周宁, 李超, 琚存勇, 马亚怀. 黑龙江省土壤可蚀性K值特征分析[J]. 农业工程学报, 2015, 31(10): 182-189. DOI: 10.11975/j.issn.1002-6819.2015.10.024
    引用本文: 周宁, 李超, 琚存勇, 马亚怀. 黑龙江省土壤可蚀性K值特征分析[J]. 农业工程学报, 2015, 31(10): 182-189. DOI: 10.11975/j.issn.1002-6819.2015.10.024
    Zhou Ning, Li Chao, Ju Cunyong, Ma Yahuai. Analysis of characteristics of soil erodibility K-value in Heilongjiang province[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2015, 31(10): 182-189. DOI: 10.11975/j.issn.1002-6819.2015.10.024
    Citation: Zhou Ning, Li Chao, Ju Cunyong, Ma Yahuai. Analysis of characteristics of soil erodibility K-value in Heilongjiang province[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2015, 31(10): 182-189. DOI: 10.11975/j.issn.1002-6819.2015.10.024

    黑龙江省土壤可蚀性K值特征分析

    Analysis of characteristics of soil erodibility K-value in Heilongjiang province

    • 摘要: 土壤可蚀性K值是评价土壤对侵蚀敏感程度和进行土壤侵蚀预报的重要参数,是支撑水土保持监测、预报和规划的重要基础。为了建立基于通用土壤流失方程的土壤侵蚀量估算数据库,需要掌握了解K值特征,该文采用对变量数字特征和离散程度的传统统计,以及克里格插值的地统计方法分析黑龙江省土壤普查相关数据和土壤可蚀性K值特征。结果表明:1)主要土类间土壤质地组分含量具有显著差异性,粗粉粒、细粉粒和黏粒含量服从正态分布且块金效应均大于75%,表现出很弱的空间相关性。2)主要土类K值期望,风砂土最大、白浆土最小,变异系数均小于10%,呈弱变异性。3)土壤质地K值期望,砂壤土最大、中黏土最小,总体上随物理性黏粒含量的增大而减小,随物理性砂粒含量减小而减小,除重黏土变异系数为19.99%,呈中等变异性外,其他土壤质地变异系数均小于10%,呈弱变异性。4)随表层厚度的增加,K值期望呈线性显著(R2=0.83)的平缓递减趋势。5)不同土壤侵蚀类型区域的K值及其分布特征差异较大,类型相同而强度不同的土壤侵蚀区域K值及其分布具有相似的分布规律。6)K值块金效应为73.30%,具有中等的空间相关性,自西向东呈平缓的线性递减分布趋势,由北至南呈上开广口抛物线状分布趋势,其极大值区与风砂土主要分布区,2个极小值区与白浆土、黑土主要分布区,具有空间一致性,此外,水土保持区划中分区的功能定位体现了K值的分布特征。该研究可为黑土资源的保护与修复提供科学依据,对黑土地能够继续、持续地保障粮食生产安全具有积极意义。

       

      Abstract: As the largest distribution area of black soil in China, Heilongjiang Province is undertaking important responsibility of food safety for country. However, due to lack of protection, it has become one of those regions undergoing the most serious soil erosion and is gradually losing its basic role of important agricultural production. Soil erodibility index (K-value) is not only an important parameter for evaluating soil's sensitivity to erosion and forcasting soil erosion process but also a key foundation for monitoring and planning of soil and water conservation. In this paper, in terms of soil census data, the characteristics of K-value were analyzed by traditional statistical and geostatistical methods. Results showed that: 1) The soil texture presented significant difference among main soil types; the contents of coarse silt, fine powder and clay obeyed normal distribution, and their spatial correlations were weak. 2) The average K-value of aeolian sandy soils was the largest (0.0281), that of albic soils was the smallest(0.0234), and all K-value of main soil types had weak variability. 3)The average K-value of sandy loam was the largest(0.0281)while moderate clay had the smallest K-value(0.0201). Generally, the average K-value reduced with the increasing physical clay content as well as the decreasing physical sand content, and all soil textures had weak variability but for heavy clay having moderate variability The difference of soil texture either in same soil type or among different soil types was effected by their components content, and this difference was also reflected in K-value. 4) There was a significant linear relationship (R2=0.83) between the average K-value and soil surface thickness and furthermore, the K-value would gently descend when the thickness increased. In other words, the thinner top soil resulted from soil and water loss can cause the increasing K-value and amplify the probability of soil erosion. Thus, the top soil would become thinner and thinner and even disappear. 5) The K-value's distribution characteristics of the areas with various soil erosion types showed obvious difference, however, those regions belonging to same soil erosion type had similar distributions although they were in different soil erosion intensity levels. In water erosion region, the distribution area of different K-values showed an increasing trend in the section from 0.0220 to 0.0241, and got the largest area in the interval from 0.0241 to 0.0245 while a decreasing trend occurred in the zone from 0.0245 to 0.0276. Generally, the distribution area of K-value increased with the increasing of K-value in wind erosion region. The K-value of freezing-thawing erosion region converged in the zone from 0.0258 to 0.0268, and the K-value of engineering erosion region was centered in the zone from 0.0229 to 0.0245. 6) The K-value had a moderate spatial correlation, and showed a gentle linear downward trend from the west to the east, as a distribution of concave parabolic shape occurred in north-south direction. In addition, the maximum K-value mostly appeared in the area of aeolian sandy soil, and the two minimum K-value areas were almost related to the areas of black soils and albic soils, respectively. We also found the distribution features of K-value coincided with the soil and water conservation regionalization well. The K-value grid database produced in this paper would provide basic parameters for soil erosion monitoring and prediction, and controlling of soil and water loss, especially provide scientific basis for the protection and restoration of black soil resources, and impose a positive effect on sustainable grain production safety in the black land. It was necessary to note that the data used in this work were a little old and their soil profile samples were not collected randomly, and thus this shortage of the data may make our results less reliable. Besides, since we lacked newer data, we didn't further analyze relevant spatial and temporal dynamic changes of K-value.

       

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