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变化环境下河南省水资源情势与驱动力分析

Analysis of Water Resources Situation and Driving Forces in Henan Province Under Changing Environment
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摘要 为了解河南省水资源利用现状及趋势,为水资源管理部门提供参考,以应对变化环境下未来水资源供需所面临的挑战,基于河南省1999—2022年有关气象水文资料及水资源统计资料,采用统计分析、Mann-Kendall趋势检验及BP神经网络方法,对河南省水资源演变情势及其驱动力进行分析研究。结果表明:河南省降水量及水资源总量年际变化较大,整体不太稳定且丰枯水年交替频繁,供用水量呈现增长趋势但增速有所放缓;全省降水量、地下水资源量及水资源总量呈现不显著的减少趋势,地表水量及耗水量呈现不显著的增加趋势,供用水量呈现显著的增加趋势;降水量、年平均气温及下垫面的变化都是影响河南省水资源总量变化的重要因素。 In order to understand the current situation and trends of water resources utilization in Henan Province and provide reference for water resources management departments to address future challenges under changing environments,an analysis was conducted based on me-teorological and hydrological data from 1999 to 2022.Statistical analysis,Mann-Kendall trend test,and BP neural network methods were em-ployed to study the evolution and driving forces of water resources in Henan Province.The results show that annual precipitation and total wa-ter resources in Henan Province exhibit significant interannual variability,overall instability,and frequent alternation between wet and dry years.Water supply and usage show a growing trend,though the growth rate is slowing.Precipitation,groundwater resources,and total water resources exhibit an insignificant decreasing trend,while surface water and water consumption show an insignificant increasing trend.Water supply and usage display a significant increasing trend.Key factors influencing the total water resources in Henan Province include precipita-tion,annual average temperature,and underlying surface conditions.
作者 张修宇 曹丹丹 陈卓 赵济泽 ZHANG Xiuyu;CAO Dandan;CHEN Zhuo;ZHAO Jize(North China University of Water Resources and Electric Power,Zhengzhou 450046,China)
出处 《人民黄河》 CAS 北大核心 2024年第8期71-75,81,共6页 Yellow River
基金 河南省科技研发计划联合基金资助项目(232103810102) 水利部黄河流域水治理与水安全重点实验室(筹)研究基金资助项目(2023-SYSJJ-04) 水利部黄河泥沙重点实验室开放课题基金资助项目(HHNS202005) 河南省重大公益科技专项(201300311500) 河南省科技攻关项目(212102311156)。
关键词 水资源情势 驱动力 Mann-Kendall趋势检验 BP神经网络 河南省 water resources situation driving force Mann-Kendall trend test BP neural network Henan Province
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