UDTR — Radar mondial des droits de la Nature

Integrating principal component analysis and machine learning to assess riverine impacts on lake water quality: a case study of the Bilate River–Lake Abaya Watershed, Rift Valley, Ethiopia

Identification

Clé publique

radar:r-b9e12e97800f017adea00b6e31ea1189

Auteurs

Dereje Yonas Herano · Tekalegn Ayele Woldesenbet · Sirak Tekleab

Année déclarée

2025

Langue déclarée

en

Type source

article

Première détection

2026-11-14T02:43:00.789131+00:00

Dernière observation des métadonnées

2026-11-14T02:43:00.789131+00:00

Dernière vérification HTTP

Non effectuée

Institutions déclarées par la source

Addis Ababa University

Pays d’affiliation déclarés

ET

Résumé documentaire — langue originale

ABSTRACT Rivers are dynamic systems that transport nutrients, sediments, and pollutants to downstream lakes, contributing to water quality deterioration and ecosystem stress. This study aimed to assess seasonal and spatial variations in water quality within the Bilate River (BR)–Lake Abaya (LA) system and quantify the river's influence on the lake. Principal component analysis (PCA) was applied to identify key drivers of water quality, while after comparison, RF and XGBoost models were used to predict target parameters. SHAP was employed to interpret model outputs by quantifying feature contributions. Statistical analyses revealed significant differences across both seasons and transects (p < 0.05). PCA showed that in the dry season, PC1 explained 51.3% of variability, driven by TDS (0.85), DO (0.75), NO3− (0.65), and PO4−3 (−0.89). In the wet season, PC1 explained 40.5% of variability, with pH (0.87), TDS (0.78), salinity (0.74), TSS (−0.83), and BOD5 (−0.78). Model evaluation showed that XGBoost achieved higher predictive accuracy for DO (CA = 0.19,0.30), NO3− (CA = 0.22,0.25), and PO4−3 (CA = 0.13,0.15), while RF performed better for TSS (CA = 0.08,0.13). SHAP analysis showed that LA's water quality, particularly TSS, DO, NO3−, and PO4−3, is strongly influenced by BR inputs. These impacts are linked to intensive agriculture and land-use changes. Therefore, restoration of wetlands and implementation of soil conservation strategies are recommended to preserve LA's water quality.

Identifiants

OPENALEX

https://openalex.org/W4417278931

DOI

10.2166/hydro.2025.085

Repères documentaires

Famille documentaire

article

Types déclarés par les sources

article

Éditeurs

IWA Publishing

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Sources

OpenAlex · Document 1

• Document · https://doi.org/10.2166/hydro.2025.085

Statut documentaire

Pertinence à examiner

Bibliothèque

Cette identité n’est pas encore intégrée à la Bibliothèque juridique.