TY - JOUR
T1 - Probabilistic Mapping of August 2018 Flood of Kerala, India, Using Space-Borne Synthetic Aperture Radar
AU - Sherpa, Sonam Futi
AU - Shirzaei, Manoochehr
AU - Ojha, Chandrakanta
AU - Werth, Susanna
AU - Hostache, Renaud
N1 - Funding Information:
Manuscript received October 26, 2019; revised December 24, 2019 and January 19, 2020; accepted January 20, 2020. Date of publication February 17, 2020; date of current version March 17, 2020. The work of Sonam Futi Sherpa and Manoochehr Shirzaei was supported in part by NASA Grant 80NSSC170567. Chandrakanta Ojha and Susanna Werth are supported by NASA under Grant NNX17AD98G. The work of Renaud Hostache was supported in part by the National Research Fund of Luxembourg through the CASCADE Project under Grant C17/SR/11682050. (Corresponding author: Sonam Futi Sherpa.) Sonam Futi Sherpa, Manoochehr Shirzaei, and Chandrakanta Ojha are with the School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287 USA (e-mail: sfsherpa@asu.edu; shirzaei@asu.edu; Chandrakanta.Ojha@asu.edu).
Publisher Copyright:
© 2020 IEEE.
PY - 2020
Y1 - 2020
N2 - Synthetic aperture radar (SAR) imaging provides an all-weather sensing technique that is suitable for near-real-time mapping of disasters such as floods. In this article, we use SAR data acquired by Sentinel-1A/B satellites to investigate a flood event that affected the Indian state of Kerala in August 2018. We apply a Bayesian approach to generate probabilistic flood maps, which contain for each pixel its probability to be flooded rather than binary flood information. We find that the extent of the flooded area begins to increase throughout Kerala after August 8, with the highest values on August 9 and August 21. We observe no apparent correlation between the spatial distributions of the flooded areas and the rainfall amounts at the district level of the study area. Instead, larger flooded areas are in the districts of Alappuzha and Kottayam, located in the downstream floodplain of the Idduki dam, which released a significant volume of water on August 16. The lack of apparent correlation is likely due to two reasons: first, there is often some delay between the rainfall event and the flooding, especially for rather large catchments where flood waves need some time to reach floodplains from higher elevations. Second, rainfall is more abundant at overhead catchments (hills and mountains), whereas flood occurs further downstream in the floodplains. Further comparison of our SAR-based flood maps with optical data and flood maps produced by moderate resolution imaging spectroradiometer highlights the advantages of our data and approach for rapid response purposes and future flood forecasting.
AB - Synthetic aperture radar (SAR) imaging provides an all-weather sensing technique that is suitable for near-real-time mapping of disasters such as floods. In this article, we use SAR data acquired by Sentinel-1A/B satellites to investigate a flood event that affected the Indian state of Kerala in August 2018. We apply a Bayesian approach to generate probabilistic flood maps, which contain for each pixel its probability to be flooded rather than binary flood information. We find that the extent of the flooded area begins to increase throughout Kerala after August 8, with the highest values on August 9 and August 21. We observe no apparent correlation between the spatial distributions of the flooded areas and the rainfall amounts at the district level of the study area. Instead, larger flooded areas are in the districts of Alappuzha and Kottayam, located in the downstream floodplain of the Idduki dam, which released a significant volume of water on August 16. The lack of apparent correlation is likely due to two reasons: first, there is often some delay between the rainfall event and the flooding, especially for rather large catchments where flood waves need some time to reach floodplains from higher elevations. Second, rainfall is more abundant at overhead catchments (hills and mountains), whereas flood occurs further downstream in the floodplains. Further comparison of our SAR-based flood maps with optical data and flood maps produced by moderate resolution imaging spectroradiometer highlights the advantages of our data and approach for rapid response purposes and future flood forecasting.
KW - Kerala 2018 flood
KW - probabilistic flood map
KW - synthetic aperture radar (SAR)
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U2 - 10.1109/JSTARS.2020.2970337
DO - 10.1109/JSTARS.2020.2970337
M3 - Article
AN - SCOPUS:85082402620
SN - 1939-1404
VL - 13
SP - 896
EP - 913
JO - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
JF - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
M1 - 9000852
ER -