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引用本文:朱燕琴,赵志斌,齐广平,等.基于降水特征的次降水侵蚀力估算模型——以黄土丘陵沟壑区典型小流域为例[J].灌溉排水学报,2023,42(11):98-105.
ZHU Yanqin,ZHAO Zhibin,QI Guangping,et al.基于降水特征的次降水侵蚀力估算模型——以黄土丘陵沟壑区典型小流域为例[J].灌溉排水学报,2023,42(11):98-105.
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基于降水特征的次降水侵蚀力估算模型——以黄土丘陵沟壑区典型小流域为例
朱燕琴,赵志斌,齐广平,赵 霞
1.甘肃农业大学 水利水电工程学院,兰州 730070;2.甘肃省水利厅 水土保持局,兰州 730030
摘要:
【目的】在分析侵蚀性降水特征的基础上,构建基于降水特征的次降水侵蚀力估算模型,研究结果可为区域水土流失定量监测和水土保持效益评价提供参考。【方法】利用甘肃黄土丘陵沟壑区安家沟小流域和龙滩小流域2个典型径流场5 a的侵蚀性降水过程资料,构建雨量(P)×雨强(I)结构与E×I30的转换关系。【结果】大于50 MJ·mm/(hm2·h)的次降水侵蚀力占侵蚀力总量的比例高达75%,是该地区降水侵蚀力的主要贡献来源。降水量P和降水动能E之间呈线性函数关系。降水单因子I30(30 min降水强度)、I60(60 min降水强度)、E(降水动能)对土壤流失量(S)产生显著影响(P<0.01)。降水双因子P×I30、P×I60与S之间的相关系数r > 0.616(P<0.01),P×I30、P×I60是影响坡面土壤流失量S的主要降水复合因子。P×I30、P×I60与E×I30符合幂函数关系,模型方程决定系数R2达到0.984 0、0.960 9。2个模型的有效系数分别为98.9%、98.1%,偏差系数分别为2.0%、3.2%。当10 mm50 MJ·mm/(hm2·h)的次降水侵蚀力预测值相对误差<10%。【结论】模型预测效果良好,指标因子P×I30、P×I60可作为该区域10 mm
关键词:  黄土丘陵沟壑区;安家沟小流域;水土流失;降水侵蚀力;侵蚀性降水
DOI:10.13522/j.cnki.ggps.2022669
分类号:
基金项目:
A Proposed Model for Estimating Individual Rainfall Erosivity Based on Rainfall Characteristics: A Case Study
ZHU Yanqin, ZHAO Zhibin, QI Guangping, ZHAO Xia
1. College of Water Conservancy and Hydropower Engineering, Gansu Agricultural University, Lanzhou 730070, China; 2. Soil and Water Conservation Bureau, Gansu Provincial Water Resources Department, Lanzhou 730030, China
Abstract:
【Objective】Rainfall is the main cause of erosion of loess soil in the arid regions in northwestern China. Understanding the relationship between soil erosion and rainfall characteristics is hence important to ameliorate soil erosion. In this paper, we analyzed individual erosive rainfall and proposed a model to predict rainfall erosivity.【Method】The analysis is based on erosive rainfall data measured in five years from two typical runoff fields, one is a hilly small waterhead located in Anjiagou and the other one is a small gully waterhead in Longtan, both in Gansu province. The relationship between soil erosion structure of rainfall (P) × rain intensity (I) and E×I30 was established.【Result】Rainfall erosivity above 50 MJ·mm/(hm2·h) was the main cause of rainfall erosivity, accounting for 75% of the total erosivity. Rainfall P and rainfall kinetic energy E was linearly correlated in that E=0.205 7P-1.067 1 (R2=0.763,n=48). Rainfall single factors I30 (30-minute rainfall intensity), I60 (60-minute rainfall intensity) and E significantly impacted soil loss (S) (P<0.01). The correlation coefficients (r) between P×I30, P×I60 and S were >0.616 (P<0.01), and P×I30 and P×I60 were hence the main rainfall factors affecting soil loss (S) on the slope. The relationship between P×I30, P×I60 and E×I30 followed power-law functions, with the determination coefficient R2 being 0.984 and 0.9609, respectively. The effective coefficient of the two models was 98.9% and 98.1%, respectively, while the associated deviation coefficient was 2.0% and 3.2%, respectively. The rainfall was 50 mm>P>10 mm. Compared with measurements, the relative error of the predicted results of the two models was less than 16%. The rainfall erosivity was above 50 MJ·mm/(hm2·h), and the relative error of the predicted rainfall erosivity was less than 10%. 【Conclusion】Both models predicted rainfall erosivity well, and P×I30, P×I60 can be used as index factors to estimate individual rainfall erosivity under 50 mm>P>10 mm in the studied regions.
Key words:  loess hilly and gully region; Anjiagou small watershed; water and soil loss; rainfall erosivity; erosive rainfall