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Inland waters are the main medium transporting microplastics to the ocean. Aggregation, vertical settlement, and horizontal transport will occur when microplastics enter the inland waterbodies. This paper reviews these behaviors of microplastics in inland waters and their influencing factors. The aggregation of microplastics were divided into homogeneous aggregation and heterogeneous aggregation, which are critical for the settlement of microplastics. The settlement of microplastics in inland water bodies is influenced by microplastic properties (size, density, and shapes) and environmental conditions (microorganisms, sedimental properties, hydraulic conditions, and so on). Horizontal transport of microplastics in water is influenced by hydrologic conditions, rainfall, river morphologies, dams, vegetation, etc. Future perspectives including laboratory simulations and numerical models involving multiple factors, the behaviors of degradable plastics, and the influence of hydrologic conditions have been proposed.

Algal blooms constitute an emerging threat to global inland water quality, yet their spatial and temporal distribution at the global scale remains largely unknown. Here we establish a global bloom database, using 2.91 million Landsat satellite images from 1982 to 2019 to characterize algal blooms in 248,243 freshwater lakes, representing 57.1% of the global lake area. We show that 21,878 lakes (8.8%) spread across six continents have experienced algal blooms. The median bloom occurrence of affected lakes was 4.6%, but this frequency is increasing; we found increased bloom risks in the 2010s, globally (except for Oceania). The most pronounced increases were found in Asia and Africa, mostly in developing countries that remain reliant on agricultural fertilizer. As algal blooms continue to expand in scale and magnitude, this baseline census will be vital towards future risk assessments and mitigation efforts. Algal blooms are occurring more frequently, as seen in a global database compiled from satellite imagery from the past few decades.

Inland water level and its dynamics are key components in the global water cycle and land surface hydrology, significantly influencing climate variability and water resource management. Satellite observations, in particular altimetry missions, provide inland water level time series for nearly three decades. Space-based remote sensing is regarded as a cost-effective technique that provides measurements of global coverage and homogeneous accuracy in contrast to in-situ sensors. The advent of Open-Loop Tracking Command (OLTC), and Synthetic Aperture Radar (SAR) mode strengthened the use of altimetry missions for inland water level monitoring. However, it is still very challenging to obtain accurate measurements of water level over narrow rivers and small lakes. This scoping systematic literature review summarizes and disseminates the research findings, highlights major results, and presents the limitations regarding inland water level monitoring from satellite observations between 2018 and 2022. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline and through a double screening process, 48 scientific publications were selected meeting the eligibility criteria. To summarize the achievements of the previous 5 years, we present fundamental statistical results of the publications, such as the annual number of publications, scientific journals, keywords, and study regions per continent and type of inland water body. Also, publications associated with specific satellite missions were analyzed. The findings show that Sentinel-3 is the dominant satellite mission, while the ICESat-2 laser altimetry mission has exhibited a high growth trend. Furthermore, publications including radar altimetry missions were charted based on the retracking algorithms, presenting the novel and improved methods of the last five years. Moreover, this review confirms that there is a lack of research on the collaboration of altimetry data with machine learning techniques.

Thailand is one of the largest contributors to plastic waste in the oceans. Since mismanaged plastic waste can enter the ocean via inland waterways, microplastic contamination in freshwater used for tap water production has been raised as a potential issue. This study was conducted to determine the abundance and characteristics of microplastics in freshwater and treated tap water in Bangkok. Freshwater and treated water were collected from the eastern and western water supply systems in the dry and wet seasons. The source waters of the eastern and western water supply systems are the Chao Phraya River and Maeklong River, respectively. Approximately 0.40–2.40 particles/L microplastics was determined in the freshwater samples. No significant differences in microplastic abundance with respect to water supply system or season were found. Approximately 82.1% of the total microplastics found in the freshwater were smaller than 300 µm in size. The percentage contribution of various microplastic size ranges decreased with increasing size. The majority of microplastics found in freshwater were fragments (90.2%), colorless (64.3%), and made of polyethylene polymer (45.1%). Only the eastern water supply system was capable of removing microplastic particles (27.7%) from freshwater. The identification of microplastics larger than 100 µm in size in the treated tap water indicated potential contamination from microplastics in the treatment system, particularly after the sand filtration unit. The major characteristics of the microplastics found in treated tap water were similar to those found in freshwater, with 85.6% fragments, 85.1% colorless, and 47.9% made of polyethylene polymer.

Accurate and frequent monitoring of inland water body levels is essential for water sources and their ecological protection and management. Water bodies such as natural lakes and manmade dams provide an ecological environment for endangered animals and endemic plants and serve as irrigation and water source for human activities. However, in situ measurements or fixed observation stations are not always available for small to large water bodies. Here, we investigate water level changes at a regional level where endangered endemic species live in the Ramsar site, a nationally protected park, and inland waters using the National Aeronautics and Space Administration’s Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) satellite launched in 2018. Most of the inland water bodies show high R 2 values ranging from 0.28 to 0.99 and the root mean square error values are widely distributed lower than 1 m. This study shows the potential and limitations of the new altimetry data source ICESat-2 ATL13 product for monitoring the long-term behavior of inland water reservoirs for sustainable monitoring. Graphical abstract

Both natural and anthropogenic processes can lead to the increasing salinity of surface waters. The knowledge about the ecological consequences of salinization on the biota is limited especially in case of microbiota, like diatoms. We collected the existing knowledge about the relationship between salinity and diatoms in fresh and saline waters. Based on the available papers, conductivity and ion composition are the most important variables shaping diatom communities. Secondary salinization can mask regional differences in diatom assemblages. Trait-based analyses highlight the competitive advantages of motile guild and the extreme trait categories in these environments. The increasing conductivity along a wide conductivity scale decreases the alpha-diversity. Salinization induces the spread and invasion of marine and brackish species into inland freshwaters as well as that of freshwater species tolerating elevated conductivity and/or need specific ions. Concerning food webs, salinity can directly change diatom communities and the subsequent upper trophic levels but most likely this effect manifests as a top-down regulation. Applicable diatom indices are available to assess the level of salinization. Furthermore, diatom-inferred salinity reconstructions are widely applied to assess the past changes of salinity. However, future models predicting ecological consequences of salinization are scarce and sometimes contradictory.

Due to its long-term and high-frequency observation capabilities, remote sensing is widely recognized as an indispensable and preferred technology for large-scale and cross-regional water quality monitoring. This paper comprehensively reviews the recent progress of remote sensing for water environment monitoring, predominantly focusing on remote sensing data sources, inversion indices, and inversion models. Specifically, we summarize the inversion methods for commonly monitored water quality parameters, including optically active constituents (such as chlorophyll-a, colored dissolved organic matter, total suspended solids, and water clarity) and non-optically active constituents (including total nitrogen, total phosphorus, and chemical oxygen demand). Furthermore, the applications of remote sensing in the field of environmental sciences such as spatiotemporal evolution and driver factor analysis of water quality, carbon budget research, and pollution source identification are also systematically reviewed. Finally, we propose that atmospheric correction algorithm improvement, multi-source data fusion, and high-precision large-scale inversion algorithms should be further developed to reduce the current dependence on empirical observation algorithms in remote sensing and overcome the limitations imposed by temporal and spatial scales and that more inversion models for non-optically active parameters should be explored to realize accurate remote sensing monitoring of these components in the future. This review not only enhances our understanding of the critical role of remote sensing in inland water quality monitoring but also provides a scientific basis for water environment management.

Water bodies (WBs), such as lakes, ponds, and impoundments, provide essential ecosystem services for human society, yet their characteristics and changes over large areas remain elusive. Here we used unprecedented data layers derived from all Landsat images available between 1984 and 2015 to understand the overall characteristics and changes of WBs between 2 epochs (i.e., 1984 to 1999 and 2000 to 2015) in China. Results show that the abundance estimate of WBs greater than 1 km² and the total WB surface area were 0.3 to 1.5 times and 0.2 to 0.5 times more than the previous estimates, respectively. The size-abundance and shoreline-area relationships of WBs in China conformed to the classic power scaling law, in contradiction to most previous studies. WB changes with various occurrence probabilities show widespread coexistence of disappearance of existent and emergence of new WBs across China driven primarily by human activities and climate change. Our results highlight the importance of using appropriate long-term satellite data to reveal the true properties and dynamics of WBs over large areas, which is essential for developing scaling theories and understanding the relative impacts of human activities and climate change on water resources in the world.

Because freshwater covers such a small fraction of the Earth's surface area, inland freshwater ecosystems (particularly lakes, rivers, and reservoirs) have rarely been considered as potentially important quantitative components of the carbon cycle at either global or regional scales. By taking published estimates of gas exchange, sediment accumulation, and carbon transport for a variety of aquatic systems, we have constructed a budget for the role of inland water ecosystems in the global carbon cycle. Our analysis conservatively estimates that inland waters annually receive, from a combination of background and anthropogenically altered sources, on the order of 1.9 Pg C y-¹ from the terrestrial landscape, of which about 0.2 is buried in aquatic sediments, at least 0.8 (possibly much more) is returned to the atmosphere as gas exchange while the remaining 0.9 Pg y-¹ is delivered to the oceans, roughly equally as inorganic and organic carbon. Thus, roughly twice as much C enters inland aquatic systems from land as is exported from land to the sea. Over prolonged time net carbon fluxes in aquatic systems tend to be greater per unit area than in much of the surrounding land. Although their area is small, these freshwater aquatic systems can affect regional C balances. Further, the inclusion of inland, freshwater ecosystems provides useful insight about the storage, oxidation and transport of terrestrial C, and may warrant a revision of how the modern net C sink on land is described.

The atmospheric contribution constitutes about 90 percent of the signal measured by satellite sensors over oceanic and inland waters. Over open ocean waters, the atmospheric contribution is relatively easy to correct as it can be assumed that water-leaving radiance in the near-infrared (NIR) is equal to zero and it can be performed by applying a relatively simple dark-pixel-correction-based type of algorithm. Over inland and coastal waters, this assumption cannot be made since the water-leaving radiance in the NIR is greater than zero due to the presence of water components like sediments and dissolved organic particles. The aim of this study is to determine the most appropriate atmospheric correction processor to be applied on Sentinel-2 MultiSpectral Imagery over several types of inland waters. Retrievals obtained from different atmospheric correction processors (i.e., Atmospheric correction for OLI ‘lite’ (ACOLITE), Case 2 Regional Coast Colour (here called C2RCC), Case 2 Regional Coast Colour for Complex waters (here called C2RCCCX), Image correction for atmospheric effects (iCOR), Polynomial-based algorithm applied to MERIS (Polymer) and Sen2Cor or Sentinel 2 Correction) are compared against in situ reflectance measured in lakes and reservoirs in the Valencia region (Spain). Polymer and C2RCC are the processors that give back the best statistics, with coefficients of determination higher than 0.83 and mean average errors less than 0.01. An evaluation of the performance based on water types and single bands–classification based on ranges of in situ chlorophyll-a concentration and Secchi disk depth values- showed that performance of these set of processors is better for relatively complex waters. ACOLITE, iCOR and Sen2Cor had a better performance when applied to meso- and hyper-eutrophic waters, compare with oligotrophic. However, other considerations should also be taken into account, like the elevation of the lakes above sea level, their distance from the sea and their morphology.