自然资源学报 ›› 2018, Vol. 33 ›› Issue (9): 1552-1562.doi: 10.31497/zrzyxb.20170858

• 资源评价 • 上一篇    下一篇

基于情景模拟的上海土地利用变化预测及其水文效应

权瑞松   

  1. 华东政法大学政治学与公共管理学院,上海 201620
  • 收稿日期:2017-08-21 修回日期:2017-12-13 出版日期:2018-09-20 发布日期:2018-09-20
  • 作者简介:权瑞松(1984- ),男,博士,硕士生导师,研究方向为城市灾害风险评估与应急管理。E-mail: quanruisong@ecupl.edu.cn
  • 基金资助:
    国家自然科学基金项目(41401600)

Prediction of Land Use Change and Its Hydrological Effect in Shanghai Based on Scenario Simulation

QUAN Rui-song   

  1. School of Political Science and Public Administration, East China University of Political Science and Law, Shanghai 201620, China
  • Received:2017-08-21 Revised:2017-12-13 Online:2018-09-20 Published:2018-09-20
  • Supported by:
    ; National Natural Science Foundation of China, No. 41401600.

摘要: 论文基于2000、2003和2006年土地利用数据,借助Terrset CA-Markov模型模拟预测2030年上海市土地利用结构,采用SCS模型探究土地利用结构变化的水文效应。结果显示:1)Terrset CA-Markov模型的模拟精度为0.85,可用于模拟2030年上海土地利用格局。2)预测结果表明,2000—2030年间,工商业用地、居住用地与道路广场组成的城市不透水地面比重由2000年的26.54%激增至2030年的59.19%。3)上海不同区域的平均径流深度整体呈增加趋势,但也存在一定的时空差异性,而这种时空差异是由上海城市化过程中的土地利用转化造成的;2000—2030年间,上海中心城区不透水地面比重较高且变化较小,而郊区不透水地面面积大幅提升,导致郊区地表径流深度增幅大于中心城区。研究结果可为完善城市风险管理与城市规划提供参考。

关键词: CA-Markov模型, Kappa系数, SCS模型, 上海, 土地利用变化

Abstract: With the acceleration of urbanization process, waterlogging problems in urban area are becoming more and more serious due to climate change. In this context, it is very important to reduce disaster risk through urban planning. The pre-condition for urban planning is to simulate future land use and to analyze its hydrological effect. Taking Shanghai as a case study, this study predicted land use in 2030 by using Terrset CA-Markov model and analyzed hydrological response to land use change based on the land use data of Shanghai in 2000, 2003 and 2006. The results revealed that the simulation accuracy of CA-Markov model reached 0.85, which met the required simulation accuracy for the prediction of land use in 2030. The proportion of urban impermeable land, which consists of industrial and commercial land, residential land and road and square, increased from 26.54% in 2000 to 59.19% in 2030. Meanwhile, the proportion of non-construction land, which consists of arable land, garden, forestry and green space, decreased from 73.46% in 2000 to 40.81% in 2030. Moreover, the surface runoff depth showed an increasing trend from 2000 to 2030, but the spatial and temporal difference among districts in Shanghai was remarkable due to the land use change. Under the assumption of daily maximum precipitation at 200.5 mm, the surface runoff depth increased 3.86 mm during 2000-2006 and 9.66 mm during 2006-2030, respectively. Generally, the increase of surface runoff depth in suburb is more than that in central urban area in Shanghai, which results from high and stable proportion of impermeable land in central urban area and significantly increased proportion of impermeable land in suburb in Shanghai during 2000-2030. The study shows that the rapid increase of impermeable surface area increased the surface runoff depth, which could increase waterlogging risk in Shanghai. In addition, to reduce the exposure and vulnerability of urban system to rainstorm waterlogging, urban planning should focus on improving drainage system and optimizing the structure and layout of land use with the consideration of eco-environmental protection. These results provide important information for local government to improve urban risk management and urban planning.

Key words: CA-Markov model, Kappa coefficient, land use change, SCS model, Shanghai

中图分类号: 

  • P343.9