Dataset and code for "Quantifying Variety-Specific Heat Resilience in Boro Rice: A Machine Learning Feature Attribution Approach for Climate Risk Management"
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Contents: Rice_dataset.xlsx contains three sheets (Hybrid_Boro, HYV_Boro, Local_Boro), each with 704 rows representing all 64 Bangladesh administrative districts across 11 Boro rice growing seasons (2014–2015 through 2024–2025). Each row records district identity, season, cultivated-area flag, yield (t/ha), and 12 seasonal climate covariates. After applying the Is_Cultivated filter and removing 7 biologically implausible outliers (yield < 0.5 or > 10.0 t/ha), the final modelling dataset contains 1,797 district-variety-year observations. Boro_Rice.py is the complete Python analysis pipeline (Python 3.12, scikit-learn 1.6, SHAP 0.51) that reproduces all figures, tables, and supplementary outputs from the raw dataset. Data Sources: Yield data: Bangladesh Bureau of Statistics (BBS) Yearbooks of Agricultural Statistics, 2014–2025 (publicly available at bbs.portal.gov.bd) Climate covariates: NASA POWER gridded reanalysis aggregated to district centroids (power.larc.nasa.gov), variables include T2M, T2M_MAX, T2M_MIN, T2M_RANGE, GWETROOT, GWETTOP, PRECTOTCORR_SUM, RH2M, ALLSKY_SFC_SW_DWN, ALLSKY_SFC_PAR_TOT, WS2M, WS2M_RANGE Key Variables (final model features): Column Description Units T2M_MAX Seasonal mean daily maximum temperature °C T2M_RANGE Seasonal mean diurnal temperature range °C GWETROOT Root-zone soil wetness fraction dimensionless (0–1) PRECTOTCORR_SUM Cumulative seasonal precipitation mm ALLSKY_SFC_SW_DWN Downward shortwave radiation flux kW·h/m²/day Yield_t_ha District-level Boro rice yield t/ha
Contents: Rice_dataset.xlsx 包含三个工作表（Hybrid_Boro、HYV_Boro、Local_Boro），每个工作表含704行数据，对应孟加拉国全部64个行政区在11个Boro水稻种植季（2014-2015至2024-2025）的观测记录。每行数据记录行政区标识、种植季、种植面积标识、产量（单位：吨/公顷）以及12个季候气候协变量。经Is_Cultivated过滤，并剔除7条不符合生物学合理性的异常值（产量低于0.5吨/公顷或高于10.0吨/公顷）后，最终建模数据集共包含1797条行政区-品种-季候观测样本。 Boro_Rice.py 为完整的Python分析流程（基于Python 3.12、scikit-learn 1.6与SHAP 0.51开发），可基于原始数据集复现全部图表、表格及辅助输出结果。 Data Sources: 产量数据：源自孟加拉国统计局（Bangladesh Bureau of Statistics, BBS）2014-2025年《农业统计年鉴》，公开获取渠道为bbs.portal.gov.bd。 气候协变量：来自NASA POWER网格化再分析数据，经聚合至行政区质心（数据可于power.larc.nasa.gov获取），涵盖变量包括T2M、T2M_MAX、T2M_MIN、T2M_RANGE、GWETROOT、GWETTOP、PRECTOTCORR_SUM、RH2M、ALLSKY_SFC_SW_DWN、ALLSKY_SFC_PAR_TOT、WS2M、WS2M_RANGE。 核心变量（最终模型特征）： | 变量名 | 描述 | 单位 | | ---- | ---- | ---- | | T2M_MAX | 季均每日最高气温 | °C | | T2M_RANGE | 季均昼夜温差 | °C | | GWETROOT | 根区土壤湿度占比 | 无量纲（0~1） | | PRECTOTCORR_SUM | 季累积降水量 | mm | | ALLSKY_SFC_SW_DWN | 向下短波辐射通量 | kW·h/m²/天 | | Yield_t_ha | 行政区级Boro水稻产量 | t/ha |
