| 王 姣.低山丘陵区 稻产量的地形影响因素研究要要要以重庆市綦江区为例[J].广东农业科学,2015,42(2):6-10 |
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低山丘陵区 稻产量的地形影响因素研究要要要以重庆市綦江区为例 |
| Influence of terrain factors on rice yield in hilly area Taking Qijiang county of Chongqing as a case |
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| DOI： |
| 中文关键词: 低山丘陵 水稻 产量 地形因素 綦江区 |
| 英文关键词: Key words low hills rice yield terrain factors Qijiang county |
| 基金项目: |
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| 摘要点击次数: 2104 |
| 全文下载次数: 860 |
| 中文摘要: |
| 在 GIS、Sim-DTA 以及 SPSS 的技术支持下，以重庆市綦江区数字高程模型以及水稻产量数据为基础数据，提取坡位、高程、坡度以及地形湿度指数 4 种地形因子，并分别与水稻产量数据进行叠加，分析地形因子与水稻产量的关系。结果表明：中坡区域对水稻总产量的贡献率最大，是目前研究区内水稻种植的优选区域，所占比例达到 57.49%；在高程250~500m 范围内，水稻种植效果最佳，水稻产量集中分布在 6 000~10 000kg/hm2范围内；在坡度 10毅~15毅范围内水稻产量分布最为集中，主要为 6 000~9 000 kg/hm2；在地形湿度指数5.75~6.50 范围内，水稻产量集中分布在 6 000~9 000 kg/hm2；高程与水稻产量呈极显著负相关，相关系数为-0.317，坡度与水稻产量呈显著负相关，相关系数为-0.121，而地形湿度指数与水稻产量呈显著正相关，相关系数为 0.145。 |
| 英文摘要: |
| Based on the technical support of GIS, Sim-DTA and SPSS, this paper took Qijiang, Chongqing asthe research area, the digital elevation model and rice yield of Qijiang as the primary data, extracted the terrainslope position, elevation, slope and topographic wetness index, made superposition with rice yield data and analyzedthe relationships between topographic factors and rice yield. The results showed that the middle slope was the optimal rice planting area, had the largest contribution rate for rice production with the proportion of 57.49%; Within the scope of 250-500 m for elevation, rice planting effect was the best, rice production intensively distributed in 6000-1 0000 kg/hm2. Within the scope of 10-15for slope, rice yield had the most concentrated distribution, and the output values were mainly distributed in 6 000-9 000 kg/hm2. Within the scope of 5.75-6.50 for topographic wetness index, rice production intensively distributed in 6 000-9 000 kg/hm2. Elevation related to the rice yield significantly and negatively at the 0.01 level with the correlation coefficient of -0.317, slope and the rice yield had significantly negative correlation at the 0.05 level with the correlation coefficient of -0.121, topographic wetness index and rice yield were significantly related at the 0.05 level with the correlation coefficient of 0.145. |
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