-down approach to predicting, preventing, and mitigating such extremes is needed for scientific and non-scientific communities to advance water resources research. It is crucial to promote and adopt smart policies and practices to manage water resources considering the possible extreme events. A specific challenge that remains unanswered in this context is how to predict and model the physical process (i.e., the rainfall-runoff chain) and cope with people’s behavior.

Dr. Ali Torabi Haghighi
Dr. Epari Ritesh Patro
Dr. Ali Danandeh Mehr
Dr. AliAkbar Hekmatzadeh
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

  • drought
  • flood
  • risk
  • climate change
  • vulnerability
  • reservoir operation

Published Papers (5 papers)

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Research

36 pages, 12837 KiB  
Article
Vulnerability of Water Resources to Drought Risk in Southeastern Morocco: Case Study of Ziz Basin
by Souad Ben Salem, Abdelkrim Ben Salem, Ahmed Karmaoui and Mohammed Yacoubi Khebiza
Water 2023, 15(23), 4085; https://doi.org/10.3390/w15234085 - 24 Nov 2023
Cited by 3 | Viewed by 1252
Abstract
Water resources in Morocco have been severely influenced by climate change and prolonged drought, particularly in the pre-Saharan zone. The Ziz watershed faces increasing pressure due to the high demographic growth, increased demand for water, excessive groundwater consumption, and investment in agriculture. But [...] Read more.
Water resources in Morocco have been severely influenced by climate change and prolonged drought, particularly in the pre-Saharan zone. The Ziz watershed faces increasing pressure due to the high demographic growth, increased demand for water, excessive groundwater consumption, and investment in agriculture. But how long will water resources withstand these problems? This study, therefore, enters into the context of the assessment of water resources and estimates their vulnerability using the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and Standardized Groundwater Index (SGI), on data from the Ziz watershed from 1986 to 2016. Additionally, climate projections were utilized to simulate the future SGI from 2017 to 2100. The Water Evaluation and Planning System (WEAP) was employed to evaluate changes in Land Use and Land Cover (LULC) during the period of 1992–2020, and to generate future scenarios for land class inflows and outflows from 2017 to 2100, in comparison to the reference period of 1986–2016, thereby incorporating the SSP climate scenarios. The results indicate that the Ziz Basin experienced significant drought events in 1986–1989 and 2000–2003. The SPI and SPEI significantly correlated with SGI in some monitoring wells and with specific accumulation periods. The LULC analysis showed an increase in agricultural land and urban land and a decrease in barren or sparse land. Climate data analysis and scenarios predict that under SSP5-8.5, minimum and maximum temperatures will increase by 2.61 °C and 2.93 °C, respectively, and precipitation will decrease by 30% over this century. This substantial shift in climate conditions is reflected in the decline in SGIs, especially in the long term under SSP5-8.5. Water availability will decrease during this century under SSP3-7.0 and SSP5-8.5, as reflected in reduced land class inflows and increased outflows. These findings emphasize the need for stakeholders to implement integrated water governance for sustainability in the Ziz watershed. Full article
(This article belongs to the Special Issue Hydrological Extremes and Water Resources Research)
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16 pages, 4100 KiB  
Article
VMD-GP: A New Evolutionary Explicit Model for Meteorological Drought Prediction at Ungauged Catchments
by Ali Danandeh Mehr, Masoud Reihanifar, Mohammad Mustafa Alee, Mahammad Amin Vazifehkhah Ghaffari, Mir Jafar Sadegh Safari and Babak Mohammadi
Water 2023, 15(15), 2686; https://doi.org/10.3390/w15152686 - 25 Jul 2023
Cited by 2 | Viewed by 1152
Abstract
Meteorological drought is a common hydrological hazard that affects human life. It is one of the significant factors leading to water and food scarcity. Early detection of drought events is necessary for sustainable agricultural and water resources management. For the catchments with scarce [...] Read more.
Meteorological drought is a common hydrological hazard that affects human life. It is one of the significant factors leading to water and food scarcity. Early detection of drought events is necessary for sustainable agricultural and water resources management. For the catchments with scarce meteorological observatory stations, the lack of observed data is the main leading cause of unfeasible sustainable watershed management plans. However, various earth science and environmental databases are available that can be used for hydrological studies, even at a catchment scale. In this study, the Global Drought Monitoring (GDM) data repository that provides real-time monthly Standardized Precipitation and Evapotranspiration Index (SPEI) across the globe was used to develop a new explicit evolutionary model for SPEI prediction at ungauged catchments. The proposed model, called VMD-GP, uses an inverse distance weighting technique to transfer the GDM data to the desired area. Then, the variational mode decomposition (VMD), in conjunction with state-of-the-art genetic programming, is implemented to map the intrinsic mode functions of the GMD series to the subsequent SPEI values in the study area. The suggested model was applied for the month-ahead prediction of the SPEI series at Erbil, Iraq. The results showed a significant improvement in the prediction accuracy over the classic GP and gene expression programming models developed as the benchmarks. Full article
(This article belongs to the Special Issue Hydrological Extremes and Water Resources Research)
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15 pages, 3369 KiB  
Article
RiTiCE: River Flow Timing Characteristics and Extremes in the Arctic Region
by Abolfazl Jalali Shahrood, Amirhossein Ahrari, Pekka M. Rossi, Björn Klöve and Ali Torabi Haghighi
Water 2023, 15(5), 861; https://doi.org/10.3390/w15050861 - 23 Feb 2023
Cited by 1 | Viewed by 2210
Abstract
(1) Background: river ice has a significant impact on nearly 66% of rivers in the Northern Hemisphere. Ice builds up during winter when the flow gradually reduces to its lowest level before the spring melt is initiated. Ice-induced floods can happen quickly, posing [...] Read more.
(1) Background: river ice has a significant impact on nearly 66% of rivers in the Northern Hemisphere. Ice builds up during winter when the flow gradually reduces to its lowest level before the spring melt is initiated. Ice-induced floods can happen quickly, posing a risk to infrastructure, hydropower generation, and public safety, in addition to ecological repercussions from the scouring and erosion of the riverbeds. (2) Methods: we used the annual daily hydrograph to develop a RiTiCE tool that detects the break-up date and develops indices to analyze timing characteristics of extreme flow in the Tana and Tornio Rivers. (3) Results: the study showed that low-flow periods in two rivers had a significant trend with a confidence level of 95%. Additionally, it was observed that the occurrence date of seasonal 90-day low- and high-flow periods occurred earlier in recent years. Conversely, the Tana River showed a negative trend in its annual minimum flow over the century, which is the opposite of what happened with the Tornio River. (4) Conclusions: the method can be used to detect the date when the river ice breaks up in a given year, leading to a better understanding of the river ice phenomenon. Full article
(This article belongs to the Special Issue Hydrological Extremes and Water Resources Research)
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22 pages, 2726 KiB  
Article
Spatiotemporal Changes in Air Temperature and Precipitation Extremes over Iran
by Mohammad Jamali, Alireza Gohari, Armita Motamedi and Ali Torabi Haghighi
Water 2022, 14(21), 3465; https://doi.org/10.3390/w14213465 - 30 Oct 2022
Cited by 8 | Viewed by 2144
Abstract
In this study, a comprehensive trend analysis was employed to study the spatiotemporal changes in precipitation characteristics with air temperature increasing over time. The nonparametric Mann–Kendall test and the quantile regression methods were applied to detect the plausible temporal trends in 11 extreme [...] Read more.
In this study, a comprehensive trend analysis was employed to study the spatiotemporal changes in precipitation characteristics with air temperature increasing over time. The nonparametric Mann–Kendall test and the quantile regression methods were applied to detect the plausible temporal trends in 11 extreme rainfall indices and three air temperature indices employed in this study. The results showed there was little evidence to suggest that increases in the maximum of 3-h and 24-h precipitation at higher temperatures resulted in similar increases in the annual precipitation, with most stations throughout Iran showing drying features with higher temperatures. Generally, most regions over Iran scaled negatively, implying a reduction in the annual precipitation ranging from −2.64 to −0.44 mm/°C at higher temperatures. The linear tendencies of the maximum 24-h precipitation ranged from −0.4 to 0.23 mm/°C. The annual precipitation of the stations located at Urmia Lake, Caspian Sea, and the Eastern Border Basins showed a decreasing trend (−3.70 to 1.11 mm/year), while the number of rainy days increased (−2.78 to 4.72), which showed the occurrence of lighter rainfall in these regions. The increasing trend in the maximum 24-h precipitation over Western and Central Iran implied a higher probability of extreme precipitation with a higher intensity. This study revealed that the shift in precipitation extremes shifted from fall to winter by increasing the elevation, but these effects have no statistical significance in Iran. Full article
(This article belongs to the Special Issue Hydrological Extremes and Water Resources Research)
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23 pages, 8045 KiB  
Article
Evaluating Three Supervised Machine Learning Algorithms (LM, BR, and SCG) for Daily Pan Evaporation Estimation in a Semi-Arid Region
by Pouya Aghelpour, Zahra Bagheri-Khalili, Vahid Varshavian and Babak Mohammadi
Water 2022, 14(21), 3435; https://doi.org/10.3390/w14213435 - 28 Oct 2022
Cited by 6 | Viewed by 2006
Abstract
Evaporation is one of the main components of the hydrological cycle, and its estimation is crucial and important for water resources management issues. Access to a reliable estimator tool for evaporation simulation is important in arid and semi-arid areas such as Iran, which [...] Read more.
Evaporation is one of the main components of the hydrological cycle, and its estimation is crucial and important for water resources management issues. Access to a reliable estimator tool for evaporation simulation is important in arid and semi-arid areas such as Iran, which lose more than 70% of their received precipitation by evaporation. Current research employs the Bayesian Regularization (BR) and Scaled Conjugate Gradient (SCG) algorithms for training the Multilayer Perceptron (MLP) model (as MLP-BR and MLP-SCG) and comparing their performance with the Levenberg–Marquardt (LM) algorithm (as MLP-LM). For this purpose, 16 meteorological variables were used on a daily scale; including temperature (5 variables), air pressure (4 variables), and relative humidity (6 variables) as input data sets, and pan evaporation as the target variable of the MLP model. The surveys were conducted during the period of 2006–2021 in Fars Province in Iran, which is a semi-arid region and has many natural lakes. Various combinations of input-target pairs were tested by several learning algorithms, resulting in seven input scenarios: (1) temperature-based (T), (2) pressure-based (F), (3) humidity-based (RH), (4) temperature–pressure-based (T-F), (5) temperature–humidity-based (T-RH), (6) pressure–humidity-based (F-RH) and (7) temperature–pressure–humidity-based (T-F-RH). The results indicated the relative superiority of the three-component scenario of T-F-RH, and a considerable weakness in the single-component scenario of RH compared with others. The best performance with a root mean square error (RMSE) equal to 1.629 and 1.742 mm per day and a Wilmott Index (WI) equal to 0.957 and 0.949 (respectively for validation and test periods) belonged to the MLP-BR model. Additionally, the amount of R2 (greater than 84%), Nash-Sutcliff efficiency (greater than 0.8) and normalized RMSE (less than 0.1) all indicate the reliability of the estimates provided for the daily pan evaporation. In the comparison between the studied training algorithms, two algorithms, BR and SCG, in most cases, showed better performance than the powerful and common LM algorithm. The obtained results suggest that future researchers in this field consider BR and SCG training algorithms for the supervised training of MLP for the numerical estimation of pan evaporation by the MLP model. Full article
(This article belongs to the Special Issue Hydrological Extremes and Water Resources Research)
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