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Wu Y, Wang H, Deng Y, Li X, Xu H. Suspended sediment dynamics and the related environmental risk assessment in a sensitive water area. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 917:170627. [PMID: 38311078 DOI: 10.1016/j.scitotenv.2024.170627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 01/15/2024] [Accepted: 01/31/2024] [Indexed: 02/06/2024]
Abstract
Suspended sediment (SS) is a natural component of aquatic environments. It is characterized by the adsorption of pollutants, and its physical properties can affect water volume quality. In this study, SS dynamics were simulated using a 2D hydrodynamic model in the Nanji Mountain Nature Reserve (NNR), and the fluxes of pollutants caused by SS were calculated to assess the biological risks during the wet (May-August) and dry (November-March) seasons. High spatial and temporal variability in SS load within the NNR was found in this study. The average SS load in the reserve increased and then decreased during the year, and the SS input from Ganjiang significantly affected the SS load in the NNR (p < 0.01). The SS load uptrend in the NNR occurred later than that of Ganjiang during the wet season because of the SS sedimentation in the NNR. And the suspension of SS in the NNR during the dry season resulted in a later SS load downtrend compared to Ganjiang. High SS load from Ganjiang during the wet season was responsible for the high nutrient and microplastic fluxes in the NNR, which were 8.38 and 10.61 times higher than those in the dry season, respectively. And the pollutant fluxes during the wet season were almost all from Ganjiang. In contrast, higher waterbird diversity and population during the dry season is the main reason for the increased biological risk of contaminants. Therefore, monitoring and managing SS and its contamination concentrations in rivers entering the lake is helpful for the protection of ecologically sensitive areas and key species in the lake.
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Affiliation(s)
- Yi Wu
- Key Laboratory of Integrated Regulation and Resource Development on Shallow Lake of Ministry of Education, College of Environment, Hohai University, Nanjing 210098, China; College of Environment, Hohai University, Nanjing 210098, China
| | - Hua Wang
- Key Laboratory of Integrated Regulation and Resource Development on Shallow Lake of Ministry of Education, College of Environment, Hohai University, Nanjing 210098, China; College of Environment, Hohai University, Nanjing 210098, China.
| | - Yanqing Deng
- Water Quality Department, Jiangxi Hydrological Bureau, Nanchang 330000, China and Key Laboratory of Hydrological and Ecological Monitoring of Poyang Lake, Nanchang 330000, China
| | - Xiaoying Li
- Key Laboratory of Integrated Regulation and Resource Development on Shallow Lake of Ministry of Education, College of Environment, Hohai University, Nanjing 210098, China; College of Environment, Hohai University, Nanjing 210098, China
| | - Haosen Xu
- Key Laboratory of Integrated Regulation and Resource Development on Shallow Lake of Ministry of Education, College of Environment, Hohai University, Nanjing 210098, China; College of Environment, Hohai University, Nanjing 210098, China
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The Dynamic Changes of Lake Issyk-Kul from 1958 to 2020 Based on Multi-Source Satellite Data. REMOTE SENSING 2022. [DOI: 10.3390/rs14071575] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Lake Issyk-Kul is the largest alpine lake in arid Central Asia. In recent years, the lake has become a subject of special concern due to the dramatic fluctuations in its water level. In this study, the long-term continuous changes in the water level of Lake Issyk-Kul were derived from hydro-meteorological stations, CryoSat-2, and ICESat-2 satellites. Changes in area were analyzed by the Joint Research Centre (JRC) Global Surface Water (GSW) dataset based on the Google Earth Engine and the variations in water volume were estimated by an empirical formula. The results indicate that the water level of Lake Issyk-Kul fluctuated between 1606.06 m and 1608.32 m during 1958–2020, showing a slight decrease of 0.02 m/year on average. The water level first experienced a significant decreasing trend of 0.05 m/year from 1958 to 1998, and then began to rise rapidly by 0.10 m/year during 1998–2006, followed by a fluctuating decline after 2006. The area of Lake Issyk-Kul exhibited a downward trend before 1998, then a rapid expansion during 1998–2006, and short-term fluctuations in decline thereafter. Meanwhile, changes in water volume of Lake Issyk-Kul followed a similar pattern of variations in water level and area. According to comprehensive analyses, the continuous downward trend of the water level before 1998 was primarily affected by substantial anthropogenic water consumption in the basin. However, since the 21st century, the increases in precipitation and glacier meltwater and the reduced water consumption have collectively facilitated the short-term recovery of Lake Issyk-Kul in water level, area, and water volume.
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Surface Water Storage in Rivers and Wetlands Derived from Satellite Observations: A Review of Current Advances and Future Opportunities for Hydrological Sciences. REMOTE SENSING 2021. [DOI: 10.3390/rs13204162] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Surface water storage (SWS), the amount of freshwater stored in rivers/wetlands/floodplains/lakes, and its variations are key components of the water cycle and land surface hydrology, with strong feedback and linkages with climate variability. They are also very important for water resources management. However, it is still very challenging to measure and to obtain accurate estimates of SWS variations for large river basins at adequate time/space sampling. Satellite observations offer great opportunities to measure SWS changes, and several methods have been developed combining multisource observations for different environments worldwide. With the upcoming launch in 2022 of the Surface Water and Ocean Topography (SWOT) satellite mission, which will provide, for the first time, direct estimates of SWS variations with an unprecedented spatial resolution (~100 m), it is timely to summarize the recent advances in the estimates of SWS from satellite observations and how they contribute to a better understanding of large-scale hydrological processes. Here, we review the scientific literature and present major results regarding the dynamic of surface freshwater in large rivers, floodplains, and wetlands. We show how recent efforts have helped to characterize the variations in SWS change across large river basins, including during extreme climatic events, leading to an overall better understanding of the continental water cycle. In the context of SWOT and forthcoming SWS estimates at the global scale, we further discuss new opportunities for hydrological and multidisciplinary sciences. We recommend that, in the near future, SWS should be considered as an essential water variable to ensure its long-term monitoring.
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Using Multisource Satellite Data to Investigate Lake Area, Water Level, and Water Storage Changes of Terminal Lakes in Ungauged Regions. REMOTE SENSING 2021. [DOI: 10.3390/rs13163221] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Lake area, water level, and water storage changes of terminal lakes are vital for regional water resource management and for understanding local hydrological processes. Nevertheless, due to the complex geographical conditions, it is difficult to investigate and analyze this change in ungauged regions. This study focuses on the ungauged, semi-arid Gahai Lake, a typical small terminal lake in the Qaidam Basin. In addition to the scant observed data, satellite altimetry is scarce for the excessively large fraction of outlier points. Here, we proposed an effective and simple algorithm for extracting available lake elevation points from CryoSat-2, ICESat-2 and Sentinel-3. Combining with the area data from Landsat, Gaofen (GF), and Ziyuan (ZY) satellites, we built an optimal hypsographic curve (lake area versus water level) based on the existing short-term data. Cross-validation was used to validate whether the curve accurately could predict the lake water level in other periods. In addition, we used multisource high-resolution images including Landsat and digital maps to extract the area data from 1975 to 2020, and we applied the curve to estimate the water level for the corresponding period. Additionally, we adopted the pyramidal frustum model (PFM) and the integral model (IM) to estimate the long-term water storage changes, and analyzed the differences between these two models. We found that there has been an obvious change in the area, water level, and water storage since the beginning of the 21st century, which reflects the impact of climate change and human activities on hydrologic processes in the basin. Importantly, agricultural activities have caused a rapid increase in water storage in the Gahai Lake over the past decade. We collected as much multisource satellite data as possible; thus, we estimated the long-term variations in the area, water level, and water storage of a small terminal lake combining multiple models, which can provide an effective method to monitor lake changes in ungauged basins.
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Recent Advancement in Remote Sensing Technology for Hydrology Analysis and Water Resources Management. REMOTE SENSING 2021. [DOI: 10.3390/rs13061097] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Water is undoubtedly the most valuable resource of human society and an essential component of the ecosystem [...]
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Implementation of an Improved Water Change Tracking (IWCT) Algorithm: Monitoring the Water Changes in Tianjin over 1984–2019 Using Landsat Time-Series Data. REMOTE SENSING 2021. [DOI: 10.3390/rs13030493] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Tianjin is the largest open city along the coastline in Northern China, which has several important wetland ecosystems. However, no systematic study has assessed the water body changes over the past few decades for Tianjin, not to mention their response to human activities and climate change. Here, based on the water change tracking (WCT) algorithm, we proposed an improved water change tracking (IWCT) algorithm, which could remove built-up shade noise (account for 0.4%~6.0% of the final water area) and correct omitted water pixels (account for 1.1%~5.1% of the final water area) by taking the time-series data into consideration. The seasonal water product of the Global Surface Water Data (GSWD) was used to provide a comparison with the IWCT results. Significant changes in water bodies of the selected area in Tianjin were revealed from the time-series water maps. The permanent water area of Tianjin decreased 282.5 km2 from 1984 to 2019. Each time after the dried-up period, due to government policies, the land reclamation happened in Tuanbo Birds Nature Reserve (TBNR), and, finally, 12.6 km2 of the lake has been reclaimed. Meanwhile, 488.6 km2 of land has been reclaimed from the sea along the coastal zone in the past 16 years at a speed of 28.74 km2 yr−1 in the Binhai New Area (BHNA). The method developed in this study could be extended to other sensors which have similar band settings with Landsat; the products acquired in this study could provide fundamental reference for the wetland management in Tianjin.
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Potential and Limitations of Satellite Altimetry Constellations for Monitoring Surface Water Storage Changes—A Case Study in the Mississippi Basin. REMOTE SENSING 2020. [DOI: 10.3390/rs12203320] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Remote sensing data are essential for monitoring the Earth’s surface waters, especially since the amount of publicly available in-situ data is declining. Satellite altimetry provides valuable information on the water levels and variations of lakes, reservoirs and rivers. In combination with satellite imagery, the derived time series allow the monitoring of lake storage changes and river discharge. However, satellite altimetry is limited in terms of its spatial resolution due to its measurement geometry, only providing information in the nadir direction beneath the satellite’s orbit. In a case study in the Mississippi River Basin (MRB), this study investigates the potential and limitations of past and current satellite missions for the monitoring of basin-wide storage changes. For that purpose, an automated target detection is developed and the extracted lake surfaces are merged with the satellites’ tracks. This reveals that the current altimeter configuration misses about 80% of all lakes larger than 0.1 km2 in the MRB and 20% of lakes larger than 10 km2, corresponding to 30% and 7% of the total water area, respectively. Past altimetry configurations perform even more poorly. From the larger water bodies represented by a global hydrology model, at least 91% of targets and 98% of storage changes are captured by the current altimeter configuration. This will improve significantly with the launch of the planned Surface Water and Ocean Topography (SWOT) mission.
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