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中国沙漠 ›› 2024, Vol. 44 ›› Issue (6): 87-99.DOI: 10.7522/j.issn.1000-694X.2024.00065

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石羊河流域产水服务供需时空变化及驱动因子

夏鸿华1,2(), 杨林山1(), 冯起1, 苏迎庆1, 邹星怡2, 贺王含2   

  1. 1.中国科学院西北生态环境资源研究院 干旱区生态安全与可持续发展重点实验室,甘肃 兰州 730000
    2.中国科学院大学,北京 100049
  • 收稿日期:2024-05-26 修回日期:2024-07-02 出版日期:2024-11-20 发布日期:2024-12-06
  • 通讯作者: 杨林山
  • 作者简介:杨林山(E-mail: yanglsh08@lzb.ac.cn
    夏鸿华(2000—),女,云南楚雄人,硕士研究生,主要从事寒区水文、水资源及水文过程研究。E-mail: xhonghua2000@163.com
  • 基金资助:
    国家自然科学基金项目(52379030);中国科学院B类先导项目(XDB0720202);中国科协青年人才托举工程项目(YESS20200089);中国科学院青年创新促进会会员项目(2022435);中国工程科技发展战略甘肃研究院咨询研究项目(GS2022ZDI03);甘肃省科技计划项目(24JRRA079)

Spatio-temporal variation and driving factors of water supply and demand in Shiyang River Basin

Honghua Xia1,2(), Linshan Yang1(), Qi Feng1, Yingqing Su1, Xingyi Zou2, Wanghan He2   

  1. 1.Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands,Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou 730000,China
    2.University of Chinese Academy of Sciences,Beijing 100049,China
  • Received:2024-05-26 Revised:2024-07-02 Online:2024-11-20 Published:2024-12-06
  • Contact: Linshan Yang

摘要:

开展流域产水服务供需匹配关系的研究对促进区域水资源科学利用及生态环境可持续发展具有重要意义。选取石羊河流域为研究区,基于1990、2000、2010、2020年遥感影像、站点监测及再分析产品数据,采用InVEST模型、用水需求估算、供需指数及地理探测器等方法综合分析1990—2020年石羊河流域产水服务供需现状及演变特征。结果表明:(1)1990—2020年,石羊河流域产水服务供给量空间上呈现西南高东北低的分布特征,1990年产水量最低(16.55×108 m3),2010年最高(19.37×108 m3)。产水服务贡献率最高的为林地及草地。(2)流域产水服务需求量整体呈现西南高东北低的空间分布特征,1990年产水服务需求量最高(20.39×108 m3),2020年最低(17.78×108 m3),耕地是流域用水服务需求量最高的土地利用类型。(3)流域西南部山地产水服务供需匹配程度较高,石羊河干支流流经区次之,而流域东北及东部地区产水服务供需匹配程度较低。研究区内供需指数两极分化明显,区域内水资源供需空间分配极度不均。时间上产水服务匹配状况有逐步好转的迹象,2020年流域产水服务的供需匹配程度有明显提高。(4)地理探测器结果表明,10种因子中影响流域产水量空间分异的最大因子是年降水量,同时,各驱动因子的交互作用解释力均大于单一因子,存在双因子增强及非线性增强两种组合形式。因此,未来亟须加强流域气候变化适应性管理政策的调整,统筹流域水资源综合管理。

关键词: 产水量, 供需关系, 时空格局, InVEST模型, 石羊河流域

Abstract:

To promote the scientific utilization of regional water resources and the sustainable development of the ecological environment, it was imperative to conduct research on the matching relationship between water yield supply and demand in river basins. In this regard, the Shiyang River Basin (SYB) was chosen as the study area. Employing a range of methodologies including remote sensing imagery, site monitoring data, and reanalysis product data from 1990, 2000, 2010, and 2020, we utilize the InVEST model, water demand estimation method, and geographic detector to comprehensively analyze the status and evolution characteristics of the water yield supply and demand in the SYB during the aforementioned period. This research aims to contribute to the advancement of sustainable water resource allocation in the region and was a critical step towards achieving long-term ecological balance and sustainable development in the basin. The results showed that: (1) Over the period spanning from 1990 to 2020, the spatial distribution of water supply within the SYB has been characterized by a high concentration in the southwest and a lower level in the northeast region. The lowest water yield occurred in 1990, measuring approximately 16.56×108 m3, while the highest yield was recorded in 2010, amounting to around 19.37×108 m3. Woodland and grassland exhibit the highest contribution rates in terms of water production. (2)The water demand in 1990 was the highest (20.39×108 m3) and the lowest in 2020 (17.78×108 m3). Cultivated land is the land use type with the highest water demand in the basin. (3) The matching degree of water supply and demand in the southwestern mountainous area of the basin is higher, followed by the Shiyang River mainstream and tributary area, while the matching degree of water supply and demand in the northeastern and eastern regions of the basin is lower. The polarization of supply and demand index in the study area is obvious, and the spatial distribution of water resources supply and demand in the region is extremely uneven. From 1990 to 2020, the matching status of water production services in Shiyang River showed signs of gradual improvement, and the matching degree of supply and demand of water production services in the basin was significantly improved in 2020. (4) The results of the geo-detector show that the largest factor affecting the spatial differentiation of water yield in the basin among the ten factors was the average annual precipitation. Additionally, the combined effect of multiple driving factors and their interactions has a greater explanatory power than that of a single factor alone. Furthermore, there were two types of enhancement observed: the synergistic effect of two-factor combinations and non-linear enhancements. Therefore, it is crucial to prioritize the strengthening of adaptive management policies for watershed climate change and to promote coordinated watershed management.

Key words: water yield, supply and demand relationship, spatio-temporal pattern, InVEST model, Shiyang River Basin

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