尼尔基水库流域的流量变化及影响因素的量化

Chunxu Han, Fengping Li, Xiaolan Li, Sheng Wang, Yanhua Xu
{"title":"尼尔基水库流域的流量变化及影响因素的量化","authors":"Chunxu Han, Fengping Li, Xiaolan Li, Sheng Wang, Yanhua Xu","doi":"10.2166/wcc.2024.652","DOIUrl":null,"url":null,"abstract":"\n \n Nierji Reservoir is the largest and most important water conservancy project in the Nenjiang River Basin. A thorough understanding of variations in streamflow and the driving factors of the Nierji Reservoir Basin (NERB) is crucial, but there are still gaps. In this paper, the annual streamflow data of Nierji Reservoir from 1898 to 2013 were applied to detect the changing trend and abruptions using the Mann–Kendall method. Additionally, a Back Propagation-Artificial Neural Network (BP-ANN) model was developed to explore the relationships between the streamflow and its influencing factors and further quantify the relative contribution of each factor to the streamflow change. The results revealed that the annual streamflow of NERB significantly increased from 1898 to 2013 but declined during 1988–2013. Human activities were found to be the primary driver of streamflow decrease during 1988–2013, accounting for nearly 75% of the total change. Specifically, GDP had the largest influence, contributing 32% to the overall variation. Forest area, precipitation, and cultivated area had smaller contributions of 25, 23, and 18%, respectively. Temperature was found to have the least impact, with a relative contribution of 2%. This study provides valuable insights into water resources management in the Nenjiang River Basin, benefiting both agriculture and ecology.","PeriodicalId":506949,"journal":{"name":"Journal of Water and Climate Change","volume":"11 11","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Variations in the streamflow of the Nierji Reservoir Basin and quantification of the influencing factors\",\"authors\":\"Chunxu Han, Fengping Li, Xiaolan Li, Sheng Wang, Yanhua Xu\",\"doi\":\"10.2166/wcc.2024.652\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n \\n Nierji Reservoir is the largest and most important water conservancy project in the Nenjiang River Basin. A thorough understanding of variations in streamflow and the driving factors of the Nierji Reservoir Basin (NERB) is crucial, but there are still gaps. In this paper, the annual streamflow data of Nierji Reservoir from 1898 to 2013 were applied to detect the changing trend and abruptions using the Mann–Kendall method. Additionally, a Back Propagation-Artificial Neural Network (BP-ANN) model was developed to explore the relationships between the streamflow and its influencing factors and further quantify the relative contribution of each factor to the streamflow change. The results revealed that the annual streamflow of NERB significantly increased from 1898 to 2013 but declined during 1988–2013. Human activities were found to be the primary driver of streamflow decrease during 1988–2013, accounting for nearly 75% of the total change. Specifically, GDP had the largest influence, contributing 32% to the overall variation. Forest area, precipitation, and cultivated area had smaller contributions of 25, 23, and 18%, respectively. Temperature was found to have the least impact, with a relative contribution of 2%. This study provides valuable insights into water resources management in the Nenjiang River Basin, benefiting both agriculture and ecology.\",\"PeriodicalId\":506949,\"journal\":{\"name\":\"Journal of Water and Climate Change\",\"volume\":\"11 11\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Water and Climate Change\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2166/wcc.2024.652\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Water and Climate Change","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2166/wcc.2024.652","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

尼尔基水库是嫩江流域最大、最重要的水利工程。全面了解聂耳基水库流域(NERB)的流量变化及其驱动因素至关重要,但目前仍存在差距。本文应用 1898 年至 2013 年尼尔基水库的年径流量数据,采用 Mann-Kendall 方法检测其变化趋势和突变。此外,还建立了一个反向传播-人工神经网络(BP-ANN)模型,以探索流量与其影响因素之间的关系,并进一步量化各因素对流量变化的相对贡献。结果表明,1898 年至 2013 年期间,东北亚区域局的年径流量明显增加,但在 1988-2013 年期间有所减少。1988-2013年间,人类活动是导致溪流减少的主要因素,占总变化的近75%。具体而言,GDP 的影响最大,占总变化的 32%。森林面积、降水量和耕地面积的影响较小,分别占 25%、23% 和 18%。温度的影响最小,相对贡献率为 2%。这项研究为嫩江流域的水资源管理提供了宝贵的见解,对农业和生态都有益处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Variations in the streamflow of the Nierji Reservoir Basin and quantification of the influencing factors
Nierji Reservoir is the largest and most important water conservancy project in the Nenjiang River Basin. A thorough understanding of variations in streamflow and the driving factors of the Nierji Reservoir Basin (NERB) is crucial, but there are still gaps. In this paper, the annual streamflow data of Nierji Reservoir from 1898 to 2013 were applied to detect the changing trend and abruptions using the Mann–Kendall method. Additionally, a Back Propagation-Artificial Neural Network (BP-ANN) model was developed to explore the relationships between the streamflow and its influencing factors and further quantify the relative contribution of each factor to the streamflow change. The results revealed that the annual streamflow of NERB significantly increased from 1898 to 2013 but declined during 1988–2013. Human activities were found to be the primary driver of streamflow decrease during 1988–2013, accounting for nearly 75% of the total change. Specifically, GDP had the largest influence, contributing 32% to the overall variation. Forest area, precipitation, and cultivated area had smaller contributions of 25, 23, and 18%, respectively. Temperature was found to have the least impact, with a relative contribution of 2%. This study provides valuable insights into water resources management in the Nenjiang River Basin, benefiting both agriculture and ecology.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Bed shear stress distribution across a meander path Impact of El Niño, Indian Ocean dipole, and Madden–Julian oscillation on land surface temperature in Kuching City Sarawak, during the periods of 1997/1998 and 2015/2016: a pilot study Comprehensive economic losses assessment of storm surge disasters using open data: a case study of Zhoushan, China Determination of the effects of irrigation with recycled wastewater and biochar treatments on crop and soil properties in maize cultivation Determination of climate change impacts on Mediterranean streamflows: a case study of Edremit Eybek Creek, Türkiye
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1