Surface Water Distribution Research Articles

Practical drought risk assessment and management framework: A step toward sustainable modernization in agricultural water management

A proposed framework to assess and manage risks associated with Agricultural Water Off-farm Conveyance and Distribution Systems (AWOCDS), quantify potential failure due to drought-induced scenarios, and provide short to long-term recovery plans to mitigate drought impacts. It makes an intellectual contribution by creating a new proactive risk assessment focusing specifically on AWOCDS as a crucial part of agricultural water management. The risk assessment comprises two components − risk probability and consequence. The former is calculated by analyzing droughts via the streamflow drought index using the DrinC calculator. The latter is determined through AWOCDS’ performance evaluation using hydraulic simulation via HEC-RAS. Additionally, water distribution is assessed spatiotemporally using adequacy and equity indicators, and an integrated consequence is developed by applying the simple additive weighting method. AWOCDS’ rehabilitation and modernization projects worldwide include three practical practices in its risk management component. These practices involve modifying standard operating procedures (SOPs) by updating maintenance, upgrading manual-based operations, and developing a centralized Model Predictive Controller (MPC) for AWOCDS automatic operation. The proposed framework underwent testing in an arid region. Based on the risk assessment results, the AWOCDS operating system failure rate ranges from 70% to 96% during extreme-severe drought scenarios and 53% to 65% during moderate-mild drought scenarios. Risk management analysis shows that a short-term recovery plan reduces the drought risk by 4% monthly and 3% yearly. However, the risk of failure ranges from 50 to 94% in mild to extreme drought scenarios. Upgrading SOPs decreases impact by 4–11% in extreme, 4–7% in moderate-severe and 7–9% in mild-moderate drought. Automating the operating system with MPC reduces impact by 40–43% and 30–56% in mild-moderate and severe-extreme drought scenarios. This proactive-based strategy can help water managers plan for rehabilitation and improve surface water distribution reliability.

A novel method to estimate the 3D chlorophyll a distribution in the South China Sea surface waters using hydrometeorological parameters

Chlorophyll a (Chl-a) is a key indicator of marine ecosystems, and certain hydro-meteorological parameters (HMPs) are highly correlated with its fluctuations. Here, relevant and accessible HMPs were used as inputs, combined with machine learning (ML) algorithms for estimating 3D Chl-a in the South China Sea (SCS). With the inputs of temperature, salinity, depth, wind speed, wind direction, sea surface pressure, and relative humidity, the LightGBM-based model performed well, achieving high R2 values of 0.985 and 0.789 in validation and testing sets, respectively. Based on a large number of in situ measurements, this model enables the estimation of the 3D distribution of summer Chl-a in the SCS over the past fifteen years using a 3D hydrographic dataset combined with surface meteorological parameters. The results show that the 3D distribution of the model estimated Chl-a is characterized similarly to the previous studies and can capture the effect of hydro-meteorological conditions on Chl-a distribution. The environmental variables affecting Chl-a were considered more comprehensively in this study, and the methodological framework has the potential to be applied to the low-cost monitoring of the remaining water quality parameters.

Are regional groundwater models suitable for simulating wetlands, rivers and intermittence? The example of the French AquiFR platform

Predicting and managing water resources at regional scale under different climate and socio-economic scenarios is crucial to support drinking water supply and other sectors. At the same time, protecting rivers and wetlands from pollutions and droughts is essential and must include groundwater given its contribution to surface water. Yet, assessing temporal and spatial variability of groundwater contributions to surface water is constrained due to limited observations. This study aims to quantify the spatio-temporal distribution of groundwater discharge (hereafter called “GW discharge”) zones, i.e. the groundwater flow to rivers and wetlands, estimated by calibrated regional groundwater flow models (French AquiFR platform). We compare simulation results with two types of surface observations: (i) the spatial distribution of surface water (BD TOPO, RAMSAR and Natura 2000 database) and (ii) an innovative datasets, the river intermittence observed in headwaters (ONDE network). Results show that simulated GW discharge zones are consistent with the observed location of rivers and wetlands. Time variations in GW discharge are well correlated with the intermittence observed at 396 of the 515 selected stations. Of these, groundwater model continues to feed surface water upstream of the station for ∼75 % of observed river drying up events, which may be consistent with a small alluvial flow. The groundwater withdrawals are shown to have a strong impact on the GW discharge and thus on the river intermittence.

A dataset of annual surface water distribution in the Yellow River Basin (1986–2023)

A dataset of annual surface water distribution in the Yellow River Basin (1986–2023)

A dynamic surface water extent service for Africa developed through continental-scale collaboration

Spatially explicit, near real time information on surface water dynamics is critical for understanding changes in water resources, and for long-term water security planning. The distribution of surface water across the African continent since 1984 and updated as every new Landsat scene becomes available is presented here, and validated for the continent for the first time. We applied the Water Observations from Space (WOfS) algorithm, developed and well-tested in Australia, to every Landsat scene acquired over Africa since the mid 1980s to provide spatial information on surface water dynamics over the past 30+ years. We assessed the accuracy of WOfS using aerial and satellite imagery. Four regional geospatial organisations, coordinated through the Digital Earth Africa Product Development Task Team, conducted the validation campaign and provided both the regional expertise and experience required for a continental-scale validation effort. We assessed whether the point was wet, dry, or cloud covered, for each of the 12 months in 2018, resulting in 34,800 labelled observations. As waterbodies larger than 100 km2 are easy to identify with Landsat resolution data and can thus boost accuracy, these were masked out. The resulting overall accuracy of the water classification was 82%. WOfS in Africa is expected to be used by ministries and departments of agriculture and water across the continent, by international organisations, academia, and the private sector. A large-scale collaborative effort, which included regional and technical skills spanning two continents was required to create a service that is regionally accurate and is both hosted on, and implemented operationally from, the African continent.

Surface water monitoring from 1984 to 2021 based on Landsat time-series images and Google Earth Engine

Dynamic monitoring of surface water bodies is essential for understanding global climate change and the impact of human activities on water resources. Satellite remote sensing is characterized by large-scale monitoring, timely updates, and simplicity, and it has become an important means of obtaining the distribution of surface water bodies. This study is based on a long time-series Landsat satellite images and the Google Earth Engine (GEE) platform, focusing on Anhui Province in China, and proposes a method for extracting surface water that combines water indices, Bias-Corrected Fuzzy Clustering Method (BCFCM), and OTSU threshold segmentation. The spatial distribution of surface water in Anhui Province was obtained from 1984 to 2021, and further analysis was conducted on the spatiotemporal characteristics of surface water in each city and three major river basins within the province. The results indicated that the overall accuracy of water extraction in this study was 94.06 %. Surface water in Anhui was most abundant in 1998 and least in 2001, with more distribution in the south than in the north. Northern Anhui is dominated by rivers, while southern Anhui has more lakes. Permanent surface water with an inundation frequency of above 75 % covered approximately 4341 km2, accounting for 32.03 % of the total water, while seasonal water with an inundation frequency between 5 % and 75 % covered about 6661 km2, accounting for 49.15 % of the total water, others were considered temporary surface water. By comparing our results with the global annual surface water released by the Joint Research Centre (JRC), we found that our study performed better in extracting lakes and rivers in terms of completeness, but the extraction results for aquaculture areas were slightly less than the JRC dataset. Overall, the long-term surface water dataset established in this study can effectively supplement the existing datasets and provide important references for regional water resource investigation, management, as well as flood monitoring.

Heavy Metal Distribution and Health Risk Assessment in Groundwater and Surface Water of Karst Lead–Zinc Mine

Heavy Metal Distribution and Health Risk Assessment in Groundwater and Surface Water of Karst Lead–Zinc Mine

Statistical and geospatial assessment of trace and toxic elements distribution in ground and surface water of northern parts of the Indo-Gangetic plains: Source identification and health risk assessment

This study focusses on ground and surface water resources in the northern parts of the Indo-Gangetic Plains. The study aims to identify potential contaminants, analyse their distribution, trace their origins, and evaluate associated health risk. Samples from 80 locations; groundwater (n = 69) and surface water (n = 11) were analysed for nineteen trace and toxic elements using ICP-MS. Eight elements in groundwater (Mn, Fe, Ni, Zn, As, Tl, U and Se) and six in surface water (Al, Mn, Fe, Ni, Zn, and Tl) exceeded WHO (2011) and BIS (2012) limits in certain areas. The geospatial analysis reveals hotspots of trace and toxic element concentration, with higher levels detected in the southeast and western regions of the study area. Correlation matrices revealed a robust correlation (∼>0.75–0.99, p < 0.01) among all trace and toxic elements (excluding Li, Be, As, Ag, and U) in surface water samples when compared to groundwater samples. Cluster analysis and principal component analysis (PCA) (explains 70.09 cumulative percent for total 6 of factors) of groundwater chemistry indicates that Zn, Ni and Tl contamination may originate from industrial activities (metallurgical processes and manufacturing). The potential sources of Mn may be both geological and human-induced, while Fe, Se, As and U can originate from specific geological formations or human-related activities like over-extraction and leaching of excess fertilizers into aquifers. For surface water, PCA (explains 92.92 cumulative percent for total 5 of factors) identifies industrial activities as the main source of Mn, Fe, Tl, Ni, and Zn, while Al originates from both geological and anthropogenic sources. The water quality index indicated poor to very poor water quality in the western and central regions, whereas the northern and eastern regions exhibited excellent water quality. Health risk assessment reveals HI values for groundwater water: 3.85 (adults), 7.70 (children); surface water: 1.52 (adults), 3.05 (children), emphasizing the urgent need for remediation measures.

SwinDefNet: A Novel Surface Water Mapping Model in Mountain and Cloudy Regions Based on Sentinel-2 Imagery

Surface water plays a pivotal role in the context of climate change, human activities, and ecosystems, underscoring the significance of precise monitoring and observation of surface water bodies. However, the intricate and diverse nature of surface water distribution poses substantial challenges to accurate mapping. The extraction of water bodies from medium-resolution satellite remote sensing images using CNN methods is constrained by limitations in receptive fields and inadequate context modeling capabilities, resulting in the loss of boundary details of water bodies and suboptimal fusion of multi-scale features. The existing research on this issue is limited, necessitating the exploration of novel deep-learning network combinations to overcome these challenges. This study introduces a novel deep learning network combination, SwinDefNet, which integrates deformable convolution and Swin Transformer for the first time. By enhancing the effective receptive field and integrating global semantic information, the model can effectively capture the diverse features of water bodies at various scales, thereby enhancing the accuracy and completeness of water extraction. The model was evaluated on Sentinel-2 satellite images, achieving an overall accuracy of 97.89%, an F1 score of 92.33%, and, notably, an accuracy of 98.03% in mountainous regions. These findings highlight the promising potential of this combined approach for precise water extraction tasks.

Legacy and alternative perfluoroalkyl acids in the Yellow River on the Qinghai-Tibet Plateau: Levels, spatiotemporal characteristics, and multimedia transport processes

The source region of the Yellow River (SRYR) located in the northeast of the Qinghai-Tibetan Plateau is not only the largest runoff-producing area in the Yellow River Basin, but also the most important freshwater-supply ecological function area in China. In this study, the short-term spatiotemporal distribution of selected legacy and alternative perfluoroalkyl acids (PFAAs) in the SRYR was first investigated in multiple environmental media. Total PFAA concentrations were in the range of 1.16-14.3 ng/L, 4.25-42.1 pg/L, and 0.21-13.0 pg/g dw in rainwater, surface water, and sediment, respectively. C4-C7 PFAAs were predominant in various environmental matrices. Spatiotemporal characteristics were observed in the concentrations and composition profiles. Particularly, the spatial distribution of rainwater and the temporal distribution of surface water exhibited highly significant differences (p<0.01). Indian monsoon, westerly air masses, and local mountain-valley breeze were the driving factors that contributed to the change of rainwater. Rainwater, meltwater runoff, and precursor degradation were important sources of PFAA pollution in surface water. Organic carbon content was a major factor influencing PFAA distribution in sediment. These results provide a theoretical basis for revealing the regional transport and fate of PFAAs, and are also important prerequisites for effectively protecting the freshwater resource and aquatic environment of the Qinghai-Tibetan Plateau.

Diversity, abundance, and expression of proteorhodopsin genes in the northern South China Sea

Proteorhodopsins have been suggested as an important strategy among phototrophs to capture solar energy in marine environments. The goals of this study was to investigate the diversity of proteorhodopsin genes and to explore their abundance, distribution, and expression in the coastal surface waters of the northern South China Sea, one of the largest marginal seas of the western North Pacific Ocean. Using 21 metagenomes, we recovered proteorhodopsin genes from a wide range of prokaryotic taxa, and chlorophyll a contributed significantly to the community composition of proteorhodopsin-containing microbes. Most proteorhodopsin sequences were predicted to encode green light-absorbing proton pumps and green light-absorbing proteorhodopsin genes were more abundant than blue-absorbing ones. The variations in the conserved residues involved in ion pumping and several uncharacterized proteorhodopsins were observed. The gene abundance pattern of proteorhodopsin types were significantly influenced by the levels of total organic carbon and soluble reactive phosphorus. Gene expression analysis confirmed the importance of proteorhodopsin-based phototrophy and revealed different expressional patterns among major phyla. In tandem, we screened 2295 metagenome-assembled genomes to describe the taxonomic distribution of proteorhodopsins. Bacteroidota are the key lineages encoding proteorhodopsins, but proteorhodopsins were predicated from members of Proteobacteria, Marinisomatota, Myxococcota, Verrucomicrobiota and Thermoplasmatota. Our study expanded the diversity of proteorhodopsins and improve our understanding on the significance of proteorhodopsin-mediated phototrophy in the marine ecosystem.

Global WaterPack - The development of global surface water over the past 20 years at daily temporal resolution

Open surface water across the globe is essential for many life forms and is an important source for human settlements, agriculture, and industry. The presence and variation in time and space is influenced by different natural conditions (e.g. climate, topography, geology) and human use (e.g. irrigation, flood protection). The information on the spatial and temporal distribution of open surface water is fundamental for many disciplines and is also required as an essential parameter for hydrological and climatological modelling. Here, we present a dataset derived from satellite earth observation, which is based on more than 6.3 million single MODIS products with a volume of approx. 300 TB. The resulting dataset reflects the situation of open surface water on a global scale for each day over the time period from 2003 to 2022 at a spatial resolution of 250 m. The dataset enables the analysis of the development of lake and reservoir surface areas, freezing cycles, and inundation areas.

Occurrence, spatiotemporal distribution and risks of macrolide antibiotics in the Weihe River and its tributaries, North-central China

The presence of antibiotics as emerging micropollutants in the aquatic environment has been raising health concerns for a number of years. Macrolides (MLs) are a large class of widely-used antibiotics, but there is a lack of information on their distribution and risks in surface waters across the central and western regions of China. To clearly describe the pollution characteristics and risks of MLs in Weihe River (the largest tributary of the Yellow River), analysis of 5 typical MLs was conducted using a newly developed LC−MS/MS method for 50 water samples collected over three seasons during 2021–2022. The results revealed that the area showed comparable ML concentrations with other regions worldwide. However, the ML concentrations were much lower than those in the river during 2016 from a previous study. Furthermore, concentrations exhibited significant seasonal variation, with highest concentrations in the winter. Along the main stream of the Weihe River, the sampling sites close to the wastewater treatment plants (WWTPs) and livestock farms exhibited higher concentrations of MLs, indicating the significant contribution from WWTPs and animal husbandry to the emission of MLs. The risk quotients (RQs) suggested that the ecological risks associated with MLs were most pronounced in winter among the three seasons, with erythromycin posing a high or medium risk to algae at all sampling sites. The results of this study will be of importance towards the goal of understanding the presence of these emerging contaminants in surface waters and any required risk reduction measures.

Beneficial ‘inefficiencies’ of western ranching: Flood-irrigated hay production sustains wetland systems by mimicking historic hydrologic processes

Ranching in the American West has long relied on riparian ecosystems to grow grass-hay to feed livestock in winter and during drought. Producers seasonally flood grasslands for hay production using stream diversions and low-tech flood-irrigation on riparian floodplains. Inundation mimics natural processes that sustain riparian vegetation and recharge groundwater. The recent doubling in use of more efficient irrigation approaches, such as center-pivot sprinklers, threatens to accelerate climate change impacts by unintentionally decoupling more inefficient, traditional practices that sustain riparian systems. To assess ecosystem services provided by flood-irrigation hay production, we developed an exhaustive spatial inventory of grass-hay production and combined it with monthly surface water distributions modeled from satellite data. Surface water data were classified by wetland hydroperiod and used to estimate the proportion of wetlands supported by grass-hay production in the Intermountain West, USA. Elevation and proportion of grass-hay relative to other irrigated lands were enumerated to examine differences in their positions and abundance within landscapes. Lastly, we overlaid the delineated grass-hay wetlands with LANDFIRE pre-Euro-American Settings layer to quantify the efficacy of flood irrigation in mimicking the conservation of historical riparian processes. Findings suggest that inefficient grass-hay irrigation mirrored the timing of natural hydrology, concentrating ∼93% of flooded grasslands in historical riparian ecosystems, affirming that at large scales, this ranching practice, in part, mimics floodplain processes sustaining wetlands and groundwater recharge. Despite representing only 2.5% of irrigated lands, grass-hay operations supported a majority (58%) of temporary wetlands, a rare and declining habitat for wildlife in the Intermountain West. Tolerance for colder temperatures confined grass-hay production to upper watershed reaches where higher value crops are constrained by growing degree days. This novel understanding of grass-hay agroecology highlights the vital role of working ranches in the resilience and stewardship of riparian systems.

Effects of cupric ions on the formation of chlorinated disinfection byproducts from nitrophenol compounds during UV/post-chlorination

Cupric ions (Cu2+) are ubiquitous in surface waters and can influence disinfection byproducts (DBPs) formation in water disinfection processes. This work explored the effects of Cu2+ on chlorinated DBPs (Cl-DBPs) formation from six representative nitrophenol compounds (NCs) during UV irradiation followed by a subsequent chlorination (i.e., UV/post-chlorination), and the results showed Cu2+ enhanced chlorinated halonitromethane (Cl-HNMs) formation from five NCs (besides 2-methyl-3-nitrophenol) and dichloroacetonitrile (DCAN) and trichloromethane (TCM) formation from six NCs. Nevertheless, excessive Cu2+ might reduce Cl-DBPs formation. Increasing UV fluences displayed different influences on total Cl-DBPs formation from different NCs, and increasing chlorine dosages and NCs concentrations enhanced that. Moreover, a relatively low pH (5.8) or high pH (7.8) might control the yields of total Cl-DBPs produced from different NCs. Notably, Cu2+ enhanced Cl-DBPs formation from NCs during UV/post-chlorination mainly through the catalytic effect on nitro-benzoquinone production and the conversion of Cl-DBPs from nitro-benzoquinone. Additionally, Cu2+ could increase the toxicity of total Cl-DBPs produced from five NCs besides 2-methyl-3-nitrophenol. Finally, the impacts of Cu2+ on Cl-DBPs formation and toxicity in real waters were quite different from those in simulated waters. This study is conducive to further understanding how Cu2+ affected Cl-DBPs formation and toxicity in chlorine disinfection processes and controlling Cl-DBPs formation in copper containing water.

Fractal evolution model of proton spatial distribution in low water/binder cement-based composites (LW/B-CC) during early-age hydration process

This study establishes the fractal evolution model of proton spatial distribution in low water/binder cement-based composites (LW/B-CC) based on fractal theory and low field nuclear magnetic resonance (LF NMR) technology. The results show that the fractal evolution process of gel water, capillary water and surface water distributions in LW/B-CC presents three stages: the first 4–6 h after the beginning of hydration, 4–6 h to 12 h, and 12 h to long-term stage. In the first and second stages, the fractal dimensions of gel and capillary water increase linearly with hydration time, while the fractal dimension of surface water decreases linearly. The boundary is a sudden change of fractal dimensions after about 4–6 h of hydration. The third stage starts after about 12 h of hydration, at which time the fractal dimensions begin to converge to fixed values. Besides, this study reveals the mathematical relationship between fractal dimension (Df) and particle size distribution modulus (q), which is conducive to achieve the full-cycle regulation of LW/B-CC.

Increasing seasonal variation in the extent of rivers and lakes from 1984 to 2022

Abstract. Knowledge of the spatial and temporal distribution of surface water is important for water resource management, flood risk assessment, monitoring ecosystem health, constraining estimates of biogeochemical cycles and understanding our climate. While global-scale spatiotemporal change detection of surface water has significantly improved in recent years due to planetary-scale remote sensing and computing, it has remained challenging to distinguish the changing characteristics of rivers and lakes. Here we analyze the spatial extent of permanent and seasonal rivers and lakes globally over the past 38 years based on new data of river system extents and surface water trends. Results show that while the total permanent surface area of both rivers and lakes has remained relatively constant, the areas with intermittent seasonal coverage have increased by 12 % and 27 % for rivers and lakes, respectively. The increase is statistically significant in over 84 % of global water catchments based on Spearman's rank correlations (rho) above 0.05 and p values less than 0.05. The seasonal river extent is nearly 32 % larger than the previously observed annual mean river extent, suggesting large seasonal variations that impact not only ecosystem health but also estimations of terrestrial biogeochemical cycles of carbon. The outcomes of our analysis are shared as the Surface Area of Rivers and Lakes (SARL) database, serving as a valuable resource for monitoring and research of hydrological cycles, ecosystem accounting, and water management.

Characteristics and Influence Rules of Roadside Ponding along the Qinghai–Tibet Highway

Due to climate change and seasonal precipitation, water conditions in the Qinghai–Tibet region are a significant factor affecting the stability of subgrades. The accumulation of large amounts of surface water leads to subgrade diseases along the Qinghai–Tibet Highway. Based on remote sensing photos obtained from Google Earth Engine and processing the photos using ENVI 5.6.3 and CAD 2019 software, this paper analyzed the distribution characteristics of surface water and studied the impact of roadside ponding on subgrade diseases. The results showed that the total area of surface water was more than 3.7 million m2, and the surface water was most widely distributed in large river areas such as the Tuotuo River and Buqu River. The subgrade diseases of the Qinghai–Tibet Highway could be categorized into three types: settlement, longitudinal crack, and frost boiling, which accounted for 71.09%, 17.13%, and 11.78% of the total number of subgrade diseases, respectively. Additionally, the ground mean annual temperature was an important factor affecting the distribution of surface water, with the surface water area showing an increasing trend with the increase in ground mean annual temperature, and roadside ponding was most likely to form in the high-temperature extremely unstable permafrost area.

Modeling of Soil Water Distribution in a Small Mid-Latitude Watershed on the British Isle for Short Term Landslide and Flood Risk Assessment

The R-TopModel hydrological model coupled with two landslide and flood probability distribution models was applied to simulate the daily hydrological conditions of a small catchment in the Midlands of the British Isles, throughout 2017. Originally, the methodology was applied to a risk area in the tropical region. In this work, the application was extended to mid-latitude watersheds. The hydrographic basin around the Carsington Water dam (located in the Midlands of the Great Britain) is chosen because it presents risks. The model Nash-Sutcliffe Efficiency for the upstream discharge from the Carsington Water dam reached 50% with a correlation coefficient of the order of 70%, an acceptable value considering the seasonal effects of the dam on evapotranspiration and higher soil permeability. Modeling the distribution of soil moisture and excess surface water allowed obtaining the spatial distribution of the maximum conditional probability of landslides and floods in the Carsington Water catchment. These probability maps obtained are consistent with long-term susceptibility maps for Great Britain.

Microplastics abundance, distribution and composition in surface waters, sediments and fish species from Amir-Kalayeh Wetland, Northern Iran.

Microplastics (MPs) pollution is considered as a globally pervasive threat to aquatic ecosystems and many studies reported this pollution in different aquatic ecosystems. However, studies on MPs pollution in wetlands are still scarce. Therefore, the aim of present study was to investigate the presence of MPs in the surface water, sediment and different fish species of Amir-Kalayeh wetland, Northern Ian. Surface water and sediment samples were collected from six stations during June to July 2022. Moreover, the gills and gastrointestinal tract (GIT) of 54 fish specimens belonging to four species including Cyprinus carpio, Tinca tinca, Esox lucius and Silurus glanis were analysed. MPs were detected in all samples with an average of 2.15 ± 1.98 items/m3 for surface water, 51.66 ± 32.20 items/kg dry weight for sediments, 0.17 ± 0.17 items/individual for fish GIT and 0.12 ± 0.12 items/individual for fish gills. There was no significant relationship between MPs abundance in surface waters and sediments as well as between MPs abundance in environmental matrices and fish (P > 0.0.5). In terms of feeding habit, no significant differences were observed between the number of MPs found in omnivorous and carnivorous fish species (P > 0.05). Moreover, no significant relationship was detected between the MPs abundance in fish tissues and body size (P > 0.05). MPs were mainly fibers, mostly transparent, and in a range size of 70-5000 µm. The dominant MPs type was nylon in all samples. This study will help increase our knowledge about MPs pollution in inland freshwater systems and suggests that management policies take essential steps to reduce this insidious problem in freshwater ecosystems.