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Determining Nutrient Loading of Amuruto River Using Quadratic and Linear Models in Rivers State, Nigera

Domaine:

environment and energy

Type de record:

paperdataset
Créateur:
A.,O.,N.,
Éditeur:
CenWor
Éditeur:
CCSDSCI
Hôte:avatar
International audience The aim of this study is to determine nutrient loading of Amuruto river in Rivers State, Nigeria using quadratic and linear models by comparing nitrate, phosphate and TDS levels in both wet season and dry season, develop quadratic and linear regression nutrient loading models for Amuruto river, identify key pollution sources and recommend nutrient pollution controls. Study utilized empirical methods to analyze seventeen physicochemical and bacteriological parameters of Amuruto river water between July 2022 – October, 2022, November, February, 2023. Quadratic and linear regression nutrient models were developed for Amuruto River based on seasonal variations in Nitrate (NO₃⁻), Phosphates (PO₄³⁻) and Total Dissolved Solids (TDS) of wet and dry seasons. Nutrient loading was assessed and correlations with other water quality parameters and its implications to ecosystem health determined. Linear and quadratic models were developed for nutrient (Nitrate, Phosphate, TDS and Staphylococcus) loading of Amuruto River. The models highlighted influence of flooding, vegetation changes, silting, aquatic weed invasion, timber lumbering, agriculture, cassava, palm oil processing, open defecation and sand mining on nutrient concentrations. Results indicated that nitrate and phosphate levels were significantly higher in wet season, suggesting increased runoff from agricultural and domestic sources. TDS levels rose during dry season, indicating higher evaporation rates and reduced dilution. Correlation analysis showed a strong relationship between nutrient concentrations and BOD, COD and THC, emphasizing impact of nutrient pollution in Amuruto river health. The findings emphasized the need for sustainable nutrient management strategies to mitigate eutrophication risks and protect aquatic life.

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hal.science

Tags

[SDE]Environmental Sciences

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