Abstract
The present study deals with the analysis of synoptic conditions that led to floods in the Sheonath river basin, which is the largest tributary of the Mahanadi river basin. To identify the flooding events a flood disaster database Dartmouth Flood Observatory is used and archives from this source were examined and flooding years were identified as 1994, 2005 and 2007. To verify the flood events derived from the database, data of streamflow is used, which is available at five locations in the river basin. The effect of flooding was observed in one of these five stations. The Synoptic conditions were constructed for the aforementioned flood events using geopotential height anomalies at 500 and 850 hPa pressure levels and Sea Level Pressure data. These conditions were studied three days before the flood event. It was observed that all the three flood events had a low-pressure system developing over the northwestern Bay of Bengal as the common feature. However, each synoptic system of each flood event has a different pathway of dissipation. After establishing the synoptic conditions that led to flooding, the ENSO (Sea Surface Temperature Anomalies-SSTA) and streamflow relationship are examined by the correlation approach. It was observed that the streamflow in this river basin is weakly correlated with SSTA. The Sheonath river basin doesn’t experience frequent flooding, nevertheless, it is essential to study the meteorological aspects of flooding that involve the evolution of pressure patterns, change in atmospheric moisture and occurrence of precipitation that will provide a better understanding of the atmospheric drivers of floods.
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Azharuddin, M., Verma, S., Verma, M.K., Prasad, A.D. (2022). A Synoptic-Scale Assessment of Flood Events and ENSO—Streamflow Variability in Sheonath River Basin, India. In: Rao, C.M., Patra, K.C., Jhajharia, D., Kumari, S. (eds) Advanced Modelling and Innovations in Water Resources Engineering. Lecture Notes in Civil Engineering, vol 176. Springer, Singapore. https://doi.org/10.1007/978-981-16-4629-4_8
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DOI: https://doi.org/10.1007/978-981-16-4629-4_8
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