Hyper-local flood forecast data to be used for better disaster mitigation planning

Community-operated rain gauges in Kerala provide real-time data to enhance disaster planning and mitigation efforts.

Data collated daily from 100 rain gauges being operated with community participation across the Periyar and Chalakudy river basins will now be available to the Ernakulam District Emergency Operation Centre (EOC) for better disaster mitigation planning in the future.

The rain gauges were installed over the past one year as a pilot project of the Community-Sourced Impact-based Flood Forecast and Early Warning System (CoS-it-FloWS), a project run by Equinoct, a Kochi-based community-sourced modelling solution provider. The project had received the recognition of the United Nations Children’s Fund’s (UNICEF) maiden Climate Tech Cohort Venture Fund Project last year.

The 100 rain gauges have been installed across Ernakulam, Idukki and Thrissur districts. Data on rainfall, river, tidal and groundwater levels that are collected primarily by students, women, and youth at the household level is then analysed and visualised through Insight Gather, a web portal to host the impact-based forecasts in the pilot basins.

“Sharing this data with the Ernakulam EOC will mark the completion of the first phase of our project. The idea is to plug gaps in government data and to scale up the project with greater community participation by collecting hyper-local data for fighting natural disasters. We also plan to create data models through the application of Artificial Intelligence (AI) for forecasting the impact of an adverse weather incident with greater accuracy during this age of climate change when rainfall forecast, especially in tropical areas, has become increasingly perilous,” said C.G. Madhusoodhanan, chief executive officer, Equinoct.

CoS-it-FloWS aims at bridging the last-mile connectivity and data gaps while providing innovative and inclusive solutions to address climate risks. This is done by empowering local communities to build hyper-local monitoring systems, developing hydrological models, and building AI modules for reducing uncertainties in flood inundation mapping and forecasting and impact-based warning systems and co-creating science-based solutions and decision support systems for disaster risk reduction with communities.

“In the next phase, the system will be put to test during an actual disaster to analyse the dependability of the data. It will be further fine-tuned by correcting mistakes, if any. With government support, the system can be scaled up further by making available even hourly updates instead of the present system of daily reports,” said C. Jayaraman, managing director, Equinoct.