Effects of climate change on boro cultivation in Bangladesh

Abstract

In this study, trends of changes in temperature and precipitation patterns in dry season (December-May) in Bangladesh has been assessed through analysis of data on temperature and precipitation for the period 1976-2005 for 34 meteorological stations all over the country. The climate trends were assessed in terms of changes in maximum and minimum temperatures and changes in precipitation patterns. Analysis of monthly average maximum and minimum temperature show increasing trend for all months of the year except January; the increasing trend was particularly significant for the months of February, April and May. On an average, monthly-average maximum temperatures of each of these months increased by about 1 °C during the 30 year period from 1976-2005 and in monthly average minimum temperature increased by about 0.80 °C during the same period (i.e., 1976 to 2005). The magnitude of increase in monthly average maximum and minimum temperatures during the 30-year period from 1976 to 2005 is quite significant. Eighteen stations (out of32) show increasing trend in number of "hot" days per year, while 13 stations (out of 31) show decreasing trend in the number of "cold" days per year; however, most of these trends are not statistically significant. Analysis of precipitation data during 1976-2005 show that for a large majority of stations, the total rainfall show decreasing trend for the winter (December to February), and premonsoon (March to May) rainfall did not show any significant change. In general, these trends are consistent with the general climate change predictions. These observations are particularly significant in the context of Bangladesh where agriculture is heavily dependent on temperature and rainfall patterns. An agro-climatic study was conducted to assess the vulnerability of boro production in Bangladesh to potential climate change. Effect of climate change on yield of two varieties ofboro rice has been assessed using the DSSAT (v4) modeling system. The yield ofBR3 and BRI4 boro varieties for the years 2008, 2030, 2050 and 2070 have been simulated for 12 locations (districts) of Bangladesh, which were selected from among the major rice growing areas in different regions of Bangladesh. The DSSAT model uses a detailed set of crop specific genetic coefficients for predicting yield and the BR3 and BRI4 were selected in the present study because "genetic coefficients" for these varieties are available in the DSSA T modeling system. Available data on soil and hydrologic characteristics of these locations, and typical crop management practice for boro rice were used in the simulations. The weather data required for the model (daily maximum and minimum temperatures, daily solar radiation and daily precipitation) were generated for the selected years and for the selected locations using the regional climate model PRECIS. The model predicted significant reduction in yield of both varieties of boro rice due to climate change; yield reductions of over 20% and 50% have been predicted for both rice varieties for the years 2050 and 2070, respectively. However, BR 14 appears to be slightly more vulnerable to climate change pheromones compared to BR3. Increases in daily maximum and minimum temperatures have been found to be primarily responsible for reduction in yield. Increases in incoming solar radiation and atmospheric carbon-dioxide concentration increases rice yield to some extent, but their effect is not significant compared to the negative effects of temperature. Variations in rainfall pattern over the growing period have also been found to affect rice yield and water requirement. Increasing temperatures and solar radiation have been found to reduce the duration of physiological maturity of the rice varieties. Model results also suggest that in addition to reducing yield, climate change may also make rice yield more vulnerable to transplanting date, predicting significant reduction in yield as transplanting date is delayed, especially beyond 15 January. DSSAT modeling system could be a useful tool for assessing possible impacts of climate change and management practices on different varieties rice and other crops.