1966-2017年贵州省降雨侵蚀力的时空分布特征

阮欧; 刘绥华; 杨广斌; 谢波

doi:10.13961/j.cnki.stbctb.2020.03.006

您当前的位置：

首页 >

文章列表页 >

1966-2017年贵州省降雨侵蚀力的时空分布特征

试验研究

- 1966-2017年贵州省降雨侵蚀力的时空分布特征
- Spatial and Temporal Distribution Characteristics of Rainfall Erosivity in Guizhou Province During 1966-2017
- 水土保持通报 2020年40卷第3期页码：35-42
- 作者机构：
  
  1. 贵州师范大学地理与环境科学学院,贵州,贵阳,550025
  2. 贵州师范大学贵州省山地资源与环境遥感应用重点实验室,贵州,贵阳,550025
- 作者简介：
- 基金信息：
  
  国家自然科学基金项目“喀斯特环境下的地物光谱与典型地物识别研究”（61540072）;贵州省科学技术基金项目（黔科合J字[2014]2127号）
- DOI：10.13961/j.cnki.stbctb.2020.03.006
  中图分类号： S157.1
- 纸质出版：2020
- 稿件说明：
移动端阅览
阮欧, 刘绥华, 杨广斌, 等. 1966-2017年贵州省降雨侵蚀力的时空分布特征[J]. 水土保持通报, 2020,40(3):35-42.

Ruan Ou, Liu Suihua, Yang Guangbin, et al. Spatial and Temporal Distribution Characteristics of Rainfall Erosivity in Guizhou Province During 1966-2017[J]. Bulletin of Soiland Water Conservation, 2020, 40(3): 35-42.
阮欧, 刘绥华, 杨广斌, 等. 1966-2017年贵州省降雨侵蚀力的时空分布特征[J]. 水土保持通报, 2020,40(3):35-42. DOI： 10.13961/j.cnki.stbctb.2020.03.006.

Ruan Ou, Liu Suihua, Yang Guangbin, et al. Spatial and Temporal Distribution Characteristics of Rainfall Erosivity in Guizhou Province During 1966-2017[J]. Bulletin of Soiland Water Conservation, 2020, 40(3): 35-42. DOI： 10.13961/j.cnki.stbctb.2020.03.006.

摘要

[目的] 分析贵州省1966—2017年降雨侵蚀力R值的时空演变规律，为评估该地区降雨对土壤侵蚀的防治、制定水土保持措施及农业生产规划提供参考。[方法] 基于贵州省33个气象站点1966—2017年的日降雨资料，利用克里金插值法、经验正交函数（EOF）方法、Mann-Kendall检验、Morlet小波分析法等，对贵州省52 a的降雨侵蚀力R值的时空特征进行了分析。[结果] ①EOF分析方法可以较好地解释降水侵蚀力的时空分布特征，其前两个特征向量累计贡献率达52%，揭示了贵州省降雨侵蚀力全局型和东西反向型两种典型的分布模态。分析特征向量所对应的时间系数可得，贵州省的降水侵蚀力主要表现为全省全年偏大、全省全年偏小、东大西小、东小西大4种类型；②贵州省降雨侵蚀力R值年内主要受汛期降雨影响，全省各县市汛期降雨侵蚀力R值均占全年总量的60%以上；③在年际变化上，降雨侵蚀力R值存在多突变的现象，1971—1981年突变频率最为频繁。通过周期检验发现其变化主周期为28 a，次周期分别为12 a和6 a。[结论] 贵州省降雨侵蚀力的时空分布与降雨量的时空分布趋势近似，整体呈现南部大北部小，夏季大冬季小的趋势，在未来几年内降雨侵蚀力R值有上升的趋势。

Abstract

[Objective] The spatial and temporal distribution of the rainfall erosivity

represented as R value

in Guizhou Province from 1966 to 2017 was analyzed to provide reference for evaluating the prevention and control of soil erosion due to rainfall. The goal was to formulate soil and water conservation and agricultural production development measures in the study area.[Methods] Based on the daily rainfall data from 33 meteorological stations in Guizhou Province during 1966-2017

Kriging

empirical orthogonal function (EOF)

Mann-Kendall examination

and Morlet wavelet analysis were utilized to analyze the R value characteristics in Guizhou Province over 52 years.[Results] ① EOF analysis well-explained the spatial temporal distribution characteristics of rainfall erosivity. The cumulative contribution rate of the first two eigenvectors reached 52%

revealing two typical distribution modes of rainfall erosivity in Guizhou Province:the whole region pattern and the east-west reverse pattern. According to the analysis of the time coefficient corresponding to the feature vector

the erosive force of rainfall in Guizhou Province was mainly manifested in four ways:the erosive force of rainfall was relatively large during the entire year

it was relatively small during the entire year

it was relatively large in the east and and small in the west

and relatively small in the east and large in the west. ② From the perspective of the entire year

the R value in Guizhou Province was mainly affected by the rainfall in flood season

and the R value in all counties and cities in the province accounted for more than 60% of the entire year. ③ The R value had multiple mutations in its interannual variation. The mutation frequency was the maximum during 1971-1981. Through the cycle test

it was observed that the main cycle of the change was 28 years

and the subcycles were 12 years and 6 years.[Conclusion] The spatial distribution of rainfall and rainfall erosivity was similar in Guizhou Province. Rainfall erosion was generally small in the south and large in the north

and small in summer and large in winter. The rainfall erosivity should increase in the next few years.

关键词

Keywords

references

王万中,焦菊英,郝小品,等.中国降雨侵蚀力

值的计算与分布(Ⅰ)[J].水土保持学报,1995,1(4):7-18.

Wischmeier W H, Smith D D. Predicting rainfall-erosion losses: A guide to conservation planning [M]. USDA: Washington, Agricultuer Handbook 537,1987.

Wischmeier W H, Smith D D. Rainfall energy and its relationship to soil loss [J]. Transactions, American Geophysical Union, 1958,39(2):285.

小高和则,远藤治郎,洪双旌.关于林地内外雨滴侵蚀的研究[J].中国水土保持,1986(4):58-61.

王万中.黄土地区降雨侵蚀力

指标的研究[J].中国水土保持,1987(12):34-38.

贾志军,王小平,李俊义.晋西黄土丘陵沟壑区降雨侵蚀力指标

值的确定[J].中国水土保持,1987(6):18-20.

贾志伟,江忠善,刘志.降雨特征与水土流失关系的研究[J].水土保持研究,1990(2):9-15.

周伏建,黄炎和.福建省天然降雨雨滴特征的研究[J].水土保持学报,1995,9(1):8-12.

吴素业.安徽大别山区降雨侵蚀力简化算法与时空分布规律[J].中国水土保持,1994(4):12-13.

章文波,谢云,刘宝元.利用日雨量计算降雨侵蚀力的方法研究[J].地理科学,2002,22(6):705-711.

章文波,付金生.不同类型雨量资料估算降雨侵蚀力[J].资源科学,2003,25(1):35-41.

伍育鹏,谢云,章文波.国内外降雨侵蚀力简易计算方法的比较[J].水土保持学报,2001,15(3):31-34.

彭琴,林昌虎,何腾兵.贵州喀斯特山区水土流失特征与水土保持研究进展[J].贵州科学,2006,24(3):66-70.

周忠发,安裕伦.贵州省水土流失遥感现状调查及空间变化分析[J].水土保持通报,2000,20(6):23-25.

简虹,骆云中,谢德体.基于Mann-Kendall法和小波分析的降水变化特征研究:以重庆市沙坪坝区为例[J].西南师范大学学报(自然科学版),2011,36(4):217-222.

曹洁萍,迟道才,武立强,等.Mann-Kendall检验方法在降水趋势分析中的应用研究[J].农业科技与装备,2008(5):35-37.

胡昌华.基于MATLAB的系统分析与设计：小波分析[M].西安:西安电子科技大学出版社,1999:210-217.

王文圣,丁晶,李跃清.水文小波分析[M].北京:化学工业出版社,2005.

王万中,焦菊英,郝小品,等.中国降雨侵蚀力

值的计算与分布(Ⅱ)[J].水土保持学报,1996,2(1):29-39.

宁丽丹,石辉.利用日降雨量资料估算西南地区的降雨侵蚀力[J].水土保持研究,2003,10(4):183-186.

戴海伦,苑爽,张科利,等.贵州省降雨侵蚀力时空变化特征研究[J].水土保持研究,2013, 20(1):37-41.

韩会庆,张娇艳,苏志华,等.2011-2050年贵州省极端气候指数时空变化特征[J].水土保持研究,2018,25(2):341-346.

浏览量

1102

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

河北省山区降雨侵蚀力的时空变化特征

坝地土壤养分分布特征研究

典型喀斯特灌丛草坡类型区土壤水变化规律研究

基于地质尺度的贵州省区域水土流失特征分析

汉江流域日降水多种小波分解与重构及其时空分布