Abstract:
Ma Oya, a significant stream in Sri Lanka, is a cultural and ecological en-
tity. The study aimed to describe the environmental dynamics in Ma Oya river basin,
during the North-East Monsoon (NEM) and South-West Monsoon (SWM) seasons in
2017 and 2022. The study integrates key Remote Sensing (RS) indices such as Nor-
malized Difference Vegetation Index (NDVI), and Land Surface Temperature (LST)
from Landsat 08 and 09 satellite sources. This study explored the changes and rela-
tionships between these RS indices, to quantitatively monitor variations in critical
environmental parameters during selected monsoon seasons. This investigation com-
bines data from satellite sources and ground-based observations. Gross Biomass Wa-
ter Productivity (GBWP) data were taken from the FAO Water Productivity Open-
access portal (WaPOR). After calculating indices, statistical analyses were applied to
explore the correlations, providing insights into the ecological dynamics. The study
revealed robust correlations between VCI, NDVI, and LST, during both the NEM and
SWM for the years 2017 and 2022. Notable differences were observed in mean LST
and NDVI values during SWM, exemplified by a mean LST of 25.41°C in September
2022 and a mean NDVI of 0.44 in the same period, indicating high variations in tem-
perature and vegetation health. The results revealed a negative correlation between
the VCI and GBWP, indicating an inverse relationship between vegetation health and
water productivity in the Ma Oya river basin. The study enhances understanding of
environmental dynamics in the Ma Oya river basin by examining the connections be-
tween LST, NDVI, VCI, and GBWP. The VCI severity levels highlight the dynamic
nature of drought conditions in the Ma Oya river basin, exhibiting significant fluctu-
ations across categories during both the NEM and SWM for the years 2017 and 2022.
The SWM showed distinct patterns, indicating more pronounced fluctuations in VCI
levels compared to the NEM. The study highlights the variations in drought severity
between monsoon seasons, providing insights into the connections between meteoro-
logical factors, vegetation health, and temperature. Limitations of this study, includ-
ing lack of satellite data, which may impact the generalizability of the findings.
