This study examined the effects of land-use changes on heavy metal pollution in runoff in a catchment of Tehran, Iran. Urban runoff samples were collected from six stations, including five various land uses and mixed land uses. The event mean concentration (EMC) was applied to determine heavy metals, including mercury (Hg), arsenic (As), cadmium (Cd), zinc (Zn), lead (Pb), and copper (Cu), in five land uses. Sampling was done during six events with different antecedent dry days (ADDs) during 2019–2020. The result revealed higher heavy metal concentrations in runoff in the industrial land use compared to other land-use types in the catchment. The calculated EMC rates were as follows: EMC Zn > EMC Pb > EMC Cu > EM As > EMC Hg > EMC Cd. This study also found that the maximum and minimum EMCs of heavy metals were associated with rainfall events with 115 and 1 dry days, respectively. In comparison to other heavy metals, mercury and arsenic were at a higher level in runoff as determined by EMC data analysis. In order to minimize the risk of heavy metal contamination of runoff, the relocation of industrial land uses from urban environments to non-urban areas is recommended.

Duration and severity are the two main variables used in drought analysis. The copula functions are appropriate for multivariate drought analysis, as it lacks the limitations of the classical multivariate distribution function. This study investigated the bivariate frequency analysis of drought duration and severity of Yazd city in Iran synoptic station during 1953–2013. To this end, first, the drought duration and severity variables were derived from the 6-month Standardized Precipitation Index. Then, considering the distribution functions, the gamma distribution function was selected for analyzing the severity and the exponential distribution function was selected for analyzing the duration and then the Clayton copula function was selected out of the three copula functions as the most appropriate one. After conducting bivariate frequency analysis, the joint seasonal and conjunctive return period and conditional return period curves were plotted. The current study well signified that multivariate analyses could present better interpretations of the reality; for example, as it was identified in conditional return period curves of the drought, for every constant duration, the amount of the return period changed as the severity changed. On the contrary, in analyzing the univariate of duration, no effects of severity were observed.

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Concerning the various effects of climate change on intensifying extreme weather phenomena all around the world, studying its possible consequences in the following years has attracted the attention of researchers. As the drought characteristics identified by drought indices are highly significant in investigating the possible future drought, the Copula function is employed in many studies. In this study, the two- and three-variable Copula functions were employed for calculating the return period of drought events for the historical, the near future, and the far future periods. The results of considering the two- and three-variable Copula functions were separately compared with the results of the calculated Due to the high correlation between drought characteristics, bivariate and trivariate of Copula functions were applied to evaluate the return periods of the drought. The most severe historical drought was selected as the benchmark, and the drought zoning map for the GCM models was drawn. The results showed that severe droughts can be experienced, especially in the upper area of the basin where the primary water resource is located. Also, the nature of the drought duration plays a decisive role in the results of calculating the return periods of drought events.

Concerning the various effects of climate change on intensifying extreme weather phenomena all around the world, studying its possible consequences in the following years has attracted the attention of researchers. As the drought characteristics identified by drought indices are highly significant in investigating the possible future drought, the Copula function is employed in many studies. In this study, the two-and three-variable Copula functions were employed for calculating the return period of drought events for the historical, the near future, and the far future periods. The results of considering the two-and three-variable Copula functions were separately compared with the results of the calculated Due to the high correlation between drought characteristics, bivariate and trivariate of Copula functions were applied to evaluate the return periods of the drought.The most severe historical drought was selected as the benchmark, and the drought zoning map for the GCM models was drawn. The results showed that severe droughts can be experienced, especially in the upper area of the basin where the primary water resource is located. Also, the nature of the drought duration plays a decisive role in the results of calculating the return periods of drought events.