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

Institutions

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Numerical Modeling of the Concentration of Microplastics in Lakes and Rivers in Kazakhstan

Natalya S. Salikova, Javier Rodrigo-Ilarri, María-Elena Rodrigo-Clavero, Lyudmila A. Makeyeva et al.
1 citations
Hydrology
Advanced Computational Techniques in Science and Engineering
3.25
article

Numerical Modeling of the Concentration of Microplastics in Lakes and Rivers in Kazakhstan

Natalya S. Salikova, Javier Rodrigo-Ilarri, María-Elena Rodrigo-Clavero, Lyudmila A. Makeyeva, Zinep M. Shaimerdenova
article en
1 citations

Abstract

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.

HydrologyVol. 12(4)
Kokshetau State University (KZ), Universitat Politècnica de València (ES)
Openalex Percentile: Top 10%
Advanced Computational Techniques in Science and Engineering
3.25
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.