Literature Review of Water Resources Agent-Based Models

Modeling the coupled social and biophysical dynamics of water resource systems is increasingly important due to expanding population, fundamental transitions in the uses of water, and changes in global and regional water cycling driven by climate change. Models that explicitly represent the coupled dynamics of biophysical and social components of water resource systems are challenging to design and implement, particularly given the complicated and cross-scale nature of water governance. Agent based models (ABMs) have emerged as a tool that can capture human decision-making and nested social hierarchies. The transferability of many agent-based models of water resource systems, however, is made difficult by the location-specific details of these models. The often ad-hoc nature of the design and implementation of these models also complicates integration of high fidelity sub-models that capture biophysical dynamics like surface-groundwater exchange and the influence of global markets for commodities that drive water use. A consistent, transferable description of the individuals, groups, and/or agencies that make decisions about water resources would significantly advance the rate at which ABMs of water resource systems can be developed, enhance their applicability across ranges of spatiotemporal scales, and aid in the synthesis and comparison of models across different sites. We outline here a framework to systematically identify the primary agents that influence the storage, redistribution, and use of water within a given system.

This resource is the literature review that supports our proposed water resources agent types that capture the operational roles that modify the water balance (see Kaiser et al., 2020). This typology characterizes common actors in water management systems but can be modified to represent the particularities of specific systems when more detailed information about specific actors is available (e.g. social networks, demographics, learning and decision-making processes). Application of the proposed typologies will support the systematic design and development of transferable scaleable water resources ABMs and facilitate the dynamical coupling of social and biophysical process modeling.

随着人口的扩张、水资源的利用方式发生根本性转变，以及气候变化驱动的全球和区域水循环变化，构建水资源系统耦合社会与生物物理动态模型的重要性日益凸显。设计并实现明确表征水资源系统生物物理和社会组成部分耦合动态的模型是一项极具挑战性的任务，尤其是在面对复杂多尺度水资源治理的背景下。基于智能体模型的（ABMs）作为一种工具，能够捕捉人类决策和嵌套的社会等级结构。然而，由于这些模型具有地域特定性，水资源系统许多基于智能体模型的转移性受到了限制。这些模型设计和实现过程中常有的随意性，也增加了整合高保真子模型（如地表水与地下水交换以及全球市场对推动水资源利用的商品的影响）的复杂性。对决定水资源个体的、群体的和/或机构进行一致且可转移的描述，将显著提高水资源系统ABMs的开发速度，增强其在时空尺度范围内的适用性，并有助于不同地点模型的综合与比较。在此，我们概述了一个框架，旨在系统性地识别影响特定系统内水资源储存、再分配和使用的核心智能体。本资源是支持我们提出的捕捉操作角色以修改水资源平衡的水资源智能体类型的文献综述（参见Kaiser等人，2020年）。该类型学表征了水管理系统中的常见行为者，但可根据可获得的具体行为者的详细信息（例如社会网络、人口统计学、学习和决策过程）进行调整以反映特定系统的特性。应用所提出的类型学将支持可转移和可扩展的水资源ABMs的系统设计和开发，并促进社会和生物物理过程模型动态耦合。