韩慧杰, 夏学齐, 吴海东, 汤明, 姜明亮. 基于GIS和土地质量地球化学数据的水稻种植适宜性评价——以安徽省青阳县为例[J]. 中国生态农业学报(中英文), 2019, 27(4): 591-600. DOI: 10.13930/j.cnki.cjea.180699
引用本文: 韩慧杰, 夏学齐, 吴海东, 汤明, 姜明亮. 基于GIS和土地质量地球化学数据的水稻种植适宜性评价——以安徽省青阳县为例[J]. 中国生态农业学报(中英文), 2019, 27(4): 591-600. DOI: 10.13930/j.cnki.cjea.180699
HAN Huijie, XIA Xueqi, WU Haidong, TANG Ming, JIANG Mingliang. Evaluation of rice planting suitability using GIS and geochemical land quality data-A case study of Qingyang County, Anhui Province[J]. Chinese Journal of Eco-Agriculture, 2019, 27(4): 591-600. DOI: 10.13930/j.cnki.cjea.180699
Citation: HAN Huijie, XIA Xueqi, WU Haidong, TANG Ming, JIANG Mingliang. Evaluation of rice planting suitability using GIS and geochemical land quality data-A case study of Qingyang County, Anhui Province[J]. Chinese Journal of Eco-Agriculture, 2019, 27(4): 591-600. DOI: 10.13930/j.cnki.cjea.180699

基于GIS和土地质量地球化学数据的水稻种植适宜性评价——以安徽省青阳县为例

Evaluation of rice planting suitability using GIS and geochemical land quality data-A case study of Qingyang County, Anhui Province

  • 摘要: 为加快安徽省青阳县的高标准基本农田建设,开展更加精准的水稻种植适宜性评价,本文根据研究区土地质量地球化学数据和当地水稻对生长环境的需求,通过层次分析法(AHP)把水稻种植适宜性评价作为目标层,把影响目标层的立地条件、理化性质、土壤质量、土地管理作为准则层,再把影响准则层中各因素的项目作为指标层,确定研究区水稻种植适宜性评价的层次模型,构建了包括土壤养分、土壤环境、土壤质地、有机质、排水和灌溉能力等在内共计12项指标的评价体系。以研究区二调图斑为评价单元,根据数字高程模型(DEM)数据获取精准的田面坡度数据,同时结合GIS空间分析技术对地球化学数据进行空间插值模拟。利用特尔菲法(Delphi)获取各指标隶属度并构建判断矩阵,使用MATLAB数学软件求出各指标的权重,计算获取水稻种植适宜性综合指数(RSI),进行适宜性评价。结果显示:“高度适宜”面积为36.89 km2,占基本农田总面积的19.80%,主要分布在研究区中部及南部地区;“适宜”和“勉强适宜”面积分别为61.95 km2和60.89 km2,分别占33.25%和32.68%,分散分布;“不适宜”面积约26.60 km2,占比14.27%,主要位于研究区中部及北部地区。利用实测水稻籽实Cd含量与该评价方法得到的水稻种植适宜性综合指数(RSI)进行分析,发现两者呈显著负相关,随着RSI的增长,水稻籽实中Cd含量逐渐降低,意味着水稻品质的提高,同时也减少了可能通过食物链对生态环境造成的危害。该结果从生态安全方面证明此评价方法的正确性和适用性。本文探讨了土地质量地球化学数据所反映的水稻生产问题,改善了以往农业种植适宜性评价工作中大量使用描述性指标和指标分级模糊不清所导致的主观性较大和评价方法不易推广等问题,不仅为作物种植适宜性评价提供了新的方法,而且为生态农业发展指明了方向。

     

    Abstract: In order to accelerate the construction of high-standard basic farmlands in Qingyang County, Anhui Province and to conduct more accurate evaluation of rice planting suitability, an Analytic Hierarchy Process (AHP) was used to evaluate the suitability of rice planting with site conditions, soil physicochemical properties, soil quality and land management as the criterion layer. We then used the driving factors as the index layer to successively devise a three-level hierarchical model for the evaluation. Thus, the evaluation system comprising 12 indicators (including soil nutrient, soil environment, soil texture, soil organic matter, drainage capability, irrigation capacity, and etc.) were constructed based on geochemical land quality data of the prime farmland in the study area and on the demand for local rice production. With the polygons of the Second Land Survey as evaluation units, the field slope was obtained from digital elevation model (DEM) data, and combined with spatial analysis technology in GIS to simulate spatial interpolation of geochemical data. The Delphi method was used to determine index membership and build judgment matrix to calculate the weight of each index in order to obtain the comprehensive rice planting suitability index (RSI). The results showed that the "highly suitable" land area was 36.89 km2, accounting for 19.80% of the total area, which was mainly distributed in the central and southern regions of the study area. The areas of "suitable" and "barely suitable" lands were respectively 61.95 km2 (33.25%) and 60.89 km2 (32.68%) and were sporadically distributed. The area of "unsuitable" land was 26.60 km2 (14.27%) and was also mainly distributed in the central and northern regions of the study area. The measured cadmium content of rice seeds and RSI were significantly negatively correlated. The cadmium content of rice grains gradually decreased with the increasing of RSI. The low heavy metal content implied improvement of rice quality and reduction in potential damage to the ecological environment through food chain. The results proved the correctness and applicability of the evaluation method from the perspective of ecological security. We explored rice production issues reflected by geochemical data of land quality. The established evaluation method of agricultural planting suitability improved the past evaluation methods, which was subjective and non-suitable for application due to many descriptive indicators and uncertain indicator grading.

     

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