Climate change and agricultural food production of Bangladesh: an impact assessment using gis-based biophysical crop simulation model.

Introduction To Spatial-Epic
Traditional decision support systems based on crop simulation models are normally site-specific. In order to address the effects of spatial variability of soil conditions and weather variables on crop production from one place/region to other, GIS is linked with biophysical agricultural management simulation model EPIC, which is known as "Spatial-EPIC". Wit the development of this model any size of agroecosystem starting from a field to a country and even bigger ca be modeled. "Spatial-EPIC" system file structure is comprised of text files, which contain estimate of parameters of different physical processes modeled by "Spatial-EPIC". These files include Basic User-Supplied Data file, Crop Parameter File, Tillage Parameter File, Pesticide Parameter File, Fertilizer Parameter File, Miscellaneous Parameter File, Multi-Run File, Output Variables File and Daily Weather Data File. ArcView 3.1 is used as a pre and post processor for data furnishing as well as graphical display of Spatial-EPIC. "Spatial-EPIC" is composed of physically based sub models for simulating weather, hydrology, erosion, plant nutrients, plant growth, soil tillage and management, and plant environment control. The model runs on daily time-step therefore, each model is linked subsequently and interactively with other sub models. In brief, the each sub module is dealt with their computation procedure. Weather: daily rain, maximum and minimum temperature, solar radiation, wind and relative humidity can be based on measured and data and/or generated stochastically. Hydrology: runoff, percolation, lateral subsurface flow are simulated. Erosion: it simulates soil erosion by wind and water (for this paper the erosion part has not been included). Nutrient Cycling: the model simulates, nitrogen and phosphorus fertilization, transformations, crop uptake and nutrient movement. Nutrient can be applied as mineral fertilizers, in irrigation water, or as animal manure. Soil: soil temperature responds to weather, soil water content and bulk density. It is computed daily in each soil layer. Tillage: the equipment used affects soil hydrology and nutrient cycling. The user can change the characteristics of simulated tillage equipment, if needed. Crop Growth: A single crop model capable of simulating major agronomic crops. Crop-specific parameters are available for most crops. The model also simulates crop grown in complete rotations. Plant Environment: It is capable of variety of cropping variables, management practices, and other naturally occurring processes. These include different crop characteristics, plant population, and dates of planting and harvesting, fertilization, irrigation, tillage and many more those are normally practiced in the field.

Climate Change Scenarios
A climate change scenario is defined as a physically consistent set of changes in meteorological variables, based on generally accepted projections of concentrations of carbon dioxide (CO2 thought to be the likely cause of future climate change). Scenarios of climate change were developed in order to estimate their effects on crop yields which may be severe in coming days as per the speculations going on throughout the world. The set of scenarios used is intended to capture a range of possible effects and set limits on the associated uncertainty. The scenarios for this study were created by changing observed daily data from the current daily-observed historical climate data (1975-1995). The scenarios are the combination of a range of temperature (-2°C, 0°C and +2°C) and precipitation (+/-25%). For simplicity, solar radiation, vapor pressure and wind speed were assumed to remain unchanged for all scenarios although some changes associated with temperature and precipitation changes is to be expected. Simulations for each cropping system were made for 6 climate scenarios and two atmospheric concentrations of 350 and 550ppm.

Conclusion
The attempt of this paper is to simulate the country level Bangladeshi agroecosystem with the help of Spatial-EPIC. Modeling within a GIS offers a mechanism to integrate the many scales of data developed in and for agricultural research. Data access, including modeling results, expands to a "decision system" or decision tool which uses a mix of process models (where appropriate/possible) and biophysical data (growing season climate characteristics, soils, terrain). An accurate spatial (and temporal) database enables the characterization of agroecosystem. This ability is vital in the developing world for efficient resource allocation in agricultural research. Agroecosystem are complex entities, which span several levels or scales, with different processes dominating each scale. Geographic data are either as a vector model or raster model. In general both the data structure can be used to represent any type of geographical data, depending on the scale desired for analysis. However, raster model fit best for modeling type of analysis involving natural resources data such as land use, soils and vegetation as their is spatial control for continuous variable and also uniform sampling of the surface being modeled. When the different thematic layers exist as grids with a common resolution, there is computation efficiency in overlaying those grids. Spatial analytical functionality is easy to implement and fast and efficient especially for operation such as spatial averaging and intersections which pose problems in vector systems.

The soil characteristics of Bangladesh were obtained after digitization of survey of Bangladesh soil map with many properties like soil texture, soil pH and soil depth. Weather data were obtained and their surfaces were generated using World Meteorological Organization station falling around 22 in number scattered throughout Bangladesh. Agricultural management data were obtained at district level. All these data were used for whole country simulation at 10 km cell size. The simulation and validation result is not complete yet. These would likely to be presented at the conference.

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