In the sun-kissed coastal region of Tamil Nadu, India, a silent battle is being waged against an invisible enemy: flooding. As climate change and land use shifts reshape the landscape, the specter of floods looms larger, threatening not just lives and homes, but also the region’s critical infrastructure and economy.
Enter Devanantham Abijith, a researcher from the Department of Civil Engineering at the National Institute of Technology, who has taken up the challenge of mapping flood vulnerabilities with unprecedented precision. His recent study, published in Geoscience Letters, leverages the power of machine learning and geospatial tools to predict how changes in land use and climate will impact flood risk across the Tamil Nadu coast.
Abijith and his team utilized Google Earth Engine and Sentinel-1 data, along with a multitude of geospatial datasets, to create a comprehensive flood susceptibility map. “The integration of these advanced tools allows us to not only identify current flood-prone areas but also to project future risks under different climate change scenarios,” Abijith explains.
The study employed a random forest algorithm to classify Land Use and Land Cover (LULC) changes and identify flood-prone areas. By analyzing data from 2000, 2010, and 2020, the team projected LULC changes up to 2050 and incorporated four future climate scenarios from the Coupled Model Intercomparison Project 6 (CMIP6) to assess average annual precipitation trends.
The results paint a concerning picture. The risk of flooding is set to increase across all scenarios from 2000 to 2100, with notable fluctuations on a decadal basis. Perhaps most alarmingly, the percentage of the area transitioning to moderate and very high flood risk is on a consistent upward trajectory. “This study underscores the urgent need for adaptive strategies in flood management,” Abijith warns.
The implications for the energy sector are profound. Flooding can disrupt power generation, transmission, and distribution, leading to significant economic losses. By providing detailed flood risk estimates, Abijith’s research offers invaluable insights for energy companies looking to fortify their infrastructure against future threats.
The energy sector is not the only one that stands to benefit. Urban planners, policymakers, and environmentalists alike can use this data to develop targeted mitigation strategies, ensuring that vulnerable communities are better protected. “Our methodology presents a viable approach for flood susceptibility mapping based on different climate change scenarios,” Abijith notes. “This can serve as a blueprint for similar studies in other coastal regions around the world.”
As the battle against flooding intensifies, Abijith’s work shines a light on the path forward. By harnessing the power of machine learning and geospatial analysis, we can turn the tide on this relentless foe, safeguarding lives, livelihoods, and critical infrastructure for generations to come. This research, published in Geoscience Letters, promises to shape future developments in the field, driving innovation and resilience in the face of climate change.
