SENSITIVITY ANALYSIS OF A PREDICTED POLLUTANTS MODEL FOR KANGIMI DAM STORAGE

Abstract

Sensitivity analysis (SA) has been widely accepted and used in sourcing and explaining hidden questions arose from mathematical models. This study aimed at use SA on an existing recently predicted pollutant model for Kangimi Dam Storage. The study calibrated and simulated the model using primary and secondary stream stage data. The SA was performed using five (5) different methods and evaluated the results by comparisons. The simulation indicated that the pollutants responded to the seasonal changes of reservoir streamflow and reached the optimum at month of August. The pollutants at months of June, July and August (2023) substantially showed a significant sensitive to streamflow discharges as it become optimal. In conclusion, the study predicted the chemostatic and chemodynamic patterns of the reservoir storage, and recommend the further study of the SA on the model for its further verification and acceptance.