Pre-event base flow as a useful indicator for flood forecasting

• Published in: Advances in water resources Vol. 180; p. 104539
• Main Authors: Shokri, Ali, Shokri, Ashkan, Koupai, Jahangir Abedi
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.10.2023
• Subjects: Event based; Intensity-duration frequency; Pre-event base flow; Rainfall intensity; Rainfall runoff; Pre-event base flow; Rainfall runoff; Intensity-duration frequency; Event based; Rainfall intensity
• ISSN: 0309-1708; 1872-9657
• DOI: 10.1016/j.advwatres.2023.104539

•Introduces pre-event baseflow as an indicator for catchment condition assessment.•Novel equation enhances event-based rainfall-runoff modelling accuracy.•Outperforms conventional models in predicting direct flow across case studies.•A promising tool for improved flood forecasting, water resource management, and planning. The hydrological cycle comprises several components, including precipitation, infiltration, evaporation, transpiration, and runoff, with the latter being a vital part of the cycle that connects precipitation to bodies of water. modelling is necessary due to limitations in standard hydrological measurement techniques, providing a better understanding of hydrological systems that were previously inaccessible, and making it essential for water resource management. Event-based rainfall-runoff modelling is a prevalent method due to its simplicity, but conventional models are limited in accounting for antecedent conditions. In order to tackle this problem, pre-event baseflow is proposed as an indicator for assessing catchment conditions for flood forecasting. This study employs a novel event-based rainfall-runoff equation that incorporates rainfall characteristics, improving hydrological modelling accuracy, and outperforms conventional models in predicting direct flow in most case studies. Overall, the study demonstrates the potential for the new equation to improve hydrological modelling accuracy and aid in a wide range of applications such as flood prediction, water resources management, and planning.