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| DOI：10.13522/j.cnki.ggps.2022669 |
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| A Proposed Model for Estimating Individual Rainfall Erosivity Based on Rainfall Characteristics: A Case Study |
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ZHU Yanqin, ZHAO Zhibin, QI Guangping, ZHAO Xia
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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
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| 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 |
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