Spatiotemporal Hydroclimate Anomalies in Bhubaneswar City, India (2000–2024): Using GIS and Python
Siba Prasad Mishra *
Geo-informatics Branch, Civil Engineering Department, Centurion University of Technology and Management, Jatni, Bhubaneswar, Odisha, India.
Dhibar, Maitri
Geo-informatics Branch, Civil Engineering Department, Centurion University of Technology and Management, Jatni, Bhubaneswar, Odisha, India.
Roy Rohan
Geo-informatics Branch, Civil Engineering Department, Centurion University of Technology and Management, Jatni, Bhubaneswar, Odisha, India.
Swarnaprabha Jena
Geo-informatics Branch, Civil Engineering Department, Centurion University of Technology and Management, Jatni, Bhubaneswar, Odisha, India.
*Author to whom correspondence should be addressed.
Abstract
The investigation identifies the geographic focus on the smart city of Bhubaneswar, Odisha, India, within the timeframe (2000–2024). The study identifies seasonal trends, extreme events, and their impacts on climate and human life. The maps are prepared using Python, like scatter plots of mean monthly and yearly rainfall (line, box, bar, and pie charts, etc.). Further, GIS-based maps prepared are the annual Rainfall distribution map of Odisha, the choropleth map for temperature distribution, slope map, relief and contour map of Bhubaneswar smart city, highlighting spatial impacts in Bhubaneswar zones (e.g., Bomi Khal, Naya Palli), etc. The slope, the contour and the population. Slum pockets maps have been prepared from the data of the Government of Odisha, NIC data and Digital Elevation Model. The analysis, supported by Python libraries (pandas, matplotlib, seaborn, geopandas, folium). The study identifies seasonal trends, extreme events and their impacts on climate and human life, focusing on urban flooding, infrastructure, health, agriculture and environmental degradation, with a geoinformatics approach. Recommendations include GIS-driven drainage mapping, rainwater harvesting, resource management, and climate-smart planning, with future research proposed for long-term trends and geospatial adaptation strategies.
The extreme events of rainfall cause waterlogged areas, urban flooding and fatalities due to heat strokes. The study discusses the impacts on climate and human life and supports the town planners and developers in climate-resilient planning, allied with SDGs 11 and 13 for sustainable urban dwellings, developing a zero slums concept in the sustainable smart city, Bhubaneswar.
Keywords: Climate change, rainfall trend, GIS, machine learning, Bhubaneswar, climate change