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黄土丘陵区降雨波动——坡面土壤侵蚀关系研究
Alternative TitleStudy on the relationship between rainfall fluctuation and slope erosion in loess hilly region
刘见波
Subtype博士
Thesis Advisor傅伯杰 ; 高光耀
2018-06
Degree Grantor中国科学院生态环境研究中心
Place of Conferral北京
Degree Name理学博士
Degree Discipline生态学
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
Abstract

      降雨是土壤侵蚀的关键驱动因子,以往研究更多关注降雨量、降雨历时和降雨强度等常规指标对土壤侵蚀的影响,而对降雨类型、降雨强度格局、降雨波动等降雨趋势变化和过程特征对土壤侵蚀的影响机理研究不够深入。黄土高原是我国土壤侵蚀最严重的区域,且降雨具有明显的变异和波动特征,植被恢复和气候变化背景下降雨波动对土壤侵蚀的影响机理是黄土高原生态建设亟需解决的科学问题。因此,开展降雨波动—坡面土壤侵蚀关系的机理和模拟研究,一方面可深入理解降雨特征对土壤侵蚀的影响机理,也可为黄土高原植被恢复后土壤侵蚀预测提供科学依据和方法支撑,具有重要的理论和实践意义。

      本研究选择黄土丘陵沟壑区的典型小流域—羊圈沟小流域,于2008-2016年对不同土地覆盖类型(林地、灌木、半灌木、草地)和坡长径流小区的次降雨径流和土壤流失进行观测,开展了以下4个方面的工作。(1)根据降雨量(PD)、降雨历时(D)和最大30 min雨强(I30)将侵蚀性降雨划分为三种降雨型,分析不同土地覆盖和坡长下径流和土壤流失对降雨型特征的响应。(2)根据新的格局划分指标(I30和峰值平均波动强度,FIRP)在降雨过程中的出现位置,确定次降雨相应的降雨强度格局(前峰型、中峰型和后峰型),分析不同土地覆盖下径流和土壤流失对降雨强度格局的响应。(3)对次降雨过程进行再分解,分析峰值强度的波动特征,建立表征降雨波动的量化指标,研究降雨波动特征与径流和土壤流失的定量关系。(4)应用降雨波动指数改进次降雨侵蚀力因子(Re),利用修正后的RUSLE系列模型评估不同土地覆盖下土壤流失的预测效果,定量分析降雨波动特征在土壤侵蚀预报中的重要作用。

      主要研究结果如下:

    (1)不同土地覆盖和坡长的土壤侵蚀效应受到降雨型的影响。雨型1的径流系数(RC)在林地下最低,而雨型2和雨型3的RC在灌木地下最低;雨型1和雨型3的土壤流失速率(SL)在草地下最高,而雨型2的SL在林地下最高。RC和SL随坡长增加总体呈降低趋势,而雨型2的SL呈先增后减趋势。随坡长变化的尺度效应还受土地覆盖和降雨型的交互影响,其中灌木地下雨型1的RC、雨型2和雨型3的SL,以及草地下雨型2的RC和SL均呈先增后减的趋势。

    (2)降雨强度格局的土壤侵蚀效应分析表明,RC的变化趋势为前峰型>后峰型>中峰型,而土壤流失系数(SLC)的变化趋势受土地覆盖的影响,在半灌木和草地下变为后峰型>前峰型>中峰型。不同土地覆盖的土壤侵蚀效应和径流-侵蚀关系也受到降雨强度格局的影响。中峰型格局下,RC和SLC受土地覆盖类型的影响最大,前峰型格局下最小;后峰型格局下,相同径流深时土壤流失速率最高,径流—侵蚀相关性最强。

    (3)降雨波动特征对坡面土壤侵蚀具有重要作用,是影响土壤侵蚀潜力的主要控制因子。降雨过程的再分解发现78%的降雨量发生在27%的降雨历时内,峰值区的降雨特征与RC和SLC的相关性高于常规的降雨特征,其中降雨峰值平均波动强度(FIRP)与RC和SLC具有最高的相关系数(r=0.77和0.80,p<0.05)。RC的主控因子为FIRP和峰值区降雨历时(D_p),而SLC的主控因子为峰值区平均雨强(I_p)和降雨强度最大相对波动指数(RFRI)。与不考虑降雨波动的统计模型相比,基于降雨波动指数的统计模型能够显著提高RC和SLC的预测效果,并且对SLC的效果更明显。

    (4)引入降雨波动特征指数计算次降雨侵蚀力因子(Re)能够有效提高RUSLE模型对土壤侵蚀的预测能力。引入RFRI指数改进后的Re对标准土壤流失速率(SL_std)变异的解释率(63-69%)远高于原始Re(37%)。考虑降雨波动特征的改进RUSLE模型能有效改进传统RUSLE模型对高侵蚀事件的低估和低侵蚀事件的高估现象,说明RFRI因子对改进Re起到关键作用。改进模型的有效性受到土地覆盖的影响,灌木地下效果最高,其次是林地,混合草地下最差。

Other Abstract

      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.

Pages120
Language中文
Document Type学位论文
Identifierhttp://ir.rcees.ac.cn/handle/311016/41488
Collection城市与区域生态国家重点实验室
Recommended Citation
GB/T 7714
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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