Runoff Losses on Urban Surfaces during Frequent Rainfall Events: A Review of Observations and Modeling Attempts

Autor: Emmanuel Berthier, Mohamad Rammal
Přispěvatelé: Centre d'Etudes et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement - Equipe-projet TEAM (Cerema Equipe-projet TEAM), Centre d'Etudes et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement (Cerema)
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Water
Water, 2020, 12 (2777), pp.36. ⟨10.3390/w12102777⟩
Water, Vol 12, Iss 2777, p 2777 (2020)
DOI: 10.3390/w12102777⟩
Popis: Quantifying urban runoff during frequent rainfall events is a key element in quality management of urban water due to their high contribution to the annual runoff flow. This explains the growing interest among hydrologists in studying runoff flow on urban surfaces. In this paper, we review most of the experimental approaches as well as the modeling ones conducted in the literature to understand and estimate runoff flow on urban areas. This review highlights the incoherence between our current understanding of the hydrological behavior of urban areas during frequent events and our conception of the loss functions in the urban drainage models. Field studies provided more insight into the determinant processes occurring on the different surface types during frequent events with depression storage being a fundamental element varying between surface types and for the same surface type and infiltration process being relatively important on paved areas especially in their cracks that constitute preferential pathways for rainwater. Analyzing a wide range of urban drainage models showed that these elements along with the temporal evolution of the hydrological behavior of urban surfaces due to seasonal and state conditions are not fully integrated in the models’ structures, which were initially developed for heavy rainfall events. Adapting the assumptions of urban drainage models based on these new factors must improve the performance of hydrological models for frequent rainfall events.
Databáze: OpenAIRE