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Special Issue "Assessment of Current and Future Vulnerability of Flooding with Hydrologic/Hydraulic Modeling and Remote Sensing Techniques"

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

Deadline for manuscript submissions: closed (31 March 2018)

Special Issue Editors

Guest Editor
Prof. Yang Hong

School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK 73019, USA
Website | E-Mail
Interests: radar/satellite remote sensing of water cycle (precipitation, evapotranspiration, soil moisture, streamflow); hydrology and water resources; hydrometeorology; hydroclimatology
Guest Editor
Dr. Xinyi Shen

University of Connecticut
Website | E-Mail
Phone: 860-486-1799
Interests: hydrology; remote sensing; flood; soil moisture; numerical modelling
Co-Guest Editor
Dr. Yaokui Cui

Peking University
E-Mail
Phone: +86-010-62751961
Interests: remote sensing; water cycle; big data; evapotranspiration; soil moisture

Special Issue Information

Dear Colleagues

Flooding hazards cause numerous economic and life losses in the present changing climate and environment. It is, therefore, important to keep developing and improving our knowledge in the field of flood vulnerability assessment and hazard alleviation. Multiple disciplines, including hydrology, hydraulics, remote sensing, and meteorology, are collaborating to assess the magnitude and impact of flood hazards. Moreover, with the increasing capacity of numerical modelling, machine learning, data archives, our ability to monitor, predict and understand the risks are growing rapidly.

Due to recent flood events, this Special Issue of Water addresses flooding in a timely manner, in particular, it seeks to highlight interdisciplinary approaches to address the complexity of flood vulnerability assessment in this changing climate and environment, including topics, such as:

  • Novel calibration/validation methods for numerical flood-inundation modelling;
  • Applying machine learning techniques/big data to flood risk/characteristic assessment;
  • New methods/data in obtaining river bathymetry;
  • Review of numerical flood simulation/prediction/design methods;
  • Flood-inundation applications using high-resolution remote sensing/GIS techniques/data/products;
  • Assessment of flood caused socioeconomic impact and hazard reduction;
  • Flood impact on sustainability of critical infrastructure, energy, food security and nexus;
  • Flood frequency/characteristics/analysis in changing climate, environment/urbanization;
  • Flood threats in changing estuaries, coasts and sea level.
Prof. Yang Hong
Dr. Xinyi Shen
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 papers will be 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 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 1500 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

  • Flood
  • Inundation
  • Hydrology
  • Remote Sensing
  • Machine Learning
  • Natural Hazard
  • Resilience and Sustainability
  • Climate Change
  • Sea Level Rise
  • Surge

Published Papers (8 papers)

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Research

Open AccessArticle Characterizing the Flash Flooding Risks from 2011 to 2016 over China
Water 2018, 10(6), 704; https://doi.org/10.3390/w10060704
Received: 23 March 2018 / Revised: 11 May 2018 / Accepted: 18 May 2018 / Published: 30 May 2018
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Abstract
Flash floods induced by heavy rainfall occur frequently in China, which cause severe damages or even casualties every year. Flash floods generally occur in small catchments, and therefore were poorly documented. A Database including 963 flash flood events in China is compiled and
[...] Read more.
Flash floods induced by heavy rainfall occur frequently in China, which cause severe damages or even casualties every year. Flash floods generally occur in small catchments, and therefore were poorly documented. A Database including 963 flash flood events in China is compiled and studied in this study. Analytical results (a) indicate flash flood condition in China; (b) shed light on the spatial-temporal distribution of flash flood under heavy rainfall and (c) detect the characteristics of the 2016 flash flood. In 2016, the deaths due to flash floods were severe and concentrated, accounting for about half of the elderly and children. Hebei and Fujian provinces were most affected by flash floods. The disasters mainly occurred in July and the major types were river floods. Despite the frequent torrential rains, inadequate monitoring and early warning systems made the flash flooding condition even worse in 2016. Full article
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Open AccessArticle Effects of Land Cover Change on Urban Floods and Rainwater Harvesting: A Case Study in Sharjah, UAE
Water 2018, 10(5), 631; https://doi.org/10.3390/w10050631
Received: 9 March 2018 / Revised: 28 April 2018 / Accepted: 10 May 2018 / Published: 13 May 2018
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Abstract
In this study, multi-temporal satellite images combined with rainfall data and field observations were used to assess the spatial and temporal changes in urban flooding and urban water harvesting potential in the coastal city of Sharjah, United Arab Emirates (UAE) during the period
[...] Read more.
In this study, multi-temporal satellite images combined with rainfall data and field observations were used to assess the spatial and temporal changes in urban flooding and urban water harvesting potential in the coastal city of Sharjah, United Arab Emirates (UAE) during the period from 1976 to 2016. During the study period, the population increased by approximately 14-fold with about a 4-fold increase in built areas. Being in a hot, dry region with average rainfall of about 100 mm/year, the city did not invest in a comprehensive drainage infrastructure. As a result, the frequency, extent and risk associated with urban floods increased significantly. The expansion of built areas progressively increased the impervious land cover in the city, decreasing the minimum precipitation required to generate runoff by approximately 32% and significantly increasing the runoff coefficient. In parallel to rapid urbanization, the urban rainwater harvesting potential significantly increased over 1976–2016. Urban flood maps were generated using three thematic factors: excess rain, land elevation and land slope. The flood maps were confirmed by locating urban flood locations in the field using GPS. This study demonstrates the impact of urbanization through assessing the relationship between urbanization, runoff, local floods and rainwater harvesting potential in Sharjah and provides a basis for developing sustainable urban storm water management practices for the city and similar cities. Full article
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Open AccessArticle An Ecological Land Cover Sampling Reclassification Model for Safety Estimation of Shoreline Systems from a Flood Defense Perspective Using Optical Satellite Remote Sensing Imaging
Water 2018, 10(3), 285; https://doi.org/10.3390/w10030285
Received: 12 November 2017 / Revised: 28 February 2018 / Accepted: 6 March 2018 / Published: 8 March 2018
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Abstract
The safety level of a shoreline is essential for flood control projects and policy formulation or modification from both economic and environmental perspectives. With the development of remote sensing (RS) techniques, high spatial-spectral resolution and quick-revolution satellite images are now available and widely
[...] Read more.
The safety level of a shoreline is essential for flood control projects and policy formulation or modification from both economic and environmental perspectives. With the development of remote sensing (RS) techniques, high spatial-spectral resolution and quick-revolution satellite images are now available and widely used in environment monitoring and management. It is therefore possible to more efficiently and conveniently identify the components of, and extract information for, shoreline environments. However, the problem is that the shoreline is always a long curve with a relatively narrow width, which limits the application of RS technology. This paper presents a method of recognizing different types of shoreline and of conveniently extracting the geographical coordinates of potential shoreline defense by analyzing and processing ecological information from an optical satellite RS data interpretation of land cover on both side of the shoreline. An application of this model in a low-resolution image case proved that the model can be used in the primary survey of a shoreline monitoring service platform as the basic tile level. The classification model is designed such that the requirements of image resolution for efficiently extracting information from the shoreline are low and the limitations imposed by a narrow shoreline width are avoided. Full article
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Open AccessArticle Extracting Farmland Features from Lidar-Derived DEM for Improving Flood Plain Delineation
Water 2018, 10(3), 252; https://doi.org/10.3390/w10030252
Received: 6 December 2017 / Revised: 16 February 2018 / Accepted: 22 February 2018 / Published: 1 March 2018
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Abstract
Flood plains, which are commonly distributed in flat river or lake basins, often contain large tracts of farmland. Therefore, flood plains require precise and detailed information on the role played by farmland in flood routing simulations, flood risk evaluation, and flood loss evaluation.
[...] Read more.
Flood plains, which are commonly distributed in flat river or lake basins, often contain large tracts of farmland. Therefore, flood plains require precise and detailed information on the role played by farmland in flood routing simulations, flood risk evaluation, and flood loss evaluation. In farmland, cultivated land parcels are not directly adjacent. The intervening non-cultivable land, which might include trails and ditches, can cover large areas. Currently, the area of non-cultivable land between cultivated land parcels is usually measured by artificial visual interpretation or by fieldwork. This study focused on the extraction of uncultivable trails, ditches, and cultivated field parcels within farmland on the basis of a Light Detection and Ranging-derived (LiDAR-derived) high-resolution gridded Digital Elevation Model (DEM). The proposed approach was applied to generate polygons of individual land parcels in a flood storage and detention area. The DEM was first smoothed and then subtracted. To remove small spots and to smooth the boundaries of the land parcels, inner and outer buffers were created to generalize the extracted polygons. Experiments proved that this approach is applicable in flood plain farmland and demonstrated that the chosen parameters were appropriate. This approach is more efficient than traditional surveying methods. For field parcel extraction, the accuracy achieved was 93.42%, using official statistics for comparison, and the Cohen’s kappa coefficient was 0.90, using a visual interpretation of an aerial image for comparison. The kappa coefficients were 0.87 and 0.77 for trail and ditch extraction, respectively. Full article
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Open AccessArticle Application of Flood Nomograph for Flood Forecasting in Urban Areas
Water 2018, 10(1), 53; https://doi.org/10.3390/w10010053
Received: 28 November 2017 / Revised: 22 December 2017 / Accepted: 8 January 2018 / Published: 10 January 2018
Cited by 1 | PDF Full-text (4141 KB) | HTML Full-text | XML Full-text
Abstract
Imperviousness has increased due to urbanization, as has the frequency of extreme rainfall events by climate change. Various countermeasures, such as structural and nonstructural measures, are required to prepare for these effects. Flood forecasting is a representative nonstructural measure. Flood forecasting techniques have
[...] Read more.
Imperviousness has increased due to urbanization, as has the frequency of extreme rainfall events by climate change. Various countermeasures, such as structural and nonstructural measures, are required to prepare for these effects. Flood forecasting is a representative nonstructural measure. Flood forecasting techniques have been developed for the prevention of repetitive flood damage in urban areas. It is difficult to apply some flood forecasting techniques using training processes because training needs to be applied at every usage. The other flood forecasting techniques that use rainfall data predicted by radar are not appropriate for small areas, such as single drainage basins. In this study, a new flood forecasting technique is suggested to reduce flood damage in urban areas. The flood nomograph consists of the first flooding nodes in rainfall runoff simulations with synthetic rainfall data at each duration. When selecting the first flooding node, the initial amount of synthetic rainfall is 1 mm, which increases in 1 mm increments until flooding occurs. The advantage of this flood forecasting technique is its simple application using real-time rainfall data. This technique can be used to prepare a preemptive response in the process of urban flood management. Full article
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Open AccessArticle Hydrologic Evaluation of Six High Resolution Satellite Precipitation Products in Capturing Extreme Precipitation and Streamflow over a Medium-Sized Basin in China
Water 2018, 10(1), 25; https://doi.org/10.3390/w10010025
Received: 22 November 2017 / Revised: 20 December 2017 / Accepted: 25 December 2017 / Published: 29 December 2017
Cited by 2 | PDF Full-text (6203 KB) | HTML Full-text | XML Full-text
Abstract
Satellite precipitation products (SPPs) are critical data sources for hydrological prediction and extreme event monitoring, especially for ungauged basins. This study conducted a comprehensive hydrological evaluation of six mainstream SPPs (i.e., TMPA 3B42RT, CMORPH-RT, PERSIANN-RT, TMPA 3B42V7, CMORPH-CRT, and PERSIANN-CDR) over humid Xixian
[...] Read more.
Satellite precipitation products (SPPs) are critical data sources for hydrological prediction and extreme event monitoring, especially for ungauged basins. This study conducted a comprehensive hydrological evaluation of six mainstream SPPs (i.e., TMPA 3B42RT, CMORPH-RT, PERSIANN-RT, TMPA 3B42V7, CMORPH-CRT, and PERSIANN-CDR) over humid Xixian basin in central eastern China for a period of 14 years (2000–2013). The evaluation specifically focused on the performance of the six SSPs in capturing precipitation and streamflow extremes. Results show that the two post-real-time research products of TMPA 3B42V7 and CMORPH-CRT exhibit much better performance than that of their corresponding real-time SPPs for precipitation estimation at daily and monthly time scales. By contrast, the newly released post-real-time research product PERSIANN-CDR insignificantly improves precipitation estimates compared with the real-time PERSIANN-RT does at daily time scale. The daily streamflow simulation of TMPA 3B42V7 fits best with the observed streamflow series among those of the six SPPs. The three month-to-month gauge-adjusted post-real-time research products can simulate acceptable monthly runoff series. TMPA 3B42V7 and CMORPH-CRT present good performance in capturing precipitation and streamflow extremes, although they still exhibit non-ignorable deviation and occurrence time inconsistency problems compared with gauge-based results. Caution should be observed when using the current TMPA, CMORPH, and PERSIANN products for monitoring and predicting extreme precipitation and flood at such medium-sized basin. This work will be valuable for the utilization of SPPs in extreme precipitation monitoring, streamflow forecasting, and water resource management in other regions with similar climate and topography characteristics. Full article
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Open AccessArticle Building Blocks: A Quantitative Approach for Evaluating Coastal Vulnerability
Water 2017, 9(12), 905; https://doi.org/10.3390/w9120905
Received: 23 August 2017 / Revised: 28 October 2017 / Accepted: 6 November 2017 / Published: 25 November 2017
Cited by 2 | PDF Full-text (8060 KB) | HTML Full-text | XML Full-text
Abstract
Climate change and associated factors such as global and regional sea-level rise; the upsurge in high-intensity flooding events; and coastal erosion are pulse and press disturbances that threaten to increase landslides in coastal regions. Under these circumstances; a rigorous framework is required to
[...] Read more.
Climate change and associated factors such as global and regional sea-level rise; the upsurge in high-intensity flooding events; and coastal erosion are pulse and press disturbances that threaten to increase landslides in coastal regions. Under these circumstances; a rigorous framework is required to evaluate coastal vulnerability in order to plan for future climate change scenarios. A vast majority of coastal vulnerability assessments across the globe are evaluated at the macro level (city scale) but not at the micro level (small town scale); particularly in the United Kingdom (UK). In order to fill this vital research gap; the current study established a coastal vulnerability index termed here as the Micro Town Coastal Vulnerability Index (MTCVI) and then applied it to Barton-on-Sea; which is a small coastal town of the Hampshire region; England; UK. MTCVI was evaluated for Barton-on-Sea coastal vulnerability by integrating both novel and existing parameters. Results suggest that the entire shoreline frontage (2 km) exhibits very high coastal vulnerability and is prone to various coastal hazards such as landslides; erosion; and wave intrusion. This suggests that Barton-on-Sea coastal amenities will require a substantial improvement in shoreline protection measures. In this study; GIS (geographic information system) coastal vulnerability and landslide maps were generated; and these maps can be used by the local authorities; district councils; coastal engineers; and planners to improve and design coastal management strategies under the climate change scenarios. Meanwhile; the methodology used in this study could also be applied to any other suitable location in the world depending on the availability of the data. Full article
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Open AccessArticle Building a High-Precision 2D Hydrodynamic Flood Model Using UAV Photogrammetry and Sensor Network Monitoring
Water 2017, 9(11), 861; https://doi.org/10.3390/w9110861
Received: 14 September 2017 / Revised: 23 October 2017 / Accepted: 4 November 2017 / Published: 6 November 2017
Cited by 3 | PDF Full-text (17212 KB) | HTML Full-text | XML Full-text
Abstract
This paper explores the potential of the joint application of unmanned aerial vehicle (UAV)-based photogrammetry and an automated sensor network for building a hydrodynamic flood model of a montane stream. UAV-based imagery was used for three-dimensional (3D) photogrammetric reconstruction of the stream channel,
[...] Read more.
This paper explores the potential of the joint application of unmanned aerial vehicle (UAV)-based photogrammetry and an automated sensor network for building a hydrodynamic flood model of a montane stream. UAV-based imagery was used for three-dimensional (3D) photogrammetric reconstruction of the stream channel, achieving a resolution of 1.5 cm/pixel. Automated ultrasonic water level gauges, operating with a 10 min interval, were used as a source of hydrological data for the model calibration, and the MIKE 21 hydrodynamic model was used for building the flood model. Three different horizontal schematizations of the channel—an orthogonal grid, curvilinear grid, and flexible mesh—were used to evaluate the effect of spatial discretization on the results. The research was performed on Javori Brook, a montane stream in the Sumava (Bohemian Forest) Mountains, Czech Republic, Central Europe, featuring a fast runoff response to precipitation events and that is located in a core zone of frequent flooding. The studied catchments have been, since 2007, equipped with automated water level gauges and, since 2013, under repeated UAV monitoring. The study revealed the high potential of these data sources for applications in hydrodynamic modeling. In addition to the ultra-high levels of spatial and temporal resolution, the major contribution is in the method’s high operability, enabling the building of highly detailed flood models even in remote areas lacking conventional monitoring. The testing of the data sources and model setup indicated the limitations of the UAV reconstruction of the stream bathymetry, which was completed by the geodetic-grade global navigation satellite system (GNSS) measurements. The testing of the different model domain schematizations did not indicate the substantial differences that are typical for conventional low-resolution data, proving the high reliability of the tested modeling workflow. Full article
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