Evidence map›Paper›PMID 41246039›Full record

ArticleMethodsX2025

FRAMe: Empirically informed agent-based modeling of flood resilience in the Mekong River Basin.

Wenhan Feng, Liang Emlyn Yang, Mei Ai, Siying Chen, Ziyao Wang, Wenhao Wu, Junxu Chen, Yiping Fang, Yun Xu, Matthias Garschagen

Abstract read
In one paragraph

Article in MethodsX, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Wenhan FengDepartment of Geography, Ludwig Maximilian University of Munich (LMU), Munich 80333, Germany.
Liang Emlyn YangDepartment of Geography, Ludwig Maximilian University of Munich (LMU), Munich 80333, Germany.
Mei AiDepartment of Geography, Ludwig Maximilian University of Munich (LMU), Munich 80333, Germany.
Siying ChenDepartment of Geography, Ludwig Maximilian University of Munich (LMU), Munich 80333, Germany.
Ziyao WangSchool of Earth Sciences, Yunnan University, 650500 Kunming, China.
Wenhao WuDepartment of Environmental Science and Engineering, Fudan University, 200433 Shanghai, China.
Junxu ChenSchool of Earth Sciences, Yunnan University, 650500 Kunming, China.
Yiping FangInstitute of Mountain Hazards and Environment, Chinese Academy of Sciences, 610299 Chengdu, China.
Yun XuInstitute of Mountain Hazards and Environment, Chinese Academy of Sciences, 610299 Chengdu, China.
Matthias GarschagenDepartment of Geography, Ludwig Maximilian University of Munich (LMU), Munich 80333, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The FRAMe (Flood Resilience Agent-Based Model) serves as a framework designed to simulate flood resilience dynamics at the community level, focusing on a rural settlement in the Mekong River basin. Integrating empirical data from extensive surveys, Bayesian networks, and hydrological simulations, the framework quantifies resilience as a trade-off between robustness (resistance to damage) and adaptability (capacity for dynamic response). Agents include households, governments, and other institutional actors, linked by social and governance networks that facilitate knowledge transfer, resource distribution, and risk communication. FRAMe incorporates mechanisms for policy interventions and individual and collective decision-making, grounded in Protection Motivation Theory and MoHuB frameworks. The framework utilizes geographic data to achieve a spatially explicit design. Sensitivity analyses across five key parameter groups covering network structure, knowledge dissemination, and policy intensity demonstrate the model's robustness and allow systematic evaluation of intervention effects. Simulation results show that increasing the intensity of government assistance reduces average recovery time by around 50 % and improves system-level robustness by about 30 %. In contrast, enhancing emergency relief primarily improves adaptability (approximately 10 %) and shortens recovery time, with limited effect on robustness. Higher knowledge dissemination roughly doubles adaptability but also introduces greater variability in robustness. By examining policy scenarios and agent behavior, FRAMe aims to inform adaptive flood management strategies and foster the improvement of community resilience.•The agent-based model is described using the ODD+

Indexed as

Agent-based modelingClimate adaptive behaviorCommunity resilienceFlood resilienceSocial network analysis

Identifiers

PMID41246039
PMCPMC12616095

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.