## 4 Results
### Assessment of Inundation
#### 4.2.2. Inundation Due to Cyclone  
The extents of inundation during eight tropical cyclones, namely, Mora, Titii, Fani, Amphan, Yaas, Sitrang, Midhili, and Renal, were assessed using SAR imagery and are illustrated in Figure 9. In May 2017, Cyclone Mora made landfall south of Chittagong, with maximum sustained wind speeds of 110 km/h, inundating approximately 6888 sq. km (Figure 9a). Although it struck the southeastern coast, the most severe inundation occurred  
Figure 8: Inundation in the coastal districts due to monsoon rainfall events of the year (**a**) 2017, (**b**) 2018, (**c**) 2019, (**d**) 2020, (**e**) 2021, (**f**) 2022, (**g**) 2023, and (**h**) 2024.  
in the southwestern region, particularly around Morrelganj Upazila. Other moderately affected areas included Maheshkhali, Begumganj (Noakhali district), and Shyammagar (Satkhira district). Cyclone Titil, classified as a very severe cyclonic storm, made landfall in October 2018 with a maximum sustained surface wind speed of 165 km/h. Although it struck the coastline near northern Andhra Pradesh and southern Odisha, significant inundation was recorded in the coastal districts of Bangladesh, with an affected area of approximately 7958 sq. km, the second-largest among eight major cyclonic events analyzed (Figure 9b). Extensive inundation was observed in Jessore, Cox's Bazar, Satkania (Chittagong district), Noakhali, and Bbola, while moderate inundation affected regions such as Feni, Morrelganj, and Galachipa (Patuakhali district). Despite the heavy rainfall reported in the southeastern coastal zone, substantial inundations also occurred in Jessore, located in the southwestern coastal region. In May 2019, Cyclone Fani, an extremely severe cyclone with a maximum wind speed of approximately 185 km/h, made landfall near the Odisha coast. Although the landfall occurred at a considerable distance from the Bangladesh coastline, the resulting depression advanced toward the country's southwest coast, leading to approximately 4934 sq. km of inundation, the smallest affected area among the eight cyclones analyzed (Figure 9c). As a result, the southwest coastal districts exhibited significantly greater inundation compared to the southeast and south-central coastal regions. Considerable inundation was observed in Khulina, Satkhira, Shyammagar, and Chittagong, with moderate inundation occurring in Chakaria, Barguna, Pirojpur, Morrelganj, Noakhali, Kalapara, and Charfasson (Bbola district). In May 2020, Super Cyclone Amphan, with wind speeds reaching 270 km/h, caused extensive inundation, affecting around 7649 sq. km (Figure 9d). Although it made landfall near the Sundarbans in West Bengal, India, substantial flooding occurred across the southwestern coastal areas and parts of the south-central region. Severely inundated areas included Morrelganj, Kaliganj, and Kalapara, with localized impacts in Chakaria. Over the next two years, the coastal zone experienced relatively lower levels of inundation. In May 2021, Cyclone Yaas (140 km/h) affected approximately 6542 sq. km, despite making landfall in Odisha and West Bengal, India (Figure 9e). In October 2022, Cyclone Sitrang (85 km/h) made landfall in Barisal, Bangladesh, inundating about 6535 sq. km (Figure 9f). Moderate flooding was also observed in Shyammagar and Chakaria. Cyclone Midhili, which struck in November 2023 with a wind speed of 95 km/h and made landfall in Patuakhali District, caused the second-least inundation among the eight events-approximately 5427 sq. km (Figure 9g). Nevertheless, significant flooding occurred in parts of Kalia, Bagerhat, and Shyammagar, with additional inundations in Chatkhil (Noakhali district) and Galachipa (Patuakhali district) due to its eastern landfall. Finally, Cyclone Renal in May 2024, with a maximum wind speed of 110 km/h, caused the most extensive inundation, affecting approximately 9243 sq. km (Figure 9h). The cyclone made landfall between Sagar Islands and Khepupara, near Mongla, triggering widespread flooding across the coastline.