1. Department of Statistics, Faculty of Mathematical Sciences, University of Kashan, Kashan, Iran. , hamid332000@yahoo.com
Abstract: (5675 Views)
Drought as a natural hazard is a gradual phenomenon, slowly affecting an area; it may last for many years and can have devastating effects on the natural environment and in human lives. Although drought forecasting plays an important role in the planning and management of water resource systems, the random nature of contributing factors contributing to the occurrence of and severity of droughts causes some difficulties in determination of the time when a drought begins or ends. The present research was planned to evaluate the capability of linear stochastic models, known as multiplicative Seasonal Autoregressive Integrated Moving Average (SARIMA) model, in the quantitative forecasting of drought in Isfahan province based on the Standardized Precipitation Index (SPI). To this end, the best SARIMA models were chosen for modelling the monthly rainfall data from 1990 to 2017 for every 10 synoptic stations in Isfahan province to forecast their monthly rainfall up to five years. The monthly time scale SPI values based on these predictions were used to assess the drought severity of different stations for the 2018- 2022 time period. The station results indicated a weak drought at the 2019- 2022 period for Isfahan, Kashan and Naeen, a severe drought in 2019 for Ardestan and Golpaygan, and a weak one in 2019 for the East of Isfahan, KabootarAbad and Shahreza stations. All other stations, except Golpayegan, Isfahan, Kashan and Naeen, faced a severe drought in 2018.
Type of Study:
Research |
Subject:
Ggeneral Received: 2019/01/24 | Accepted: 2019/05/25 | Published: 2020/02/29