The aim of this study is to assess and forecast spatial pattern changes of dust and wind speed in Hamun-e Helmand basin, Sistan region. This region has the most dust events and the strongest winds, including 120-day winds. Wind speed and dust data of seven synoptic stations were therefore extracted from the Iran Meteorological Organization during 1990–2018. Wind and dust speed were predicted for 2020–2030 period using Autoregressive Integrated Moving Average (ARIMA) model and neural network, then analyzed by spatial pattern distribution using Hotspot G Index. The results showed that both models have a good efficiency in predicting wind and dust speed. However, due to error assessment in ARIMA model, neural network was more accurate in prediction. The results of spatial autocorrelation showed that cluster pattern of dust formed a pattern based on ARIMA model with an area of 21.01 and 20.64, neural network with an area of 19.67 and 19.47 for the two statistical periods 2018–2025 and 2026–2035, respectively, in the eastern half of the basin, namely Zabol and Zahak. The condition of autocorrelation of wind speed pattern was similar to that of the dust, except that the wind speed not only extended to the south of the basin, but also had spatial autocorrelation positive pattern in the northern half of the basin as small spots based on ARIMA model with an area of 18.71 and 15.16, neural network with an area of 22.12 and 15.68 for the two statistical periods 2018–2025 and 2026–2035, respectively.

本研究的目的是评估和预测锡斯坦地区哈蒙-赫尔曼德盆地沙尘和风速的空间格局变化。该地区的沙尘事件最多，风力最强，包括 120 天的风。因此，1990-2018 年期间从伊朗气象组织中提取了七个天气站的风速和沙尘数据。使用自回归综合移动平均 (ARIMA) 模型和神经网络预测 2020-2030 年期间的风和沙尘速度，然后使用热点 G 指数通过空间模式分布进行分析。结果表明，两种模型都具有较好的风尘速度预测效果。然而，由于ARIMA模型中的误差评估，神经网络在预测上更加准确。空间自相关结果表明，2018-2025年和2026-2035年两个统计周期，基于ARIMA模型的沙尘聚类格局分别形成面积为21.01和20.64，神经网络面积分别为19.67和19.47的格局，在盆地的东半部，即 Zabol 和 Zahak。风速模式自相关的情况与沙尘相似，只是风速不仅向盆地南部延伸，而且在盆地北半部也有空间自相关正模式，为基于ARIMA 模型面积分别为 18.71 和 15.16，神经网络面积分别为 22.12 和 15.68，分别用于 2018-2025 和 2026-2035 两个统计周期。47 分别在 2018-2025 年和 2026-2035 年两个统计期间，在盆地东半部，即 Zabol 和 Zahak。风速模式自相关的情况与沙尘相似，只是风速不仅向盆地南部延伸，而且在盆地北半部也有空间自相关正模式，为基于ARIMA 模型面积分别为 18.71 和 15.16，神经网络面积分别为 22.12 和 15.68，分别用于 2018-2025 和 2026-2035 两个统计周期。47 分别在 2018-2025 年和 2026-2035 年两个统计期间，在盆地东半部，即 Zabol 和 Zahak。风速模式自相关的情况与沙尘相似，只是风速不仅向盆地南部延伸，而且在盆地北半部也有空间自相关正模式，为基于ARIMA 模型面积分别为 18.71 和 15.16，神经网络面积分别为 22.12 和 15.68，分别用于 2018-2025 和 2026-2035 两个统计周期。