Attribution analysis of the spatiotemporal variation in water balance in a typical semiarid basin in northern China
文献类型：期刊论文
| 作者 | Lu, Wen1,2,3; Tang, Jialiang3; Lu, Chunxia4; Lu, Chuiyu1,2; Jia, Yangwen1,2; Sun, Qingyan1,2; He, Xin1,2; Zhang, Xifeng3 |
| 刊名 | HYDROLOGICAL PROCESSES
 |
| 出版日期 | 2022-08-01 |
| 卷号 | 36期号:8页码:16 |
| 关键词 | Budyko hypothesis climate change human activities Upper Yongding River Basin |
| ISSN号 | 0885-6087 |
| DOI | 10.1002/hyp.14651 |
| 通讯作者 | Tang, Jialiang(jltang@imde.ac.cn) |
| 英文摘要 | Climate change and anthropogenic factors have significantly impacted hydrological regimes, especially in semiarid regions. Using the trend-free pre-whitening Mann-Kendall (TFPW-MK) test and linear regression, trends of precipitation, temperature, runoff, and water balances from different spatiotemporal scales were analysed during the past sixty years in the Upper Yongding River Basin (UYRB). Based on the Choudhury-Yang equation, the contributions of climate change and human activities to runoff variation were further quantified in five mountainous catchments, and the actual effects of climate change and human activities on the water balance in the whole UYRB were also discussed. The results suggest that the UYRB has become much warmer and drier. The lower annual precipitation and intensity in summer were directly attributed to runoff reductions. Intra-annual scale analyses of meteorological, hydrological and biological responses helped the comprehensive interpretation of the runoff trends. Human activities, including agricultural irrigation, were the main causes for runoff reduction, especially in the middle and lower reaches, and the contribution of human activities increased gradually in recent decades. The water balance changed drastically temporally, with the precipitation being converted less to runoff and more to evaporated fractions, which was also due to the second order effects of climate change and vegetation improvement. It is suggested that low water-consumption plant species and the related water-saving techniques in agriculture and afforestation should be introduced for the sustainable development in the similar regions. |
| WOS关键词 | HAIHE RIVER-BASIN ; CLIMATE-CHANGE ; VARIABILITY ; RUNOFF ; CATCHMENT ; EVAPOTRANSPIRATION ; STREAMFLOW ; AREA |
| 资助项目 | \Applied Technology Research and Development Program of Heilongjiang Province[GA19C005] ; National Major Science and Technology Program for Water Pollution Control and Treatment[2017ZX07101001] ; National Natural Science Foundation of China[41371241] |
| WOS研究方向 | Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:000849925200008 |
| 出版者 | WILEY |
| 资助机构 | \Applied Technology Research and Development Program of Heilongjiang Province ; National Major Science and Technology Program for Water Pollution Control and Treatment ; National Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/182147]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Tang, Jialiang |
| 作者单位 | 1.China Inst Water Resources & Hydropower Res IWHR, Dept Water Resources, Beijing, Peoples R China 2.China Inst Water Resources & Hydropower Res IWHR, State Key Lab Simulat & Regulat Water Cycles Rive, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Mt Hazards & Environm, Key Lab Mt Surface Proc & Ecol Regulat, Chengdu 610041, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lu, Wen,Tang, Jialiang,Lu, Chunxia,et al. Attribution analysis of the spatiotemporal variation in water balance in a typical semiarid basin in northern China[J]. HYDROLOGICAL PROCESSES,2022,36(8):16. |
| APA | Lu, Wen.,Tang, Jialiang.,Lu, Chunxia.,Lu, Chuiyu.,Jia, Yangwen.,...&Zhang, Xifeng.(2022).Attribution analysis of the spatiotemporal variation in water balance in a typical semiarid basin in northern China.HYDROLOGICAL PROCESSES,36(8),16. |
| MLA | Lu, Wen,et al."Attribution analysis of the spatiotemporal variation in water balance in a typical semiarid basin in northern China".HYDROLOGICAL PROCESSES 36.8(2022):16. |
入库方式： OAI收割
来源：地理科学与资源研究所
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