Can Bangladesh produce enough cereals to meet future demand?

Bangladesh faces huge challenges in achieving food security due to its high population, diet changes, and limited room for expanding cropland and cropping intensity. The objective of this study is to assess the degree to which Bangladesh can be self-sufficient in terms of domestic maize, rice and wheat production by the years 2030 and 2050 by closing the existing gap (Yg) between yield potential (Yp) and actual farm yield (Ya), accounting for possible changes in cropland area. Yield potential and yield gaps were calculated for the three crops using well-validated crop models and site-specific weather,management and soil data, and upscaled to the whole country.We assessed potential grain production in the years 2030 and 2050 for six land use change scenarios (general decrease in arable land; declining ground water tables in the north; cropping of fallow areas in the south; effect of sea level rise; increased cropping intensity; and larger share of cash crops) and three levels of Yg closure (1: no yield increase; 2: Yg closure at a level equivalent to 50% (50% Yg closure); 3: Yg closure to a level of 85% of Yp (irrigated crops) and 80% of water-limited yield potential or Yw (rainfed crops) (full Yg closure)). In addition, changes in demand with low and high population growth rates, and substitution of rice by maize in future diets were also examined. Total aggregated demand of the three cereals (in milled rice equivalents) in 2030 and 2050, based on the UN median population variant, is projected to be 21 and 24% higher than in 2010. Current Yg represent 50% (irrigated rice), 48–63% (rainfed rice), 49% (irrigated wheat), 40% (rainfed wheat), 46% (irrigated maize), and 44% (rainfed maize) of their Yp or Yw.With 50% Yg closure and for various land use changes, self-sufficiency ratio will be N1 for rice in 2030 and about one in 2050 but well below one for maize and wheat in both 2030 and 2050. With full Yg closure, self-sufficiency ratios will be well above one for rice and all three cereals jointly but below one for maize and wheat for all scenarios, except for the scenario with drastic decrease in boro rice area to allow for area expansion for cash crops. Full Yg closure of all cereals is needed to compensate for area decreases and demand increases, and then even some maize and large amounts of wheat imports will be required to satisfy demand in future. The results of this analysis have important implications for Bangladesh and other countries with high population growth rate, shrinking arable land due to rapid urbanization, and highly vulnerable to climate change

Rooting for food security in Sub-Saharan Africa

There is a persistent narrative about the potential of Sub-Saharan Africa (SSA) to be a 'grain breadbasket' because of large gaps between current low yields and yield potential with good management, and vast land resources with adequate rainfall. However, rigorous evaluation of the extent to which soils can support high, stable yields has been limited by lack of data on rootable soil depth of sufficient quality and spatial resolution. Here we use location-specific climate data, a robust spatial upscaling approach, and crop simulation to assess sensitivity of rainfed maize yields to root-zone water holding capacity. We find that SSA could produce a modest maize surplus but only if rootable soil depths are comparable to that of other major breadbaskets, such as the US Corn Belt and South American Pampas, which is unlikely based on currently available information. Otherwise, producing surplus grain for export will depend on expansion of crop area with the challenge of directing this expansion to regions where soil depth and rainfall are supportive of high and consistent yields, and where negative impacts on biodiversity are minimal

Offshore monopile in the southern North Sea: Part I, calibrated input sea state

Safe, reliable access is an essential precondition for the successful maintenance of offshore wind farms. Access from vessels to wind turbines depends on the severity of the sea state in the vicinity of the turbine support structure. This paper presents a validation of a numerical boundary condition developed to reproduce the seasonal sea state at Teesside Offshore Wind Farm, off the coast of the UK. The boundary condition, called customSpectrum, was derived from wave energy spectra obtained by analysis of existing field measurements of wave free-surface displacement at the wind farm site and implemented in OpenFoam, the open-source computational fluid dynamics library. OpenFoam was then used to simulate typical spring, summer, autumn and winter sea states as uni-directional waves. Predicted surface elevations and significant wave heights were found to be in agreement with in situ buoy data, thus validating the OpenFoam model. Satisfactory agreement was achieved between analytical and numerically predicted spectral density functions for the horizontal and vertical water particle velocity components. It was found that the wave activity at Teesside is uni-modal in spring and autumn, and bi-modal in summer and winter. Extending the procedure to multi-directional waves in crossing seas is recommended

Use of agro-climatic zones to upscale simulated crop yield potential

Yield gap analysis, which evaluates magnitude and variability of difference between crop yield potential (Yp) or water limited yield potential (Yw) and actual farm yields, provides a measure of untapped food production capacity. Reliable location-specific estimates of yield gaps, either derived from research plots or simulation models, are available only for a limited number of locations and crops due to cost and time required for field studies or for obtaining data on long-term weather, crop rotations and management practices, and soil properties. Given these constraints, we compare global agro-climatic zonation schemes for suitability to up-scale location-specific estimates of Yp and Yw, which are the basis for estimating yield gaps at regional, national, and global scales. Six global climate zonation schemes were evaluated for climatic homogeneity within delineated climate zones (CZs) and coverage of crop area. An efficient CZ scheme should strike an effective balance between zone size and number of zones required to cover a large portion of harvested area of major food crops. Climate heterogeneity was very large in CZ schemes with less than 100 zones. Of the other four schemes, the Global Yield Gap Atlas Extrapolation Domain (GYGA-ED) approach, based on a matrix of three categorical variables (growing degree days, aridity index, temperature seasonality) to delineate CZs for harvested area of all major food crops, achieved reasonable balance between number of CZs to cover 80% of global crop area and climate homogeneity within zones. While CZ schemes derived from two climate-related categorical variables require a similar number of zones to cover 80% of crop area, within-zone heterogeneity is substantially greater than for the GYGA-ED for most weather variables that are sensitive drivers of crop production. Some CZ schemes are crop-specific, which limits utility for up-scaling location-specific evaluation of yield gaps in regions with crop rotations rather than single crop species

Mapping rootable depth and root zone plant-available water holding capacity of the soil of sub-Saharan Africa

In rainfed crop production, root zone plant-available water holding capacity (RZ-PAWHC) of the soil has a large influence on crop growth and the yield response to management inputs such as improved seeds and fertilisers. However, data are lacking for this parameter in sub-Saharan Africa (SSA). This study produced the first spatially explicit, coherent and complete maps of the rootable depth and RZ-PAWHC of soil in SSA. We compiled geo-referenced data from 28,000 soil profiles from SSA, which were used as input for digital soil mapping (DSM) techniques to produce soil property maps of SSA. Based on these soil properties, we developed and parameterised (pedotransfer) functions, rules and criteria to evaluate soil water retention at field capacity and wilting point, the soil fine earth fraction from coarse fragments content and, for maize, the soil rootability (relative to threshold values) and rootable depth. Maps of these secondary soil properties were derived using the primary soil property maps as input for the evaluation rules and the results were aggregated over the rootable depth to obtain a map of RZ-PAWHC, with a spatial resolution of 1 km2. The mean RZ-PAWHC for SSA is 74 mm and the associated average root zone depth is 96 cm. Pearson correlation between the two is 0.95. RZ-PAWHC proves most limited by the rootable depth but is also highly sensitive to the definition of field capacity. The total soil volume of SSA potentially rootable by maize is reduced by one third (over 10,500 km3) due to soil conditions restricting root zone depth. Of these, 4800 km3 are due to limited depth of aeration, which is the factor most severely limiting in terms of extent (km2), and 2500 km3 due to sodicity which is most severely limiting in terms of degree (depth in cm). Depth of soil to bedrock reduces the rootable soil volume by 2500 km3, aluminium toxicity by 600 km3, porosity by 120 km3 and alkalinity by 20 km3. The accuracy of the map of rootable depth and thus of RZ-PAWHC could not be validated quantitatively due to absent data on rootability and rootable depth but is limited by the accuracy of the primary soil property maps. The methodological framework is robust and has been operationalised such that the maps can easily be updated as additional data become available

Counting Complex Disordered States by Efficient Pattern Matching: Chromatic Polynomials and Potts Partition Functions

Counting problems, determining the number of possible states of a large system under certain constraints, play an important role in many areas of science. They naturally arise for complex disordered systems in physics and chemistry, in mathematical graph theory, and in computer science. Counting problems, however, are among the hardest problems to access computationally. Here, we suggest a novel method to access a benchmark counting problem, finding chromatic polynomials of graphs. We develop a vertex-oriented symbolic pattern matching algorithm that exploits the equivalence between the chromatic polynomial and the zero-temperature partition function of the Potts antiferromagnet on the same graph. Implementing this bottom-up algorithm using appropriate computer algebra, the new method outperforms standard top-down methods by several orders of magnitude, already for moderately sized graphs. As a first application, we compute chromatic polynomials of samples of the simple cubic lattice, for the first time computationally accessing three-dimensional lattices of physical relevance. The method offers straightforward generalizations to several other counting problems.Comment: 7 pages, 4 figure