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) | Viewed by 57957

Special Issue Editors


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Guest Editor
1. School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73019-3072, USA
2. National Weather Center, ARRC Suite 4610, University of Oklahoma, 120 David L. Boren Blvd, Norman, OK 73072, USA
Interests: radar and satellite remote sensing; hydrology and water security; water resource engineering and GIS
Special Issues, Collections and Topics in MDPI journals
Civil and Environmental Engineering, University of Connecticut, 159 Discovery Dr., Storrs, CT 06269, USA
Interests: flood inundation modeling and observatory; Humans, Disasters, and the Built Environment; microwave remote sensing; artificial intelligence; compound flooding
Special Issues, Collections and Topics in MDPI journals

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Co-Guest Editor
Peking University
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

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Keywords

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

Published Papers (11 papers)

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Research

13 pages, 6821 KiB  
Article
Estimation of Urbanization Impacts on Local Weather: A Case Study in Northern China (Jing-Jin-Ji District)
by Hui-Dong Su, Xuejian Cao, Da-Cheng Wang, Yang-Wen Jia, Guangheng Ni, Junhua Wang, Mingxi Zhang and Cunwen Niu
Water 2019, 11(4), 797; https://doi.org/10.3390/w11040797 - 17 Apr 2019
Cited by 9 | Viewed by 2574
Abstract
With the past rapid economic development and large population growth, Jing-Jin-Ji District has been undergoing rapid urbanization, which has caused considerable regional weather changes in local regions. In this paper, we used the Weather Research and Forecasting (WRF) model to quantitatively analyze the [...] Read more.
With the past rapid economic development and large population growth, Jing-Jin-Ji District has been undergoing rapid urbanization, which has caused considerable regional weather changes in local regions. In this paper, we used the Weather Research and Forecasting (WRF) model to quantitatively analyze the effects of past urbanization and potential future urbanization on the regional weather in the center of Jing-Jin-Ji District. The hydrometeorological data from two weeks in July 2019 were used to simulate the influence of urbanization on local weather in the Jing-Jin-Ji District at regional scales using a single-layer canopy parameterization scheme. To better quantify the differences in temperature and precipitation induced by urbanization, three simulation scenarios were designed, which were no urban cover (NU), current urbanization cover (CU), and full urban land cover (FU), respectively. The results showed that: (1) Urbanization progress (from NU to CU and from CU to FU) in Jing-Jin-Ji District increased the daytime temperature, night temperature, and temperature difference between day and night, while decreasing the total rainfall and peak rainfall. (2) Compared with NU, the mean temperature of the CU and FU increased 0.3 K and 0.6 K, respectively, and the mean precipitation of CU and FU decreased by approximately 6% and 8.4%, respectively. (3) The main influence of urbanization on weather was reflected by the maximum temperature and peak rainfall, while the other impacts were relatively insignificant. (4) Compared with NU, the maximum temperature of CU and FU increased 0.82 K and 1.35 K, respectively, and the peak rainfall of NU and FU decreased by approximately 9.5% and 19.0%, respectively; The results of this study bring to light the urban management strategies for policy makers. Full article
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16 pages, 3752 KiB  
Article
Update of Early Warning Indicators of Flash Floods: A Case Study of Hunjiang District, Northeastern China
by Meihong Ma, Jingnan Zhang, Huidong Su, Dacheng Wang and Zhongliang Wang
Water 2019, 11(2), 314; https://doi.org/10.3390/w11020314 - 12 Feb 2019
Cited by 7 | Viewed by 3651
Abstract
The China flash flood investigation and evaluation database (CFFIED) covers important information needed for China’s flash flood warning. This paper uses a statistical induction method, inference formula method and standardized unit hydrograph method to explore its principle, characteristics, and key steps. Then based [...] Read more.
The China flash flood investigation and evaluation database (CFFIED) covers important information needed for China’s flash flood warning. This paper uses a statistical induction method, inference formula method and standardized unit hydrograph method to explore its principle, characteristics, and key steps. Then based on the field investigation and the latest data on the flash flood, the Hunjiang District in northeastern China was selected as the research area. Firstly, three typical riverside villages, Xiangmo-1 and Sanchahe-3, Shangqing-4, were screened, and the flash flood warning indicators (e.g., water level, flow rate, critical rainfall) in the CFFIED were updated. Then, the maximum error of the flood peak, estimated by the inference formula method and the water level flow relationship method, is only 10.6%, which indicates that the predicted flood peak flow has high credibility and can check and identify the early warning index; the Manning formula is more accurate in calculating the water level flow relationship. However, the calculated ratio is lower and the roughness is higher, and the flow is smaller under the same water level. Finally, the updated flash flood warning indicators were obtained in the Hunjiang District, which improves the accuracy of the flash flood warning, and provides a reference for updating the early warning indicators in other areas. Full article
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21 pages, 13369 KiB  
Article
A Numerical Framework for Evaluating Flood Inundation Hazard under Different Dam Operation Scenarios—A Case Study in Naugatuck River
by Sage Hardesty, Xinyi Shen, Efthymios Nikolopoulos and Emmanouil Anagnostou
Water 2018, 10(12), 1798; https://doi.org/10.3390/w10121798 - 07 Dec 2018
Cited by 16 | Viewed by 3870
Abstract
Worldwide, many river floodplains contain critical infrastructure that is vulnerable to extreme hydrologic events. These structures are designed based on flood frequency analysis aimed at quantifying the magnitude and recurrence of the extreme events. This research topic focuses on estimating flood vulnerability at [...] Read more.
Worldwide, many river floodplains contain critical infrastructure that is vulnerable to extreme hydrologic events. These structures are designed based on flood frequency analysis aimed at quantifying the magnitude and recurrence of the extreme events. This research topic focuses on estimating flood vulnerability at ungauged locations based on an integrative framework consisting of a distributed rainfall–runoff model forced with long-term (37 years) reanalysis meteorological data and a hydraulic model driven by high-resolution airborne LiDAR-derived terrain elevation data. The framework is applied to a critical power infrastructure located within Connecticut’s Naugatuck River Basin. The hydrologic model reanalysis is used to derive 50-, 100-, 200-, and 500-year return period flood peaks, which are then used to drive Hydrologic Engineering Center’s River Analysis System (HEC-RAS) hydraulic simulations to estimate the inundation risk at the infrastructure location under different operation strategies of an upstream reservoir. This study illustrates the framework’s potential for creating flood maps at ungauged locations and demonstrates the effects of different water management scenarios on the flood risk of the downstream infrastructure. Full article
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12 pages, 3593 KiB  
Article
Characterizing the Flash Flooding Risks from 2011 to 2016 over China
by Meihong Ma, Bingshun He, Jinhong Wan, Pengfei Jia, Xirong Guo, Liang Gao, Lane W. Maguire and Yang Hong
Water 2018, 10(6), 704; https://doi.org/10.3390/w10060704 - 30 May 2018
Cited by 22 | Viewed by 4329
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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17 pages, 7194 KiB  
Article
Effects of Land Cover Change on Urban Floods and Rainwater Harvesting: A Case Study in Sharjah, UAE
by Abdallah Shanableh, Rami Al-Ruzouq, Abdullah Gokhan Yilmaz, Mohsin Siddique, Tarek Merabtene and Monzur Alam Imteaz
Water 2018, 10(5), 631; https://doi.org/10.3390/w10050631 - 13 May 2018
Cited by 52 | Viewed by 6685
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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16 pages, 9703 KiB  
Article
An Ecological Land Cover Sampling Reclassification Model for Safety Estimation of Shoreline Systems from a Flood Defense Perspective Using Optical Satellite Remote Sensing Imaging
by Dongju Wu and Hui Xu
Water 2018, 10(3), 285; https://doi.org/10.3390/w10030285 - 08 Mar 2018
Cited by 1 | Viewed by 3049
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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16 pages, 17477 KiB  
Article
Extracting Farmland Features from Lidar-Derived DEM for Improving Flood Plain Delineation
by Tianlu Qian, Dingtao Shen, Changbai Xi, Jie Chen and Jiechen Wang
Water 2018, 10(3), 252; https://doi.org/10.3390/w10030252 - 01 Mar 2018
Cited by 9 | Viewed by 3339
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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13 pages, 4141 KiB  
Article
Application of Flood Nomograph for Flood Forecasting in Urban Areas
by Eui Hoon Lee, Joong Hoon Kim, Yeon Moon Choo and Deok Jun Jo
Water 2018, 10(1), 53; https://doi.org/10.3390/w10010053 - 10 Jan 2018
Cited by 17 | Viewed by 5792
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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6203 KiB  
Article
Hydrologic Evaluation of Six High Resolution Satellite Precipitation Products in Capturing Extreme Precipitation and Streamflow over a Medium-Sized Basin in China
by Shanhu Jiang, Shuya Liu, Liliang Ren, Bin Yong, Linqi Zhang, Menghao Wang, Yujie Lu and Yingqing He
Water 2018, 10(1), 25; https://doi.org/10.3390/w10010025 - 29 Dec 2017
Cited by 38 | Viewed by 5288
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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8060 KiB  
Article
Building Blocks: A Quantitative Approach for Evaluating Coastal Vulnerability
by Komali Kantamaneni, Xiaoping Du, Sainath Aher and Rao Martand Singh
Water 2017, 9(12), 905; https://doi.org/10.3390/w9120905 - 25 Nov 2017
Cited by 26 | Viewed by 8569
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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17212 KiB  
Article
Building a High-Precision 2D Hydrodynamic Flood Model Using UAV Photogrammetry and Sensor Network Monitoring
by Jakub Langhammer, Jana Bernsteinová and Jakub Miřijovský
Water 2017, 9(11), 861; https://doi.org/10.3390/w9110861 - 06 Nov 2017
Cited by 36 | Viewed by 9656
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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