Riverine Microplastic Quantification: A Novel Approach Integrating Satellite Images, Neural Network, and Suspended Sediment Data as a Proxy

Abstract

Rivers transport terrestrial microplastics (MP) to the marine system, demanding cost-effective and frequent monitoring, which is attainable through remote sensing. This study aims to develop and test microplastic concentration (MPC) models directly by satellite images and indirectly through suspended sediment concentration (SSC) as a proxy employing a neural network algorithm. These models relied upon high spatial (26 sites) and temporal (198 samples) SSC and MPC data in the Tisza River, along with optical and active sensor reflectance/backscattering. A feedforward MLP neural network was used to calibrate and validate the direct models employing k-fold cross-validation (five data folds) and the Optuna library for hyperparameter optimization. The spatiotemporal generalization capability of the developed models was assessed under various hydrological scenarios. The findings revealed that hydrology fundamentally influences the SSC and MPC. The indirect estimation method of MPC using SSC as a proxy demonstrated higher accuracy (R2 = 0.17–0.88) than the direct method (R2 = 0–0.2), due to the limitations of satellite sensors to directly estimate the very low MPCs in rivers. However, the estimation accuracy of the indirect method varied with lower accuracy (R2 = 0.17, RMSE = 12.9 item/m3 and MAE = 9.4 item/m3) during low stages and very high (R2 = 0.88, RMSE = 7.8 item/m3 and MAE = 10.8 item/m3) during floods. The worst estimates were achieved based on Sentinel-1. Although the accuracy of the MPC models is moderate, it still has practical applicability, especially during floods and employing proxy models. This study is one of the very initial attempts towards MPC quantification, thus more studies incorporating denser spatiotemporal data, additional water quality parameters, and surface roughness data are warranted to improve the estimation accuracy.

Microplastic Contamination of Fine-Grained Sediments and Its Environmental Driving Factors along a Lowland River: Three-Year Monitoring of the Tisza River and Central Europe

“…After the preliminary survey of 2019, 2020 could be considered the baseline survey, as the MP measurements were complemented with more sites, grain size analyses and suspended sediment measurements [7,14,21,22,31]. The results of the 2020 measurements [14] could be considered the baseline; thus, these results are briefly introduced for a better understanding of the processes.…”

Comparative Analysis of Riverine Plastic Pollution Combining Citizen Science, Remote Sensing and Water Quality Monitoring Techniques

“…These flood waves mobilise the mismanaged plastic waste from the valley slopes, floodplains and banklines. The MaP transport rate is the highest during flood peaks [22,28], but also a large amount of MiP is transported by the floods [32,33]. River cleanup actions can target the floating/drifting riverine litter during flood events, but high discharge makes these operations very risky.…”

“…The microplastic content of sediments of the Tisza and its tributaries has been studied systematically since 2019 [30][31][32][33][34][35]. Each summer, a sampling campaign was performed from the source of the Tisza in Ukraine to its confluence in Serbia and in the near-confluence sections of the main tributaries.…”

“…The MaP pollution of the Tisza and the mountainous areas of the catchment were documented by Liro et al [16], Mohsen et al [22] and Magyar et al [27]. Besides, one of the longest and most detailed microplastic surveys of the world was performed in the river system of the Tisza, revealing the MiP transport in the river and its accumulation in the sediments [30][31][32][33][34][35].…”

“…The increased MaP pollution contributes to the increased microplastic pollution of the Tisza River. According to the annually repeated (since 2019) monitoring along the river [30][31][32][33][34], the microplastic pollution of the sediments was the highest in 2019 (3177±1970 items/kg). In the same year, the largest MaP accumulation (18.8 thousand m 2 ) was detected upstream of the Kisköre Dam [22].…”