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Remotely Monitoring Water, Sediment, and Carbon Transported in Rivers and...
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Remotely Monitoring Water, Sediment, and Carbon Transported in Rivers and Estuaries

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: 30 April 2024 | Viewed by 3764

Special Issue Editors

Dr. Dong Liu

E-Mail Website
Guest Editor
Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
Interests: remote sensing; water environment; carbon cycle
Special Issues, Collections and Topics in MDPI journals
Dr. Chang Huang

E-Mail Website
Guest Editor
Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi’an 710127, China
Interests: remote sensing of surface water; river discharge; flood inundation; image fusion; Google Earth Engine
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Hongtao Duan

E-Mail Website
Guest Editor
Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
Interests: remote sensing; water environment; watershed management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the inland environment, rivers are the main source of fresh water available to human beings, They are also regulating hydrological and ecological cycles, playing a unique role in supporting global biodiversity, biogeochemical cycles and human society, by means of transporting water, sediment and carbon. In addition to the water, sediment and carbon are also critical components of the fluvial system. Riverine sediment and carbon-related matter can serve as key food/energy sources for microbial activities, transports poisonous metals and hazardous pollutants, consume dissolved oxygen during decomposition, increase drinking water treatment costs, influence phytoplankton growth by absorbing ultraviolet–visible light connects carbon pools of various ecosystems, and regulates water quality conditions. Water, sediment, and carbon transports in rivers show great spatiotemporal variations under the backgrounds of global warming and artificial disturbance. Transitional observation has the disadvantage of being laborious and ineffective. Remote sensing technologies, having the advantages of comprehensive coverage and periodic revisit periods, can serve as a superior alternative observation manner.

Although remote sensing technology has been widely applied to monitor water environments in open oceans and lakes, its application in rivers that are relatively narrower is limited. For river studies, atmospheric correction and proximity effect correction are especially critical as most of the rivers are only several to tens of pixels wide. In addition to satellite imagery, UAV aerial images could provide very high-resolution river observation information, and could be valuable for validating or assisting sediment inversion modeling. This Special Issue aims to publish studies about water, sediment, and carbon transport in rivers. Through this Special Issue, we hope more researchers will use remote sensing as an advanced/low-cost method to monitor riverine transport of water, sediment, and carbon in the future.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Remote sensing of sediment concentration and transportation in rivers;
  • Remote sensing of river discharge;
  • Remote Sensing of river carbon flux;
  • Atmospheric correction of satellite data;
  • Remote Sensing of water environment;
  • Driving factors, reasons, and/or explanations;
  • Other areas related to the topic.

Dr. Dong Liu
Dr. Chang Huang
Prof. Dr. Hongtao Duan
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. Remote Sensing 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 2700 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

  • sediment transportation
  • soil conservation
  • human activities
  • water quality
  • climate change
  • carbon export/flux
  • atmospheric correction

Published Papers (4 papers)

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Research

19 pages, 2875 KiB  
Article
Estimating the Colored Dissolved Organic Matter in the Negro River, Amazon Basin, with In Situ Remote Sensing Data
by Rogério Ribeiro Marinho, Jean-Michel Martinez, Tereza Cristina Souza de Oliveira, Wagner Picanço Moreira, Lino A. Sander de Carvalho, Patricia Moreira-Turcq and Tristan Harmel
Remote Sens. 2024, 16(4), 613; https://doi.org/10.3390/rs16040613 - 06 Feb 2024
Viewed by 843
Abstract
Dissolved organic matter (DOM) is a crucial component of continental aquatic ecosystems. It plays a vital role in the carbon cycle by serving as a significant source and reservoir of carbon in water. DOM provides energy and nutrients to organisms, affecting primary productivity, [...] Read more.
Dissolved organic matter (DOM) is a crucial component of continental aquatic ecosystems. It plays a vital role in the carbon cycle by serving as a significant source and reservoir of carbon in water. DOM provides energy and nutrients to organisms, affecting primary productivity, organic composition, and the food chain. This study presents empirical bio-optical models for estimating the absorption of colored dissolved organic matter (aCDOM) in the Negro River using in situ remote sensing reflectance (Rrs) data. Physical–chemical data (TSS, DOC, and POC) and optical data (aCDOM and Rrs) were collected from the Negro River, its tributaries, and lakes and empirical relationships between aCDOM at 440 nm, single band, and the ratio bands of Rrs were assessed. The analysis of spectral slope shows no statistically significant correlations with DOC concentration or aCDOM absorption coefficient. However, strong relationships were observed between DOC and aCDOM (R2 = 0.72), aCDOM and Rrs at 650 nm (R2 > 0.80 and RMSE < 1.75 m−1), as well as aCDOM and the green/red band ratio (R2 > 0.80 and RMSE < 2.30 m−1). aCDOM displayed large spatial and temporal variations, varying from 1.9 up to 20.1 m−1, with higher values in rivers of the upper course of the Negro basin and lower values in rivers with total solids suspended > 10 mg·L−1. Environmental factors that influence the production of dissolved organic matter include soil type, dense forest cover, high precipitation, and low erosion rates. This study demonstrated that aCDOM can serve as an indicator of DOC, and Rrs can serve as an indicator of aCDOM in the Negro basin. Our findings offer a starting point for future research on the optical properties of Amazonian black-water rivers. Full article
(This article belongs to the Special Issue Remotely Monitoring Water, Sediment, and Carbon Transported in Rivers and Estuaries)
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20 pages, 5320 KiB  
Article
Monitoring Suspended Sediment Transport in the Lower Yellow River using Landsat Observations
by Mengwei Duan, Zhiqiang Qiu, Ruren Li, Keyu Li, Shujie Yu and Dong Liu
Remote Sens. 2024, 16(2), 229; https://doi.org/10.3390/rs16020229 - 06 Jan 2024
Viewed by 740
Abstract
The spatiotemporal variations in suspended sediment concentration (SSC) in the lower reaches of the Yellow River exhibit significant variability and are influenced by reservoir operations. Understanding the spatiotemporal distribution characteristics of SSC in water holds crucial implications for environmental protection and reservoir operation [...] Read more.
The spatiotemporal variations in suspended sediment concentration (SSC) in the lower reaches of the Yellow River exhibit significant variability and are influenced by reservoir operations. Understanding the spatiotemporal distribution characteristics of SSC in water holds crucial implications for environmental protection and reservoir operation management. Based on daily-scale SSC monitoring data from four hydrological stations in the lower Yellow River, this study established an SSC remote sensing model applicable to Landsat series satellite data. The independent variable of the model, Rrs(NIR)/(Rrs(G) + Rrs(R) + Rrs(SWIR)), demonstrated sensitivity to water bodies with different SSC values. Distinctive spatiotemporal characteristics in sediment transport were observed across the lower Yellow River. Spatially, the SSC values in the Sanmenxia and Xiaolangdi reservoirs were notably lower than those in other river sections, averaging 1008.42 ± 602.83 mg/L and 1177.89 ± 627.95 mg/L, respectively. Over time, the majority of the river sections (96%) exhibited decreasing trends in SSC during 1984–2022, particularly in the downstream Xiaolangdi reservoir, with average SSC values of 4265.58 ± 1101.77 mg/L in the 1980s and 1840.80 ± 2255.15 mg/L in the 2020s. Seasonal variations in SSC were prominent, with higher summer concentrations, averaging 5536.43 ± 2188.77 mg/L (2020s summer) and 814.11 ± 158.27 mg/L (2020s winter). Reductions in SSC during 1984–2022 primarily occurred in summer, weakening its seasonal variability in the lower Yellow River. Water discharge emerged as a critical factor influencing suspended sediment transport, with SSC increasing in high-water-flow months. Following the construction of the Xiaolangdi reservoir, the relationship between SSC and water discharge at different stations underwent notable alterations. This study enhances our understanding of the spatiotemporal dynamics of suspended sediment transport in the lower Yellow River, providing valuable insights for utilizing long-term Landsat series data in the dynamic monitoring of river sediment transport. Full article
(This article belongs to the Special Issue Remotely Monitoring Water, Sediment, and Carbon Transported in Rivers and Estuaries)
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18 pages, 7979 KiB  
Article
Classification of River Sediment Fractions in a River Segment including Shallow Water Areas Based on Aerial Images from Unmanned Aerial Vehicles with Convolution Neural Networks
by Mitsuteru Irie, Shunsuke Arakaki, Tomoki Suto and Takuto Umino
Remote Sens. 2024, 16(1), 173; https://doi.org/10.3390/rs16010173 - 31 Dec 2023
Viewed by 907
Abstract
Riverbed materials serve multiple environmental functions as a habitat for aquatic invertebrates and fish. At the same time, the particle size of the bed material reflects the tractive force of the flow regime in a flood and provides useful information for flood control. [...] Read more.
Riverbed materials serve multiple environmental functions as a habitat for aquatic invertebrates and fish. At the same time, the particle size of the bed material reflects the tractive force of the flow regime in a flood and provides useful information for flood control. The traditional riverbed particle size surveys, such as sieving, require time and labor to investigate riverbed materials. The authors of this study have proposed a method to classify aerial images taken by unmanned aerial vehicles (UAVs) using convolutional neural networks (CNNs). Our previous study showed that terrestrial riverbed materials could be classified with high accuracy. In this study, we attempted to classify riverbed materials of terrestrial and underwater samples including that which is distributed in shallow waters where the bottom can be seen using UAVs over the river segment. It was considered that the surface flow types taken overlapping the riverbed material on images disturb the accuracy of classification. By including photographs of various surface flow conditions in the training data, the classification focusing on the patterns of riverbed materials could be achieved. The total accuracy reached 90.3%. Moreover, the proposed method was applied to the river segments to determine the distribution of the particle size. In parallel, the microtopography was surveyed using a LiDAR UAV, and the relationship between the microtopography and particle size distribution was discussed. In the steep section, coarse particles were distributed and formed riffles. Fine particles were deposited on the upstream side of those riffles, where the slope had become gentler due to the dammed part. The good concordance between the microtopographical trends and the grain size distribution supports the validity of this method. Full article
(This article belongs to the Special Issue Remotely Monitoring Water, Sediment, and Carbon Transported in Rivers and Estuaries)
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20 pages, 5720 KiB  
Article
Modeling of Suspended Particulate Matter Concentration in an Extremely Turbid River Based on Multispectral Remote Sensing from an Unmanned Aerial Vehicle (UAV)
by Yinghui Zhai, Pu Zhong, Hongtao Duan, Dan Zhang, Xin Chen and Xingjian Guo
Remote Sens. 2023, 15(22), 5398; https://doi.org/10.3390/rs15225398 - 17 Nov 2023
Viewed by 719
Abstract
Following consecutive years of governance efforts, there has been a substantial reduction in sediment transport in the Yellow River, resulting in significant changes in its water–sediment dynamics. This necessitates precise monitoring of sediment-bearing tributary inflows, a crucial requirement for effective governance strategies on [...] Read more.
Following consecutive years of governance efforts, there has been a substantial reduction in sediment transport in the Yellow River, resulting in significant changes in its water–sediment dynamics. This necessitates precise monitoring of sediment-bearing tributary inflows, a crucial requirement for effective governance strategies on the Loess Plateau’s current developmental stage. While satellite remote sensing technology has been widely used to estimate suspended particulate matter concentration (CSPM) in open water bodies like oceans and lakes, its application in narrow rivers presents challenges related to hybrid pixel and proximity effects. As a result, the effectiveness and competence of satellite remote sensing in monitoring CSPM in such confined river environments are reduced. This study attempted to use unmanned aerial vehicle (UAV) remote sensing with multispectral technology to invert CSPM in the Wuding River, a sediment-bearing Yellow River tributary. A novel CSPM concentration inversion model was introduced for highly turbid river settings. The results showed that the accuracy of the new band ratio model in this study is significantly improved compared with the existing models. The validation dataset had a coefficient of determination (R2) of 0.83, a root mean square error (RMSE) of 3.73 g/L, and a mean absolute percentage error (MAPE) of 44.95% (MAPE is 40.68% at 1–20 g/L, and 12.37% at >20 g/L). On this basis, the UAV also monitored the impacts of heavy rainfall on the CSPM, resulting in a rapid rise and fall in CSPM over a period of ten hours. This study demonstrated the potential of UAV remote sensing for CSPM monitoring in extremely turbid narrow rivers (tens to tens of meters), especially before and after rainfall sediment production events, which can provide technical support for accurate sediment management and source identification in the main tributaries of the Yellow River and help realize the goal of high-quality development of the Yellow River Basin. Full article
(This article belongs to the Special Issue Remotely Monitoring Water, Sediment, and Carbon Transported in Rivers and Estuaries)
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