人民黄河2024，Vol.46Issue(5)：91-97,7.DOI:10.3969/j.issn.1000-1379.2024.05.015
基于SWAT模型的蓝绿水短缺指数计算与风险评价
Calculation of Blue and Green Water Scarcity Index and Risk Assessment Based on SWAT Model
摘要
Abstract
In order to reduce the risk of water shortage of Qinhe River Basin,this paper took Qinhe River Basin as the research object,esti-mated the blue and green water resources in Qinhe River Basin from 2010 to 2016 based on the output results of the SWAT model,calculated the blue and green water scarcity index through the blue and green water footprint and the blue and green water availability,and quantitatively evaluated the blue and green water shortage situation in Qinhe River Basin by dividing four risk levels of blue and green water shortage.The results show that:a)The average annual blue water resources in Qinhe River Basin are 910 million m3,accounting for 12.0%of the total water resources,and the average annual green water resources are 6.69 billion m3,accounting for 88.0%of the total water resources,and the main component of water resources in Qinhe River Basin is green water resources;b)Under the annual scale,the blue water shortage index of most molecular basins in Qinhe River is greater than 1.0,and the risk level of blue water shortage is relatively serious risk,especially in Jiaozuo City in the downstream area;c)Under the annual scale,the index of green water scarcity in each subbasin of Qinhe River shows some differences,the average annual green water shortage index in most sub-basins is in the range of 0.5-1.0,and the green water shortage faces moderate risk;On the whole,the risk level of green water shortage is lower than that of blue water shortage.Based on the analysis of water shortage indexes of blue water and green water,it put forward suggestions on reducing the water safety risk of Qinhe River Basin.关键词
蓝绿水/SWAT模型/水短缺指数/风险评价/沁河流域Key words
blue and green water/SWAT model/water scarcity index/risk evaluation/Qinhe River Basin分类
建筑与水利引用本文复制引用
程琰,左其亭,邱曦..基于SWAT模型的蓝绿水短缺指数计算与风险评价[J].人民黄河,2024,46(5):91-97,7.基金项目
国家重点研发计划项目(2021YFC3200201) （2021YFC3200201）
国家自然科学基金资助项目(52279027) （52279027）
