Temperature rise is a concern for future agriculture in different regions of the globe. This study aimed to reveal the future changes and variabilities in minimum temperature (Tmin) and maximum temperature (Tmax) in the monthly, seasonal, and annual scale over Bangladesh using 40 General Circulation Models (GCMs) of Coupled Model Intercomparison Project Phase 5 (CMIP5) for two radiative concentration pathways (RCPs, RCP4.5 and RCP8.5). The statistical downscaling climate model (SimCLIM) was used for downscaling and to ensemble temperature projections (Tmax and Tmin) for the near (2021–2060) and far (2071–2100) periods compared to the base period (1986–2005). Multi-model ensemble (MME) exhibited increasing Tmax and Tmin for all the timescales for all future periods and RCPs. Sen’s slope (SS) analysis showed the highest increase in Tmax and Tmin in February and relatively less increase in July and August. The mean annual Tmax over Bangladesh would increase by 0.61°C and 1.75°C in the near future and 0.91°C and 3.85°C in the far future, while the mean annual Tmin would rise by 0.65°C and 1.85°C in the near future and 0.96°C and 4.07°C in the far future, for RCP4.5 and RCP8.5, respectively. The northern and northwestern parts of the country would experience the highest rise in Tmax and Tmin, which have traditionally been exposed to temperature extremes. In contrast, the southeastern coastal region would experience the least rise in temperature. A higher increase in Tmin than Tmax was detected for all timescales, signifying a future decrease in the diurnal temperature range (DTR). The highest increase in Tmax and Tmin will be in winter compared to other seasons for both the periods and RCPs. The spatial variability of Tmax and Tmin changes can be useful for the long-term planning of the country.
Understanding of crop water requirement is essential for irrigation scheduling and selection of cropping pattern in any particular area. A study was conducted to estimate irrigation requirement and made irrigation scheduling of T. Aman (wet season) and Boro (dry season irrigated) rice in the western region of Bangladesh using CROPWAT model. Historical climate data from three weather stations in the region along with soil and crop data were used as input to FAO Penman-Monteith method to estimate reference evapotranspiration (ET o ). Effective rainfall was calculated using USDA soil conservation method. The model estimated1408 mm annual ET o in the study area, of which the highest amounts of 175 mm was in April and the lowest (70 mm) in December. The average annual rainfall was 1592 mm of which 986 mm was effective for plant growth and development. The model estimated ET c of BRRI dhan49, which was 473 to 458 mm, depending on its transplanting dates from 15 July to 15 August. Rice transplanted on 15 July required no irrigation, whereas three supplemental irrigations amounting 279 mm were required for transplanting on 15 August. The CROPWAT model estimated seasonal irrigation water requirement of 1212 mm (12 spilt applications) for BRRIdhan28 transplanted on 15 January. This model has also a potentiality to make irrigation scheduling of other crops.
Appraisal of the long-term precipitation trends and variability is crucial for sustainable water resources management. This research intended to evaluate Bangladesh's monthly, seasonal, and annual spatiotemporal rainfall variability using 40 global climate models for two representative concentration pathways (RCPs), RCP4.5 and RCP8.5. Statistical downscaling climate model (SimCLIM) was used for downscaling and ensemble projection of rainfall in near (2011-2040), middle (2041-2070), and far (2071-2100) futures. Modified Mann-Kendall test was applied to detect future rainfall trends. The results revealed a significant increasing trend in rainfall in near and middle futures for RCP4.5 and in all three future periods for RCP8.5 at all meteorological stations of Bangladesh during significant rainfall months (May-October). The results also showed a decreasing trend in rainfall in dry months (December-January) at many stations. The highest increase in rainfall was projected in June at a rate of 0.10-1.11 mmÁyear −1 for RCP4.5 and 3.34-4.98 mmÁyear −1 for RCP8.5 in different future periods. Monsoon rainfall showed the highest increase, and winter rainfall the lowest increase for all RCPs and future periods. The increase in annual precipitation over Bangladesh was projected 2.76-5.98% in three future periods for RCP4.5 and 6.98-26.
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