Abstract
Jordan is very vulnerable to drought because of its location in the arid to semi-arid part of the Middle East. Droughts coupled with water scarcity are becoming a serious threat to the economic growth, social cohesion and political stability. Rainfall time series from four rain stations covering the Jordan River Basin were analyzed for drought characterization and forecasting using standardized precipitation index (SPI), Markov chain and autoregressive integrated moving average (ARIMA) model. The 7-year moving average of Amman data showed a decreasing trend while data from the other three stations were stable or showed an increasing trend. The frequency analysis indicated 2-year return period for near zero SPI values while the return period for moderate drought was 7 years. Successive droughts had occurred at least three times during the past 40 years. Severe droughts are expected once every 20 - 25 year period at all rain stations. The extreme droughts were rare events with return periods between 80 and 115 years. There are equal occurrence probabilities for drought and wet conditions in any given year, irrespective, of the condition in the previous year. The results showed that ARIMA model was successful in predicting the overall statistics with a given period at annual scales. The overall number of predicted/observed droughts during the validation periods were 2/2 severe droughts for Amman station and, 0/1, 1/1, 0/1 extreme droughts for Amman, Irbid and Mafraq stations, respectively. In addition, the ARIMA model also predicted 3 out of 4 actual moderate droughts for Amman and Mafraq stations. It was concluded that early warning of developing droughts can be deduced form the monthly Markov transitional probabilities. ARIMA models can be used as a forecasting tool of the future drought trends. Using the first and second order Markov probabilities can complement the ARIMA predictions.
Highlights
Drought is a natural dynamic phenomenon that can inflict damages of disastrous proportions, which includes among other effects, the reduction of crop production and distressing the general population over the lack of water
Reference [32] statistically analyzed the historical rainfall record at Amman station. They suggested that stating the mid-1950s, there was an abrupt decline in the number of rainy days, but their analysis for the precipitation record at Mafraq station showed insignificant differences in the number of rainy days between the pre-1950 and post-1960 periods
Drought forecasting can be a challenging task since exact predictions of the Standardized Precipitation Index (SPI) values are not possible using autoregressive integrated moving average (ARIMA) model
Summary
Drought is a natural dynamic phenomenon that can inflict damages of disastrous proportions, which includes among other effects, the reduction of crop production and distressing the general population over the lack of water. Droughts occur in almost all climatic regions of the world with varying frequency, severity and duration but their impacts are aggravated in countries with limited water supply like Jordan. Many definitions of droughts have been adopted with reference to the components of the hydrological cycle and to the different impacts on water resources and ecosystems [2]. Reference [3] defined drought as a temporary imbalance of water availability consisting of a persistent lower than average precipitation of uncertain frequency, duration and severity, of unpredictable or extremely hard to predict occurrence, resulting in diminished water resources availability. Reference [4] introduced a broader and possibly more operational definition of drought as: the state of adverse and wide-spread hydrological, environmental social and economical impacts due to less than generally anticipated water resources quantities.
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