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Remote Sensing for Hydrology
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Remote Sensing for Hydrology

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "New Sensors, New Technologies and Machine Learning in Water Sciences".

Deadline for manuscript submissions: closed (25 June 2024) | Viewed by 4043

Special Issue Editor

Dr. Chou Xie

E-Mail Website
Guest Editor
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100000, China
Interests: SAR application; wetland; water level; remote sensing for hydrology

Special Issue Information

Dear Colleagues,

Remote sensing provides key data for monitoring the hydrological environment of wetlands, monitoring floods, and drawing water resource maps, while geographic information systems provide the best tools for water resource, drought, and flood risk management. This Special Issue will showcase the best practices, cutting-edge technologies, and applications of remote sensing, geographic information systems, and hydrological models in wetland hydrological environments, water resource mapping, water and flood inundation mapping, and risk management. The latest technologies include temporal detection of wetland inundation range, temporal detection of wetland water level, monitoring of suspended sediment transport and hydrological recharge in deltas, geospatial technology, and comprehensive hydrological and hydraulic modeling, which can be used for drawing flood risk maps, flood forecasting and the identification of flood evacuation routes, rainfall runoff and urban flood simulation, as well as satellite radar and optical image classification of urban water bodies and flood inundation. The application of these technologies is expected to greatly alleviate the pressure on water resources and enable people to better mitigate and adapt to the catastrophic effects of drought and floods.

Dr. Chou Xie
Guest Editor

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

  • remote sensing
  • hydrological environment
  • flood inundation mapping
  • water resource map
  • flood risk management

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Published Papers (2 papers)

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Research

25 pages, 67157 KiB  
Article
Impact of Utilizing High-Resolution PlanetScope Imagery on the Accuracy of LULC Mapping and Hydrological Modeling in an Arid Region
by Chithrika Alawathugoda, Gilbert Hinge, Mohamed Elkollaly and Mohamed A. Hamouda
Water 2024, 16(16), 2356; https://doi.org/10.3390/w16162356 - 22 Aug 2024
Cited by 3 | Viewed by 1771
Abstract
Accurate land-use and land-cover (LULC) mapping is crucial for effective watershed management and hydrological modeling in arid regions. This study examines the use of high-resolution PlanetScope imagery for LULC mapping, change detection, and hydrological modeling in the Wadi Ham watershed, Fujairah, UAE. The [...] Read more.
Accurate land-use and land-cover (LULC) mapping is crucial for effective watershed management and hydrological modeling in arid regions. This study examines the use of high-resolution PlanetScope imagery for LULC mapping, change detection, and hydrological modeling in the Wadi Ham watershed, Fujairah, UAE. The authors compared LULC maps derived from Sentinel-2 and PlanetScope imagery using maximum likelihood (ML) and random forest (RF) classifiers. Results indicated that the RF classifier applied to PlanetScope 8-band imagery achieved the highest overall accuracy of 97.27%. Change detection analysis from 2017 to 2022 revealed significant transformations, including a decrease in vegetation from 3.371 km2 to 1.557 km2 and an increase in built-up areas from 3.634 km2 to 6.227 km2. Hydrological modeling using the WMS-GSSHA model demonstrated the impact of LULC map accuracy on simulated runoff responses, with the most accurate LULC dataset showing a peak discharge of 1160 CMS at 930 min. In contrast, less accurate maps showed variations in peak discharge timings and magnitudes. The 2022 simulations, reflecting urbanization, exhibited increased runoff and earlier peak flow compared to 2017. These findings emphasize the importance of high-resolution, accurate LULC data for reliable hydrological modeling and effective watershed management. The study supports UAE’s 2030 vision for resilient communities and aligns with UN Sustainability Goals 11 (Sustainable Cities and Communities) and 13 (Climate Action), highlighting its broader relevance and impact. Full article
(This article belongs to the Special Issue Remote Sensing for Hydrology)
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19 pages, 23401 KiB  
Article
Integrating Geographic Information Systems and Hydrometric Analysis for Assessing and Mitigating Building Vulnerability to Flash Flood Risks
by Mohamed Wahba, Mustafa El-Rawy and Nassir Al-Arifi
Water 2024, 16(3), 434; https://doi.org/10.3390/w16030434 - 29 Jan 2024
Cited by 4 | Viewed by 1732
Abstract
Climate change represents an overwhelming challenge that demands urgent intervention for effective resolution. Among the devastating consequences of climate change, flash floods stand out as one of the most catastrophic repercussions. This research focuses on two primary objectives. Firstly, it aims to evaluate [...] Read more.
Climate change represents an overwhelming challenge that demands urgent intervention for effective resolution. Among the devastating consequences of climate change, flash floods stand out as one of the most catastrophic repercussions. This research focuses on two primary objectives. Firstly, it aims to evaluate the existing state of flash flood intensity (FFI) in a specific area of Hamamatsu city, Japan, which frequently experiences flash flood incidents. Secondly, it seeks to develop a mitigation plan to alleviate the adverse impacts of flooding on buildings within the area. To accomplish these objectives, four parameters related to FFI (namely, runoff depth, runoff velocity, runoff duration, and affected portion) were selected and estimated through the implementation of hydrological and hydrodynamic models. Additionally, a hydrological model was employed, utilizing a storm event with a return period of 100 years as input. During this simulated storm event, FFI values were calculated and categorized into four distinct levels. The results revealed that more than one-tenth of the examined buildings encountered the highest scale of FFI (category 4), while categories 3 and 4 combined accounted for nearly three-quarters of all buildings in the study area. Moreover, two mitigation strategies were adopted to prevent flooding within the buildings’ vicinity. Finally, this study provides a valuable framework and guidance for decision-makers and insurance companies, enabling them to assess the flood hazard status of buildings and make informed decisions accordingly. Full article
(This article belongs to the Special Issue Remote Sensing for Hydrology)
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