生态与农村环境学报 ›› 2019, Vol. 35 ›› Issue (12): 1505-1515.doi: 10.19741/j.issn.1673-4831.2019.0340

• 专论与综述 • 上一篇    下一篇

基于实测站点的区域森林水源涵养量空间化方法综述

吴溪1,2, 史文娇1,3   

  1. 1. 中国科学院地理科学与资源研究所/陆地表层格局与模拟院重点实验室, 北京 100101;
    2. 江苏省测绘工程院, 江苏 南京 210013;
    3. 中国科学院大学资源与环境学院, 北京 100049
  • 收稿日期:2019-05-13 出版日期:2019-12-25 发布日期:2019-12-21
  • 通讯作者: 史文娇 E-mail:shiwj@lreis.ac.cn
  • 作者简介:吴溪(1993-),女,江苏徐州人,硕士,主要研究方向为全球变化与区域生态。E-mail:wux@lreis.ac.cn
  • 基金资助:
    国家重点研发计划(2017YFA0604703);国家自然科学基金(41771111);中国科学院地理科学与资源研究所优秀青年人才基金(2016RC201);中国科学院青年创新促进会(2018071);自然资源部调查监测项目(JCQQ191504-06)

Spatial Simulation Methods of Regional Forest Water Conservation Based on Observed Data: A Review

WU Xi1,2, SHI Wen-jiao1,3   

  1. 1. Institute of Geographic Sciences and Natural Resources Research/Key Laboratory of Land Surface Pattern and Simulation, Chinese Academy of Sciences, Beijing 100101, China;
    2. Jiangsu Province Surveying & Mapping Engineering Institute, Nanjing 210013, China;
    3. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2019-05-13 Online:2019-12-25 Published:2019-12-21

摘要: 在全球气候变暖、人口增加和淡水资源紧张等多重压力下,水资源存储和保护至关重要,森林水源涵养是对降雨的截留、存储和调控,是调节气候、存储水资源的重要过程。已有的大尺度水源涵养量研究多是基于水文或遥感模型估算,缺乏基于站点实测数据的大尺度区域水源涵养量空间化方法的系统研究。该研究提出了基于实测站点的大尺度区域森林水源涵养量空间化框架,总结了林冠层、枯落物层、土壤层和森林水源涵养量的影响因子及其影响方式;在此基础上,综述了结合影响因子的站点空间化方法,总结了森林水源涵养量空间化存在的问题;最后,指出了站点空间化过程中辅助变量选择、分区分模型空间化、森林水源涵养量动态变化等方面的未来研究方向。

关键词: 森林水源涵养, 影响因子, 空间化, 大尺度, 综合蓄水能力

Abstract: Due to global climatic change, increase in population, and scare of fresh water, forest water conservation play an important roles in interception, storage and redistribution of precipitation. Large-scale spatial estimations of forest water conservation have been mostly studied by using hydrology or remote sensing models, but there is a lack of spatial estimation of forest water conservation at a large scale based on observed data. This paper proposed the framework of the spatial prediction for forest water conservation at a large scale based on observed data at sites, and then investigated the factors affecting canopy interception, litter water-holding, soil storage and forest water conservation. Further, the methods of spatial simulation based on observed data were introduced, including regression model, machine learning and geostatistical methods and the combination of multiple methods. In addition, the problems, including method for measuring forest water conservation and the process of spatial simulation for forest water conservation based on observed data, were summarized. Finally, the future research orientation of forest water conservation in a large-scale region has been presented on the bases of observed data at three aspects, including selection of auxiliary variables, spatialization of different regions with different models and spatial analysis of dynamic forest water conservation in a large-scale region.

Key words: forest water conservation, influencing factor, spatial simulation, large-scale, water conservation capacity

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