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Lawachara National Park (LNP) is one of the most renowned protected areas in Bangladesh and a natural habitat of critically endangered Hoolock gibbon. The study's purpose was to assess the long-term change of forest cover using the Normalized Difference Vegetation Index (NDVI) technique and evaluate the impact of co-management. Landsat images acquired from the USGS glovis website were used to assess forest cover change using NDVI, a popular technique for identification and estimation of forest areas. NDVI value ranges from (− 1) to (+ 1); a negative value indicates non-vegetated areas including water bodies, road surfaces, settlements, etc., whereas a positive value near (+ 1) indicates the highest density vegetation. NDVI value (0) indicates bare land without vegetation. Based on NDVI values, the forest areas have been divided into four categories, namely: (1) very low or no vegetation area, (2) low-density vegetation area, (3) moderate-density vegetation area, and (4) dense vegetation area. A household survey was carried out among the people living in the adjacent villages to LNP. The study of assessing the forest cover change of LNP using remotely sensed data revealed that, after the initiation of co-management, the dense vegetation area increased by 8.62% in 2006 compared to 2001, but it decreased by 0.77% in 2014. In 2018, dense vegetation decreased by 3.86% relative to the dense vegetation area of 2014. If it is compared as a whole, it can be said that the forest cover has improved under co-management, and the household survey revealed that forest dependence has been reduced which might be considered as one of the reasons for forest cover improvement. However, more improvement can be achieved by focusing on the villages where forest dependence is still high. Betel leaf cultivation inside the forest area is creating a problem for wildlife and also hampering the natural composition of flora. Therefore, it is recommended to rehabilitate betel leaf cultivators outside the forest area with proper compensation. This will harness the full potentiality of the co-management practice, it needs complete monitoring and goodwill from every stakeholder, and hence it will bring good for the whole country.

Sustainable rice production in the coastal region of Bangladesh is threatened due to various climatic impacts. The study investigated the current scenario of rice production and identified the linkage among different input variables related to rice production such as seed, urea, pesticide, etc. in three districts of Patuakhali, Khulna, and Cox’s Bazar, using a log–log model and panel data analysis. The Stochastic Model of multiple regression analysis helped to identify the most important input variables. The input factors found common in all three study areas were seed. The log–log model was used to identify how climatic factors influenced these input variables. Identifying such factors would help to ensure sustainable agriculture production in the future. Seed cost showed a negative elasticity in Patuakhali, while urea cost showed a negative elasticity in Khulna region. Time series forecasting of rice production up to 2030 in the study areas was examined using the best fitted ARIMA model. While rice production showed an increasing trend in two regions, it did not show a satisfactory upward trend in Kutubdia, which is mostly related to their mismanagement of fertilizer use and irrigation water scarcity. The analysis from the research indicated that an area-specific adaptation plan is required to sustain the agricultural production, as the input variables for rice production were not found similar for three different study districts where a specific attention needs to be given. Moreover, to address the nonexistence of quality panel data for rice production, measures have been introduced which includes an online data collection system using a mobile application.

Climate-induced changes, such as extreme cyclones, devastating tidal surges, severe floods, river erosion, excessive rainfall, and overwhelming salinity intrusion, occur more frequently and unpredictably across Bangladesh. The frequency and intensity of these hazards are likely to increase due to climate change. This study considers the baseline situation of the grassroots people of Mongla Upazila & community perception of climate change vulnerability and the local community-based adaptation strategies. Data were collected from respondents in Sundarban, Mithakahali, Chandpai, Sonailtola unions of Mongla Upazila, Bagerhat District, Bangladesh, an area subjected to frequent climate-related hazards. Many of the respondents within the target communities did not recognize the frequency and intensity of climate change. Most notably, although salinity was widely recognized as a significant problem for the community – agriculture, fisheries, biodiversity, trees, and plants, are all highly vulnerable – very few perceived an increased risk due to climate change. This suggests that communities do not predict perfectly an increased threat from these hazards and thus may not recognize the need to implement adaptation strategies further. In this research, the highest hazard score is 12, obtained by 100 families, illustrating that those families are in the most precarious position in terms of different climatic disasters the region faces. The table also elucidates that the hazard score of 12 is obtained by five families, illustrating that those families are in the most precarious position in terms of the region's different climatic disasters. The table also elucidates that the hazard score of forty-nine families is between 10 to 11.5, more than 25% of the total respondents. Forty-two families lie between 8.5–9.5, 43% of the total Respondent. The rest of the four respondents' score lies between 5.5-8, 3.56% of the total respondents.

Renewable energy is of great importance for today’s world which is generally produced from natural sources. Countries like Bangladesh has to use this energy to meet their energy demand. Day by day the demand of electricity is increasing in stormy pace but our resource is limited. So using renewable resources i.e. solar power to meet the demand of electricity is highly necessary especially rural and remote areas. This paper examined the nature and extent of solar energy in Boyarjapha village of Paikgachha Upazila of Khulna district to analyse the effects of solar panel in their daily life. Many positive impacts of solar power were found out such as better quality lighting, education, entertainment, communications, business, increasing working hours, women empowerment, increasing awareness etc. There are a few bad effects of solar energy too. But Government intervention is a must to ensure better quality results in coming future. Similarly, government has to take serious steps to advertise solar electricity in remote areas of Bangladesh

Bangladesh is one of the most disaster prone countries of the world and has been subjected to frequent natural disasters in many forms, particularly cyclonic storms and storm surges. The low-lying coastal areas are particularly vulnerable, thus placing these population, infrastructure, agriculture, livestock and economic development in a high-risk situation. The situation calls for an effective cyclone warning and dissemination system. With a view to address that this research intends to develop and manage a website containing all the information for helping in taking decision about disaster management. As its common knowledge that disaster victims need immediate, efficient and effective rescue and relief services, this system will provide relief and rescue workers with a platform easy to use, fast to search, retrieve and access information and most importantly will help in preventing the duplication of relief works. Overall, proper co-ordination will be ensured among the existing organization seems to be lacking due to the shortage of effective information dissemination system.

In this study, an attempt has been made to simulate the Heat Wave conditions in temperature range of ≥ 36ºC and its associated thermodynamic features over Bangladesh from 19 may to 25 May, 2017, using Advanced Research and Forecasting Model (WRF-ARW) - version 4.0. The WRF model was run for 6 days on a single domain of 10 km. horizontal resolution, using 6 hourly GFS datasets from 0000 UTC of each starting day of the required events as initial and lateral boundary conditions. For simulation, Kessler Scheme (KF) for microphysics, Yonsei University Scheme (YUS) for Planetary Boundary Layer (PBL) parametrization, Rapid Radiative Transfer Model (RRTM) for long wave radiation, and Dudhia Scheme (DS) for short wave radiation and Kain- Fritsch (KF) scheme for cumulus parametrization were used. The models have been analyzed numerically using several meteorological parameters such as Mean Sea Level Pressure, Relative Humidity, Temperature, Wind Pattern, Rainfall and Latent Heat, and the output is visualized by Grid Analysis and Display System (GrADS) and surfer. To validate the model performance, model-simulated values of Relative Humidity, Temperature (maximum) and Mean Sea Level Pressure were compared with observed data (Bangladesh Meteorological Department). From the analysis it is clear that the performance of the model is reasonably well to the observations, so that for the up-coming events for extreme temperature conditions the model can be used for the prediction which will bring social and economic benefits.