Modeling Climate Change Effect from Deforestation using Bayesian Decision Model

Abstract

This study is aimed at carrying out a study on the effects of deforestation as a result of global warming and climate change crisis. A model was established using the Bayesian decision model to know the impact of deforestation here in the environment. The model was formulated from the data gotten from Bill of Engineering Measurement and Evaluation on benefit and purpose of water resource projects in Delta state. Consequently, from the results of prior probabilities of the state of nature and the likelihood of the alternatives courses of action, and applying prior-posterior decision models to the uncertain system, the following decision were arrived at: plantation and forestry has the highest expected monetary value at 1st iteration with the value of N 24.0B, hydropower has the highest expected monetary value at 2nd iteration with the value of N26.61B.The results of Bayesian decision model gave a clear indication that energy resource project of hydropower has the highest expected monetary value of N26.61 at 2nd iteration, making it the most suitable for government to invest on, for maximum yield. The Environmental authority is expected to pay the researcher/consultant or forecaster the expected value of system information, value of N8.43B for information generated using the Bayesian decision model spreadsheet. there should be government regulations to curb the felling of trees by enforcing rules and laws to govern it and the government should enforce a law to ensure monitoring the forests and defaulter penalized. Deforestation crisis should be reduced to the bearest minimum with the felling of one tree leads to planting of ten seedling of trees as a sustainable measure put in place.