Intra-annual variation in the attribution of runoff evolution in the Yellow River source area

地表径流 大洪水 水文学(农业) 气候变化 环境科学 降水 地质学 流域 径流曲线数 生长季节 地理 生态学 岩土工程 气象学 生物 地图学 考古
作者
Yongxin Ni,Xizhi Lv,Zhongbo Yu,Jianwei Wang,Li Ma,Qiufen Zhang
出处
期刊:Catena [Elsevier BV]
卷期号:225: 107032-107032 被引量:20
标识
DOI:10.1016/j.catena.2023.107032
摘要

Accurately understanding the intra-annual variation in runoff evolution attribution is essential for basin-scale water resources management. In this study, the runoff in the Yellow River source area was divided into two intra-annual time scales: flood season, non-flood season and spring, summer, autumn and winter, and the sensitivity and attribution differences of runoff changes in the Yellow River source area at different intra-annual time scales were quantitatively assessed based on the time-varying Budyko framework. Results show that the runoff in the Yellow River source area decreases during the flood season and spring, summer and autumn, and increases during the non-flood season and winter from 1960 to 2020, with an insignificant decreasing trend in annual runoff. Flood season and autumn runoff changes are the main reasons for the reduction in annual runoff. Runoff in the Yellow River source area is most sensitive to the underlying surface such as vegetation and soil freeze–thaw change, and in terms of climate change, non-flood season and autumn runoff is more sensitive to changes in precipitation, while flood season and summer runoff is more sensitive to changes in potential evaporation. The underlying surface change is the dominant factor for annual runoff change. And for the intra-annual runoff change, the non-flood season, spring and winter runoff in the Yellow River source area is dominated by the underlying surface change, and flood season, summer and autumn runoff is dominated by the climate change. These findings can provide theoretical support for the scientific response to environmental change and the enhancement of water conservation capacity in the Yellow River source area.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
WW应助吴彦祖采纳,获得10
1秒前
科研通AI6.2应助TannerPavent采纳,获得10
1秒前
内向小笼包完成签到,获得积分10
1秒前
2秒前
机灵的雅蕊完成签到,获得积分10
3秒前
5秒前
7秒前
640发布了新的文献求助10
7秒前
helpme完成签到,获得积分10
7秒前
平淡板凳发布了新的文献求助30
9秒前
烟花应助Ashley采纳,获得10
9秒前
黎行云完成签到,获得积分10
9秒前
11秒前
Jelly发布了新的文献求助30
12秒前
星辰大海应助加菲丰丰采纳,获得30
12秒前
天天快乐应助LiuHX采纳,获得10
12秒前
阳光怀亦发布了新的文献求助10
15秒前
天天快乐应助Ada采纳,获得10
16秒前
17秒前
18秒前
今后应助Play采纳,获得10
20秒前
21秒前
qfyyyyyyy发布了新的文献求助10
21秒前
阳光怀亦完成签到,获得积分20
22秒前
23秒前
cdercder应助shelly采纳,获得10
24秒前
Orange应助科研小白采纳,获得10
24秒前
小怪兽kk发布了新的文献求助10
25秒前
Fuch完成签到 ,获得积分10
26秒前
Daurzr完成签到,获得积分10
27秒前
27秒前
xinyan完成签到,获得积分10
28秒前
敏感手套发布了新的文献求助10
28秒前
30秒前
池台下发布了新的文献求助10
30秒前
平淡绿草发布了新的文献求助10
30秒前
领导范儿应助上岸采纳,获得10
31秒前
31秒前
LL完成签到,获得积分10
32秒前
33秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Cronologia da história de Macau 5000
Braunwald’s Heart Disease, 2 Vol Set A Textbook of Cardiovascular Medicine 13th Edition 1000
Petrology and Plate Tectonics 800
Prompt Engineering for Clinicians: Harnessing AI in Everyday Medical Practice 600
Electrode Potentials 550
Handbook Of Synthetic Methodologies And Protocols Of Nanomaterials 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 光电子学 物理化学 电极 基因 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 6998476
求助须知:如何正确求助?哪些是违规求助? 8674030
关于积分的说明 18392029
捐赠科研通 6473995
什么是DOI,文献DOI怎么找? 3099710
关于科研通互助平台的介绍 2163528
邀请新用户注册赠送积分活动 2076119