TY - JOUR
T1 - Decoding the Vitality of Earth Observation for Flood Monitoring in the Lower Godavari River Basin, India
AU - Mukherjee, Jayesh
AU - Ghosh, Surajit
N1 - Publisher Copyright:
© 2023, Geological Society of India, Bengaluru, India.
PY - 2023/6/26
Y1 - 2023/6/26
N2 - The entire Indian subcontinent experienced devastating floods in the year 2022. The central section of the Godavari river basin (GRB) received torrential rainfall from the southwest monsoon during the second week of July 2022. This study exhibits how Earth observation (EO) datasets and cloud platforms like Google Earth Engine (GEE) can be used for swift, lucid and accurate decoding of the flood inundation signatures. Geospatial analysts can estimate concurrent floods using high-resolution C-band SAR/Sentinel-1 images, gridded precipitation and streamflow forecast datasets. The GPM (IMERG) precipitation data showed an incremental trend with prime hotspots, rainfall dissemination and retrieval from 01–20 July 2022 in the mid-GRB. The flood inundation layers were derived based on Otsu’s method with selective topographic conditions from Sentinel-1 in GEE. Five significant flood affected case sites were identified in the lower GRB from Kothapalli to Yanam town, where the Godavari river meets the Bay of Bengal. Large stretches of agricultural lands were found to be inundated, resulting in extensive economic losses. Such flooded farmlands surrounding Kothapalli, Bhadrachalam, Kunavaram, Polavaram and Yanam towns were estimated as 60, 91, 86, 170 and 142 km2 on 16 and 21 July 2022, respectively. The results were validated and cross-verified using bulletins and maps issued by various national agencies. Hence, EO, GEE and cloud analytical techniques are modern untapped potential e-assets vital for incorporation in policy frameworks helping disaster managers with comprehensive flood condition analysis.
AB - The entire Indian subcontinent experienced devastating floods in the year 2022. The central section of the Godavari river basin (GRB) received torrential rainfall from the southwest monsoon during the second week of July 2022. This study exhibits how Earth observation (EO) datasets and cloud platforms like Google Earth Engine (GEE) can be used for swift, lucid and accurate decoding of the flood inundation signatures. Geospatial analysts can estimate concurrent floods using high-resolution C-band SAR/Sentinel-1 images, gridded precipitation and streamflow forecast datasets. The GPM (IMERG) precipitation data showed an incremental trend with prime hotspots, rainfall dissemination and retrieval from 01–20 July 2022 in the mid-GRB. The flood inundation layers were derived based on Otsu’s method with selective topographic conditions from Sentinel-1 in GEE. Five significant flood affected case sites were identified in the lower GRB from Kothapalli to Yanam town, where the Godavari river meets the Bay of Bengal. Large stretches of agricultural lands were found to be inundated, resulting in extensive economic losses. Such flooded farmlands surrounding Kothapalli, Bhadrachalam, Kunavaram, Polavaram and Yanam towns were estimated as 60, 91, 86, 170 and 142 km2 on 16 and 21 July 2022, respectively. The results were validated and cross-verified using bulletins and maps issued by various national agencies. Hence, EO, GEE and cloud analytical techniques are modern untapped potential e-assets vital for incorporation in policy frameworks helping disaster managers with comprehensive flood condition analysis.
UR - http://www.scopus.com/inward/record.url?scp=85163365309&partnerID=8YFLogxK
U2 - 10.1007/s12594-023-2387-9
DO - 10.1007/s12594-023-2387-9
M3 - Article
SN - 0016-7622
VL - 99
SP - 802
EP - 808
JO - Journal of the Geological Society of India
JF - Journal of the Geological Society of India
IS - 6
ER -