Statistical modeling is one of the fundamental techniques for quantitatively characterizing hydroclimatological processes, global warming, extreme climatological events, and risk and reliability in hydroclimatology. To understand and manage the hydroclimatological processes that control our environment, it is important to advance hydroclimatological modeling, estimate the impact of climate change, and know how these processes influence human society (or disaster). Massive mathematical modeling and multisource data set can be applied to assess or model hydroclimatological processes. Based on the recently developed scientific knowledge and methods, we can improve our understanding of hydroclimatological processes.

This special issue is intended to bring together scientists and practitioners in the fields of statistical and stochastic climatology and hydrology and provide a forum for exchange of the latest developments in these fields. We invite scientists and practitioners to contribute original research articles that will contribute to our understanding of the hydroclimatological processes.

Potential topics include, but are not limited to:

• Statistical or stochastic modeling of the impact of climate change in hydroclimatology
• Ungauged sites and local and regional frequency analysis
• Statistical or stochastic modeling of extremes and risk and reliability in hydroclimatology
• Advances in data acquisition validation and homogenization
• Advances in hydroclimatological modeling based on multisource information
• Different ways of validation of the model results