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January 17, 2026Water0 citationsOpen Access

Assessment of Small-Settlement Wastewater Discharges on the Irtysh River Using Tracer-Based Mixing Diagnostics and Regularized Predictive Models

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SASamal AnapyanovaVKValentina KolpakovaMKMonika Kulisz

Key Points

  • The study aims to quantify the impact of wastewater discharges on the Irtysh River and develop predictive models for effluent quality.
  • Utilized field–analytical framework in East Kazakhstan's Irtysh River.
  • Sampled paired upstream and downstream sites for 22 water quality indicators.
  • Compiled influent–effluent records from two treatment facilities.
  • Employed mixed diagnostics to assess dilution and changes in water quality.
  • Applied regularized regression for predictive modeling of BOD and COD.
  • TF1 showed significant dilution (D≈2000) with high deviations from mixing expectations for several constituents.
  • TF2 exhibited modest deviations with θ values near unity indicating minor changes.
  • Lasso regression model accurately predicted effluent quality with high R² values (up to 0.997).
  • Results support modernization efforts for efficient water-quality management in small treatment facilities.

Abstract

An integrated field–analytical framework was applied to quantify the impact of two small-settlement treatment facilities (TF1 and TF2) on the Irtysh River (East Kazakhstan). The main objective of this study is to quantify effluent-driven dilution and non-conservative changes in key water-quality indicators downstream of TF1 and TF2 and to evaluate parsimonious models for predicting effluent-outlet BOD and COD from upstream measurements. Paired upstream–downstream control sections are sampled in 2024–2025 for 22 indicators, and plant influent–effluent records are compiled for key wastewater variables. Chloride-based conservative mixing indicated very strong dilution (approximately D≈2. 0×103 for TF1 and D≈4. 2×102 for TF2). Deviations from the mixing line were summarized using a transformation diagnostic θ. At TF1, several constituents exceeded mixing expectations (θ≈13 for COD, θ≈42 for ammonium, and θ≈6 for phosphates), while nitrate shows net attenuation θ<0. At TF2, θ values cluster near unity, indicating modest deviations. Under a small-sample regime N=10 and leave-one-out validation, regularized regression provided accurate forecasts of effluent-outlet BOD and COD. Lasso under LOOCV performed best (BODₐfter: RMSE = 0. 626, MAE = 0. 459, and R2=0. 976; CODₐfter: RMSE = 0. 795, MAE = 0. 634, and R2=0. 997). The results reconcile strong reach-scale dilution with constituent-specific local departures and support targeted modernization and operational forecasting for water-quality management in small facilities.

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Cite This Study

Anapyanova et al. (2026) studied this question.

synapsesocial.com/papers/696b26b2d2a12237a9349f3bhttps://doi.org/10.3390/w18020232
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