AI-Enhanced Flood Prediction and Environment Health Risk Communication: A Counselling Framework for Sustainable Development in the Niger Delta of Nigeria - Nathan Udoinyang; Edna Abibetu ABIDDE; Enebi AVWORO; Osiokor Onoriode ALEXANDER (RADINKA JAYA UTAMA PUBLISHER, PADANG, INDONESIA, 2026)
This study examines the integration of artificial intelligence (AI) in flood prediction and counselling-based environmental health risk communication in the Niger Delta region of Nigeria. The aim is to develop a comprehensive framework that enhances disaster preparedness and supports sustainable development. A mixed-method research design was employed, involving 450 respondents selected from Delta, Bayelsa, and Rivers States. Data were collected through structured questionnaires and interviews and then analysed using descriptive statistics, thematic analysis, and multiple regression techniques. The findings reveal that while flood risk awareness is high among residents, awareness of AI-based prediction systems and communication effectiveness remain moderate. Thematic results indicate that mistrust in government communication and delays in information dissemination are key barriers to effective risk communication and the adoption of AI-based prediction systems among residents. Regression analysis shows that AI prediction systems (β = 0.42) and counselling communication (β = 0.37) significantly improve environmental health risk awareness, leading to rejection of the null hypothesis. The study concludes that integrating AI technologies with counselling frameworks enhances risk communication, promotes behavioural change, and improves disaster preparedness. It recommends increased investment in AI systems, the incorporation of counselling services in disaster management, and the development of trust-based communication strategies. This integrated approach is essential for achieving sustainable development goals in flood-prone regions.