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Remote Sensing Monitoring of Natural Disasters and Human Impacts in Asian Rivers

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 30738

Special Issue Editors


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Guest Editor
National Institute of Education (NIE) and Asian School of the Environment (ASE), Nanyang Technological University, Singapore
Interests: fluvial geomorphology; hydrology; human impacts and remote sensing
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China
Interests: earth surface fluvial processes analysis; hydrological modelling using remote sensing and GIS techniques; river hydromorphology; soil erosion and river sediment transport; river response to climate change and anthropogenic activities
Special Issues, Collections and Topics in MDPI journals
Water Engineering and Management, School of Engineering and Technology, Asian Institute of Technology, Pathum Thani 12120, Thailand
Interests: ecosystem services; urban water hydrology; IoT; data analytics; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Asia contains several of the world’s largest rivers, such as the Pearl, Mekong, Yangtze, Indus, Ganges, Amu Darya, Salween, Red, Chao Phraya and Rajang Rivers, and smaller river basins that are among the most productive in water and sediment yield of the whole planet. For example, the South China Sea is the largest sink of sediments among the marginal seas worldwide and is estimated to trap more than 700 million tons of fluvial sediments each year. The hydro-sedimentologic regimes of the fluvial basins in Asia are largely vulnerable to tropical cyclones, recurrent floods and frequent landslides and to episodic geological events such as earthquakes and volcanic eruptions. For that reason, Asian rivers are considered the riskiest and most vulnerable area to natural hazards and disasters in the world. This area currently concentrates many of the fastest growing and important economic activities in countries (e.g., India, China and Association of Southeast Asian Nations) and also contains some of the most important geopolitical hotspots of international territorial conflicts. Because of the explosive growth in demography, development, and economy experienced by such Asian countries, the impacts on the fluvial systems have been suffering from the population explosion and the resultant extreme human impacts, which are the highest ever recorded in recent history. As a consequence, human-induced changes in the hydro-geomorphologic regimes, sediment inputs, and floodplain storage capacity have triggered substantial impacts on deltas, and coastal and marine environments that depend on the organic and inorganic fluxes contributed by fluvial systems.

Since most of the deltas around the Indo-West Pacific are “river-dominated deltas,” their complexity, mass balance, and land areas depend on the balance between river supply, coastal removal of sediment, and crustal subsidence. For example, reductions of sediment supply reduce the area of the deltas. This is considered one of the most significant geological changes in the world affecting habitability. It has been recently reported that Asian deltas are facing the most severe challenges on the planet in terms of vulnerability to population pressures, combined with relative sea-level rise and poor delta governance.

For example, in southern China, explosive urbanization and land-use change have dramatically affected the sediment fluxes to the South China Sea. The sediment fluxes from 10 major Chinese rivers to the Pacific Ocean had decreased from about 2100 Mt per year to only 575 Mt per year during the period 1955-2007. The Pearl River Delta, the most densely urbanized place in the world, is currently no longer experiencing aggradation, mainly due to the impoundment of sediment in reservoirs and to river bed sediment dredging from rivers and coasts, which reduced sediment fluxes to the South China Sea by 67% across the 20th century. Massive sand extraction from the Pearl River and in the coastal zones to build skyscrapers and to construct thousands of kilometers of river dikes, hydroelectric dams, and artificial islands in the South China Sea not only modified river hydraulics but are also depleting sediment storages in the basin. Indus, Mekong, Chao Phraya and Red Rivers in Vietnam also experienced a dramatic decrease in sediment fluxes recently due to reservoir trapping. Although reservoir trapping, farming, and rapid urbanization have significantly elevated sediment yields in Taiwan. Despite the significant impact of the rivers in Malaysian Borneo on the annual sediment budget of the South China Sea, the human impacts on their fluvial systems have yet been studied.

Remote sensing can be considered one of the most efficient and relevant means to regularly assess the spatiotemporal dynamics of various riverine environments, including channels, floodplains, lakes, reservoirs, and wetlands over a large scale, due to environmental impacts. Remote sensing technology has widely shown that it can aid in addressing some of the critical drivers and consequences of the fluvial environmental changes at multiple spatiotemporal scales. This Special Issue on “Natural disasters and human impacts in Asian rivers” is dedicated to contributing to the fast-growing current trend of remote sensing applications to assess environmental impacts in Asian rivers. We invite studies on recent advances in the study of rivers in Asia solidly based on any types (active or passive) and platforms of remote sensing from multidisciplinary points of view, including water resources issues, fluxes, or the management of large rivers, as well as review articles synthesizing the history and development of remote sensing with a focus on any aspects of environmental impacts concerned with rivers in Asia. We particularly encourage the submission of remote sensing studies analyzing the vulnerability and responses of fluvial systems suffering from unprecedentedly high human impacts in Asia, the highest ever recorded in recent Earth history, such as dam construction, deforestation, or sand mining activities.

Dr. Edward Park
Dr. Xiankun Yang
Dr. Huu Loc Ho
Guest Editors

Manuscript Submission Information

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Keywords

  • Asian rivers
  • Human impacts
  • Natural disasters
  • Hydrological regimes
  • Environmental impacts

Published Papers (7 papers)

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Research

19 pages, 3512 KiB  
Article
Assessing the Performance of the Satellite-Based Precipitation Products (SPP) in the Data-Sparse Himalayan Terrain
by Sonu Kumar, Giriraj Amarnath, Surajit Ghosh, Edward Park, Triambak Baghel, Jingyu Wang, Malay Pramanik and Devesh Belbase
Remote Sens. 2022, 14(19), 4810; https://doi.org/10.3390/rs14194810 - 26 Sep 2022
Cited by 7 | Viewed by 1756
Abstract
Located on the south-facing slope of the Himalayas, Nepal receives intense, long-lasting precipitation during the Asian summer monsoon, making Nepal one of the most susceptible countries to flood and landslide hazards in the region. However, sparse gauging and irregular measurement constrain the vulnerability [...] Read more.
Located on the south-facing slope of the Himalayas, Nepal receives intense, long-lasting precipitation during the Asian summer monsoon, making Nepal one of the most susceptible countries to flood and landslide hazards in the region. However, sparse gauging and irregular measurement constrain the vulnerability assessments of floods and landslides, which rely highly on the accuracy of precipitation. Therefore, this study evaluates the performance of Satellite-based Precipitation Products (SPPs) in the Himalayas region by comparing different datasets and identifying the best alternative of gauge-based precipitation for hydro-meteorological applications. We compared eight SPPs using statistical metrics and then used the Multi-Criteria Decision-Making (MCDM) technique to rank them. Secondly, we assessed the hydrological utility of SPPs by simulating them through the GR4J hydrological model. We found a high POD (0.60–0.80) for all SPPs except CHIRPS and PERSIANN; however, a high CC (0.20–0.40) only for CHIRPS, IMERG_Final, and CMORPH. Based on MCDM, CMORPH and IMERG_Final rank first and second. While SPPs could not simulate daily discharge (NSE < 0.28), they performed better for monthly streamflow (NSE > 0.54). Overall, this study recommends CMORPH and IMERG_Final and improves the understanding of data quality to better manage hydrological disasters in the data-sparse Himalayas. This study framework can also be used in other Himalayan regions to systematically rank and identify the most suitable datasets for hydro-meteorological applications. Full article
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21 pages, 6334 KiB  
Article
Assessment of Large-Scale Seasonal River Morphological Changes in Ayeyarwady River Using Optical Remote Sensing Data
by Dhyey Bhatpuria, Karthikeyan Matheswaran, Thanapon Piman, Theara Tha and Peeranan Towashiraporn
Remote Sens. 2022, 14(14), 3393; https://doi.org/10.3390/rs14143393 - 14 Jul 2022
Cited by 2 | Viewed by 3502
Abstract
Monitoring morphologically dynamic rivers over large spatial domains at an adequate frequency is essential for informed river management to protect human life, ecosystems, livelihoods, and critical infrastructures. Leveraging the advancements in cloud-based remote sensing data processing through Google Earth Engine (GEE), a web-based, [...] Read more.
Monitoring morphologically dynamic rivers over large spatial domains at an adequate frequency is essential for informed river management to protect human life, ecosystems, livelihoods, and critical infrastructures. Leveraging the advancements in cloud-based remote sensing data processing through Google Earth Engine (GEE), a web-based, freely accessible seasonal river morphological monitoring system for Ayeyarwady River, Myanmar was developed through a collaborative process to assess changes in river morphology over time and space. The monitoring system uses Landsat satellite data spanning a 31-year long period (1988–2019) to map river planform changes along 3881.4 km of river length including Upper Ayeyarwady, Lower Ayeyarwady, and Chindwin. It is designed to operate on a seasonal timescale by comparing pre-monsoon and post-monsoon channel conditions to provide timely information on erosion and accretion areas for the stakeholders to support planning and management. The morphological monitoring system was validated with 85 reference points capturing the field conditions in 2019 and was found to be reliable for operational use with an overall accuracy of 89%. The average eroded riverbank area was calculated at around 45, 101, and 134 km2 for Chindwin, Upper Ayeyarwady, and Lower Ayeyarwady, respectively. The historical channel change assessment aided us to identify and categorize river reaches according to the frequency of changes. Six hotspots of riverbank erosion were identified including near Mandalay city, the confluence of Upper Ayeyarwady and Chindwin, near upstream of Magway city, downstream of Magway city, near Pyay city, and upstream of the Ayeyarwady delta. The web-based monitoring system simplifies the application of freely available remote sensing data over the large spatial domain to assess river planform changes to support stakeholders’ operational planning and prioritizing investments for sustainable Ayeyarwady River management. Full article
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15 pages, 71593 KiB  
Article
Application of UAV and GB-SAR in Mechanism Research and Monitoring of Zhonghaicun Landslide in Southwest China
by Bo Liu, Kun He, Mei Han, Xiewen Hu, Guotao Ma and Mingyang Wu
Remote Sens. 2021, 13(9), 1653; https://doi.org/10.3390/rs13091653 - 23 Apr 2021
Cited by 19 | Viewed by 3014
Abstract
This paper presents a recent rainfall-induced landslide in China that occurred on August 21, 2020 and resulted in nine deaths. The sliding material traveled a distance of 800 m, with an altitude difference of about 180 m. A field investigation, remote sensing based [...] Read more.
This paper presents a recent rainfall-induced landslide in China that occurred on August 21, 2020 and resulted in nine deaths. The sliding material traveled a distance of 800 m, with an altitude difference of about 180 m. A field investigation, remote sensing based on an unmanned aerial vehicle (UAV), in situ monitoring, and a rainfall data analysis were carried out to reveal the deposit characteristics, causative factors, post-landslide behavior, and the mechanism of the landslide. A saltatory micro-relief of the original slope determined the multiple-stage failure type of the slide, and also promoted the entrainment effect during the landslide movement. After the first-initiation sliding stage, the motion of this landslide involved typical progressive movement, and over time, the style of the runout generally turned into a flow-like form. Furthermore, the antecedent cumulative rainfall of 149.5 mm directly contributed to the occurrence of the landslide. Using the GB-SAR early warning system, the post-landslide residual failure was successfully predicted 10 min in advance. The combination of the UAV and GB-SAR technique can surely be beneficial for other inaccessible landslide investigations as well and improves the emergency rescue security. Full article
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20 pages, 8658 KiB  
Article
Flood Monitoring in Rural Areas of the Pearl River Basin (China) Using Sentinel-1 SAR
by Junliang Qiu, Bowen Cao, Edward Park, Xiankun Yang, Wenxin Zhang and Paolo Tarolli
Remote Sens. 2021, 13(7), 1384; https://doi.org/10.3390/rs13071384 - 3 Apr 2021
Cited by 37 | Viewed by 7856
Abstract
Flood hazards result in enormous casualties and huge economic losses every year in the Pearl River Basin (PRB), China. It is, therefore, crucial to monitor floods in PRB for a better understanding of the flooding patterns and characteristics of the PRB. Previous studies, [...] Read more.
Flood hazards result in enormous casualties and huge economic losses every year in the Pearl River Basin (PRB), China. It is, therefore, crucial to monitor floods in PRB for a better understanding of the flooding patterns and characteristics of the PRB. Previous studies, which utilized hydrological data were not successful in identifying flooding patterns in the rural and remote regions in PRB. Such regions are the key supplier of agricultural products and water resources for the entire PRB. Thus, an analysis of the impacts of floods could provide a useful tool to support mitigation strategies. Using 66 Sentinel-1 images, this study employed Otsu’s method to investigate floods and explore flood patterns across the PRB from 2017 to 2020. The results indicated that floods are mainly located in the central West River Basin (WRB), middle reaches of the North River (NR) and middle reaches of the East River (ER). WRB is more prone to flood hazards. In 2017, 94.0% flood-impacted croplands were located in WRB; 95.0% of inundated croplands (~9480 hectares) were also in WRB. The most vulnerable areas to flooding are sections of the Yijiang, Luoqingjiang, Qianjiang, and Xunjiang tributaries and the lower reaches of Liujiang. Our results highlight the severity of flood hazards in a rural region of the PRB and emphasize the need for policy overhaul to enhance flood control in rural regions in the PRB to ensure food safety. Full article
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23 pages, 4723 KiB  
Article
Landslide-Induced Mass Transport of Radionuclides along Transboundary Mailuu-Suu River Networks in Central Asia
by Fengqing Li, Isakbek Torgoev, Damir Zaredinov, Marina Li, Bekhzod Talipov, Anna Belousova, Christian Kunze and Petra Schneider
Remote Sens. 2021, 13(4), 698; https://doi.org/10.3390/rs13040698 - 14 Feb 2021
Cited by 6 | Viewed by 2575
Abstract
Seismically triggered landslides are a major hazard and have caused severe secondary losses. This problem is especially important in the seismic prone Mailuu-Suu catchment in Kyrgyzstan, as it hosts disproportionately sensitive active or legacy uranium sites with deposited radioactive extractive wastes. These sites [...] Read more.
Seismically triggered landslides are a major hazard and have caused severe secondary losses. This problem is especially important in the seismic prone Mailuu-Suu catchment in Kyrgyzstan, as it hosts disproportionately sensitive active or legacy uranium sites with deposited radioactive extractive wastes. These sites show a quasi-continuous release of radioactive contamination into surface waters, and especially after natural hazards, a sudden and massive input of pollutants into the surface waters is expected. However, landslides of contaminated sediments into surface waters represent a substantial exposure pathway that has not been properly addressed in the existing river basin management to date. To fill this gap, satellite imagery was massively employed to extract topography and geometric information, and the seismic Scoops3D and the one-dimensional numerical model, Hydrologic Engineering Centre, River Analysis System (HEC-RAS), were chosen to simulate the landslide-induced mass transport of total suspended solids (TSS) and natural radionuclides (Pb-210 as a proxy for modeling purposes) within the Mailuu-Suu river networks under two earthquake and two hydrological scenarios. The results show that the seismically vulnerable areas dominated in the upstream areas, and the mass of landslides increased dramatically with the increase of earthquake levels. After the landslides, the concentrations of radionuclides increased suddenly and dramatically. The peak values decreased along the longitudinal gradient of river networks, with the concentration curves becoming flat and wide in the downstream sections, and the transport speed of radionuclides decreased along the river networks. The conclusions of this study are that landslides commonly release a significant amount of pollutants with a relatively fast transport along river networks. Improved quantitative understanding of waterborne pollution dispersion across national borders will contribute to better co-ordination between governments and regulatory authorities of riparian states and, consequently, to future prevention of transnational political conflicts that have flared up in the last two decades over alleged pollution of transboundary water bodies. Full article
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20 pages, 6840 KiB  
Article
A Novel Method for River Bank Detection from Landsat Satellite Data: A Case Study in the Vietnamese Mekong Delta
by Doan Van Binh, Basil Wietlisbach, Sameh Kantoush, Ho Huu Loc, Edward Park, Giovanni de Cesare, Do Huy Cuong, Nguyen Xuan Tung and Tetsuya Sumi
Remote Sens. 2020, 12(20), 3298; https://doi.org/10.3390/rs12203298 - 10 Oct 2020
Cited by 22 | Viewed by 4834
Abstract
River bank (RB) erosion is a global issue affecting livelihoods and properties of millions of people. However, it has not received enough attention in the Vietnamese Mekong Delta (VMD), i.e., the world’s third largest delta, compared to salinity intrusion and flooding. There have [...] Read more.
River bank (RB) erosion is a global issue affecting livelihoods and properties of millions of people. However, it has not received enough attention in the Vietnamese Mekong Delta (VMD), i.e., the world’s third largest delta, compared to salinity intrusion and flooding. There have been several studies examining RB and coastal erosion in the VMD using remotely sensed satellite data, but the applied methodology was not adequately validated. Therefore, we developed a novel SRBED (Spectral RB Erosion Detection) method, in which the M-AMERL (Modified Automated Method for Extracting Rivers and Lakes) is proposed, and a new RB change detection algorithm using Landsat data. The results show that NDWI (Normalized Difference Water Index) and MNDWI (Modified Normalized Difference Water Index) using the M-AMERL algorithm (i.e., NDWIM-AMERL, MNDWIM-AMERL) perform better than other indices. Furthermore, the NDWIM-AMERL; SMA (i.e., NDWIM-AMERL using the SMA (Spectral Mixture Analysis) algorithm) is the best RB extraction method in the VMD. The NDWIM-AMERL; SMA performs better than the MNDWI, NDVI (Normalized Difference Vegetation Index), and WNDWI (Weighted Normalized Difference Water Index) indices by 35–41%, 70% and 30%, respectively. Moreover, the NDVI index is not recommended for assessing RB changes in the delta. Applying the developed SRBED method and RB change detection algorithm, we estimated a net erosion area of the RB of –1.5 km2 from 2008 to 2014 in the Tien River from Tan Chau to My Thuan, with a mean erosion width of –2.64 m and maximum erosion widths exceeding 60 m in places. Our advanced method can be applied in other river deltas having similar characteristics, and the results from our study are helpful in future studies in the VMD. Full article
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21 pages, 13356 KiB  
Article
Sentinel-1 SAR Time Series-Based Assessment of the Impact of Severe Salinity Intrusion Events on Spatiotemporal Changes in Distribution of Rice Planting Areas in Coastal Provinces of the Mekong Delta, Vietnam
by Phung Hoang-Phi, Nguyen Lam-Dao, Cu Pham-Van, Quang Chau-Nguyen-Xuan, Vu Nguyen-Van-Anh, Sridhar Gummadi and Trung Le-Van
Remote Sens. 2020, 12(19), 3196; https://doi.org/10.3390/rs12193196 - 30 Sep 2020
Cited by 10 | Viewed by 5731
Abstract
Food security has become a key global issue due to rapid population growth, extensive conversion of arable lands, and declining overall productivity in some areas because of the effects of floods, water shortage, salinity intrusion, and plant diseases. In this study, we analyzed [...] Read more.
Food security has become a key global issue due to rapid population growth, extensive conversion of arable lands, and declining overall productivity in some areas because of the effects of floods, water shortage, salinity intrusion, and plant diseases. In this study, we analyzed the relationship between the pattern of salinity intrusion and the spatiotemporal distribution of rice cultivation in the winter–spring crops of 2015, 2016, 2019 and 2020 in coastal provinces of the Vietnamese Mekong Delta. Sentinel-1 (S-1) data were used to extract the spatial distribution information of six rice growth stages based on a rice age algorithm. The classification accuracy of rice crop growth stages was found to have an overall accuracy of 85% and a Kappa coefficient of 0.80 (n = 373). For evaluating salinity intrusion effects, salinity isolines (4 g/L) were used to determine the percentage of rice areas affected. Results show that in the years observed to have severe salinity intrusion such as 2016 and 2020, a strong shift in planting calendar was identified to avoid salinity intrusion, with some areas being sown or transplanted 10–30 days earlier than normal planting. In addition, the lack of irrigation water and salinity intrusion limits rice cultivation in the dry season of coastal areas. Further analysis from the S-1 data confirms that the spatiotemporal distribution of rice cultivation is related to the change in government policy/recommendation affected by salinity intrusion. These findings demonstrate the potential and feasibility of using S-1 data to develop an operational rice crop adaptation framework on the delta scale. Full article
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