Special Issue "Extreme Hydrology: Induced Impacts and Vulnerability of Water Resources"

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

Deadline for manuscript submissions: 15 August 2022 | Viewed by 7372

Special Issue Editors

Prof. Dr. Assefa M. Melesse
E-Mail Website
Leading Guest Editor
Prof. Dr. Prasad Daggupati
E-Mail Website
Co-Guest Editor
School of Engineering, University of Guelph, Guelph, ON, Canada
Interests: watershed modeling; water quantity and quality; water scarcity and drought; climate change; ephemeral gullies
Special Issues, Collections and Topics in MDPI journals
Dr. Khabat Khosravi
E-Mail Website
Co-Guest Editor
Department of Watershed Management Engineering, Sari Agricultural and Natural Resources University, Sari, Iran
Interests: watershed hydrology; flood modeling; river engineering and sediment transport; natural hazards; groundwater modeling and vulnerability assessment; GIS and machine learning in soil and water science
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Extreme hydrometeorological events are becoming a common phenomenon. Drought and floods are natural hazards that are having an impact on the livelihood of many communities, leading to a loss of life and damage to natural resources and the environment. The world is experiencing an alarming rate of population increase, land degradation, decline in freshwater resources, and shrinkage of natural and fragile ecosystems. The expansion of agricultural and urban areas has been going on for decades at the expense of forest cover and wetland areas.

With the changing climate and frequent and extreme weather phenomena leading to extreme drought and flood events, water resources managers and policy-makers are struggling to offset the impacts on communities, freshwater availability, water quality, human welfare, and agricultural production and services. These efforts will require an understanding of the behaviors of these extreme phenomena, their linkages to climate dynamics, and the predictability and simulation of the extent of these events. This Special Issue calls for high-quality research papers on drought monitoring and modeling, flood processes and forecasting, climate-change-related extreme events, water quality degradation, land degradation, and soil erosion, ground and surface water vulnerability, and other related areas. The role of remote sensing in the monitoring and mapping of drought and flood-affected areas and the generation of model parameters for modeling extreme hydrologic events will be also covered in this Special Issue.

Prof. Dr. Assefa M. Melesse
Dr. Khabat Khosravi
Prof. Dr. Prasad Daggupati
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 2200 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

  • floods
  • drought
  • extreme hydrology
  • monitoring and modeling of extreme events
  • flood forecasting
  • watershed hydrology
  • natural hazards assessment
  • river engineering
  • soil and water conservation practices
  • climate change
  • remote sensing
  • groundwater modeling and vulnerability assessment

Published Papers (6 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Article
Improving Flow Discharge-Suspended Sediment Relations: Intelligent Algorithms versus Data Separation
Water 2021, 13(24), 3650; https://doi.org/10.3390/w13243650 - 19 Dec 2021
Viewed by 957
Abstract
Information on the transport of fluvial suspended sediment loads (SSL) is crucial due to its effects on water quality, pollutant transport and transformation, dam operations, and reservoir capacity. As such, adopting a reliable method to accurately estimate SSL is a key topic for [...] Read more.
Information on the transport of fluvial suspended sediment loads (SSL) is crucial due to its effects on water quality, pollutant transport and transformation, dam operations, and reservoir capacity. As such, adopting a reliable method to accurately estimate SSL is a key topic for watershed managers, hydrologists, river engineers, and hydraulic engineers. One of the most common methods for estimating SSL or suspended sediment concentrations (SSC) is sediment rating curve (SRC), which has several weaknesses. Here, we optimize the SRC equation using two main approaches. Firstly, three well recognized metaheuristic algorithms (genetic algorithm (GA), particle swarm optimization (PSO), and imperialist competitive algorithm (ICA)) were used together with two classical approaches (food and agriculture organization (FAO) and non-parametric smearing estimator (CF2)) to optimize the coefficients of the SRC regression model. The second approach uses separation of data based on season and flow discharge (Qw) characteristics. A support vector regression (SVR) model using only Qw as an input was employed for SSC estimation and the results were compared with the SRC and its optimized versions. Metaheuristic algorithms improved the performance of the SRC model and the PSO model outperformed the other algorithms. These results also indicate that the model performance was directly related to the temporal separation of data. Based on these findings, if data are more homogenous and related to the limited climatic conditions used in the estimation of SSC, the estimations are improved. Moreover, it was observed that optimizing SRC through metaheuristic models was much more effective than separating data in the SCR model. The results also indicated that with the same input data, SVR was superior to the SRC model and its optimized version. Full article
Show Figures

Figure 1

Article
Sediment Yield and Reservoir Sedimentation in Highly Dynamic Watersheds: The Case of Koga Reservoir, Ethiopia
Water 2021, 13(23), 3374; https://doi.org/10.3390/w13233374 - 30 Nov 2021
Cited by 1 | Viewed by 931
Abstract
Soil erosion is exacerbated by unsustainable land-use activities and poor management practices, undermining reservoir storage capacity. To this effect, appropriate estimation of sediment would help to adopt sustainable land-use activities and best management practices that lead to efficient reservoir operations. This paper aims [...] Read more.
Soil erosion is exacerbated by unsustainable land-use activities and poor management practices, undermining reservoir storage capacity. To this effect, appropriate estimation of sediment would help to adopt sustainable land-use activities and best management practices that lead to efficient reservoir operations. This paper aims to investigate the spatial variability of sediment yield, amount of sediment delivery into the reservoir, and reservoir sedimentation in the Koga Reservoir using the Soil and Water Assessment Tool (SWAT). Sediment yield and the amount entered into the reservoir were also estimated using a rating curve, providing an alternative approach to spatially referenced SWAT generated suspended sediment load. SWAT was calibrated from 1991 to 2000 and validated from 2002 to 2007 using monthly observations. Model performance indicators showed acceptable values using Nash-Sutcliffe efficiency (NSE) correlation coefficient (R2), and percent bias (PBIAS) for flow (NSE = 0.75, R2 = 0.78, and PBIAS = 11.83%). There was also good agreement between measured and simulated sediment yields, with NSE, R2, and PBIAS validation values of 0.80, 0.79, and 6.4%, respectively. The measured rating curve and SWAT predictions showed comparable mean annual sediment values of 62,610.08 ton/yr and 58,012.87 ton/yr, respectively. This study provides an implication for the extent of management interventions required to meet sediment load targets to a receiving reservoir, providing a better understanding of catchment processes and responses to anthropogenic and natural stressors in mixed land use temperate climate catchments. Findings would benefit policymakers towards land and water management decisions and serve as a prototype for other catchments where management interventions may be implemented. Specifically, validating SWAT for the Koga Reservoir is a first step to support policymakers, who are faced with implementing land and water management decisions. Full article
Show Figures

Figure 1

Article
A Deterministic Topographic Wetland Index Based on LiDAR-Derived DEM for Delineating Open-Water Wetlands
Water 2021, 13(18), 2487; https://doi.org/10.3390/w13182487 - 10 Sep 2021
Cited by 4 | Viewed by 745
Abstract
Wetlands play a significant role in flood mitigation. Remote sensing technologies as an efficient and accurate approach have been widely applied to delineate wetlands. Supervised classification is conventionally applied for remote sensing technologies to improve the wetland delineation accuracy. However, performing supervised classification [...] Read more.
Wetlands play a significant role in flood mitigation. Remote sensing technologies as an efficient and accurate approach have been widely applied to delineate wetlands. Supervised classification is conventionally applied for remote sensing technologies to improve the wetland delineation accuracy. However, performing supervised classification requires preparing the training data, which is also considered time-consuming and prone to human mistakes. This paper presents a deterministic topographic wetland index to delineate wetland inundation areas without performing supervised classification. The classic methods such as Normalized Difference Vegetation Index, Normalized Difference Water Index, and Topographic Wetness Index were chosen to compare with the proposed deterministic topographic method on wetland delineation accuracy. The ground truth sample points validated by Google satellite imageries from four different years were used for the assessment of the delineation overall accuracy. The results show that the proposed deterministic topographic wetland index has the highest overall accuracy (98.90%) and Kappa coefficient (0.641) among the selected approaches in this study. The findings of this paper will provide an alternative approach for delineating wetlands rapidly by using solely the LiDAR-derived Digital Elevation Model. Full article
Show Figures

Figure 1

Article
Evaluation of Regional Climate Models (RCMs) Using Precipitation and Temperature-Based Climatic Indices: A Case Study of Florida, USA
Water 2021, 13(17), 2411; https://doi.org/10.3390/w13172411 - 02 Sep 2021
Viewed by 1052
Abstract
The overarching objective of this study was to evaluate the performance of nine precipitation-based and twelve temperature-based climatic indices derived from four regional climate models (CRCM5-UQUAM, CanRCM4, RCA4 and HIRHAM5) driven by three global circulation models (CanESM2, EC-EARTH and MPI-ESM-LR) and their ensemble [...] Read more.
The overarching objective of this study was to evaluate the performance of nine precipitation-based and twelve temperature-based climatic indices derived from four regional climate models (CRCM5-UQUAM, CanRCM4, RCA4 and HIRHAM5) driven by three global circulation models (CanESM2, EC-EARTH and MPI-ESM-LR) and their ensemble mean for the reference period of 31 years (1975–2005). The absolute biases, pattern correlation, the reduction of variance (RV) and the Standardized Precipitation Evapotranspiration Index (SPEI at 3-, 6- and 12-month aggregate periods) techniques were used to evaluate the climate model simulations. The result, in general, shows each climate model has a skill in reproducing at least one of the climatic indices considered in this study. Based on the pattern correlation result, however, EC-EARTH.HIRHAM5 and MPI-ESM-LR.CRCM5-UQAM RCMs showed a relatively good skill in reproducing the observed climatic indices as compared to the other climate model simulations. EC-EARTH.RCA4, CanESM2.RCA4 and MPI-ESM-LR.CRCM5-UQAM RCMs showed a good skill when evaluated using the reduction of variance. The ensemble mean of the RCMs showed relatively better skill in reproducing the observed temperature-based climatic indices as compared to the precipitation-based climatic indices. There were no exceptional differences observed among the performance of the climate models compared to the SPEI, but CanESM2.CRCM5-UQAM, EC-EARTH.RCA4 and the ensemble mean of the RCMs performed relatively good in comparison to the other climate models. The good performance of some of the RCMs has good implications for their potential application for climate change impact studies and future trend analysis of extreme events. They could help in developing an early warning system to mitigate and prepare for possible future impacts of climate extremes (e.g., drought) and vulnerability to climate change across Florida. Full article
Show Figures

Figure 1

Article
Event Based Post-Fire Hydrological Modeling of the Upper Arroyo Seco Watershed in Southern California
Water 2021, 13(16), 2303; https://doi.org/10.3390/w13162303 - 22 Aug 2021
Viewed by 1335
Abstract
Understanding, development and integration of pre-fire and post-fire watershed hydrological processes into a watershed hydrological model in a wild-fire repeating region similar to parts of California is critical for emergency assessments. 95% of the upper Arroyo Seco watershed located in Los Angeles County [...] Read more.
Understanding, development and integration of pre-fire and post-fire watershed hydrological processes into a watershed hydrological model in a wild-fire repeating region similar to parts of California is critical for emergency assessments. 95% of the upper Arroyo Seco watershed located in Los Angeles County in southern California was burned by the Station fire that occurred in August 2009, significantly increasing the watershed observed runoff. This watershed was employed to develop the January 2008 rainfall runoff model as a pre-fire event-based watershed hydrological model. This pre-fire watershed model was subsequently employed in the rainfall events of 18 January 2010 and 27 February 2010, a few months after the fire event of August 2009. The pre-fire watershed model when employed in the post-fire rainfall events without considering the fire effects vastly underestimated the simulated discharge. For this reason, in this study of the post-fire catchment runoff modeling the following points are taken into consideration: (a) a realistic distributed initial soil moisture condition; (b) a formulation that includes a reduction factor and a burn severity factor, as multiplying factors to soil hydraulic conductivity in the soil characteristic curve; and (c) runoff routing parameterization under burned conditions. Developing the post-fire Arroyo Seco watershed model by using the above-mentioned points enhanced the Nash–Sutcliffe Efficiency from −24% to 82% for the 18 January 2010 rainfall event and from −47% to 96% for the 27 February 2010 rainfall event. Full article
Show Figures

Figure 1

Article
Experimental Analysis of Incipient Motion for Uniform and Graded Sediments
Water 2021, 13(13), 1874; https://doi.org/10.3390/w13131874 - 05 Jul 2021
Viewed by 1160
Abstract
So far, few studies have focused on the concept of critical flow velocity rather than bed shear stress for incipient sediment motion. Moreover, few studies have focused on sediment mixtures (graded sediment) and shape rather than uniform sediment for incipient motion condition. Different [...] Read more.
So far, few studies have focused on the concept of critical flow velocity rather than bed shear stress for incipient sediment motion. Moreover, few studies have focused on sediment mixtures (graded sediment) and shape rather than uniform sediment for incipient motion condition. Different experiments were conducted at a hydraulic laboratory at the University of Guilan in 2015 to determine hydraulic parameters on the incipient motion condition. The aim of this study is to conduct a comparison between uniform and graded sediments, and a comparison between round and angular sediments. Experiments included rounded uniform bed sediments of 5.17, 10.35, 14 and 20.7 mm, angular uniform sediment of 10.35 mm, and graded sediment. Results demonstrated that angular sediment has a higher critical shear velocity than rounded sediment for incipient motion. Results also showed that for a given bed sediment, although critical shield stress and relative roughness increased with the bed slope, the particle Froude number (based on critical velocity) decreased. In terms of the sediment mixture, the critical shear stress (Vc*) was higher for the graded sediment than for the three finer uniform sediment sizes. The finer fractions of the mixture have a higher particle Froude number than their corresponding uniform sediment value, while the coarser fractions of the mixture showed a lower stability than their corresponding uniform sediment value. Results demonstrated that the reduction in the particle Froude number was more evident in lower relative roughness conditions. The current study provides a clearer insight into the interaction between initial sediment transport and flow characteristic, especially particle Froude number for incipient motion in natural rivers where stream beds have different gravel size distribution. Full article
Show Figures

Figure 1

Back to TopTop