In recent years, dust storms with huge adverse impacts on the environment have become more frequent and intense in the southwest of Iran. The first step to control or influence the dust storm process is source identification. The objective of this study is to detect the major sources of dust storms in Bushehr Province of Iran using the analytic network processes (ANP) and the weather research and forecasting (WRF) models. Five synoptic stations for this purpose were examined over 17 years from 2001 to 2017. The spatial data includes land use, NDVI, slope, aspect-slope, elevation, and soil used as the major layers. The layers were weighted by applying the paired comparison and analytic hierarchy process methods. Also, local scale pressure systems were identified using the WRF numerical model. Results revealed that pressure systems at the local scale in different seasons are located exactly over areas prone to dust storm generation within the study area. Furthermore, the WRF model correctly showed the atmospheric pressure and wind field locations at a local scale. Based on ANP output, more than 25% of Bushehr Province has been active as dust-prone regions at a local scale. The ANP model identified the zones of erosion-prone areas, and the WRF model determined the location of permanent or semi-permanent pressure systems. Results demonstrated that applying the WRF and ANP models provided a useful tool to identify and validate the local dust sources with high accuracy in the study sites.

近年来，对环境造成巨大不利影响的沙尘暴在伊朗西南部变得更加频繁和剧烈。控制或影响沙尘暴过程的第一步是源识别。本研究的目的是使用分析网络过程 (ANP) 和天气研究与预报 (WRF) 模型检测伊朗布什尔省沙尘暴的主要来源。从 2001 年到 2017 年的 17 年间，为此目的检查了五个天气站。空间数据包括土地利用、NDVI、坡度、坡向坡度、高程和用作主要层的土壤。通过应用配对比较和层次分析处理方法对层进行加权。此外，使用 WRF 数值模型确定了局部尺度压力系统。结果显示，不同季节局部尺度的压力系统正好位于研究区内容易发生沙尘暴的区域上方。此外，WRF 模型正确地显示了局部尺度的大气压力和风场位置。根据 ANP 输出，布什尔省超过 25% 的地区作为局部范围内的粉尘多发地区一直活跃。ANP 模型确定了易受侵蚀的区域，而 WRF 模型确定了永久或半永久压力系统的位置。结果表明，应用 WRF 和 ANP 模型提供了一种有用的工具，可以在研究地点以高精度识别和验证当地的沙尘源。WRF 模型正确显示了局部尺度的大气压力和风场位置。根据 ANP 输出，布什尔省超过 25% 的地区作为局部范围内的粉尘多发地区一直活跃。ANP 模型确定了易受侵蚀的区域，而 WRF 模型确定了永久或半永久压力系统的位置。结果表明，应用 WRF 和 ANP 模型提供了一种有用的工具，可以在研究地点以高精度识别和验证当地的沙尘源。WRF 模型正确显示了局部尺度的大气压力和风场位置。根据 ANP 输出，布什尔省超过 25% 的地区作为局部范围内的粉尘多发地区一直活跃。ANP 模型确定了易受侵蚀的区域，而 WRF 模型确定了永久或半永久压力系统的位置。结果表明，应用 WRF 和 ANP 模型提供了一种有用的工具，可以在研究地点以高精度识别和验证当地的沙尘源。