基于多源降水融合数据的江苏省降雨侵蚀力时空特征

鞠艳; 杨星; 齐斐; 夏骑兵; 张雯叶

doi:10.13961/j.cnki.stbctb.2025.02.025

您当前的位置：

首页 >

文章列表页 >

基于多源降水融合数据的江苏省降雨侵蚀力时空特征

试验研究

- 基于多源降水融合数据的江苏省降雨侵蚀力时空特征
- Spatiotemporal characteristics of rainfall erosivity based on multi-source precipitation merged data in Jiangsu Province
- 水土保持通报 2025年45卷第2期页码：241-250
- 作者机构：
  
  1. 江苏省水利科学研究院,江苏,南京,210017
  2. 南京市高淳区水务局,江苏,南京,211300
- 作者简介：
- 基金信息：
  
  江苏省水利科技项目“高邮灌区仿真模拟技术研究及应用”(Z2022041);江苏省水利科学研究院自主科研经费专项资金项目“多源降水融合的江苏省降雨侵蚀力及其变化研究”(2023Z046)
- DOI：10.13961/j.cnki.stbctb.2025.02.025
  中图分类号： S157.1
- 网络首发：2025-05-16，
  
  纸质出版：2025
- 稿件说明：
移动端阅览
鞠艳, 杨星, 齐斐, 等. 基于多源降水融合数据的江苏省降雨侵蚀力时空特征[J]. 水土保持通报, 2025,45(2):241-250.

Ju Yan, Yang Xing, Qi Fei, et al. Spatiotemporal characteristics of rainfall erosivity based on multi-source precipitation merged data in Jiangsu Province[J]. Bulletin of Soiland Water Conservation, 2025, 45(2): 241-250.
鞠艳, 杨星, 齐斐, 等. 基于多源降水融合数据的江苏省降雨侵蚀力时空特征[J]. 水土保持通报, 2025,45(2):241-250. DOI： 10.13961/j.cnki.stbctb.2025.02.025.

Ju Yan, Yang Xing, Qi Fei, et al. Spatiotemporal characteristics of rainfall erosivity based on multi-source precipitation merged data in Jiangsu Province[J]. Bulletin of Soiland Water Conservation, 2025, 45(2): 241-250. DOI： 10.13961/j.cnki.stbctb.2025.02.025.

摘要

[目的

]

研究江苏省不同的时间和空间尺度的降雨侵蚀力及其侵蚀密度特征，为区域降雨侵蚀力预测和土壤侵蚀控制的重要参考。[方法

]

基于江苏省96个气象观测站点的降雨数据和GPM IMERG，ERA5降水产品，研发了一种基于站点—卫星降水融合的降雨侵蚀力计算方法，重建了江苏省2001—2023年降雨侵蚀力，并进一步研究其侵蚀密度及易发区划分。[结果

]

①该方法具有一定的可靠性，融合降雨侵蚀力相较于卫星降雨侵蚀力和站点降雨侵蚀力，具有较高的相关系数、较小的偏差和均方根误差，能有效捕捉降雨侵蚀力的高值，减少不确定性和误差。②2001—2023年江苏省多年平均降雨侵蚀力为4 709.39 MJ·mm/(hm

·h·a)，空间分布为北低南高，季节差异明显，夏季多冬季少。③2001—2023年江苏省年降雨侵蚀力呈增加趋势，气候倾向率季节存在差异，春季、夏季和秋季研究区南部呈显著的增加趋势，北部呈不显著的下降趋势，冬季反之。④江苏省年侵蚀密度为4.96 MJ/(hm

·h)，空间分布呈北高南低，降雨侵蚀最易发区为徐州市东部、连云港市北部和镇江市西部、南京市北部零星地区，不易受侵蚀的区域为扬州市和泰州市地区。[结论

]

基于站点—卫星降水融合方法估算区域降雨侵蚀力较为可靠，减少不确定性和误差，提高了卫星遥感反演降水在土壤水蚀领域的应用精度。

Abstract

[Objective] Integrated rainfall erosivity in Jiangsu Province was evaluated at different temporal and spatial scales

and the erosion density characteristics in Jiangsu Province were explored to provide an important reference for regional rainfall erosivity prediction and soil erosion control. [Methods] This study developed a station-satellite merged calculation method for rainfall erosivity based on rainfall data from 96 meteorological stations and precipitation products of GPM IMERG and ERA5. The rainfall erosivity of Jiangsu Province from 2001 to 2023 was reconstructed

and its erosivity density and prone area division were studied . [Results] ① Method reliability was confirmed because the fusion rainfall erosivity had a higher correlation coefficient

lower deviation

and lower root mean square error than did the rainfall erosivity calculated by satellites and stations. This method captures high values of rainfall erosivity and reduces uncertainty and error. ② The mean annual rainfall erosivity in Jiangsu Province from 2001 to 2023 was 4 709.39 MJ·mm/(hm2·h·yr); the spatial distribution was 'low in the north

high in the south’. Seasonal rainfall erosivity showed a pattern of 'more in summer

less in winter’. ③ Annual rainfall erosivity in Jiangsu Province showed an increasing trend from 2001 to 2023. The climate tendency rate showed a significant increasing trend in the south of Jiangsu Province in spring

summer

and autumn

and an insignificant decreasing trend in the north

which was the opposite in winter. ④ The annual erosivity density of Jiangsu Province was 4.96 MJ/(hm2·h)

and the spatial distribution was 'high in the north

low in the south’. The areas most vulnerable to rainfall erosivity were east of Xuzhou

north of Lianyungang

west of Zhenjiang

and the northern part of Nanjing City. The less vulnerable areas were Yangzhou City and Taizhou City. [Conclusion] The estimation of regional rainfall erosivity based on site-satellite precipitation merged data is reliable

reduces uncertainty and error

and improves the accuracy of satellite remote sensing applied in the field of soil erosion.

关键词

Keywords

references

鞠艳,杨星,董阿忠,等.里下河平原区径流模拟及其对极端降水响应分析[J].水文,2024,44(4):82-88. Ju Yan, Yang Xing, Dong Azhong, et al. Runoff simulation and its response to extreme precipitation in the Lixia River plain [J]. Journal of China Hydrology, 2024,44(4):82-88.

宋爽,牛天一,陈长胜,等.吉林省不同量级降雨下的降雨侵蚀力特征[J].水土保持通报,2024,44(4):215-224. Song Shuang, Niu Tianyi, Chen Changsheng, et al. Characteristics of rainfall erosivity under different magnitudes of rainfall in Jilin Province [J]. Bulletin of Soil and Water Conservation, 2024,44(4):215-224.

张悦,张艳,史飞航,等.基于不同模型的黄河中游降雨侵蚀力时空变化分析[J].水土保持通报,2023,43(2):220-229. Zhang Yue, Zhang Yan, Shi Feihang, et al. Temporal and spatial variation of rainfall erosivity in middle reaches of Yellow River based on different models [J]. Bulletin of Soil and Water Conservation, 2023,43(2):220-229.

Yue Tianyu, Xie Yun, Yin Shuiqing, et al. Effect of time resolution of rainfall measurements on the erosivity factor in the USLE in China [J]. International Soil and Water Conservation Research, 2020,8(4):373-382.

邹玉霞,樊国中,刘淑婧,等.1960—2017年重庆市不同量级降雨侵蚀力

值的时空变化特征[J].水土保持学报,2022,36(6):41-48. Zou Yuxia, Fan Guozhong, Liu Shujing, et al. Spatio-temporal variations of rainfall erosivity

values of different magnitudes in Chongqing from 1960 to 2017[J]. Journal of Soil and Water Conservation, 2022,36(6):41-48.

梁宇靖,沈润平,师春香,等.基于CLDAS融合降水的中国降雨侵蚀力研究[J].干旱区地理,2022,45(5):1333-1346. Liang Yujing, Shen Runping, Shi Chunxiang, et al. Rainfall erosivity in China based on CLDAS fusion precipitation [J]. Arid Land Geography, 2022,45(5):1333-1346.

田丹丹,殷水清.雷达测雨及其在土壤侵蚀中的应用研究进展[J].水土保持学报,2019,33(6):1-9. Tian Dandan, Yin Shuiqing. Advances in radar rainfall measurement and its application in soil erosion [J]. Journal of Soil and Water Conservation, 2019,33(6):1-9.

高歌,殷水清,陈涛,等.长江流域降雨侵蚀力时空变化及成因分析[J].农业工程学报,2022,38(3):84-92. Gao Ge, Yin Shuiqing, Chen Tao, et al. Spatiotemporal variation and cause analysis of rainfall erosivity in the Yangtze River basin of China [J]. Transactions of the Chinese Society of Agricultural Engineering, 2022,38(3):84-92.

邢贞相,段维义,刘明阳,等.四种网格化降水产品估算中国大陆区域降雨侵蚀力比较[J].农业工程学报,2023,39(5):100-109. Xing Zhenxiang, Duan Weiyi, Liu Mingyang, et al. Comparison of the four gridded precipitation products for estimating regional rainfall erosivity in Mainland China [J]. Transactions of the Chinese Society of Agricultural Engineering, 2023,39(5):100-109.

熊立华,刘成凯,陈石磊,等.遥感降水资料后处理研究综述[J].水科学进展,2021,32(4):627-637. Xiong Lihua, Liu Chengkai, Chen Shilei, et al. Review of post-processing research for remote-sensing precipitation products [J]. Advances in Water Science, 2021,32(4):627-637.

戴强,刘超楠,张亚茹,等.基于多模式雷达遥感的陆表降雨反演研究进展[J].遥感学报,2023,27(7):1574-1589. Dai Qiang, Liu Chaonan, Zhang Yaru, et al. Development of precipitation retrieval based on multimode radar remote sensing [J]. National Remote Sensing Bulletin, 2023,27(7):1574-1589.

罗梦琦,刘霞,郭红丽,等.江苏省水土流失动态监测降雨侵蚀力因子站点密度优化研究[J].江苏水利,2024(3):7-11. Luo Mengqi, Liu Xia, Guo Hongli, et al. Study on optimization of site density of rainfall erosivity factor for dynamic monitoring of soil erosion in Jiangsu Province [J]. Jiangsu Water Resources, 2024(3):7-11.

余寒,杨凯,闵俊杰,等.近50年江苏省降雨侵蚀力的时空变化[J].江西农业学报,2018,30(10):106-111. Yu Han, Yang Kai, Min Junjie, et al. Spatio-temporal variations of rainfall erosivity in Jiangsu Province in recent 50 years [J]. Acta Agriculturae Jiangxi, 2018,30(10):106-111.

齐斐,张春强,刘霞,等.基于M-K检验和地统计分析的沂蒙山区降雨侵蚀力时空变化趋势研究[J].水土保持通报,2021,41(5):146-153. Qi Fei, Zhang Chunqiang, Liu Xia, et al. Spatiotemporal variation trend analysis of rainfall erosivity in Yimeng Mountain region based on M-K test and geostatistical analysis [J]. Bulletin of Soil and Water Conservation, 2021,41(5):146-153.

梁宇靖.CLDAS-prcp融合降水改进及其在降雨侵蚀力中的应用[D].江苏南京:南京信息工程大学,2023. Liang Yujing. Improvement of CLDAS-prcp fusion precipitation and its application in rainfall erosivity [D]. Nanjing, Jiangsu: Nanjing University of Information Science & Technology, 2023.

李麒崙,张万昌,易路,等.GPM与TRMM降水数据在中国大陆的精度评估与对比[J].水科学进展,2018,29(3):303-313. Li Qilun, Zhang Wanchang, Yi Lu, et al. Accuracy evaluation and comparison of GPM and TRMM precipitation product over China’s Mainland [J]. Advances in Water Science, 2018,29(3):303-313.

Ju Yan, Yang Xing, Wang Dongmei, et al. Spatiotemporal variation of extreme precipitation in the Lixia River basin, China, between 1960 and 2019 under global warming, atmospheric circulation, and local effects [J]. Journal of Hydrologic Engineering, 2023,28(10):05023016.

Li Peixi, Yu Zhongbo, Jiang Peng, et al. Spatiotemporal characteristics of regional extreme precipitation in Yangtze River basin [J]. Journal of Hydrology, 2021,603:126910.

Sobie S R, Murdock T Q. High-resolution statistical downscaling in Southwestern British Columbia [J]. Journal of Applied Meteorology and Climatology, 56(6):1625-1641.

Chao Lijun, Zhang Ke, Li Zhijia, et al. Geographically weighted regression based methods for merging satellite and gauge precipitation [J]. Journal of Hydrology, 2018,558:275-289.

Fenta A A, Tsunekawa A, Haregeweyn N, et al. Improving satellite-based global rainfall erosivity estimates through merging with gauge data [J]. Journal of Hydrology, 2023,620:129555.

Tu Jun, Xia Zongguo. Examining spatially varying relationships between land use and water quality using geographically weighted regression: I. Model design and evaluation [J]. Science of the Total Environment, 2008,407(1):358-378.

殷水清,章文波,谢云,等.基于高密度站网的中国降雨侵蚀力空间分布[J].中国水土保持,2013(10):45-51. Yin Shuiqing, Zhang Wenbo, Xie Yun, et al. Spatial distribution of rainfall erosivity in China based on high-density station network [J]. Soil and Water Conservation in China, 2013(10):45-51.

刘宝元,郭索彦,李智广,等.中国水力侵蚀抽样调查[J].中国水土保持,2013(10):26-34. Liu Baoyuan, Guo Suoyan, Li Zhiguang, et al. Sampling survey of hydraulic erosion in China [J]. Soil and Water Conservation in China, 2013(10):26-34.

鞠艳,张珂,李炳锋,等.金沙江流域实际蒸散发时空分布特征及其影响因子[J].水资源保护,2022,38(6):104-110. Ju Yan, Zhang Ke, Li Bingfeng, et al. Spatiotemporal distribution of actual evapotranspiration and its influencing factors in the Jinsha River basin [J]. Water Resources Protection, 2022,38(6):104-110.

Dabney S M, Yoder D C, Vieira D A N, et al. Enhancing RUSLE to include runoff-driven phenomena [J]. Hydrological Processes, 2011,25(9):1373-1390.

Panagos P, Borrelli P, Poesen J, et al. The new assessment of soil loss by water erosion in Europe [J]. Environmental Science & Policy, 2015,54:438-447.

惠品宏,陈燕,杨杰,等.针对江苏省气温和降水的高分辨率降尺度模拟及预估[J].气象科学,2022,42(4):481-494. Hui Pinhong, Chen Yan, Yang Jie, et al. Dynamical downscaling and projection of surface air temperature and precipitation in Jiangsu Province with high resolution [J]. Journal of the Meteorological Sciences, 2022,42(4):481-494.

张洋,彭瑶,刘竞妍,等.江苏省水土流失重点防治区划分[J].水土保持通报,2014,34(2):300-306. Zhang Yang, Peng Yao, Liu Jingyan, et al. Regiona-lization of key proventing and controlling areas of soil and water loss in Jiangsu Province [J]. Bulletin of Soil and Water Conservation, 2014,34(2):300-306.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

1991—2023年陕西省榆林市降雨侵蚀力时空变化

嘉陵江典型小流域降雨特征对不同土地利用类型产流产沙的影响

黄土高原丘陵沟壑区降雨侵蚀力的时空分布与变化趋势

黄土高原降雨侵蚀力时空分布

三峡库区大宁河流域降雨侵蚀力时空分布特征