基于生态足迹法的水资源承载力研究——以北京市为例  

Research on water resources carrying capacity based on ecological footprint——A case study of Beijing

作　　者：门宝辉 蒋美彤 MEN Baohui;JIANG Meitong(Beijing Key Laboratory of Energy Safety and Clean Utilization,North China Electric Power University,Beijing102206,China)

机构地区：[1]华北电力大学可再生能源学院能源安全与清洁利用北京市重点实验室

出　　处：《南水北调与水利科技》2019年第5期29-36,共8页South-to-North Water Transfers and Water Science & Technology

基　　金：国家重点研发计划（2016YFC0401406）~~

摘　　要：为分析和评估区域水资源可持续发展状态,以水资源生态足迹系统的框架体系作为基础,引入水资源足迹广度与深度,区分水资源流量资本与存量资本,结合北京市实际情况,在现有人口和水资源条件下,计算水资源生态承载力的同时探讨改进的差分自回归移动平均模型ARIMA与广义神经网络GRNN的组合模型在水资源生态足迹中的拟合预测效果。结果显示:北京市长期处于水资源赤字这种不安全状态下,研究期内水资源足迹深度均大于1,平均水资源生态足迹为0.169hm^2/cap,约是平均水资源生态承载力的2倍,万元工业增加值用水量、万元GDP用水量、万元农业增加值用水量三个指标是影响北京市水资源生态足迹的重要因素。ARIMA(3,2,1)与GRNN耦合模型对北京市水资源生态足迹的拟合及预测效果优于单纯的ARIMA模型,其预测结果可为北京市水资源更有效地进行保护和配置提供参考。To analyze and evaluate the sustainable development status of regional water resources,this paper used framework of water resources ecological footprint system as foundation.This study introduced the breadth and depth of water resources footprint to distinguish water resources flow capital and stock capital,combined the actual situation of Beijing to calculate the ecological carrying capacity of water resources,and discussed the fitting prediction effect of the improved combination model of ARIMA and GRNN in water resources ecological footprint.Results showed that under the unsafe state of Beijing′s long-term water deficit,the depth of water resources in the study period is greater than 1,and the average water ecological footprint was0.169 hm^2/cap,which is about twice the average ecological carrying capacity of water resources.The three indicators,i.e.,water consumption per ten thousand yuan of value-added by industry,ten thousand yuan,and ten thousand yuan GDP water added value of agricultural water use were important factors which influenced the ecological footprint of water resources of Beijing.The effect of ARIMA(3,2,and 1)and GRNN coupling model on the fitting and prediction of the ecological footprint of water resources in Beijing was better than that of ARIMA model alone.The prediction results can provide reference for the more effective protection and allocation of water resources in Beijing.

关 键 词：水资源承载力 水资源生态足迹 差分自回归移动平均模型 广义回归神经网络 

分 类 号：TV211.1[水利工程—水文学及水资源]