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 succ...
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Published in | Environmental monitoring and assessment Vol. 195; no. 4; p. 504 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
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Springer International Publishing
01.04.2023
Springer Nature B.V |
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Abstract | 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. |
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AbstractList | 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. 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. |
ArticleNumber | 504 |
Author | Halwatura, D. Ahmed, S. H. Bellanthudawa, B. K. A. Kendaragama, K. M. N. Nawalage, N. M. S. K. Neththipola, M. M. T. D. |
Author_xml | – sequence: 1 givenname: B. K. A. orcidid: 0000-0002-1830-8949 surname: Bellanthudawa fullname: Bellanthudawa, B. K. A. email: aravindabellanthudawa@gmail.com organization: Department of Civil, Environmental, and Construction Engineering, University of Central Florida – sequence: 2 givenname: N. M. S. K. orcidid: 0000-0002-9635-1563 surname: Nawalage fullname: Nawalage, N. M. S. K. organization: Ministry of Public Service, Provincial Council and Local Government – sequence: 3 givenname: D. orcidid: 0000-0002-0135-4690 surname: Halwatura fullname: Halwatura, D. organization: Department of Zoology and Environment Sciences, University of Colombo – sequence: 4 givenname: S. H. orcidid: 0000-0002-8954-9942 surname: Ahmed fullname: Ahmed, S. H. organization: Department of Computer Science, University of Central Florida, Department of Computer Science, DHA Suffa University – sequence: 5 givenname: K. M. N. surname: Kendaragama fullname: Kendaragama, K. M. N. organization: Department of Geology, Geological Survey and Mines Bureau – sequence: 6 givenname: M. M. T. D. orcidid: 0000-0002-6393-5554 surname: Neththipola fullname: Neththipola, M. M. T. D. organization: Department of Plant and Molecular Biology, University of Kelaniya |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/36952040$$D View this record in MEDLINE/PubMed |
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Keywords | Flood management Tropical river basin Regeneration process Vegetation indices Biophysical and biochemical features |
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SubjectTerms | Atmospheric Protection/Air Quality Control/Air Pollution Basins Climate change Climate change scenarios Climate models Earth and Environmental Science Ecology Ecotoxicology Environment Environmental Management Environmental monitoring Environmental Monitoring - methods Environmental science Feedback Flood basins Flood management Floods Global climate MODIS Monitoring/Environmental Analysis Normalized difference vegetative index Photosynthetically active radiation Primary production Recovery Regeneration Regeneration (biological) Rehabilitation Remote sensing Remote Sensing Technology River basins Rivers Spectroradiometers Temporal variations Vegetation Vegetation index |
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Title | Biophysical and biochemical features’ feedback associated with a flood episode in a tropical river basin model |
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