Multiagent System and Rainfall-Runoff Model in Hydrological Problems: A Systematic Literature Review

Abstract

Typically, hydrological problems require approaches capable of describing and simulating part of the hydrological system, or the environmental consequences of natural or anthropic actions. Tools such as Multiagent System (MAS) and Rainfall-Runoff Model (RRM) have been used to help researchers to develop and better understand water systems. Thus, this study presents a Systematic Literature Review (SLR) on the joint use of MAS and RRM tools, in the context of hydrological problems. SLR was performed based on a protocol defined from the research question. Initially, 79 papers were found among six bibliographic databases. This total was reduced over four stages of selection, according to exclusion criteria. In the end, three papers were considered satisfactory within the scope of the research, where they were summarized, analyzed, and compared. While the MAS and RRM tools can interact with their results in a coupled model, SLR showed that there are still major challenges to be explored concerning the dynamics between them, as the steps of scales and validation. However, the coupling of MAS and RRM can provide an interesting alternative tool to analyse decision-making about water resources management systems.

Modeling runoff in Bhima River catchment, India: A comparison of artificial neural networks and empirical models

“…There are a variety of hydrological models readily accessible for estimating runoff, most of which are sophisticated and require substantial inputs. For rainfall-runoff modeling, scientists across the regions globally have created multiple models (Leitzke & Adamatti 2021). These models are divided into two types: conceptual models and physically based models.…”