Numerical Modeling of the Concentration of Microplastics in Lakes and Rivers in Kazakhstan
This research presents a detailed numerical modeling study focused on estimating the concentration of microplastics (MPs) in freshwater ecosystems. This research covers three lakes (Kopa, Zerendinskoye, and Borovoe) and the Yesil River, applying differential equations to model the spatial distribution and seasonal variations in MP concentrations. The methodology integrates field survey data collected during three different seasons (spring, summer, and autumn) from both sediment and water samples. The MP concentrations were found to follow an exponential decay pattern from the shore toward the center of the lakes, with higher concentrations near the shoreline. The modeling framework is calibrated using regression analysis, which provides the best-fit parameters for the distance–concentration curves. This study employs sensitivity analysis to justify the decay coefficient, resulting in a selected value of k = 0.09. Model performance is assessed using statistical metrics such as the root mean square error (RMSE) and the coefficient of determination (R2), ensuring accuracy in predicting MP concentrations across different environmental compartments. This work represents a novel contribution to the field by applying numerical modeling techniques to an understudied geographical area. The findings highlight significant seasonal and spatial variations in MP concentrations, emphasizing the need for comprehensive monitoring. This study’s results contribute valuable insights into the environmental behavior of MPs in freshwater systems and support efforts to develop effective management strategies to mitigate pollution.
Authors
- Natalya S. Salikova (ORCID: https://orcid.org/0000-0002-0009-5826)
- Javier Rodrigo-Ilarri (ORCID: https://orcid.org/0000-0001-8380-7376)
- María-Elena Rodrigo-Clavero (ORCID: https://orcid.org/0000-0002-8611-0504)
- Lyudmila A. Makeyeva (ORCID: https://orcid.org/0000-0001-5355-2173)
- Zinep M. Shaimerdenova
Institutions
- Kokshetau State University (KZ)
- Universitat Politècnica de València (ES)
Publication Details
- Journal
- Hydrology
- Published
- 2025-04-16
- DOI
- https://doi.org/10.3390/hydrology12040093
- Citations
- 1
- Primary Topic
- Advanced Computational Techniques in Science and Engineering
- Type
- article
- Field-Weighted Citation Impact
- 3.25