基于空间面板STIRPAT模型的水足迹影响因素分析——以山东省为例
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国家自然科学基金重大项目(71991481,71991480);中央高校基本业务费(35842020061);自然资源部资源环境承载力评价重点实验室开放课题(CCA2017.06)


Influence factors of water footprint based on spatial panel STIRPAT Model: A case study of Shandong Province
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    摘要:

    随着中国水资源供需矛盾加剧,虚拟水成为地区水资源管理中不可或缺的一环,为提高地区水资源综合利用效率和探索水资源区域一体化管理提供了新思路。采用"自下而上"法核算了山东省17个城市农业、工业、生活、生态与灰水足迹,在分析2009-2018年水足迹时空分布规律基础上,综合运用探索性空间数据分析方法、面板数据STIRPAT模型和空间杜宾模型,揭示了水足迹的空间自相关特征,量化分析了人口数量、富裕程度、技术进步、城镇化和产业升级等影响因素对水足迹的本地影响效应与空间溢出效应。结果显示:①2009-2018年山东省水足迹总量均呈现波动上升的变化趋势;空间布局上呈现东部沿海和西部平原水足迹高,中部山地水足迹低的特点。②山东省水足迹具有正向的空间自相关性,相比地理位置相邻,水足迹的空间相关性受人口数量因素影响更大,表现出明显的"高高"聚集和"低低"聚集特征,但是受到经济因素的主要影响,区域间水足迹空间相关性随时间发展逐渐下降。③人口数量是山东省水足迹增长的重要来源,经济增长是推动各地区间水资源竞争关系的最重要因素。城镇化能够缓解本地水资源压力,技术进步和产业升级不仅能缓解本地水资源压力,而且通过空间溢出效应有效缓解临近地区水资源压力,是实施水资源区域一体化管理策略的重要着眼点。

    Abstract:

    With the increasing gap between supply and demand of water resources in China, the virtual water has become an indispensable part of regional water resources management system. It is a new research framework to improve the comprehensive utilization efficiency and explore the feasibility of regional integrated management of water resources. This paper calculated the agricultural, industrial, residential, ecological water footprints, and grey water footprints of 17 cities in Shandong Province based on a bottom-up method. Based on the spatio-temporal analysis of water footprints from 2009 to 2018, we explored the spatial autocorrelation characteristics of water footprints using the exploratory spatial data analysis method. Then, we quantified the local impact effect and spatial spillover effect of influencing factors, such as population, economic growth, technological progress, urbanization, and industrial upgrading based on the combination of the panel data STIRPAT model and the spatial Dobbin model. The results show that ① the water footprint of Shandong Province from 2009 to 2018 presented an upward trend with fluctuation. The spatial layout shows the characteristics of the high water footprint in eastern coastal cities and western plain cities but the low water footprint in central mountain cities. ② The water footprint of Shandong Province has a positively spatial autocorrelation. Compared with the geographical locations, the spatial correlation of the water footprint is more affected by the population factor, showing obvious "High-High" aggregation type and "Low-Low" aggregation type. However, this kind of effect from population factor gradually decreases with time. In recent years, the economic factors have become the main influencing factors of the spatial effect of water footprint. ③ Population is an important source of water footprint, and economic growth is the most important factor in promoting water resources competition between regions. Urbanization can alleviate the pressure on water resource demand in local cities. While, the technological progress and industrial upgrading can not only alleviate the pressure of water resources demand in the local cities but also effectively alleviate the pressure of water resources demand in adjacent cities. Therefore, the technological progress and industrial upgrading should be the focus of the regional integrated management strategy of water resources.

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刘宁,李华姣,边志强,刘晓佳.基于空间面板STIRPAT模型的水足迹影响因素分析——以山东省为例.生态学报,2022,42(22):9335~9347

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