基于TOPSIS和耦合协调度的高标准农田改造提升项目遴选

    Project optimization for high-standard farmland upgrading using TOPSIS and coupling coordination degree

    • 摘要: 科学确定高标准农田改造提升的重点区域是切实发挥高标准农田建设成效、提升粮食生产能力的关键。该研究以山东省乐陵市为研究区,运用层次分析法和优劣解距离法(technique for order preference by similarity to ideal solution, TOPSIS)构建考虑农田基础设施、耕地地力质量和水资源利用状况的高标准农田改造提升迫切性评价体系,并基于维度间的耦合协调度及其空间特征划定改造提升项目区。结果表明:1)乐陵市已建高标准农田占耕地面积的87.93%,西南和东部地区建设基础较好,南部和中部薄弱;高等地力农田面积较少,分布于中南地区和东北地区;水资源利用状况总体呈现“中部高、北部和南部低”的特征。2)农田基础设施、耕地地力质量和水资源利用状况3个维度间的耦合协调度指数为0.41~0.85,高值聚集分布于西南部、东部和东北部,低值聚集分布于南部和西北部,中值交叉分布于中西部和中南部地区。3)基于耦合协调度指数及其空间特征遴选出12个高标准农田改造提升项目区,根据指数分级结果从低到高确立为近期(8633.23 hm2)、中期(11004.64 hm2)、远期(9102.62 hm2)建设项目。结合各项目区立地条件和高障碍度、高频率障碍因子,建议围绕资金整合、水源保障、设施配套、地力提升、结构改良等方面分类推进。该方法对于高标准农田改造提升区域选择以及重点建设方向确定具有一定借鉴价值。

       

      Abstract: 67 million hectares of high-standard farmland has been constructed in China by the end of 2022. The production quality and capacity of these farmland need to be upgraded after long-time utilization, low investment, and disaster damage. The next construction is required for the food security. However, there is seldom report so far. This study aims to optimize the projects and then upgrade the high-standard farmland using TOPSIS and coupling coordination degree. Taking the Laoling City, Shandong Province as the research area, 87.93% of field was built into the high-standard farmland from 2013 to 2022. The evaluation index system was constructed from three aspects: construction foundation, fertility quality and water resource utilization. 14 indicators were contained, such as farmland area, building time, cost input, road accessibility, field breakage degree, soil organic matter, soil P, soil K, salinity degree, soil texture, water quantity, pond density, ditch density and water system connectivity. Furthermore, 57 688.44 hm2 high-standard farmland from 950 administrative villages were taken as the evaluation unit to realize the implicative construction. The AHP (analytic hierachy process) and TOPSIS (technique for order preference by similarity to ideal solution) analysis were chosen to evaluate the current situation as functional effectiveness of facilities, potential to arable land productivity and sustainable utilization of water resources. The production capacity of farmland was also evaluated to determine the coupling coordination degree for the cooperativity among three aspects. The upgrading project areas were delimited using the cooperativity index and spatial patterns. The results show that: 1) The construction foundation was relatively superior in the southwest and eastern regions, while the weak performance distributed mainly in the south and central regions. High fertility areas were accounted for a small proportion of 14.46% in the central, southern and northeast regions. Water resources presented a trend of high in the central region and low in the northern and southern regions. 2) The coupling coordination index of the three dimensions were ranged from 0.41 to 0.85. The high values were clustered in the southwest, east and northeast, whereas, the low values were in the south and northwest, and the median cross-distributed in the central and southern regions. 3) According to the coupling coordination degree index, the information and pertinency target, the evaluation units were broadly classified as near-term, mid-term and long-term construction sequences, where the areas of each period were 8 633.23, 11 004.64 and 9 102.62 hm2, respectively. According to spatial pattern, three sequences were divided into 12 upgrading projects with the average stage of 4 projects. Different obstruction factors were optimized to improve the quality and efficiency of each project, in term of water source security, facilities, fund integration, land capacity and structural improvement. The construction quality and operation period of high-standard farmland were considered to balance the land use with productivity degradation. The optimal configuration was achieved under the constraint of water resources, following the principle of coordination and adaptation to local conditions. Thus the finding can also provide a strong reference to select the priority areas for the high-standard farmland.

       

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