Climate change rather than vegetation greening dominates runoff change in China
文献类型：期刊论文
| 作者 | Song, Zhihong6,7,8; Xia, Jun1,4,5,8; Wang, Gangsheng1,3,8; She, Dunxian5,8; Hu, Chen8; Piao, Shilong2 |
| 刊名 | JOURNAL OF HYDROLOGY
 |
| 出版日期 | 2023-05-01 |
| 卷号 | 620页码:9 |
| ISSN号 | 0022-1694 |
| 关键词 | Vegetation greening Climate change China Hydrologic cycle |
| DOI | 10.1016/j.jhydrol.2023.129519 |
| 通讯作者 | Xia, Jun(xiajun666@whu.edu.cn) ; Wang, Gangsheng(wanggs@whu.edu.cn) |
| 英文摘要 | China leads the world in vegetation greening and accounts for one-fourth of the global net increase in leaf area over the past two decades. However, it remains elusive on the relative importance of vegetation greening and climate change on China's hydrological cycle due to the lack of observational-based constraints on notorious model uncertainties. Here, we developed a process-based distributed hydrological model that couples a nonlinear runoff generation mechanism with a remotely-sensed evapotranspiration (ET) module. This model could well capture the spatiotemporal patterns of the main hydrological components (runoff, ET, and soil moisture) at grid scale and streamflow at watershed scale during 1982-2012 over the mainland China. We show that the changes in climatic factors (precipitation and potential ET) dominated hydrologic change at the national scale, with climate induced runoff decrease by 7.6 mm year(-1) compared to 0.6 mm year(-1) caused by vegetation change. Vegetation effect was primarily notable in water-limited regions as a higher correlation between vegetation contribution to runoff change and absolute leaf area index (LAI) trend in water-limited regions (r = 0.52, p < 0.01) than energy-limited regions (r = 0.19, p < 0.01). Our results highlight the significance of region-dependent differential measures for sustainable water resources management and climate change adaptation under a changing climate. |
| WOS关键词 | TERRESTRIAL EVAPOTRANSPIRATION ; FILTERING METHOD ; WATER ; MODEL ; CO2 ; EVAPORATION ; DATASET ; SCALE |
| 资助项目 | National Natural Science Foundation of China[41890823] ; Fundamental Research Funds for Central Public Welfare Research Institutes[CKSF2023298/SZ] ; National Key R & D Program of China[2017YFA0603702] ; Excellent Young Scientists Fund ; Na- tional Natural Science Foundation of China[U21A20156] |
| WOS研究方向 | Engineering ; Geology ; Water Resources |
| 语种 | 英语 |
| 出版者 | ELSEVIER |
| WOS记录号 | WOS:000989332600001 |
| 资助机构 | National Natural Science Foundation of China ; Fundamental Research Funds for Central Public Welfare Research Institutes ; National Key R & D Program of China ; Excellent Young Scientists Fund ; Na- tional Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/197425]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Xia, Jun; Wang, Gangsheng |
| 作者单位 | 1.Wuhan Univ, Inst Water Carbon Cycles & Carbon Neutral, Wuhan 430072, Peoples R China 2.Peking Univ, Sino French Inst Earth Syst Sci, Coll Urban & Environm Sci, Beijing 100871, Peoples R China 3.Univ Oklahoma, Inst Environm Genom, Norman, OK 73019 USA 4.Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China 5.Wuhan Univ, Hubei Key Lab Water Syst Sci Sponge City Construct, Wuhan 430072, Peoples R China 6.Hubei Prov Key Lab Basin Water Resources & Ecol En, Wuhan 430010, Peoples R China 7.Changjiang Water Resources Commiss, Changjiang River Sci Res Inst, Wuhan 430010, Peoples R China 8.Wuhan Univ, State Key Lab Water Resources & Hydropower Engn Sc, Wuhan 430072, Peoples R China |
| 推荐引用方式 GB/T 7714 | Song, Zhihong,Xia, Jun,Wang, Gangsheng,et al. Climate change rather than vegetation greening dominates runoff change in China[J]. JOURNAL OF HYDROLOGY,2023,620:9. |
| APA | Song, Zhihong,Xia, Jun,Wang, Gangsheng,She, Dunxian,Hu, Chen,&Piao, Shilong.(2023).Climate change rather than vegetation greening dominates runoff change in China.JOURNAL OF HYDROLOGY,620,9. |
| MLA | Song, Zhihong,et al."Climate change rather than vegetation greening dominates runoff change in China".JOURNAL OF HYDROLOGY 620(2023):9. |
入库方式： OAI收割
来源：地理科学与资源研究所
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