SOURCE:

Faculty: Engineering
Department: Agricultural And Bio-resources Engineering

CONTRIBUTORS:

Ubah,J.I;
Orakwe, L.C;
Chukwuma, G.O;

ABSTRACT:

This study was aimed at modeling the hydrodynamic and surface water quality of Ele River, Nnewi for pollution prediction. The surface water quality was determined by modeling the irrigation water quality parameters and forecasting the water quality characteristics for one year using Artificial Neural Network (ANN). The River was divided into ten sampling points of ten (10) meters apart starting from the point of discharge. Water samples were collected for laboratory analysis and statistical modelling from April 2015-March 2019. The irrigation water quality parameters considered include: Total Dissolved Solids (TDS), Electrical Conductivity (EC), Calcium(Ca), Magnesium (Mg), Sodium (Na), Bicarbonate(HCO3), Sulphate(SO4), Nitrate-Nitrogen(N-NO3), Ammonium-Nitrogen(NH4-N) and pH. The analyses and statistical modeling showed that Ca, Mg, pH, HCO3, N-NO3, NH4-N were within the FAO permissible range while SO4 and Na were above the permissible standard. During rainy season, TDS and EC exceeded the FAO permissible standard from point 1 to point 3 and later decreased as the river flows down the river course. Also, the results showed that in the dry season, TDS and EC concentration values were found to have exceeded the FAO permissible range from point 1 to 5.Thus, the river quality from point 1 to 5 may not be safe for agricultural production while from point 5 to 10, is safe for agricultural production, although there is pressing need for wastewater treatment especially at points 1 -5 for optimum water usage and safety for irrigation purposes. The training model performance evaluation shows that R2 values ranges from 0.981 to 0.990, 0.981 to 0.988, 0.981 to 0.989, 0.982 to 0.989, 0.983 to 0.990, 0981 to 0.989, 0.981 to 0.985, 0.981 to 0.988, 0.981 to 0.988 and 0.983 to 0.990 for pH, TDS, EC, Mg, Ca, Na, NO3-N, SO4, NH4-N, and HCO3, respectively; the testing performance shows that the R2 value ranges from 0.952 to 0.967, 0.953 to 0.970, 0.951 to 0.967, 0.951 to 0.969, 0.951 to 0.968, 0.953 to 0.968, 0.952 to 0.968, 0.951 to 0.969, 0.952 to 0.968 and 0.954 to 0.964 for pH, TDS, EC, Mg, Ca, Na, NO3-N, SO4, NH4-N, and HCO3-, respectively. The forecast performance evaluation shows that the R2 values range are from 0.945 to 0.968, 0.946 to 0.968, 0.944 to 0.967, 0.948 to 0.969, 0.944 to 0.967, 0.949 to 0.965, 0.944 to 0.963, 0.941 to 0.968, 0.940 to 0.967 and 0.944 to 0.970 for pH, TDS, EC, Mg, Ca, Na, NO3-N, SO4, NH4-N, and HCO3 while the Root Mean Squared Error (RMSE) ranges from 0.022 to 0.088, 0.012 to 0.087, 0.015 to 0.085, 0.019 to 0.080, 0.010 to 0.082, 0.014 to 0.084, 0.014 to 0.086, 0.036 to 0.083, 0.030 to 0.090 and 0.032 to 0.089 for Ph, TDS, EC, Mg, Ca, Na, NO3-N, SO4-, NH4-N, and HCO3 respectively. For the hydrodynamic modeling, the aim is to model the sediment transport of Ele River using computational fluid dynamics model. The governing equations of fluid flow and particle movement were modeled using COMSOL Multiphysics 5.3a. The result was validated using experimental data and the model result which showed good agreement with coefficient of determination of 0.99. Study results showed that sediment at the river banks had lower velocities compared to sediments midstream. This implies higher sediment deposition at the banks due to low flow velocity. These sediments deposition constitute problems to the river system through degradation of water quality and blocking irrigation nozzles, decreasing the irrigation efficiency and crop production. Analysis of variance and post-hoc analysis were done which showed significant differences among all the parameters except for Bicarbonate where there was no level of significance among the point values since the P-value was greater than 0.05.