Urbanization is closely associated with land use land cover (LULC) changes that correspond to land surface temperature (LST) variation and urban heat island (UHI) intensity. Major districts of Bangladesh have a large population base and commonly lack the resources to manage fast urbanization effects, so any rise in urban temperature influences the population both directly and indirectly. However, little is known about the impact of rapid urbanization on UHI intensity variations during the winter dry period in the major districts of Bangladesh. To this end, we aim to quantify spatiotemporal associations of UHI intensity during the winter period between 2000 and 2019 using remote-sensing and geo-spatial tools. Landsat-8 and Landsat-5 imageries of these major districts during the dry winter period from 2000 to 2020 were used for this purpose, with overall precision varying from 81% to 93%. The results of LULC classification and LST estimation showed the existence of multiple UHIs in all major districts, which showed upward trends, except for the Rajshahi and Rangpur districts. A substantial increase in urban expansion was observed in Barisal > 32%, Mymensingh > 18%, Dhaka > 17%, Chattogram > 14%, and Rangpur > 13%, while a significant decrease in built-up areas was noticed in Sylhet < −1.45% and Rajshahi < −3.72%. We found that large districts have greater UHIs than small districts. High UHI intensities were observed in Mymensingh > 10 °C, Chattogram > 9 °C, and Barisal > 8 °C compared to other districts due to dense population and unplanned urbanization. We identified higher LST (hotspots) zones in all districts to be increased with the urban expansion and bare land. The suburbanized strategy should prioritize the restraint of the high intensity of UHIs. A heterogeneous increase in UHI intensity over all seven districts was found, which might have potential implications for regional climate change. Our study findings will enable policymakers to reduce UHI and the climate change effect in the concerned districts.

Evaluation of drought is essential and useful to eradicate climate change impact. Therefore, this study aims to explore the spatiotemporal drought intensity trend in seven climatic zones of Bangladesh during 1979–2019. Mann-Kendall trend test and Standardized Precipitation Evapotranspiration Index (SPEI) are employed to identify drought trend and status, whereas spatial visualization is checked through Inverse Distance Weighting Interpolation. The study's findings emphasize the decreasing rate of SPEI in all climatic zones except the south-eastern zone, which is > 0.0065, >0.007, >0.0128, and >-0.0001 for SPEI 09 12, 24, and 06, respectively. Furthermore, the northern region has the highest value in SPEI in some periods with the highest decrease rate in SPEI 06, SPEI 09, SPEI 12 demonstrates greater drought responsibilities. The Barisal (.>-3.75), Rangpur (>-3.65), Dinajpur ((>-3.00), Rajshahi (>-4.35), Bogra (>-4.50), Ishurdi (>-3.45), Faridpur (>-4.30) and Madaripur (>-2.10) found under extreme drought-prone climatic zone. Thus, the study recommends taking initiatives and management for water resources to adopt mitigation planning for drought-prone climatic zones.

Rainfall trend analysis is common for climate change observation following the flood, drought, and other extreme hydrometeorological possibilities. Therefore, this study aims to evaluate the spatiotemporal rainfall trend for seven climatic zones in Bangladesh during 1979–2019. For the trend exploration Mann-Kendall (MK) trend test, slope estimator (Sens) and IDW techniques were utilised from the dataset of 27 stations. The findings shows descending annual trend of >-2.50, >1.95, >-1.80, >-1.60, >-1.31 and >-0.50 for the zones of (C)western region, (A)northern part of northern region, (B)north-western region, (E)south-central region, (D)south-western region and (G)north-eastern region, respectively, whereas ascending trend found for only (F)south-eastern region >1.83. Except for post-monsoon season zone F > 2.90 trends, all other seasonal trend is in a declining position. An increasing magnitude of rainfall is found >0.0355(F) for annual, >0.136(A), 0.0146(C), 0.0047(F) and 0.0093(G) for pre-monsoon, >0.0046(D), >0.0329(F) for post-monsoon, >0.0039(G) for winter and >0.0273(F) for monsoon seasons while all other zones are in decreased nature. Heterogeneously significant rainfall magnitude for annual, pre-monsoon, post-monsoon and monsoon seasons was also found, which includes >.03(F), >0.01(C), >0.03(F), >1.51(F), respectively. The findings recommend adopting operations and advanced design for water management with consideration of agricultural development and climate change.