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1980—2023年天山北坡经济带耕地与水库空间关系演变及影响因素

Evolution and influencing factors of spatial relationship between cropland and reservoirs in the Economic Belt on the North Slope of Tianshan Mountains from 1980 to 2023

  • 摘要: 厘清天山北坡经济带水土资源空间关系演变及影响因素,对干旱区粮食安全和农业高质量发展具有重大意义。该研究采用核密度分析、重心模型和空间错位指数等方法探索1980—2023年天山北坡经济带耕地与水库之间的空间关系与演变特征,利用区位熵和地理探测器模型揭示其空间失衡的主导因素。结果表明:1)1980—2023年研究区耕地面积和水库库容均呈扩大趋势,两者高密度区在空间上存在一致性,但水库高值区范围显著小于耕地;2)1980—2023年研究区耕地面积与水库库容之间始终存在空间错位,但整体错位有所变小;3)耕地与水库的地理分布存在不同的空间偏好,但均呈趋向于近河流、坡度小和低城镇化率的空间偏好;4)耕地与水库的空间分布受复杂因素共同影响,其中农业机械总动力、第一产业产值和距河流距离等因子主导耕地空间分布,距河流距离、海拔和地形等因子主导水库空间分布。该研究揭示了天山北坡耕地与水库的空间关系演变,深化了水土资源空间匹配及其机制,可为干旱区“以水定地”战略实施与水土资源优化调控提供科学支撑。

     

    Abstract: This study aims to clarify the spatial evolution and influencing factors of the cropland and reservoirs in the Economic Belt on the North Slope of Tianshan Mountains (EBTM), particularly for food security and high-quality agriculture in arid areas. The kernel density analysis, center of gravity model, and spatial dislocation index were used to explore the spatial relationship and evolution between cropland and reservoirs in EBTM from 1980 to 2023. The location entropy and geographic detector were used to reveal the dominant factors of spatial imbalance. The results show that: 1) The area of cultivated land in EBTM shared an expansion trend from 1980 to 2023, increasing from 2.25 to 3.37 million hectares, an increase of 50.1%. At the same time, the number of reservoirs in EBTM continued to increase, from 112 to 269, an increase of 140.2%. The reservoir capacity in EBTM shares an increasing trend, growing from 4.0×109 m3 to 1.0×1010 m3, with a growth rate of 155.0%. As such, the cropland area and reservoir capacity showed an expanding trend. The high-density areas were consistent in space, but the high-value area of the reservoir was significantly smaller than that of cropland. 2) There was a spatial dislocation between the cropland area and the reservoir capacity, but the overall dislocation was smaller. There was a positive correlation on the spatial mismatch between cropland and reservoir capacity in EBTM, accounting for 58.5%. The expansion of the arable land was greater than the replenishment rate of reservoir capacity. 3) There were different spatial preferences for the geographical distribution of the cropland and reservoirs. But they all tended to be close to rivers, with the small slopes and low urbanization rate. The spatial distribution of the cropland was preferred the plains and plateaus with the low altitude, flat slope, near rivers, low urbanization level, and high degree of agricultural mechanization; The spatial distribution of the reservoirs was preferred the plateaus or small/medium undulating mountains with the medium to high altitudes, flat slopes, near rivers, and low levels of urbanization. 4) The spatial distribution of cropland and reservoirs was dominated by the complex factors, among which the total power of agricultural machinery, the output value of the primary industry and the distance from the river dominated the spatial distribution of cropland, and the distance from the river. The altitude and topography dominated the spatial distribution of the reservoir. The factor interaction indicated that the explanation of the inter-factor interaction for the spatial analysis of cultivated land and reservoirs was greater than that of the single factor, indicating the nonlinear and dual factor enhancement. There was the spatial matching of the cropland and reservoirs in EBTM. The finding can provide the scientific support for the decision-making on the "land determined by water " strategy, as well as the optimization and regulation of water—land resources in arid areas.

     

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