English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

. Managing water resources in a complex adaptive natural–humansystem is a challenge due to the difficulty of modeling human behavior underuncertain risk perception. The interaction between human-engineered systemsand natural processes needs to be modeled explicitly with an approach thatcan quantify the influence of incomplete/ambiguous information ondecision-making processes. In this study, we two-way coupled anagent-based model (ABM) with a river-routing and reservoir management model(RiverWare) to address this challenge. The human decision-making processes isdescribed in the ABM using Bayesian inference (BI) mapping joined with acost–loss (CL) model (BC-ABM). Incorporating BI mapping into an ABM allows anagent's psychological thinking process to be specified by a cognitive mapbetween decisions and relevant preceding factors that could affectdecision-making. A risk perception parameter is used in the BI mapping torepresent an agent's belief on the preceding factors. Integration of the CLmodel addresses an agent's behavior caused by changing socioeconomicconditions. We use the San Juan River basin in New Mexico, USA, to demonstratethe utility of this method. The calibrated BC-ABM–RiverWare model is shown tocapture the dynamics of historical irrigated area and streamflow changes. Theresults suggest that the proposed BC-ABM framework provides an improvedrepresentation of human decision-making processes compared to conventionalrule-based ABMs that do not take risk perception into account. Futurestudies will focus on modifying the BI mapping to consider direct agents'interactions, up-front cost of agent's decision, and upscaling the watershedABM to the regional scale.

Using a coupled agent-based modeling approach to analyze the role of risk perception in water management decisions