Trend analysis and ARIMA modeling for forecasting precipitation pattern in Wadi Shueib catchment area in Jordan

Abstract

In this present work, the daily precipitation data obtained from five gauging stations were analyzed to find the trend and prediction of precipitation for water deficit area of Wadi Shueib catchment in Jordan. Mann–Kendall (MK) test with Sen’s slope estimator and innovative trend analysis (ITA) were carried out for monthly, average, and seasonal data, derived from daily precipitation for a minimum of 44 years of record. The ITA method detected trend at all stations, in different trend levels (low, medium, and high), while MK test detected no trend except at two stations during the same period. The Box–Jenkins forecasting method with autoregressive integrated moving average (ARIMA) model was used to predict the changes in precipitation for projected years. Best-fit ARIMA models were found based on diagnostic check procedure in Box–Jenkins method. The best-fit ARIMA models, validated with 10 years of data (2007–2016), were used for predicting precipitation up to 2026, and ITA was used to find the trend of precipitation in the future. The future trend shows that the high level (heavy rain) is decreasing at all stations and low level (normal rain) is increasing, except in the month of December, which shows an increasing trend. This observed pattern warrants effective water management strategies for already water-stressed area of Wadi Shueib catchment in Jordan.