|Alternative Title||Study on the relationship between rainfall fluctuation and slope erosion in loess hilly region|
|Thesis Advisor||傅伯杰 ; 高光耀|
|Place of Conferral||北京|
|Keyword||黄土高原,降雨型,降雨强度格局,降雨波动,次降雨侵蚀力 Loess Plateau, Rainfall Regiem, Rainfall Intensity Pattern, Rainfall Fluctuation, Event Rainfall Erosivity|
Rainfall is the key driving factor of soil erosion. Previous studies paid more attention to the effects of general rainfall indexes on soil erosion, such as rainfall amount, duration and intensity etc., but the research on the influence mechanism of rainfall trend change and process characteristics on soil erosion, such as rainfall types, rainfall intensity pattern and rainfall fluctuations etc., is not deep enough. The Loess Plateau is the most serious erosion area in China, and rainfall in this region has significant variation and fluctuant characteristics. Under the background of vegetation restoration and climate change, the influence mechanism of rainfall fluctuation on soil erosion is a scientific problem that needs to be solved urgently in the ecological construction of the Loess Plateau. Therefore, the mechanism and simulation study of the relationship between rainfall fluctuation and slope erosion, on the one hand can be used to deep understand the influence mechanism of rainfall characteristics on soil erosion, and on the other hand can provide scientific basis and method support for the prediction of soil erosion after vegetation restoration in the Loess Plateau, which has important theoretical and practical significance.
This study used runoff plots to observe event runoff and soil loss during 2008-2016 with different types of land cover (e.g., forest, shrub, sub-shrub and grass) and slope lengths in Yangjuangou small catchment, which is a typical and small catchment in loess hilly and gully region. Four studies were carried out in the following: (1) To divided erosive rainfall into three rainfall regimes based on rainfall depth (PD), duration (D) and the maximum 30-min intensity (I30), and then to analyse the response of runoff and soil loss with different land cover and slope lengths to the characteristics of rainfall regime. (2) To determine the rainfall intensity pattern (e.g., early-peak, center-peak and late-peak) based on the position of new division indexes (e.g., I30 and the average fluctuant intensity of rainfall peaks, FIRP) in the rainfall processes, then analysing the response of runoff and soil loss with different land cover to rainfall intensity pattern. (3) To analyse the fluctuation characteristics of peak intensity by the disaggregation of event rainfall processes, and to establish the quantitative indexes of rainfall fluctuation, for studying the quantitative relationships between rainfall fluctuation characteristics and runoff and soil loss. (4) To apply rainfall fluctuation indexes to improve the event rainfall erosivity (Re), and using the modified RUSLE series models to evaluate the prediction effects of soil loss under different land cover, and then to quantitatively investigate the important role of rainfall fluctuation characteristics in the prediction of soil erosion.
The main results are as follows:
(1) Soil erosion effects of different land cover and slope length were influenced by rainfall regime. The runoff coefficient (RC) of rainfall regime 1 was the lowest in forest land, but the RC of rainfall regime 2 and regime 3 were the lowest in shrub land. The highest Soil loss rate (SL) of rainfall regime 1 and regime 3 were found in grass land, but in forest land for rainfall regime 2. RC and SL tended to decrease with the increase of slope length, while SL showed a tendency of increase first and then decrease when rainfall regime 2 happened. The scale effects of slope length variation on soil erosion were also influenced by the interaction of land cover and rainfall regime. It was also showed the tendency of increase first and then decrease in some cases, such as RC of regime 1 and SL of regime 2 and regime 3 in shrub land, and RC and SL of regime 2 in grass land.
(2) The analysis of soil erosion effect of rainfall intensity pattern showed that the change trend of RC was early-peak > late-peak > center-peak, but the change trend of the soil loss coefficient (SLC) was affected by land cover, and it became late-peak > early-peak > center-peak in sub-shrub land and grass land. Soil erosion effect of different land cover and the relationship of runoff-soil loss were also affected by rainfall intensity pattern. For center-peak pattern, the effects of land cover types on RC and SLC were strongest, but the least for early-peak pattern; for late-peak pattern, it had the highest soil loss under the same runoff depth, and the correlation between runoff and soil loss was also strongest.
(3) Rainfall fluctuation characteristics had an important role on slope soil erosion, which was the main controlling factors to affect soil erosion potential. The disaggregation of rainfall processes found that about 78% of the total PD dropped only in less than 27% of total D. The results indicated that the characteristics of rainfall peak zone showed higher correlation with RC and SLC than general rainfall characteristics, especially the index of fluctuant intensity of rainfall peaks (FIRP) displaying the highest correlation coefficient (r=0.77 and 0.65, respectively, p<0.05). RC was controlled by FIRP and the duration of rainfall peak zone (D_p), and the mainly controlling factors of SLC were the average intensity of rainfall peak zone (I_p) and the max-relative fluctuation index of rainfall intensity (RFRI). Compared with the statistical models without considering rainfall fluctuation, statistical models based on rainfall fluctuation indexes could significantly improve the prediction effect of RC and SLC, and the effect was stronger for SLC.
(4) Introducing rainfall fluctuation indexes to calculate event rainfall erosivity (Re) could effectively improve the prediction ability of RUSLE model for soil erosion. The improved Re using RFRI index showed higher explanatory power (63-69%) to the variation of standardized soil loss (SL_std) than that of the initial Re (37%). The RUSLE models improved by considering rainfall fluctuation characteristics could effectively correct the underestimation of the high erosion events and the overestimation of the low erosion events caused by the initial RUSLE model, suggesting that it was the RFRI index that played a key role in improving Re. Moreover, the effectiveness of modified models was influenced by land cover, and they had the best prediction effect of soil loss in shrub land, followed by forest land, and the least in mixed grass land.
|刘见波. 黄土丘陵区降雨波动——坡面土壤侵蚀关系研究[D]. 北京. 中国科学院生态环境研究中心,2018.|
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