tam-ng/Drought_Forecasting_TimeSeries

Identified the most appropriate Time-Series method to forecast drought in African countries, acting as a critical early warning for drought managements # Drought_Forecasting_TimeSeries ## Introduction Globally, droughts are the biggest concern from climate change. Frequency and intensity of droughts has increased over the last century – Since 1900 Global droughts have affected 2 billion people and lead to more than 11 million deaths ## Objectives - Our Focus: Horn of Africa - Identified the most appropriate Time-Series method to forecast drought in African countries, acting as a critical early warning for drought managements - With the goal of maximizing the impact of our predictions we have decided to focus on the region most affected by droughts: Somalia, Ethiopia ## Data - Using Meteorlogical Drought indicator: SPEI - Monthly SPEI measurements from the capitals of Somalia & Ethiopia  spei.csic.es - SPEI: Measures drought severity according to its intensity and duration, and can identify the onset and end of drought episodes - SPEI takes into account both precipitation and potential evaporation in determining drought, therefore, SPEI captures the main impact of increased temperatures on water demand ## Modeling 1.Benchmark Models: Naive, Mean, Seasoan Naive, Naive with drift 2.Exponential Smoothing 3.ARIMA, sARIMA 4.Spectral Analysis 5.VAR, Regression with ARIMA error 6.TBATS 7.ARCH/GARCH