[1]LI Xue,YU Kunxia,LI Peng,et al.Spatiotemporal Evolution and Driving Force of Rainfall Concentration in the Yellow River Basin[J].Research of Soil and Water Conservation,2023,30(05):266-273.[doi:10.13869/j.cnki.rswc.2023.05.008.]
Copy

Spatiotemporal Evolution and Driving Force of Rainfall Concentration in the Yellow River Basin

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 30 Number of periods: 2023 05 Page number: 266-273 Column: Public date: 2023-08-10
Title:
Spatiotemporal Evolution and Driving Force of Rainfall Concentration in the Yellow River Basin
Author(s):
LI Xue1, YU Kunxia1, LI Peng1, LI Zhanbin1, YANG Zhi2, ZHANG Guojun2, ZHANG Xiaoming3, MA Wentao2
(1.State Key Laboratory of Eco-hydraulics in Northwest Arid Region of China, Xi'an University of Technology, Xi 'an 710048, China; 2.Ningxia Soil and Water Conservation Monitoring Station, Yinchuan 750000, China; 3.Ecological Engineering Research Center for Soil and Water Conservation, Ministry of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100000, China)
Keywords:
rainfall concentration;  Yellow River Basin;  spatiotemporal evolution;  driving force;  cross wavelets
CLC:
TV125
DOI:
10.13869/j.cnki.rswc.2023.05.008.
Abstract:
[Objective] Investigating the spatial and temporal evolution of rainfall concentration in the Yellow River Basin and its driving forces can reveal the intra-annual distribution of rainfall in the region and provide a scientific basis for the prevention of extreme rainfall and the control of soil erosion and water resources planning in the basin. [Methods] Theil-Sen Median analysis and Mann-Kendall test were used to investigate the trend characteristics of rainfall concentration in the Yellow River basin based on the month-by-month raster rainfall data from 1961—2018. The influence of the three selected atmospheric anomalous circulation factors and sunspots on rainfall concentration were discussed. [Results](1)The average annual rainfall in the middle and lower reaches of the Yellow River basin was much greater than that in the upper reaches, with the maximum average annual rainfall in the middle and lower reaches of the basin from Sanmenxia to Huankou and below Huankou reaching 867 mm, while the average annual rainfall in the upper reaches of the Yellow River from Lanzhou to the northern part of Hekou town was only 115 mm.(2)The rainfall concentration in the Yellow River Basin varied greatly from watershed to watershed, with significant seasonal variations in the watershed from Longmen to Sanmenxia, and abnormal concentrations in the northeastern part of the watershed from Lanzhou to Hekou town.(3)Areas with significant trends in rainfall concentration in the Yellow River basin mainly concentrated above Longyangxia, from Longyangxia to Lanzhou and from Lanzhou to Hekou town.(4)Both sunspots and atmospheric circulation anomalies had influence on rainfall concentration, with atmospheric circulation anomalies directly influencing rainfall concentration and sunspots indirectly influencing rainfall concentration through atmospheric circulation anomalies. This study investigated the rainfall concentration in the Yellow River Basin, which could provide a scientific basis for the prevention of extreme rainfall and the control of soil erosion and water resources planning in the Yellow River Basin. [Conclusion] The concentration of rainfall in different water resource zones in the Yellow River Basin varied greatly. When formulating erosion control measures and water resource planning policies, it is necessary to tailor them to the actual rainfall conditions in different water resource zones.
References:
[1] 宋晓猛,张建云,孔凡哲,等.北京地区降水极值时空演变特征[J].水科学进展,2017,28(2):161-173.
[2] 闫宝伟,刘昱,江慧宁,等.考虑降雨空间异质性的动态临界雨量预警指标推求[J].水利学报,2020,51(3):342-348.
[3] 韩谞,潘保柱,陈越,等.黄河水环境特征与氮磷负荷时空分布[J].环境科学,2021,42(12):5786-5795.
[4] 宋晓猛,张建云,占车生,等.气候变化和人类活动对水文循环影响研究进展[J].水利学报,2013,44(7):779-790.
[5] 冶运涛,梁犁丽,龚家国,等.长江上游流域降水结构时空演变特性[J].水科学进展,2014,25(2):164-171.
[6] 莫崇勋,莫桂燕,阮俞理,等.澄碧河水库流域降雨变化分析[J].节水灌溉,2017,267(11):56-61.
[7] Van Wijngaarden W A, Syed A. Changes in annual precipitation over the Earth's land mass excluding Antarctica from the 18 th century to 2013[J]. Journal of Hydrology, 2015,531:1020-1027.
[8] 黄生志,杜梦,李沛,等.变化环境下降雨集中度的变异与驱动力探究[J].水科学进展,2019,30(4):496-506.
[9] 刘业森,刘媛媛,李敏,等.降雨数据空间分辨率在城市流域洪峰变化分析中的影响[J].地球信息科学学报,2022,24(7):1326-1336.
[10] 樊晶晶.变化环境下水文要素变异研究[D].西安:西安理工大学,2016.
[11] 郑彦辰,李建柱,荣佑同,等.降雨时空分布量化及其在洪水过程分类中的应用[J].水利学报,2022,53(5):560-573.
[12] Oliver J E. Monthly precipitation distribution:a comparative index[J]. the Professional Geographer, 1980,32(3):300-309.
[13] Martin-Vide J. Spatial distribution of a daily precipitation concentration index in peninsular Spain[J]. International Journal of Climatology: A Journal of the Royal Meteorological Society, 2004,24(8):959-971.
[14] De Luís M, García-Cano M F, Cortina J, et al. Climatic trends, disturbances and short-term vegetation dynamics in a Mediterranean shrubland[J]. Forest ecology and management, 2001,147(1):25-37.
[15] Chatterjee S, Khan A, Akbari H, et al. Monotonic trends in spatio-temporal distribution and concentration of monsoon precipitation(1901—2002), West Bengal, India[J]. Atmospheric Research, 2016,182:54-75.
[16] 段亚雯,朱克云,马柱国,等.中国区域1961—2010年降水集中指数(PCI)的变化及月分配特征[J].大气科学,2014,38(6):1124-1136.
[17] Shiau J T. Effects of gamma-distribution variations on SPI-based stationary and nonstationary drought analyses[J]. Water Resources Management, 2020,34:2081-2095.
[18] 王卫平,刘永强,赵求东,等.新疆地区极端降水时空变化特征及对气温变化的响应[J].农业工程学报,2022,38(4):133-142.
[19] 郑金丽,严子奇,李东,等.黄河流域降雨—径流关系时空演变研究[J].水资源与水工程学报,2021,32(4):77-85,92.
[20] 杨大文,李翀,倪广恒,等.分布式水文模型在黄河流域的应用[J].地理学报,2004,59(1):143-154.
[21] 贺振,贺俊平.基于SPOT-VGT的黄河流域植被覆盖时空演变[J].生态环境学报,2012,21(10):1655-1659.
[22] 张金萍,张航.黄河流域降水时空演变规律研究[J].中国农村水利水电,2022,473(3):60-68.
[23] 蔡博峰,于嵘.基于遥感的植被长时序趋势特征研究进展及评价[J].遥感学报,2009,13(6):1170-1186.
[24] Tucker C J, Newcomb W W, Los S O, et al. Mean and inter-year variation of growing-season normalized difference vegetation index for the Sahel 1981—1989[J]. International Journal of Remote Sensing, 1991,12:1133-1135.
[25] Theil H. A rank-invariant method of linear and polynomial regression analysis[J]. Henri Theil'S Contributions to Economics and Econometrics:Econometric Theory and Methodology, 1992:345-381.
[26] Sen P K. Estimates of the regression coefficient based on Kendall's tau[J]. Journal of the American Statistical Association, 1968,63(324):1379-1389.
[27] Stuart M. Understanding robust and exploratory data analysis[J]. the Statistician, 1984,33:320-321.
[28] Toi'/c I. Spatial and temporal variability of winter and summer precipitation over Serbia and Montenegro[J]. Theoretical and Applied Climatology, 2004,77:47-56.
[29] 于延胜,陈兴伟.基于Mann-Kendall法的水文序列趋势成分比重研究[J].自然资源学报,2011,26(9):1585-1591.
[30] 袁丽华,蒋卫国,申文明,等.2000—2010年黄河流域植被覆盖的时空变化[J].生态学报,2013,33(24):7798-7806.
[31] 贾路,于坤霞,邓铭江,等.西北地区降雨集中度时空演变及其影响因素[J].农业工程学报,2021,37(16):80-89.
[32] Xu G C, Zhang J X, Li P, et al. Vegetation restoration projects and their influence on runoff and sediment in China[J]. Ecological Indicators, 2018,95:233-241.
[33] 张会兰,李丹勋,姜晓明,等.基于阶段特性的岷江镇江关以上流域水沙趋势多尺度分析[J].水力发电学报,2013,32(3):127-133.
[34] 罗光坤. Morlet小波变换理论与应用研究及软件实现[D].南京:南京航空航天大学,2007
[35] 邵骏.基于交叉小波变换的水文多尺度相关分析[J].水力发电学报,2013,32(2):22-26,42.
[36] 张洪波,俞奇骏,陈克宇,等.基于小波变换的径流周期与ENSO事件响应关系研究[J].华北水利水电大学学报:自然科学版,2016,37(4):59-66.
[37] 陈亮,段建平,马柱国.大气环流形势客观分型及其与中国降水的联系[J].地球科学进展,2018,33(4):396-403.
Similar References:

Memo

-

Last Update: 2023-08-10

Online：12060       Total Traffic Statistics：27403820

Website Copyright: Research of Soil and Water Conservation Shaanxi ICP No.11014090-10
Tel: 029-87012705　Address: Editorial Department of Research of Soil and Water Conservation, No. 26, Xinong Road, Yangling, Shaanxi　Postcode: 712100