JWSS - Journal of Water and Soil Science

The purpose of this study was to analyze the temporal variations of dust phenomenon and its relationship with the climatic elements in Yazd city, located near one of the critical centers of dust production in the center of Iran. For this purpose, the Dust Storm Index was first calculated. After the standardization of precipitation, temperature, maximum wind speed, average wind speed, relative humidity and, dust storm index, the co-linearity effect between variables was calculated by using inflation variance factor. Then, several regression models were prepared based on the optimal Ridge parameter. The performance of the models was evaluated based on the determination coefficient, F value and Root Mean Square Error. Finally, by using the most accurate model, the impact of climate parameters on the dust events changes was determined. The results showed that the incidence of dust events in the spring was more than the rest of the year. Based on the optimal model (Model 12), it was found that the main factor influencing the dust storm index variations in different seasons was the surface winds speed. It was also shown that 39%, 25%, 46% and 31% of dust storm index changes in winter, spring, summer, and autumn were due to the interaction of the five climatic parameters studied in this study.

Population growth, urbanization, and land use change have increased disastrous floods. Iran is also among the countries at high risk of floods. The latest examples of flood damage are the devastating floods of the spring of 2019 with significant mortality and financial losses in more than ten provinces of the country. The purpose of this study is to prepare an urban flood risk map of District 4 City Shiraz. The vulnerability of the region was made using PROMETHEE Ⅱ and COPRAS multi-criteria decision-making models and urban flood hazard zones were prepared by partial least squares regression (PLSR) and ridge regression (RR) models and a risk map was obtained by multiplying the vulnerability and hazard in ArcGIS software. The highest percentage of the study area in the PROMETHEE Ⅱ and COPRAS models belongs to the moderate class of vulnerability. The evaluation of the vulnerability models using Boolean logic and RMSE and MAPE statistics, showed that the COPRAS model provided better results than the PROMETHEE model. The results of partial least square regression (PLSR) and ridge regression (RR) models in flood risk modeling were analyzed by the Taylor diagram, which showed the superiority of the ridge regression (RR) model and the accuracy of this model in preparing urban flood hazard maps. The risk map of the study area indicated that 34% of the area (973 ha) is in the range of high and very high flood risk.