![]() ![]() Since large river networks of the country are fed by Himalayan snowmelt and local rainfall, high rainfall evidently affects riverbank erosion 12, while low rainfall reduces freshwater flow towards coastal areas, causing salinity ingress further inland 13 and affecting the livelihoods of millions. For instance, a moderate rainfall deficit causes a decline in groundwater in subsequent years 10, causing an increase in irrigation costs, reducing farmers’ profit, and overwhelming a vast majority of the rural population 11. It is also a primary source of groundwater replenishment. Nearly 40% of total crops in the country are rain-fed, and the rest depend on groundwater irrigation 9, meaning that rainfall variability, especially monsoonal amount (1500 mm), severely affects rain-fed agriculture, which has implications for food security due to its large population. It experiences a reduction in crop production of 20 to 30% in a drought year 8. Ozaki 7 showed that the country experiences economic damage of US$ 2.2 billion, equivalent to 1.5% of gross domestic product (GDP) during an abnormal flood year. Any change in rainfall patterns in terms of deficit/surplus or even a subtle shift can lead to climatic extremes such as drought and floods. For instance, nearly 70% of total rainfall occurs in the monsoon season (June to September), and <3% takes place in the dry season (December to February) 6. However, the country is susceptible to hydrometeorological hazards due to its flat topography and high rainfall seasonality 4, 5. ![]() Located in a tropical monsoonal climatic region, Bangladesh receives nearly 2200 mm of rainfall every year, which supports agriculture, the environment and livelihood activities since time immemorial 1, 2, 3. The product can provide reliable insights regarding various hydrometeorological issues, including historical floods, droughts, and groundwater recharge for a well-recognized global climate hotspot, Bangladesh. The BDGR also showed its capability in replicating temporal patterns and trends of observed rainfall with greater accuracy. The temporal variability in mean PBIAS for 1901–2018 was in the range of −4.5 to 4.3%, NRMSE between 9 and 19% and R 2 in the range of 0.87 to 0.95. ![]() The results revealed spatial variability of the percentage bias (PBIAS) in the range of −2 to 2%, normalized root mean square error (NRMSE) 0.88 at most of the locations. Leave-one-out cross-validation was used to assess product’s ability to capture spatial and temporal variability. In-situ rainfall observations retrieved from a number of sources, including national organizations and undigitized data from the colonial era, were used. A high-resolution (1 km × 1 km) monthly gridded rainfall data product during 1901–2018, named Bangladesh Gridded Rainfall (BDGR), was developed in this study. ![]()
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