Abstract

The monitoring of water quality for both domestic and commercial use is absolutely essential for policy formulation that affects both public and environmental health. This study investigates the quality of water of river Molo system which lies in the Kenyan Rift Valley. The river is considered a vital source of water for the residents and industrial activities in Nakuru and Baringo Counties. Six water samples were collected during the dry season of December 2017. Various physicochemical parameters were determined in situ by use of a portable pH meter. These parameters included pH, temperature, electrical conductivity and total dissolved solids (TDS). Anions such as fluorides, sulfates, phosphates, nitrates, chlorides, carbonates and bicarbonates were determined using conventional methods such as titrimetry and (ultra-violet visible) UV–Vis techniques. The cations including sodium, potassium, calcium and magnesium were determined using flame photometry. The results showed that the water had pH values ranging from 7.90 to 9.66 units, temperature ranged from 14.02 to 31.5 °C, while electrical conductivity ranged from 181 to 1637 μS/cm, TDS (69–823 mg/L), F (2.76–3.28 mg/L), sulfates (4.97–85.66 mg/L), phosphates (0.13–11.06 mg/L), nitrates (1.73–6.16 mg/L), chlorides (38.5–69.4 mg/L), carbonates (18–148 mg/L), bicarbonates (54–384 mg/L), sodium (19–1800 mg/L), potassium (8.9–121 mg/L), magnesium (4.8–106.8 mg/L) and calcium (13.4–77.4 mg/L). The pH, temperature, fluorides and sodium were above the World Health Organization permissible limits for drinking water in S4 and S5. All the water samples fall under bicarbonate or freshwater zone. The sampling points can be classified into five water types: Na–Mg–Ca–HCO3, Na–HCO3, Na–Ca–Mg–HCO3–CO3, Na and Na–Ca–HCO3–CO3. Chemical indices such as sodium adsorption ratio, magnesium hazard, percent sodium and permeability index are reported. Accordingly, the findings from this work indicate that the river Molo water in general is good for irrigation.

Highlights

  • There have been enhanced attempts aimed at developing water models that predict water quality regimes and forecast histories of intensive mineralization which influence groundwater systems, resulting in occurrence of different water classifications (Wang et al 2014; Chau 2005)

  • This study has demonstrated that pH values were high indicating that water is alkaline possibly due to application of fertilizers in the nearby farms around the study area in addition to other anthropogenic sources

  • Electrical conductivity, phosphates, sodium and potassium were above the World Health Organization permissible limit especially in station 4 (S4) and S5

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Summary

Introduction

There have been enhanced attempts aimed at developing water models that predict water quality regimes and forecast histories of intensive mineralization which influence groundwater systems, resulting in occurrence of different water classifications (Wang et al 2014; Chau 2005). Studies such as the artificial neural network (ANN) model for suspended sediment forecasting in several time steps, soft computing methods such as adaptive neuro-fuzzy inference system (ANFIS) and AquaChem computational models have. This study will not invest in the study of heavy metals and hazardous organics but will focus primarily on physicochemical parameters which can be used to determine the water quality index

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