Evaluating flood dynamics and effects in Nagpur city using remote sensing and Shannon’s entropy analysis

Flood is among the most disastrous natural disasters since they are responsible for massive damage to infrastructure, severe fatalities and injuries, innumerable economic losses, and social disruptions worldwide. These damages caused by floods have been worsening in recent years worldwide because of environmental degradation, climatic change, and high-speed urbanization. A rising precipitation rate increases the chances of floods in flood-vulnerable areas. A flash flood is a rapid flooding of geomorphic low-lying regions caused by remarkably high rainfall in a short duration. On September 23rd, 2023 a flooding event in the Nagpur, Maharashtra, it is directly impact on the human death and economic loss entire city. In the present study, the change in the dynamics of Nagpur city was analysed by employing remote sensing and GIS techniques to assess the change in the land use and land cover patterns. Landsat imagery of year 2000, 2010, 2020, and 2023 was used for land use and land cover classification. This analysis reveals that there is an increase in built-up area from 72.85 sq. km in year 2000 to 185.4 sq. km in year 2023. The built up land is increased this changes where directly affects the infiltration rate of rainwater into the soil. The total area covered by water bodies is reduced to 2.29 sq. km in 2023 which were 12.2 sq. km in year 2000. It is indicates the encroachment of built-up land on the water bodies. On the day of flash flood occurrence, it was observed that Nagpur city received 145 mm rainfall which is highest in the month of September, 2023. The Shannon entropy model was used to estimate the population dynamics and growth patterns of Nagpur city. Higher entropy values were obtained during the analysis which indicates the rapid transformation of city in all directions. Population dynamics of Nagpur city also indicate the inflation in population from 4,067,637 in 2000 to 4,653,570 in 2010. The SAR water index was calculated using Google Earth Engine to detect the water surges in residential areas during the flood. Precautionary measures should be taken by governing authorities to avoid such disasters. Proper city planning and improvements in drainage systems are recommended within the city. It is needed for an hour to develop a river monitoring system and early warning system, as well as preventive measures that should be implemented, like the construction of retaining walls to control the flood water.