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京津以南河北平原地下水位下降驱动因子的定量评估 被引量:21

Evaluation of Groundwater Level Drawdown Driving Forces in the Hebei Plain to the South of Beijing and Tianjin
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摘要 自1970年代以来,在自然因素和人为活动的交互影响下,京津以南河北平原地下水位持续下降并产生了一系列地质环境问题,严重影响了该区域社会经济的可持续发展。本文从降水、地表径流、气温等自然因素及地下水超采、水利工程修建、农作物产量水平提高、耗水型作物面积扩大等人为因素初步分析了京津以南河北平原地下水位下降的主要原因;通过建立投影寻踪回归模型,定量评价了各因素对地下水位下降的影响,确定了各影响因素对地下水位下降的相对贡献率。结果表明:地下水开采是引起地下水位下降的最主要因素,对地下水位下降的相对贡献率为54.7%,其中工业、农业、生活用水对地下水位下降的相对贡献率分别为6.6%、43.7%和4.4%;其次是降水和地表径流,其相对贡献率分别为25.6%和19.7%。 From the 1970s, under the impact of natural and human factors, the groundwater table in the Hebei Plain has been declining,causing a range of geological and environmental disasters. These disasters include subsidence, seawater intrusion, salinization, desertification and so on, which have seriously threatened the ecological environment and become the key factors of restricting the socio-economic sustainable development of the Hebei Plain. This paper analyzed the causes of groundwater withdrawal from such natural factors as precipitation, surface water and temperature, and from such human aspects as over-exploitation of groundwater, building of water conservancy, improvement of crop production and enlargement of water-consuming crops. The contribution of driving forces to groundwater table drawdown was assessed through building Projection Pursuit Regression model. The result indicates that the exploitation of groundwater is the first factor, which accounts for 54.7% of groundwater withdrawal. According to the proportion of groundwater consumed by industry, agriculture and domestic, the percent of groundwater table drawdown caused by the three sectors were 6.6%, 43.7% and 4.4% respectively. The second is precipitation, with 25.6%, and the third is surface water, with 19.7%. This paper provides scientific basis for groundwater sustainable use.
作者 许月卿
出处 《地理科学进展》 CSCD 北大核心 2003年第5期490-498,共9页 Progress in Geography
基金 中国科学院知识创新工程项目(KZCX2-310-01-05)资助
关键词 京津以南河北平原 地下水位下降 驱动因子 投影寻踪回归 定量评估 the Hebei Plain to the south of Beijing and Tianjin groundwater level drawdown driving forces projection pursuit regression
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