TY - JOUR
T1 - Geospatial assessment of a severe flood event in the Nilwala River basin, Sri Lanka
AU - Madhushani, Charuni I.
AU - Makumbura, Randika K.
AU - Basnayake, Vindhya
AU - Pawar, Uttam
AU - Azamathulla, Hazi Md
AU - Rathnayake, Upaka
N1 - Publisher Copyright:
© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.
PY - 2024/8
Y1 - 2024/8
N2 - Lessons learned from previous flood disasters are significant in mitigating future flood damages. Therefore, this study aims at understanding the disastrous damage caused by the 2017 flood that occurred in southern Sri Lanka. Most of the recent studies related to natural disasters have incorporated geospatial analysis to produce more convincing maps. However, generated flood maps using geospatial analysis for major flood events are limited in Sri Lanka. In order to fill the research gap, this study explores flood-affected areas using geospatial data for a severe flood event that occurred in May 2017 in the Nilwala River Basin, southern Sri Lanka. This is the first-ever study of the river basin even if it is annually flooded causing significant damage. We utilized Sentinel-2 images to identify the land use and land cover (LULC) of the downstream area of the basin. The study focused on two divisional secretariat (DS) divisions, specifically Matara and Thihagoda, which experienced significant impacts. The satellite images for the pre-flood and flood-affected areas were identified and compared to showcase that 46 km2 of area out of 109 km2 tested were inundated. Results found from the research paved to present applicable disaster management practices to mitigate the damages from future floods to the basin. In addition, a predominant influence has also been noted in the chosen DS divisions. Therefore, it is crucial to concentrate more research in this area to reduce the severity of the damage.
AB - Lessons learned from previous flood disasters are significant in mitigating future flood damages. Therefore, this study aims at understanding the disastrous damage caused by the 2017 flood that occurred in southern Sri Lanka. Most of the recent studies related to natural disasters have incorporated geospatial analysis to produce more convincing maps. However, generated flood maps using geospatial analysis for major flood events are limited in Sri Lanka. In order to fill the research gap, this study explores flood-affected areas using geospatial data for a severe flood event that occurred in May 2017 in the Nilwala River Basin, southern Sri Lanka. This is the first-ever study of the river basin even if it is annually flooded causing significant damage. We utilized Sentinel-2 images to identify the land use and land cover (LULC) of the downstream area of the basin. The study focused on two divisional secretariat (DS) divisions, specifically Matara and Thihagoda, which experienced significant impacts. The satellite images for the pre-flood and flood-affected areas were identified and compared to showcase that 46 km2 of area out of 109 km2 tested were inundated. Results found from the research paved to present applicable disaster management practices to mitigate the damages from future floods to the basin. In addition, a predominant influence has also been noted in the chosen DS divisions. Therefore, it is crucial to concentrate more research in this area to reduce the severity of the damage.
KW - Flood mapping
KW - Floods
KW - Geospatial analysis
KW - Land use and land cover (LULC) classification
KW - Satellite images
UR - http://www.scopus.com/inward/record.url?scp=85198843119&partnerID=8YFLogxK
U2 - 10.1007/s40899-024-01133-z
DO - 10.1007/s40899-024-01133-z
M3 - Article
AN - SCOPUS:85198843119
SN - 2363-5037
VL - 10
JO - Sustainable Water Resources Management
JF - Sustainable Water Resources Management
IS - 4
M1 - 152
ER -