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Hydrology
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Flood Inundation Mapping in Hydrological Systems
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Flood Inundation Mapping in Hydrological Systems

A special issue of Hydrology (ISSN 2306-5338). This special issue belongs to the section "Surface Waters and Groundwaters".

Deadline for manuscript submissions: closed (15 November 2023) | Viewed by 12746

Special Issue Editors

Dr. Robert Szczepanek

E-Mail Website
Guest Editor
Faculty of Geography and Geology, Jagiellonian University, Cracow, Poland
Interests: hydroinformatics; data science; GIS; flood marks; machine learning
Prof. Dr. Ibrahim Demir

E-Mail Website
Guest Editor
Civil and Environmental Engineering, University of Iowa, Iowa City, IA, USA
Interests: hydroinformatics; intelligent systems; scientific computing; scientific visualization; data analytics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Flood inundation mapping in hydrological systems has many purposes. Scientists use the collected data to verify hydrological models and provide decision makers and residents with valuable information about potential threats. Traditional flood information gathering methods rely on manuscripts, oral testimony, surveys, and flood marks. Due to technological advances, remote sensing methods are increasingly used. Initially, the sensors were mounted on airplanes and satellites, but recently, unmanned aerial vehicles (UAVs) and surveillance cameras have become more and more popular. Social media is a source of information about natural disasters with great potential. Information about floods is made available almost in real time in the form of photos, videos, or tweets.

This diversity of data types and large amounts of data are successfully used by machine learning systems to generalize and synthesize information related to natural hazards. For these reasons, flood mapping has become an interdisciplinary issue.

This Special Issue aims to collect papers covering a wide range of the methods and techniques of flood inundation mapping, from traditional to the most advanced:

  • Traditional flood mapping methods;
  • Data-driven flood map generation (e.g., HAND, machine learning);
  • Crowdsourced data collection;
  • Mobile applications (e.g., virtual gauges);
  • Satellite remote sensing (e.g., SAR);
  • Drones (UAV) in flood mapping;
  • Implementation of machine learning.

Dr. Robert Szczepanek
Prof. Dr. Ibrahim Demir
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. Hydrology 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 1800 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 mapping
  • remote sensing
  • satellites in flood mapping
  • drones (UAV) in flood mapping
  • crowdsourced data
  • mobile applications and social media
  • flood marks
  • machine learning

Published Papers (7 papers)

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Research

18 pages, 8338 KiB  
Article
Mountain Streambed Roughness and Flood Extent Estimation from Imagery Using the Segment Anything Model (SAM)
by Beata Baziak, Marek Bodziony and Robert Szczepanek
Hydrology 2024, 11(2), 17; https://doi.org/10.3390/hydrology11020017 - 31 Jan 2024
Viewed by 1544
Abstract
Machine learning models facilitate the search for non-linear relationships when modeling hydrological processes, but they are equally effective for automation at the data preparation stage. The tasks for which automation was analyzed consisted of estimating changes in the roughness coefficient of a mountain [...] Read more.
Machine learning models facilitate the search for non-linear relationships when modeling hydrological processes, but they are equally effective for automation at the data preparation stage. The tasks for which automation was analyzed consisted of estimating changes in the roughness coefficient of a mountain streambed and the extent of floods from images. The Segment Anything Model (SAM) developed in 2023 by Meta was used for this purpose. Images from many years from the Wielka Puszcza mountain stream located in the Polish Carpathians were used as the only input data. The model was not additionally trained for the described tasks. The SAM can be run in several modes, but the two most appropriate were used in this study. The first one is available in the form of a web application, while the second one is available in the form of a Jupyter notebook run in the Google Colab environment. Both methods do not require specialized knowledge and can be used by virtually any hydrologist. In the roughness estimation task, the average Intersection over Union (IoU) ranges from 0.55 for grass to 0.82 for shrubs/trees. Ultimately, it was possible to estimate the roughness coefficient of the mountain streambed between 0.027 and 0.059 based solely on image data. In the task of estimation of the flood extent, when selecting appropriate images, one can expect IoU at the level of at least 0.94, which seems to be an excellent result considering that the SAM is a general-purpose segmentation model. It can therefore be concluded that the SAM can be a useful tool for a hydrologist. Full article
(This article belongs to the Special Issue Flood Inundation Mapping in Hydrological Systems)
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21 pages, 11627 KiB  
Article
Flood Perception from Local Perspective of Rural Community vs. Geomorphological Control of Fluvial Processes in Large Alluvial Valley (the Middle Vistula River, Poland)
by Daria Wiesława Krasiewicz and Grzegorz Wierzbicki
Hydrology 2023, 10(10), 191; https://doi.org/10.3390/hydrology10100191 - 26 Sep 2023
Cited by 1 | Viewed by 1607
Abstract
The origin and dynamics of a 2010 pluvial flood in the valley of a large European river are described. In order to study how local people perceive this catastrophic event a small administrative unit (rural municipality) within the Holocene floodplain (thus flooded to [...] Read more.
The origin and dynamics of a 2010 pluvial flood in the valley of a large European river are described. In order to study how local people perceive this catastrophic event a small administrative unit (rural municipality) within the Holocene floodplain (thus flooded to 90%) was chosen. Using a questionnaire a human-research survey was performed in the field among 287 people living in flood-prone areas. Almost half of the interviewees feel safe and do not expect a flood recurrence (interpreted as a levee effect). Seventeen percent believe the levee was intentionally breached due to political issues. Six percent of interviewees link the breach with small mammals using levees as a habitat, e.g., beavers, moles, and foxes. The sex and age of interviewees are related to these opinions. Most interviewees (39%) think that flooding was a result of embankment (dyke) instability. The spatial distribution of the survey results are analyzed. Maps presenting: inundation height, economic loss, attitude to geohazards and perception of possible flood recurrence were drawn. Causes of the flood as viewed by local inhabitants and in the context of the riverine geological setting and its processes are discussed. Particular attention is paid to processes linking the levee breach location with specific geomorphic features of the Holocene floodplain. A wide perspective of fluvial geomorphology where erosive landforms of crevasse channels (and associated depositional crevasse splays) are indicators of geohazards was adopted. This distinct geomorphological imprint left by overbank flow is considered a natural flood mark. Such an approach is completely neglected by interviewees who overestimate the role of hydrotechnical structures. Full article
(This article belongs to the Special Issue Flood Inundation Mapping in Hydrological Systems)
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24 pages, 10756 KiB  
Article
Flood Inundation and Depth Mapping Using Unmanned Aerial Vehicles Combined with High-Resolution Multispectral Imagery
by Kevin J. Wienhold, Dongfeng Li, Wenzhao Li and Zheng N. Fang
Hydrology 2023, 10(8), 158; https://doi.org/10.3390/hydrology10080158 - 28 Jul 2023
Viewed by 1919
Abstract
The identification of flood hazards during emerging public safety crises such as hurricanes or flash floods is an invaluable tool for first responders and managers yet remains out of reach in any comprehensive sense when using traditional remote-sensing methods, due to cloud cover [...] Read more.
The identification of flood hazards during emerging public safety crises such as hurricanes or flash floods is an invaluable tool for first responders and managers yet remains out of reach in any comprehensive sense when using traditional remote-sensing methods, due to cloud cover and other data-sourcing restrictions. While many remote-sensing techniques exist for floodwater identification and extraction, few studies demonstrate an up-to-day understanding with better techniques in isolating the spectral properties of floodwaters from collected data, which vary for each event. This study introduces a novel method for delineating near-real-time inundation flood extent and depth mapping for storm events, using an inexpensive unmanned aerial vehicle (UAV)-based multispectral remote-sensing platform, which was designed to be applicable for urban environments, under a wide range of atmospheric conditions. The methodology is demonstrated using an actual flooding-event—Hurricane Zeta during the 2020 Atlantic hurricane season. Referred to as the UAV and Floodwater Inundation and Depth Mapper (FIDM), the methodology consists of three major components, including aerial data collection, processing, and flood inundation (water surface extent) and depth mapping. The model results for inundation and depth were compared to a validation dataset and ground-truthing data, respectively. The results suggest that UAV-FIDM is able to predict inundation with a total error (sum of omission and commission errors) of 15.8% and produce flooding depth estimates that are accurate enough to be actionable to determine road closures for a real event. Full article
(This article belongs to the Special Issue Flood Inundation Mapping in Hydrological Systems)
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21 pages, 14365 KiB  
Article
Applying Floodplain Inundation Modeling to Estimate Suitable Spawning Habitat and Recruitment Success for Alligator Gar in the Guadalupe River, Texas
by Kimberly M. Meitzen, Clinton R. Robertson, Jennifer L. Jensen, Daniel J. Daugherty, Thomas B. Hardy and Kevin B. Mayes
Hydrology 2023, 10(6), 123; https://doi.org/10.3390/hydrology10060123 - 31 May 2023
Cited by 3 | Viewed by 1677
Abstract
We developed a floodplain inundation model to extract specific flood extent and depth parameters and combined these with vegetation land cover and historic flow data to quantify spatial habitat suitability and temporal hydrologic metrics that support Alligator Gar Atractosteus spatula spawning within a [...] Read more.
We developed a floodplain inundation model to extract specific flood extent and depth parameters and combined these with vegetation land cover and historic flow data to quantify spatial habitat suitability and temporal hydrologic metrics that support Alligator Gar Atractosteus spatula spawning within a 257 km segment of the lower Guadalupe River, Texas, USA. We modeled nine flows across a range of flood frequency recurrence intervals from 257 m3s−1 to ~4997 m3s−1 and estimated the availability of suitable spawning water depths (0.2 to 2 m) and lateral connectedness between the river and suitable floodplain landcover types. We estimated the ages via otoliths of 95 Alligator Gar collected in the reach to determine the year that they were recruited into the system. We analyzed a total of 30 Indicators of Hydrologic Alteration flow metrics to examine how the spatially derived suitable habitats related to the temporal aspects of flow occurrence during the spawning season for the period of flow record April–July (1935–2020) and to the years spanning the recruitment data of the Alligator Gar (1981–2010). A non-linear relationship existed between suitable spawning habitat area and the flow regime, with the most habitat availability corresponding to the 10–20-year flood recurrence interval frequency with peak flows of 2057–3108 m3s−1, respectively. The Alligator Gar recruitment data indicated that six years provided high recruitment, which correlated with peak flows of ~5-year frequency with an available spawning area of ~9000 Ha, moderate recruitment years related to peak flows with ~3-year frequency with an available spawning area of 6000 Ha, and low recruitment years where spawning was likely to occur at least every other year with at least 2500 Ha of available spawning area. The results of this model support the development of legislatively mandated environmental flow standards for the Guadalupe River Basin, inform field-based efforts for collecting empirical and observational data on the species’ reproduction, and provide spatial and temporal information for designing conservation strategies for Alligator Gar. Full article
(This article belongs to the Special Issue Flood Inundation Mapping in Hydrological Systems)
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16 pages, 9249 KiB  
Article
Validating the Quality of Volunteered Geographic Information (VGI) for Flood Modeling of Hurricane Harvey in Houston, Texas
by T. Edwin Chow, Joyce Chien and Kimberly Meitzen
Hydrology 2023, 10(5), 113; https://doi.org/10.3390/hydrology10050113 - 17 May 2023
Cited by 2 | Viewed by 1606
Abstract
The primary objective of this study was to examine the quality of volunteered geographic information (VGI) data for flood mapping of Hurricane Harvey. As a crowdsourcing platform, the U-Flood project mapped flooded streets in the Houston metro area. This research examines the following: [...] Read more.
The primary objective of this study was to examine the quality of volunteered geographic information (VGI) data for flood mapping of Hurricane Harvey. As a crowdsourcing platform, the U-Flood project mapped flooded streets in the Houston metro area. This research examines the following: (1) If there are any significant differences in water depth (WD) among the hydraulic and hydrologic (H&H) model, the Federal Emergency Management Agency (FEMA) reference floodplain map, and the VGI? (2) Are there any significant differences in the inundated areas between the floodplain modeled by the VGI and hydraulic simulation? This study used HEC-RAS to simulate flood inundation maps and validated the results with high water marks (HWM) and the FEMA-modeled floodplain after Hurricane Harvey. The statistical results showed that there were significant differences in the WD, the inundated road count, and the length inside/outside of HEC-RAS-modeled floodplain. The results also showed that a less consistent decreasing trend between the U-Flood data and the modeled floodplain over time and space. This study empirically evaluated the data quality of the VGI based on observed and modeled data in flood monitoring. The findings from this study fill the gaps in the literature by assessing the uncertainty and data quality of VGI, providing insights into using supplementary data in flood mapping research. Full article
(This article belongs to the Special Issue Flood Inundation Mapping in Hydrological Systems)
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19 pages, 7546 KiB  
Article
Application of Running Water-Type Retarding Basin to Old Kinu River Floodplain, Japan
by Tadaharu Ishikawa and Ryosuke Akoh
Hydrology 2023, 10(4), 94; https://doi.org/10.3390/hydrology10040094 - 15 Apr 2023
Cited by 1 | Viewed by 1370
Abstract
In the upper and middle reaches of rivers in Japan, river channels used to meander in a comparatively narrow floodplain and heavy rain runoff used to naturally expand over the entire floodplain, retarding floods toward the downstream. Recent continuous levee building to prevent [...] Read more.
In the upper and middle reaches of rivers in Japan, river channels used to meander in a comparatively narrow floodplain and heavy rain runoff used to naturally expand over the entire floodplain, retarding floods toward the downstream. Recent continuous levee building to prevent river overflow has had two kinds of negative effects, namely an increase in flood damage in areas of a floodplain closed by levees and river terraces at the time of runoff over the river channel capacity, and an increase in the flood peak toward the downstream. This study introduces the concept of a running water-type retarding basin that mitigates flood damage by allowing excess runoff to pass through the floodplain, restoring a natural hydrological process. After a description of the concept of the facility design, a design example is presented for a closed floodplain of the Kinu River Floodplain, where excess runoff caused severe flood damage in 2015, to quantify the performance and effects of the running water-type retarding basin. Full article
(This article belongs to the Special Issue Flood Inundation Mapping in Hydrological Systems)
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18 pages, 2947 KiB  
Article
Intercomparison of Automated Near-Real-Time Flood Mapping Algorithms Using Satellite Data and DEM-Based Methods: A Case Study of 2022 Madagascar Flood
by Wenzhao Li, Dongfeng Li and Zheng N. Fang
Hydrology 2023, 10(1), 17; https://doi.org/10.3390/hydrology10010017 - 08 Jan 2023
Cited by 3 | Viewed by 1898
Abstract
Numerous algorithms have been developed to automate the process of delineating water surface maps for flood monitoring and mitigation purposes by using multiple sources such as satellite sensors and digital elevation model (DEM) data. To better understand the causes of inaccurate mapping information, [...] Read more.
Numerous algorithms have been developed to automate the process of delineating water surface maps for flood monitoring and mitigation purposes by using multiple sources such as satellite sensors and digital elevation model (DEM) data. To better understand the causes of inaccurate mapping information, we aim to demonstrate the advantages and limitations of these algorithms through a case study of the 2022 Madagascar flooding event. The HYDRAFloods toolbox was used to perform preprocessing, image correction, and automated flood water detection based on the state-of-the-art Edge Otsu, Bmax Otsu, and Fuzzy Otsu algorithms for the satellite images; the FwDET tool was deployed upon the cloud computing platform (Google Earth Engine) for rapid estimation of flood area/depth using the digital elevation model (DEM) data. Generated surface water maps from the respective techniques were evaluated qualitatively against each other and compared with a reference map produced by the European Union Copernicus Emergency Management Service (CEMS). The DEM-based maps show generally overestimated flood extents. The satellite-based maps show that Edge Otsu and Bmax Otsu methods are more likely to generate consistent results than those from Fuzzy Otsu. While the synthetic-aperture radar (SAR) data are typically favorable over the optical image under undesired weather conditions, maps generated based on SAR data tend to underestimate the flood extent as compared with reference maps. This study also suggests the newly launched Landsat-9 serves as an essential supplement to the rapid delineation of flood extents. Full article
(This article belongs to the Special Issue Flood Inundation Mapping in Hydrological Systems)
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