王静, 姚顺波, 刘天军. 退耕还林背景下降水利用效率时空演变及驱动力探讨[J]. 农业工程学报, 2020, 36(1): 128-137. DOI: 10.11975/j.issn.1002-6819.2020.01.015
    引用本文: 王静, 姚顺波, 刘天军. 退耕还林背景下降水利用效率时空演变及驱动力探讨[J]. 农业工程学报, 2020, 36(1): 128-137. DOI: 10.11975/j.issn.1002-6819.2020.01.015
    Wang Jing, Yao Shunbo, Liu Tianjun. Spatio-temporal evolution and driving forces of rainfall use efficiency in land restoration[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2020, 36(1): 128-137. DOI: 10.11975/j.issn.1002-6819.2020.01.015
    Citation: Wang Jing, Yao Shunbo, Liu Tianjun. Spatio-temporal evolution and driving forces of rainfall use efficiency in land restoration[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2020, 36(1): 128-137. DOI: 10.11975/j.issn.1002-6819.2020.01.015

    退耕还林背景下降水利用效率时空演变及驱动力探讨

    Spatio-temporal evolution and driving forces of rainfall use efficiency in land restoration

    • 摘要: 为了给退耕还林(草)政策的有效制定和实施提供有针对性的理论依据,以宝鸡地区作为研究区域,选取植被生长季(3-11月),基于标准化植被降水利用效率(standardized rainfall use efficiency, Z(RUE))模型,综合气候、土地利用/覆盖及光学遥感3个维度,分离自然因素和人为因素,监测年际、季和月尺度上的Z(RUE)时空演变特征,进一步采用灰色关联法探讨了其驱动力。结果表明:1)在2001-2017年,宝鸡地区经过2轮退耕还林(草)工程,Z(RUE)整体上呈提高趋势,尤其是第一轮后呈显著提高趋势的像元面积占比最高,达65.69%。全区由第一轮工程实施中的以人为干预增加区域为主转变为以人为干预减少为主;2)春季Z(RUE)变化的年际差异最小,转变点出现在2009年,表现为2001-2009年和2009-2017年分别呈正、负增长分布。夏季Z(RUE)的增加最显著,秋季年际差异最大。年际、春尺度上各年的Z(RUE)均值分别在草地、耕地最高,城乡用地的Z(RUE)在夏秋两季最高;3)不同植被类型、不同坡度、不同坡向的Z(RUE)变化均呈"三高一低"峰值分布。高峰值出现在4月、6月和11月(最大值),低峰值出现在9月(最小值),分别对应着农田植被的返青(4月)、收割(6月)和播种期(9月);4)宝鸡地区Z(RUE)变化的主要驱动因子是气温、日照时数(光照)和人均GDP。退耕还林(草)背景下,宝鸡地区生长季的草地植被改善趋势最好,这与Z(RUE)在草地上呈提高趋势高度吻合。另外,除扶风、麟游、凤县外,其余各县(区)均为气候变化对宝鸡地区Z(RUE)变化的贡献率大于人类活动。

       

      Abstract: Returning farmland to forest (grass), named Grain for Green Project, is one of the major ecological land restoration in China. In the context of the global climate change, the study of the impact of precipitation patterns on the productivity of ecosystems become an important means to evaluate the use efficiency of returning farmland to forests (grass) for the ecological restoration. Baoji region was used to this research in order to provide a specific theoretical reference for the improvement and implementation of the subsequent national ecological restoration policy, and the corresponding vegetation growth season was selected as March-November. Based on the standardized rainfall use efficiency Z(RUE) model and integrated climate, land use/cover and optical remote sensing, this present study explored the influence of the temporal and spatial evolution characteristics of Z(RUE) and driving forces by the use of isolated natural and human factors to monitor the inter-annual and seasonal growth seasons. The result shows: 1) In 2001 to 2017, after two rounds of returning farmland to forests (grass) in Baoji area, Z(RUE) showed an overall improvement trend, especially in the area of pixels that showed a significant increase after the first round. The highest increase was 65.69%. The whole region was changed from the artificial intervention region to the reduction of human intervention under the first round of the project implementation; 2) The spring Z(RUE) change was the smallest among the inter-annual differences, and the transition point appeared in 2009, which was the period of 2001 to 2009 and 2009 to 2017 were positive and negative growth distribution, respectively. Z(RUE) in Summer increased most significantly, together with the largest annual difference in Autumn. The Z(RUE) mean of each year on the inter-annual and spring scales was the highest in the grassland and cultivated land, respectively, and the Z(RUE) of urban and rural land was the highest in Summer and Autumn; 3) Different type of vegetation, slope, direction of slope angle, change of Z(RUE) were in the peak distribution of "three high and one low". The much higher peaks occurred in April, June, and November (maximum), whereas the low peaks occurred in September (minimum), corresponding to greening (April), harvesting (June), and sowing (September); 4) Illumination duration become the main driving factor for the Z(RUE) variations in Baoji area. The main driving factors were temperature, sunshine hours and per capita GDP. Since the implementation of the project of returning farmland to forests (grass), the grassland improvement trend in the growing season was the best, indicating consistent with the increasing trend of Z(RUE) on the grassland. Except Fufeng, Linyou County and Fengxian, the remaining counties (districts) have much more contributed to the variation of Z(RUE) than human activities in Baoji area of China.

       

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