Replication package for "Regional trade and sustainable intensification advance rice self-sufficiency in East Africa"

Optimization model for sustainable intensification of agriculture under regional trade This replication package contains the code and data required to reproduce the analysis presented in the article "Regional trade and sustainable intensification advance rice self-sufficiency in East Africa". The model maxmizes farmers' benefits subject to resource constraints. Scripted routines and optimization model The main model is written in GAMS. R scripts are used for pre- and post-processing data. Current versions of GAMS and R are required for replication. Run the contained scripts in the following sequence: Use MAIN_data_processing.R to pre-process input data, then convert it to GAMS data format by running input_xlsx_to_gdx.gms Run the baseline optimization in BASE_rice_model.gms with fixed scenario to determine water use in this fixed setting. Use water_constraint.R to scale the water use from baseline and use it in the actual opitmization model. Run the main optimization model in rice_model.gms. Due to the significant amount of scenarios this can take some time. Use gdx_to_csv.gms to convert data from GAMS to CSV fomrat to make it readable with other programmes, including R. Use reproduce_figures_numbers.R to analyze optimization model outputs and reproduce numbers, percentages and figures included in the article. This package provides the following datasets: Input datasets Custom Global Agro-Ecological Zones version extended for double-cropping and high spatial resolution of rice in GAEZ_rice_data.zip Productions costs assesmbled from literature and processed for use in this modeling framework in production_costs.csv subbasin_to_marketshed.csv and subbasin_to_country.csv provide mapping of spatial units for use in the GAMS model. These datasets need to be downloaded to fully reproduce the analysis: Supplementary data from Traberend et al. (2021) at: https://doi.org/10.1016/j.oneear.2021.02.012 Producer Prices from FAOSTAT Rice areas from SPAM: https://doi.org/10.7910/DVN/FSSKBW The economic model in GAMS can be run without the full data integration by using the processed data file provided in: model_inputs_cleaned.xlsx A sensitivity check using a variation of income elasticities to compute demand can be run by instead using the processed input data in model_inputs_POS_INC.xlsx Output data Output data of the economic optimization is provided in the csv files in results_csv.zip. This archive contains the main results used in the article and the outputs for model runs for the sensitivity checks using alternative income elasticities reported in the Supplementary.区域贸易框架下农业可持续集约化优化模型 本复现套件包含复现论文《区域贸易与可持续集约化提升东非水稻自给率》中所述分析所需的代码与数据集。 本模型以农户收益最大化为目标，同时受资源约束条件限制。 ## 脚本例程与优化模型 主模型采用GAMS编写，R脚本用于数据的预处理与后处理。复现分析需使用当前最新版本的GAMS与R，请按以下顺序运行内置脚本： 1. 运行`MAIN_data_processing.R`完成输入数据的预处理，随后执行`input_xlsx_to_gdx.gms`将数据转换为GAMS数据格式。 2. 执行`BASE_rice_model.gms`中的固定情景基准优化，确定该固定设定下的水资源使用量。 3. 运行`water_constraint.R`对基准情景的水资源使用量进行缩放，并将其应用于实际优化模型。 4. 执行`rice_model.gms`中的主优化模型。由于需运行大量情景，该步骤可能耗时较长。 5. 运行`gdx_to_csv.gms`将GAMS输出的数据转换为CSV格式，以便包括R在内的其他程序读取。 6. 运行`reproduce_figures_numbers.R`分析优化模型的输出结果，复现论文中的数值、占比与图表。 ## 本套件提供的数据集 ### 输入数据集 1. `GAEZ_rice_data.zip`：适配双季稻种植的定制化高空间分辨率全球农业生态区划（Global Agro-Ecological Zones, GAEZ）水稻版本数据集。 2. `production_costs.csv`：从公开文献汇编并经本建模框架处理后的生产成本数据集。 3. `subbasin_to_marketshed.csv`与`subbasin_to_country.csv`：为GAMS模型提供空间单元映射关系的数据集。 ## 需额外下载的数据集 以下数据集需额外下载，方可完整复现分析： 1. Traberend等人（2021）的补充数据：https://doi.org/10.1016/j.oneear.2021.02.012 2. FAOSTAT发布的生产者价格数据 3. SPAM提供的水稻种植面积数据：https://doi.org/10.7910/DVN/FSSKBW ## 可选运行方式 若无需完整数据集成，可通过使用`model_inputs_cleaned.xlsx`中提供的已处理数据文件运行GAMS中的经济模型。若需采用收入弹性变体计算需求以开展敏感性分析，则可改用`model_inputs_POS_INC.xlsx`中的已处理输入数据。 ## 输出数据 经济优化模型的输出数据存储于`results_csv.zip`压缩包内的CSV文件中。该归档包含论文中使用的核心结果，以及补充材料中报告的、采用替代收入弹性开展敏感性检查的模型运行输出。