Abstract:
Floods are one of the most disastrous and
dangerous catastrophes faced by humanity for ages.
Though mostly deemed a natural phenomenon, foods
can be anthropogenic and can be equally devastating
in modern times. Remote sensing with its non-evasive
data availability and high temporal resolution stands
unparalleled for food mapping and modelling. Since
foods in India occur mainly in monsoon months,
optical remote sensing has limited applications in
proper food mapping owing to lesser number of
cloud-free days. Remotely sensed microwave/synthetic
aperture radar (SAR) data has penetration ability and
has high temporal data availability, making it both
weather independent and highly versatile for the study
of foods. This study uses space-borne SAR data in
C-band with VV (vertically emitted and vertically
received) and VH (vertically emitted and horizontally
received) polarization channels from Sentinel-1A
satellite for SAR interferometry-based food mapping
and runof modeling for Rupnagar (Punjab) foods
of 2019. The food maps were prepared using coherence-based thresholding, and digital elevation
map (DEM) was prepared by correlating the
unwrapped phase to elevation. The DEM was further
used for Soil Conservation Service-curve number
(SCS-CN)-based runof modelling. The maximum
runof on 18 August 2019 was 350 mm while the
average daily rainfall was 120 mm. The estimated
runof signifcantly correlated with the rainfall with
an R2
statistics value of 0.93 for 18 August 2019. On
18 August 2019, Rupnagar saw the most devastating
foods and waterlogging that submerged acres of land
and displaced thousands of people.
