Now showing 1 - 10 of 27
  • Publication
    Metadata only
    Recent intensification of riverbed mining in the Mekong Delta revealed by extensive bathymetric surveying
    (Elsevier, 2023)
    Lau, Rachel Yu San
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    ;
    Tran, Dung Duc
    ;

    Large-scale sand extraction has had significant and compounding impacts on the riverine environment of the Vietnamese Mekong Delta (VMD). Yet, effective and targeted implementation of regulations and sustainable management remains hindered by scant data availability, limiting a comprehensive understanding of the delta's sand mining scale and extent. This study assessed recent intensifying patterns of sand mining activities in the VMD mainly based on extensive bathymetric surveys carried out across 800 km2 of the VMD river channel from 2017 to 2022. Our results revealed severe riverbed deepening across the VMD, with the upper reaches of the Hau (Bassac) River experiencing an average incision of 1.4 m from 2017 to 2022, resulting in sediment losses of 127 Mm3. Similarly, the upper reaches of the Tien (Mekong) River and the Co Chien branch showed incisions of 1.3 m and 0.7 m from 2017 to 2020, accompanied by sediment losses of 139 Mm3 and 87 Mm3, respectively. The observed spatial and temporal variability in incisions, along with widespread sand mining pockmarks along the riverbed profiles, provide strong evidence of the significant contribution of sand mining to changes in riverbed morphology. The progressive lowering of riverbed elevation provides further evidence of the recent intensification of sand mining activities. Additionally, field surveys highlighted the proximity of perceived sites of bank collapse to pitted riverbeds, providing reliable indications of sand mining-induced erosion. Ultimately, we intend for this evidence-based assessment of sand mining activities in the VMD to contribute to informed quantitative assessments of sediment budgets and effective implementation of regulatory frameworks for sustainable sand mining in the future.

      18
  • Publication
    Metadata only
    Deadly disasters in southeastern South America: Flash floods and landslides of February 2022 in Petrópolis, Rio de Janeiro
    (European Geosciences Union, 2023)
    Alcantara, Enner
    ;
    Marengo, Jose A.
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    Mantovani, Jose Roberto
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    Londe, Luciana
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    Lau, Rachel Yu San
    ;
    ;
    Lin, Nina Yunung
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    Mendes, Tatiana Sussel Goncalves
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    Cunha, Ana Paula
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    Pampuch, Luana
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    Seluchi, Marcelo
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    Simoes, Silvio
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    Cuartas, Luz Adriana
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    Goncalves, Demerval
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    Massi, Klecia
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    Alvala, Regina
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    Moraes, Osvaldo
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    Filho, Carlos Souza
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    Mendes, Rodolfo
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    Nobre, Carlos
    On 15 February 2022, the city of Petrópolis in the highlands of the state of Rio de Janeiro, Brazil, received an unusually high volume of rain within 3 h (258 mm), generated by a strongly invigorated mesoscale convective system. It resulted in flash floods and subsequent landslides that caused the deadliest landslide disaster recorded in Petrópolis, with 231 fatalities. In this paper, we analyzed the root causes and the key triggering factors of this landslide disaster by assessing the spatial relationship of landslide occurrence with various environmental factors. Rainfall data were retrieved from 1977 to 2022 (a combination of ground weather stations and the Climate Hazards Group InfraRed Precipitation – CHIRPS). Remotely sensed data were used to map the landslide scars, soil moisture, terrain attributes, line-of-sight displacement (land surface deformation), and urban sprawling (1985–2020). The results showed that the average monthly rainfall for February 2022 was 200 mm, the heaviest recorded in Petrópolis since 1932. Heavy rainfall was also recorded mostly in regions where the landslide occurred, according to analyses of the rainfall spatial distribution. As for terrain, 23 % of slopes between 45–60∘ had landslide occurrences and east-facing slopes appeared to be the most conducive for landslides as they recorded landslide occurrences of about 9 % to 11 %. Regarding the soil moisture, higher variability was found in the lower altitude (842 m) where the residential area is concentrated. Based on our land deformation assessment, the area is geologically stable, and the landslide occurred only in the thin layer at the surface. Out of the 1700 buildings found in the region of interest, 1021 are on the slope between 20 to 45∘ and about 60 houses were directly affected by the landslides. As such, we conclude that the heavy rainfall was not the only cause responsible for the catastrophic event of 15 February 2022; a combination of unplanned urban growth on slopes between 45–60∘, removal of vegetation, and the absence of inspection were also expressive driving forces of this disaster.
    WOS© Citations 6Scopus© Citations 20  38
  • Publication
    Metadata only
    Uncovering the lack of awareness of sand mining impacts on riverbank erosion among Mekong Delta residents: Insights from a comprehensive survey
    (Nature Research, 2023)
    Tran, Dung Duc
    ;
    Thien, Nguyen Duc
    ;
    Yuen, Kai Wen
    ;
    Lau, Rachel Yu San
    ;
    ;

    Global sand demand due to infrastructure construction has intensified sand mining activities in many rivers, with current rates of sand extraction exceeding natural replenishment. This has created many environmental problems, particularly concerning riverbank stability, which adversely affects the livelihoods of people in the Vietnamese Mekong Delta (VMD). However, sand mining’s social impacts in the region remain inadequately understood. Here we assess locals’ perception of sand mining activities in the VMD and its impacts on riverbank erosion. Residents living along the Bassac River, a hotspot of sand mining, were interviewed. Our results showed that while sand mining is perceived as destructive to the environment, few were aware of its role in worsening riverbank erosion. Only residents directly affected by riverbank collapse were aware of the implications of sand mining and its negative effect on bank stability, as they seem to have actively sought clarification. Our findings highlight the need for greater awareness and understanding among the locals regarding sand mining’s impact on riverbank stability.

      11
  • Publication
    Open Access
    Machine learning of key variables impacting extreme precipitation in various regions of the contiguous United States
    (Wiley, 2023)
    Lin, Xinming
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    Fan, Jiwen
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    Hou, Jason Z.
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    Amplification in extreme precipitation intensity and frequency can cause severe flooding and impose significant social and economic consequences. Variations in extreme precipitation intensity, frequencies, and return periods can be attributed to many physical variables across spatial and temporal scales. Here we employ ensemble machine learning (ML) methods, namely random forest (RF), eXtreme Gradient Boosting (XGB), and artificial neural networks (ANN), to explore key contributing variables to monthly extreme precipitation intensity and frequency in six regions over the United States. We further establish emulators for return periods. Results show that the ML models for intensity perform better in regions with obvious seasonality (i.e., Northern Great Plains, Southern Great Plains, and West Coast) than the other three regions (Northeast, Southwest, and Rocky Mountains), while for frequency the models perform well for most regions. The Shapley additive explanation is used to help explain the relationships between extreme precipitation characteristics and identify top variables for RF and XGB. We find that latent heat flux, relative humidity, soil moisture, and large-scale subsidence are key common variables across the regions for both monthly intensity and frequency, and their compound effects are non-negligible. The developed ML models capture the probability and return period of extreme precipitation well for all regions and may be used for decision making (e.g., infrastructure planning and design).
    WOS© Citations 2  55  88
  • Publication
    Embargo
    Significant advancement in subseasonal-to-seasonal summer precipitation ensemble forecast skills in China mainland through an innovative hybrid CSG-UNET method
    (IOP Publishing, 2024)
    Lyu, Yang
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    Zhu, Shuopeng
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    Zhi, Xiefei
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    Ji, Yan
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    Fan, Yi
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    Dong, Fu

    Reliable Subseasonal-to-Seasonal (S2S) forecasts of precipitation are critical for disaster prevention and mitigation. In this study, an innovative hybrid method CSG-UNET combining the UNET with the censored and shifted gamma distribution based ensemble model output statistic (CSG-EMOS), is proposed to calibrate the ensemble precipitation forecasts from ECMWF over the China mainland during boreal summer. Additional atmospheric variable forecasts and the data augmentation are also included to deal with the potential issues of low signal-to-noise ratio and relatively small sample sizes in traditional S2S precipitation forecast correction. The hybrid CSG-UNET exhibits a notable advantage over both individual UNET and CSG-EMOS in improving ensemble precipitation forecasts, simultaneously improving the forecast skills for lead times of 1–2 weeks and further extending the effective forecast timeliness to ∼4 weeks. Specifically, the climatology-based Brier Skill Scores are improved by ∼0.4 for the extreme precipitation forecasts almost throughout the whole timescale compared with the ECMWF. Feature importance analyze towards CSG-EMOS model indicates that the atmospheric factors make great contributions to the prediction skill with the increasing lead times. The CSG-UNET method is promising in subseasonal precipitation forecasts and could be applied to the routine forecast of other atmospheric and ocean phenomena in the future.

    Scopus© Citations 2  26  19
  • Publication
    Metadata only
    Extent of saltwater intrusion and freshwater exploitability in the coastal Vietnamese Mekong Delta assessed by gauging records and numerical simulations
    (Elsevier, 2024)
    Tran, Dung Duc
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    Pham, Thi Bich Thuc
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    Phan, Thi Thanh Hang
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    Duong, Ba Man
    ;

    Climate change-driven sea level rise has intensified salinity intrusion (SI) in deltas worldwide, posing significant threats to the exploitation of freshwater resources. In the Vietnamese Mekong Delta (VMD), the third largest delta globally, SI is a recurring challenge along the coastline, degrading freshwater resources for agricultural and domestic use and affecting socio-economic development. In this paper, we investigate the spatiotemporal extent of salinity intrusion in the Ben Tre Province, the hotspot of salinity disaster within the VMD. Long-term salinity monitoring data (25 years from 1996 to 2020) has been analyzed, and a 1D (Mike 11) coupled with 3D hydrodynamic model (Mike 3) was developed. Three scenarios were used to investigate the freshwater resources exploitation: (i) the year of investigation (2021), (ii) 2021 to 2030 climate change impacts, considering different annual exceedance probability of the upstream Mekong discharge (i.e., average flow, relatively low, low and very low), and (iii) extreme salinity intrusion (i.e., the 2016 condition). Our results indicated that salinity patterns are well-stratified at the beginning and end of the dry season but well-mixed during the middle period. Furthermore, over the last 25 years, SI has progressively increased and started earlier in the dry season. The modeling scenarios for SI have also revealed a growing complexity in the exploitation of freshwater resources, highlighting challenges related to timing, depth, and geographical location. The exceedance probability scenarios disclosed higher and deeper salinity intrusion along the channel in VMD, ranging from 50 % to 95 %. This poses significant limitations on the feasibility of freshwater exploitation throughout the Ben Tre Province. Under the current trajectory of climate change, the 2030 scenario anticipates salinity intrusion reaching further inland from the 2021 scenario. This is likely to exacerbate the existing challenges in freshwater resource exploitation, even with comprehensive water infrastructure. We, therefore, propose several management strategies to adapt to salinity intrusion: storing freshwater in main rivers, maintaining consistent operation of water infrastructure systems, and encouraging water-saving distribution and exploitation methods. Moreover, we also recommend supporting the development of new drought-tolerant crop patterns.

    Scopus© Citations 6  21
  • Publication
    Open Access
    Significant changes in cloud radiative effects over Southwestern United States during the COVID-19 flight reduction period
    (Elsevier, 2024) ;
    Lin, Yun
    ;
    Wang, Xianfeng
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    Gu, Yu
    ;
    Yim, Steven Hung-Lam
    Aircraft-induced clouds (AICs) are one of the most visible anthropogenic atmospheric phenomena, which mimic the natural cirrus clouds and perturb global radiation budget by reducing incoming shortwave (SW) radiation and trapping outgoing longwave (LW) radiation. The COVID-19 pandemic has caused a 70 % global decline in flight numbers from mid-March to October 2020, which provided a unique opportunity to examine the climatic impact of AICs. Among various regions, Western Europe and the Contiguous United States experienced the most substantial reduction in air traffic during the COVID-19 pandemic. Interestingly, only the Southwestern United States demonstrated a significant decrease in cirrus clouds, leading to notable changes in shortwave (SW) and longwave (LW) cloud radiative effects. Such changes were likely due to the reduction in AICs. However, further investigations indicated that this region also experienced abnormal high pressure and low relative humidity in the middle and upper atmosphere, resulting in unusual subsidence and dryness that prohibit the formation and maintenance of cirrus cloud. While it remains challenging to quantify the exact climatic impact of reduced AICs, the remarkable anomalies documented in this study provide valuable observational benchmark for future modelling studies of the climatic impact AICs.
    Scopus© Citations 1  70  344
  • Publication
    Metadata only
    Climatological occurrences of hail and tornadoes associated with mesoscale convective systems in the United States
    (European Geosciences Union, 2023) ;
    Fan, Jiwen
    ;
    Zhe, Feng

    Hail and tornadoes are hazardous weather events responsible for significant property damage and economic loss worldwide. The most devastating occurrences of hail and tornadoes are commonly produced by supercells in the United States. However, these supercells may also grow upscale into mesoscale convective systems (MCSs) or be embedded within them. The relationship between hail and tornado occurrences with MCSs in the long-term climatology has not been thoroughly examined. In this study, radar features associated with MCSs are extracted from a 14-year MCS tracking database across the contiguous United States, and hazard reports are mapped to these MCS features. We investigate the characteristics of hail and tornadoes in relation to MCSs, considering seasonal and regional variabilities. On average, 8 %–17 % of hail events and 17 %–32 % of tornado events are associated with MCSs, depending on the criteria used to define MCSs. The highest total and MCS-associated hazard events occur from March to May, while the highest MCS-associated portion (23 % for hail and 45 % for tornadoes) is observed in winter (December–February) due to the dominance of MCSs caused by strong synoptic forcing. As hailstone size increases, the fraction associated with MCS decreases, but there is an increasing trend for tornado severity from EF0 to EF3 (Enhanced Fujita Scale). Violent tornadoes at EF4 and EF5 associated with MCSs were also observed, which are generated by supercells embedded within MCSs.

    Scopus© Citations 1  47
  • Publication
    Embargo
    Influences of approaching tropical cyclones on water vapor and aerosols in the atmospheric boundary layer of Guangdong-Hong Kong-Macau Greater Bay Area of China
    (Elsevier, 2023)
    Huang, Tao
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    Li, Yubin
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    Lolli, Simone
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    Cheng, Jack Chin Ho
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    Lam, David Hok Yin
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    Leung, W. H.
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    Lee, Harry F.
    ;
    Yim, Steve H. L.
    WOS© Citations 1Scopus© Citations 1  65  1
  • Publication
    Open Access
    A 1940-2020 spatiotemporal analysis of thermal discomfort days in Southeast Asian countries
    (IOP Publishing, 2024)
    Wong, Meei Chyi
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    ;
    Zhi, Xiefei
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    Dong, Luojie
    The high temperature and humidity make Southeast Asia (SEA) one of the regions most susceptible to the occurrence of thermal discomfort days (TDDs) in the world. In the context of global warming, SEA's rapid population growth and urban expansion further exacerbated the region's exposure to TDD, posing greater risks in public health. However, there exists a significant knowledge gap in the understanding of the long-term spatiotemporal evolution of TDD, as well as its projection in the future. By utilizing the newly released ERA5 datasets of Universal Thermal Climate Index (UTCI) and Mean Radiant Temperature (MRT), this study presented the 81-year analysis of TDDs in SEA countries, spanning from 1940 to 2020, with projections extending to 2100. While the mean increase in UTCI was relatively modest, the corresponding rise in TDD likelihood was disproportionately larger, indicating a heightened risk of exposure. A distinct contrast was observed between continental and maritime regions, with maritime countries showing smaller absolute rises in both indices but larger trends in TDD frequency due to oceanic moderating effects. Seasonal analyses highlighted the dominant influence of the East Asia monsoon over SEA, and spatial analyses revealed a negative correlation between TDD occurrence and elevation, with low-lying areas being hotspots. Projections for 2050 suggest continued warming. These findings underscore the urgency of proactive measures to address climate change impacts, particularly in vulnerable maritime and low-lying areas, providing valuable insights for enhancing climate resilience and adaptation in SEA. Our findings reveal critical insights into the trends and future scenarios of thermal discomfort in the region, underscoring the urgent need for effective climate adaptation strategies.
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