Modeling and Validation of Residential Water Demand in Agent-Based Models: A Systematic Literature Review

Abstract

Current challenges, such as climate change or military conflicts, show the great importance of urban supply infrastructures. In this context, an open question is how different scenarios and crises can be studied in silico to assess the interaction between the needs of social systems and technical infrastructures. Agent-based modeling is a suitable method for this purpose. This review investigates (i) how agent-based models of residential water demand should be validated, (ii) how such models are commonly built and (iii) validated, and (iv) how these validation practices compare to the recommendations drawn from question (i). Therefore, a systematic literature review using the PRISMA framework is conducted. Out of 207 screened papers, 35 models are identified with an emphasis on highly realistic models (i.e., highly detailed and representing specific real-world systems) for planning, management, and policy of urban water resources. While some models are thoroughly validated, quantified validation distinct from calibration data should be emphasized and used to communicate the confidence in results and recommendations drawn from the models. Pattern-oriented validation, validation on multiple levels and on higher moments of aggregated statistics should be considered more often. These findings expand prior literature by providing a more extensive sample of reviewed articles and recommending specific approaches for the validation of models.

A Framework for the Simulation-Based Selection of Socio-Technical Models Using Technical Requirements Analysis

“…In a prior review, (Sattler et al, 2023) have shown that a multitude of potential social models including various decision variables and structures and are presented in the scientific literature in the case urban water infrastructures. Therefore, selecting the right model for a given socio-technical system remains a challenge.…”

“…Therefore, the importance of including human factors into the modeling of infrastructures has been highlighted, leading to the paradigm of socio-technical models consisting of technical and social sub-models. The scientific literature presents a multitude of social models for such socio-technical models of infrastructure (Sattler et al, 2023). It therefore remains an open challenge to select the right model for a given socio-technical system, i.e.…”