Accepted Paper
Paper short abstract
This study develops an early warning model for drought and salinity intrusion in the Mekong Delta, integrating vulnerability assessment, policy analysis, and climate change impact simulations to support mitigation and sustainable adaptation based on predictive indicators.
Paper long abstract
In the context of increasingly climate change, drought and salinity intrusion have become major challenges to livelihoods and sustainable development in the Mekong Delta (MD). Sea-level rise has intensified and spatially expanded salinity intrusion, affecting agricultural production, livelihoods, and the daily lives of local communities. In response, numerous early warning systems have been developed to support risk management and decision-making. However, in practice, many of these systems remain predominantly technically oriented and have yet to fully reflect how local communities perceive information, make decisions, and adapt in their everyday lives.
This study approaches drought and salinity intrusion from an equity-and people-centred perspective, emphasizing the role of local knowledge, lived experience, and access to resources in shaping adaptive responses to climate-related risks. Accordingly, the study aims to monitor and track the dynamics of drought and salinity intrusion in the MD; to develop an early warning model that is context-specific and responsive to local needs; and to project the impacts of drought and salinity intrusion under different climate change and sea-level rise scenarios. These efforts seek to provide a scientific basis for proposing sustainable adaptation solutions.
The study addresses key research questions: How do different community groups experience and respond to drought and salinity intrusion in their daily lives and production activities? What sources of information do they access, use, and perceive as reliable in their decision-making processes? How can local communities better understand and engage with the ways in which climate change adaptation policies and intervention programmes are implemented in practice?
Integrating diverse datasets for people-centred early warning systems: Bridging local and scientific knowledge, engaging knowledge hierarchies