Abstract:Machine learning (ML) models have emerged as potential methods for rainfall-runoff modeling in recent decades. The appeal of ML models for such applications is owing to their competitive performance when compared to alternative approaches, ease of application, and lack of rigorous distributional assumptions, among other attributes. Despite the promising results, most ML models for rainfall-runoff applications have been limited to areas where rainfall is the primary source of runoff. The potential of Random For… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.