Statistical Model for Predicting Salinity of Water at Doho 1 Irrigation Scheme in Busia.
Abstract
The concentration of salts in water or salt affects crop yields to a good extent. Irrigation salinity can be controlled by various methods including modelling. Therefore, this study aimed at designing a model for predicting the salinity of the water at the Doho Irrigation Scheme in Butaleja district, eastern Uganda for better rice growing. This study used the different water chemical parameters from the different sites of the scheme, where water samples were collected and measured in the laboratory. A multivariate regression method was used to model water salinity through the Electrical Conductivity as the dependent variable and other water chemical parameters like potassium (K), Sodium (Na), pH and Calcium (Ca) were used as independent variables. A non-linear statistical model was derived from the chemical results of the irrigation scheme, presented and validated by applying it on the water samples that were not used during the design of the model. The model measured salinity levels and can be used to determine which water chemical levels are good for rice growing in Doho and other similar situations. Hence, the model can be used to improve food quality and quantity as required in the food production goal
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Copyright (c) 2021 Keneema Christine, Semwogerere Twaibu, PhD, Kamalha Edwin, Alio Deborah, Kawuma Carol
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