Flood is one of the natural disasters that causes a lot of damage to human societies every year. Meanwhile, cities have the highest risk and probability of flood damage (Hallegatte et al., 2013; Chen et al., 2016; Jiang et al., 2018). Urbanization is a global trend and is not limited to some countries. At the beginning of the 21st century, the world's urban population has reached 50% of the world's population and is projected to exceed 61% by 2025. That is why studies related to urban floods are becoming more and more important, and many researchers from all over the world are focusing on it (Mark et al., 2004; Maksimović et al., 2009; Seyoum et al., 2012; Henonin et al., 2013; Moftakhari et al., 2017; Jamali et al., 2018).
Structural flood control measures have been one of the dominant methods of flood management for many years. However, in recent years, this traditional method has been seriously questioned due to high uncertainty in determining the design flood due to various reasons such as climate change and changing rainfall patterns (Song and Chung, 2016). In contrast, new methods have been introduced and developed that place more emphasis on non-structural control measures. The most important achievement in this field has been the change of policies from crisis management to flood risk management (Söderholm et al., 2018).
In recent decades, many studies have been conducted on flood risk reduction programs, especially in urban areas (Ten Veldhuis, 2011; Tsakiris, 2014; Hammond et al., 2018; Park and Lee, 2019; Nofal et al., 2020, Mubeen et al., 2021). It is obvious that the proper and effective planning and implementation of various programs to reduce the destructive effects of floods and preparedness against them requires evaluating the effects of this event and accurately estimating the amount of damage to different sections of society (Dutta et al., 2003; Pingel and Ford, 2004; Merz et al., 2010; Hammond et al., 2015; Wobus et al., 2013; Wedawatta et al., 2014; Chen et al., 2016; Martins et al., 2018; Jiménez-Jiménez et al., 2020). Hence, a comprehensive set of flood studies focuses on flood damage assessment and examines its various aspects (Freni et al., 2010; Notaro et al., 2014; Tate et al., 2014; Arighi and Campo, 2019).
Previous studies have shown that various parameters should be considered in urban flood modeling. One of the most important of these parameters, which has been emphasized in previous studies, is the non-stationarity in rainfall (Vasiliades et al., 2014; Salas et al., 2014; Yang et al., 2020). The uncertainties in flood damage assessments are decreased via the interrelated factors, such as the rates of climate change and urbanization in urban flood simulations. In other words, the alternations in flood frequency could be the result of the combined effects of climate changes and human activities. Consequently, considering the effects of non-stationarity in rainfalls leading to extreme urban floods, hydrological modelling would help the future hydraulic urban flood map simulations and urban flood damage assessments to have higher accuracy.
Another important parameter in urban flood damage modeling is an urban development that should be considered in urban flood modeling and flood losses (Vogel et al., 2011, Kaspersen et al., 2017; Zhou et al., 2019; Hodgkins et al., 2019). To be more specific, since land-use changes have altered the pattern of green spaces in urban areas as the result of the numerous buildings and streets made leading to the diminution of permeable surfaces, the imbalance in the natural water cycle has increased. Therefore, the time that runoff reaches the peak has decreased, in contrast to flood volume and flood peak discharge (James, 1965; Lorup et al., 1998, Campana and Tucci, 2001; Ranzi et al., 2002; Liu et al., 2005; Nirupama and Simonovic, 2007; Saghafian et al., 2008; Suriya and Mudgal, 2012; Miller et al., 2014; Cutter et al., 2018).
According to the studies that the authors have done, there has been no focus on how the combination of the factors of urban development and non-stationarity in rainfalls affect urban flood damages modelling. As a novel strategy, in the current study, it was tried to fill this gap, and the authors assessed the rate of each of these factors’ effects and also both of them simultaneously on hydrological and hydraulic urban flood simulations, and economical damages of the future forecasted floods having various return periods. Besides, rainfall non-stationary conditions have been previously studied mostly using statistical analysis in the literature. It should be mentioned that the simultaneous use of statistical methods and hydrological/hydraulic modeling has been considered in the present study.