Biophysical and biochemical features' feedback associated with a flood episode in a tropical river basin model.

Global climate change scenarios such as frequent and extreme floods disturb the river basins by destructing the vegetation resulting in rehabilitation procedures being more costly. Thus, understanding the recovery and regeneration of vegetation followed by extreme flood events is critical for a successful rehabilitation process. Spatial and temporal variation of biochemical and biophysical features derived from remote sensing technology in vegetation can be incorporated to understand the recovery and regeneration of vegetation. The present study explores the flood impact on vegetation caused by major river basins in Sri Lanka (a model tropical river basin) by comparing pre-flood and post-flood cases. The study utilized enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), the fraction of photosynthetically active radiation (FPAR), and gross primary productivity (GPP) of the Moderate Resolution Imaging Spectroradiometer (MODIS) platform. A remarkable decline in EVI, LAI, FPAR, GPP, and vegetation condition index was observed in the post-flood case. Notably, coupled GPP-EVI and GPP-LAI portrayed dependency of features and showed a significant impact triggered by the flood episode by narrowing the feature in post-flood events. EVI depicted the highest regeneration (0.333) while GPP presented the lowest regeneration (0.093) after the flood event. Further, it was revealed that 1.18 years have been on the regeneration. The regeneration of GPP and LAI remained low comparatively justifying the magnitude and impact of the flood event. The study revealed successful implications of vegetation indices on flood basin management of small to large tropical river basins.