A Geostatistical Approach to the Seasonal Precipitation Effect on Boro Rice Production in Bangladesh

Abstract

Geographical assessments on the relationship between climate variability and crop production are important for planning adaptation programs to climate change impacts on Asian rice production. This paper analyses the seasonal precipitation consequences to irrigated crop yields, in opposition to the idea that irrigated crop yields are not affected by precipitation changes. Geostatistical methods are applied to assess changes in the patterns of seasonal precipitation and corresponding changes in the Boro crop production in Bangladesh. Surfaces depicting changes in the monsoon, non-monsoon and total precipitation from 2006 to 2007, and changes in three varieties of Boro crop yield and Total Boro yield from 2006-2007 to 2007-2008 crop years are generated through Splines, Inverse Distance Weighting and Ordinary Kriging methods. Performance evaluation of these models is also performed. The relationships between the surfaces of different precipitation seasons and the surfaces of different Boro yield seasons are then assessed. The results show that there is a significant correlation between seasonal precipitation changes and Boro yield changes with notable correlation coefficients and similarity in the patterns. A significant conformity of the high precipitation zones to the high Boro yielding zones is also depicted.

Agricultural Productivity, Hired Labor, Wages, and Poverty: Evidence from Bangladesh

“…al. (2012), Bhowmik and Costa (2012) and the references cited there in), which is also con…rmed in our data. The evidence from the reduced form regressions show that a higher rainfall shock increases agricultural wages sig-ni…cantly, but reduces the amount of agricultural hired labor.…”

“…al. (2012), Bhowmik and Costa (2012)). We also provide an instrumental variables interpretation of our estimates, using rainfall variations across upazila and over time (relative to mean) as an instrument for crop yield (rice yield).…”

Representativeness impacts on accuracy and precision of climate spatial interpolation in data-scarce regions

“…The influence of the number of data on the accuracy and precision of spatial interpolation has been discussed as of utmost importance (Sluiter, ; Li and Heap, ) and several studies have highlighted the consequences of scarce data (e.g. Goovaerts, ; Bhowmik and Cabral, ; Bhowmik, , ; Bhowmik and Costa, ). By contrast, the present study shows that the representativeness of the data, i.e.…”

“…Thus, in regions with abundant data, satisfactory accuracy and precision might be obtained without taking their representativeness into account (Dirks et al, 1998;Kyriakidis et al, 2001;Kastelec and Košmelj, 2002;Diodato, 2005;Hijmans et al, 2005;Haberlandt, 2007). However, in data-scarce regions, where the accuracy and precision of spatial interpolation have been questioned due to few data (Goovaerts, 2000;Carrera-Hernández and Gaskin, 2007;Bhowmik and Costa, 2012), the representativeness of the climate data should be treated as highly important. Particularly in the spatial interpolation of precipitation, which is a highly variable spatial phenomenon, satisfactory representativeness should be ensured in order to obtain satisfactory accuracy and precision (Tabios and Salas, 1985;Phillips et al, 1992;Hewitson and Crane, 2005).…”

Temporal Patterns of the Two-Dimensional Spatial Trends in Summer Temperature and Monsoon Precipitation of Bangladesh

“…In light of the results from this study, many regions of the country will lose their particular crop productivities. Bhowmik and Costa [45] have already discovered the decrease in the nonrain-fed irrigated crop production with the decrease in precipitation in Bangladesh. Further threats are most likely to take place in the near future, which must be taken into account in the climate resilience activities in the country.…”