Advancing the Monitoring and Modelling of Freshwater Systems with New Remote Sensing Technologies

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: 20 December 2024 | Viewed by 1926

Special Issue Editors


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Guest Editor
Global Institute for Water Security, School of Environment and Sustainability, University of Saskatchewan, Saskatoon, SK S7N 3H5, Canada
Interests: surface water quality modelling; ice-jam flood hazard mapping; ice-jam flood risk assessment; remote sensing of river ice covers; river ice hydraulic modelling
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Guest Editor
Department of Geography, Planning and Environment, Concordia University, Montreal, QC, Canada
Interests: fluvial mixing processes; eco-hydraulics (fish passage); remote sensing techniques (large-scale particle image velocimetry, particle tracking velocimetry, photogrammetric bathymetry reconstruction); 3D high-speed object tracking; coding research tools

Special Issue Information

Dear Colleagues,

As Guest Editors of the Special Issue “Advancing the Monitoring and Modelling of Freshwater Systems with New Remote Sensing Technologies”, we welcome you to submit an article highlighting new methodologies and techniques in remote sensing for the advancement of monitoring and modelling river, lake and groundwater systems. Technologies may include space-borne, airborne and near-ground remote sensing platforms to aid in a wide range of river and lake monitoring and modelling applications. The scope of these applications can include, to name but a few, aquatic ecology, habitat, water quality, sediment transport, geomorphology, flood forecasting and ice detection and characterization. It is hoped that these papers will also promote the exchange of new ideas and forge new collaborations between researchers, academics, engineers and government officials interfacing in the fields of remote sensing and freshwater systems.

Prof. Dr. Karl-Erich Lindenschmidt
Dr. Jason Duguay
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 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

  • airborne remote sensing
  • flood forecasting
  • fluvial geomorphology
  • ice detection
  • ice characterization
  • near-ground remote sensing
  • river and lake modelling
  • river and lake monitoring
  • sediment transport
  • space-borne remote sensing
  • water quality

Published Papers (2 papers)

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Research

14 pages, 1397 KiB  
Article
Exploring the Integration of Unmanned Aerial System Technologies into Stormwater Control Inspection Programs
by Jarrell Whitman, Michael Perez and Roy Sturgill
Water 2023, 15(22), 3924; https://doi.org/10.3390/w15223924 - 10 Nov 2023
Viewed by 751
Abstract
Construction stormwater best management practices and post-construction stormwater control measures are controls and techniques designed to manage and treat stormwater runoff. Departments of Transportation (DOTs) within the United States rely on these practices to treat and improve water quality emanating from DOT rights [...] Read more.
Construction stormwater best management practices and post-construction stormwater control measures are controls and techniques designed to manage and treat stormwater runoff. Departments of Transportation (DOTs) within the United States rely on these practices to treat and improve water quality emanating from DOT rights of way. To ensure operational performance, these practices undergo periodical inspections to identify if operational deficiencies exist and if corrective measures need to be deployed. The inspection process is often conducted on foot by a qualified inspector and can require a substantial labor effort to complete. Recently, unmanned aerial system (UAS) technologies have been utilized in the construction sector to survey, monitor, and improve safety. This study sought to identify and document practices regarding UAS technologies when conducting inspections of stormwater practices. Through a distributed DOT survey questionnaire (80% response rate) and four case example interviews, this study investigates how UAS stormwater inspections have been deployed by DOTs and the strategies and programs that have been adopted or created. Key findings outline (1) use of UAS technologies for stormwater inspections, (2) applying UAS technologies within a DOT, (3) staffing and equipping needs, and (4) managing UAS inspection datasets. The study also identifies challenges and implementational strategies to facilitate the development of a UAS stormwater inspection program within a DOT. Full article
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22 pages, 5400 KiB  
Article
Long-Time Water Quality Variations in the Yangtze River from Landsat-8 and Sentinel-2 Images Based on Neural Networks
by Yuanyuan Yang and Shuanggen Jin
Water 2023, 15(21), 3802; https://doi.org/10.3390/w15213802 - 30 Oct 2023
Cited by 1 | Viewed by 972
Abstract
Total phosphorus (TP) and total nitrogen (TN) represent the primary water quality parameters indicative of the eutrophication status in the mainstream of the Yangtze River. Nowadays, satellite remote sensing offers an economical and efficient method for monitoring the water environment with a broad [...] Read more.
Total phosphorus (TP) and total nitrogen (TN) represent the primary water quality parameters indicative of the eutrophication status in the mainstream of the Yangtze River. Nowadays, satellite remote sensing offers an economical and efficient method for monitoring the water environment with a broad geographical scope, while single satellite and traditional methods are still limited. In this paper, inversion models of TN and TP are constructed and evaluated based on the neural networks (NNs) algorithm and random forest (RF) algorithm in the upper, middle, and lower reaches of the Yangtze River, respectively. Subsequently, the monthly variations of TN and TP concentrations are estimated and analyzed in the mainstream of the Yangtze River using Landsat-8 and Sentinel-2 satellites images from January 2016 to December 2022. The results show that the NNs model exhibits better estimation performance than the RF model within the study area. The accuracy of the TN model varies across different sections, with R2 values of 0.70 in the upstream, 0.67 in the midstream, and 0.74 in the downstream, accompanied by respective RMSE values of 0.21 mg/L, 0.21 mg/L, and 0.23 mg/L. Similarly, the TP model exhibits varying accuracy in different sections, with R2 values of 0.71 in the upstream, 0.69 in the midstream, and 0.78 in the downstream, along with corresponding RMSE values of 0.008 mg/L, 0.012 mg/L, and 0.008 mg/L. From 2016 to 2022, the concentrations of TN and TP in the mainstream of the Yangtze River exhibited an overall downward trend, with TN decreasing by 13.7% and TP decreasing by 46.2%. Furthermore, this study also gives the possible causes of water quality changes in the mainstream of the Yangtze River with a specific focus on hydrometeorological factors. Full article
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