土壤持水特性参数与土壤质地尺度关系的联合多重分形分析

Soil water-retention characteristics at measurement scales are generally different from those at application scales, and there is scale disparity between them and soil physical properties. The relationships between two water-retention parameters, the scaling parameter related to the inverse of the air-entry pressure (αvG, cm-1) and the curve shape factor related to soil pore-size distribution (n) of the van Genuchten water-retention equation, and soil texture (sand, silt, and clay contents) were examined at multiple scales. One hundred twenty-eight undisturbed soil samples were collected from a 640-m transect located in Fuxin, China. Soil water-retention curves were measured and the van Genuchten parameters were obtained by curve fitting. The relationships between the two parameters and soil texture at the observed scale and at multiple scales were evaluated using Pearson correlation and joint multifractal analyses, respectively. The results of Pearson correlation analysis showed that the parameter αvG was significantly correlated with sand, silt, and clay contents at the observed scale. Joint multifractal analyses, however, indicated that the parameter αvG was not correlated with silt and sand contents at multiple scales. The parameter n was positively correlated with clay content at multiple scales. Sand content was significantly correlated with the parameter n at the observed scale but not at multiple scales. Clay contents were strongly correlated to both water-retention parameters because clay content was relatively low in the soil studied, indicating that water retention was dominated by clay content in the field of this study at all scales. These suggested that multiple-scale analyses were necessary to fully grasp the spatial variability of soil water-retention characteristics.     

内蒙古草原碳、氮储量:气候与土壤质地的关系

Understanding the spatial variability of soil carbon(C) storage and its relationship with climate and soil texture is critical for developing regional C models and for predicting the potential impact of climate change on soil C storage. On the basis of soil data from a transect across the Inner Mongolian grasslands, we determined the quantitative relationships of C and nitrogen(N) in bulk soil and particle-size fractions(sand, silt, and clay) with climate and soil texture to evaluate the major factors controlling soil C and N storage and to predict the effect of climate changes on soil C and N storage. The contents of C and N in the bulk soil and the different fractions in the 0–20 and 20–40 cm soil layers were positively correlated with the mean annual precipitation(MAP) and negatively correlated with the mean annual temperature(MAT). The responses of C storage in the soil and particle-size fractions to MAP and MAT were more sensitive in the 0–20 cm than in the 20–40 cm soil layer. Although MAP and MAT were both important factors influencing soil C storage, the models that include only MAP could well explain the variation in soil C storage in the Inner Mongolian grasslands. Because of the high correlation between MAP and MAT in the region, the models including MAT did not significantly enhance the model precision. Moreover, the contribution of the fine fraction(silt and clay) to the variation in soil C storage was rather small because of the very low fine fraction content in the Inner Mongolian grasslands.     

Soil texture prediction through stratification of a regional soil spectral library

Knowing the spatial distribution of soil texture,which is a physical property,is essential to support agricultural and environmental decision making.Soil texture can be estimated using visible,near infrared,and shortwave infrared(Vis-NIR-SWIR)spectroscopy.However,the performance of spectroscopic models is variable because of soil heterogeneity.Currently,few studies address the effects of soil sample variability on the performance of the models,especially for larger spectral libraries that include soils that are more heterogeneous.Therefore,the objectives of this study were to:i)apply Vis-based color parameters on the stratification of a regional soil spectral library;ii)evaluate the performance of the predictive models generated from the spectral library stratification;iii)compare the performance of stratified models(SMs)and the model without stratification(WSM),and iv)explain possible changes in prediction accuracy based on the SMs.Thus,a regional soil spectral library with 1535 samples from the State of Santa Catarina,Brazil was used.Soil reflectance data were obtained by Vis-NIR-SWIR spectroscopy in the laboratory using a spectroradiometer covering the 350–2500 nm spectral range.Sand,silt,and clay fractions were determined using the pipette method.Twenty-two components of color parameters were derived from the Vis spectrum using the colorimetric models.A cubist regression algorithm was used to assess the accuracy of the applicability of the initial models(SMs and WSM)and of the validation between the clusters.Fractional order derivatives(FODs)at 0.5,1.5,and 2 intervals were used to explain possible changes in the performance of the SMs.The SMs with higher contents of clay and iron oxides obtained the highest accuracy,and the most important spectral bands were identified,mainly in the 480–550 and 850–900 nm ranges and the 1400,1900,and 2200 nm bands.Therefore,stratification of soil spectral libraries is a good strategy to improve regional assessments of soil resources,reducing prediction errors in the qualitative determination of soil properties.     

美国新墨西哥州卡皮林火山土壤性质的空间变异性

Non-agricultural lands are surveyed sparsely in general. Meanwhile, soils in these areas usually exhibit strong spatial variability which requires more samples for producing acceptable estimates. Capulin Volcano National Monument, as a typical sparsely-surveyed area, was chosen to assess spatial variability of a variety of soil properties, and furthermore, to investigate its implications for sampling design. One hundred and forty one composited soil samples were collected across the Monument and the surrounding areas. Soil properties including pH, organic matter content, extractable elements such as calcium (Ca), magnesium (Mg), potassium (K), sodium (Na), phosphorus (P), sulfur (S), zinc (Zn), and copper (Cu), as well as sand, silt, and clay percentages were analyzed for each sample. Semivariograms of all properties were constructed, standardized, and compared to estimate the spatial variability of the soil properties in the area. Based on the similarity among standardized semivariograms, we found that the semivariograms could be generalized for physical and chemical properties, respectively. The generalized semivariogram for physical properties had a much greater sill value (2.635) and effective range (7 500 m) than that for chemical properties. Optimal sampling density (OSD), which is derived from the generalized semivariogram and defines the relationship between sampling density and expected error percentage, was proposed to represent, interpret, and compare soil spatial variability and to provide guidance for sample scheme design. OSDs showed that chemical properties exhibit a stronger local spatial variability than soil texture parameters, implying more samples or analysis are required to achieve a similar level of precision.     

湿润速率和粘粒含量对红壤沟间侵蚀的影响

An aggregate stability test and a simulated rainfall test were conducted on four representative Ultisols from southeastern China. The soils selected, with clay contents ranging between 117 and 580 g kg-1 , were derived from shale and Quaternary red clay. The stability of aggregates (2–5 mm in diameter) obtained from the soil samples were determined by the Le Bissonnais method. For determination of infiltration, runoff, and erosion, the soil samples were packed in 30 cm × 60 cm trays, wetted at rates of 2, 10, and 60 mm h-1 , and then exposed to simulated rainfall at 60 mm h-1 for 1 h. The results indicated that both aggregate stability and slaking caused by fast wetting increased with increasing clay content. The effect of wetting rate (WR) on infiltration and seal formation varied with clay contents. In the soil with low clay content (sandy loam), the infiltration rate was affected slightly by WR due to low aggregate stability and slaking. In the soils with medium clay content (silt clay loam and clay), WR affected infiltration significantly due to the high aggregate slaking force. In the soil with high clay content, the effect of WR on infiltration was significant, but not as evident as in the soils with medium clay content, which may be related to high aggregate stability by wetting partially compensating for slaking force. The effect of WR on soil loss was similar to that of runoff, but more pronounced. The findings from this study indicated that the relationship between wetting rate and clay content should be considered when predicting interrill erosion in Ultisols.     

植被覆盖和雨强对附着在沉积物上的养分流失, 泥沙颗粒组成及体积分形维数的影响

Vegetation and rainfall are two important factors affecting soil erosion and thus resulting in nutrient loss in the Chinese Loess Plateau.A field experiment was conducted to investigate the effects of rainfall intensities(60,100 and 140 mm h-1) and vegetation(Caragana korshinskii) coverages(0%,30% and 80%) on soil loss,nutrient loss,and the composition and volume fractal dimension of eroded sediment particles under simulated rainfall conditions.The results showed that vegetation cover,rainfall intensity and their interaction all had significant effects on sediment transport and the sedimentbound nutrient loss.Higher rainfall intensity and lower coverage led to higher sediment and nutrient losses.Positive linear relationships were observed between soil loss and nutrient loss.The treatments showed more significant effects on the enrichment ratio(ER) of nitrogen(ERN) than organic matter(EROM) and phosphorus(ERP).Compared with the original surface soil,the eroded sediment contained more fine particles.Under the same coverage,the clay content significantly decreased with increasing rainfall intensity.The ER of sediment-bound nutrients was positively correlated with that of clay,suggesting that the clay fraction was preferentially eroded and soil nutrients were mainly adsorbed onto or contained within this fraction.There were increments in the fractal dimension of the sediment particles compared to that of the original surface soil.Moreover,the fractal dimension was positively correlated with clay,silt,and sediment-bound OM,N,and P contents,whereas it was negatively correlated with sand content.This study demonstrated that fractal dimension analysis can be used to characterize differences in particle-size distribution and nutrient loss associated with soil erosion.     

结合多等级代表性采样和模糊隶属度的区域土壤制图方法

High-resolution and detailed regional soil spatial distribution information is increasingly needed for ecological modeling and land resource management. For areas with no point data, regional soil mapping includes two steps: soil sampling and soil mapping. Because sampling over a large area is costly, efficient sampling strategies are required. A multi-grade representative sampling strategy, which designs a small number of representative samples with different representative grades to depict soil spatial variations at different scales,could be a potentially efficient sampling strategy for regional soil mapping. Additionally, a suitable soil mapping approach is needed to map regional soil variations based on a small number of samples. In this study, the multi-grade representative sampling strategy was applied and a fuzzy membership-weighted soil mapping approach was developed to map soil sand percentage and soil organic carbon(SOC) at 0–20 and 20–40 cm depths in a study area of 5 900 km2 in Anhui Province of China. First, geographical sub-areas were delineated using a parent lithology data layer. Next, fuzzy c-means clustering was applied to two climate and four terrain variables in each stratum. The clustering results(environmental cluster chains) were used to locate representative samples. Evaluations based on an independent validation sample set showed that the addition of samples with lower representativeness generally led to a decrease of root mean square error(RMSE). The declining rates of RMSE with the addition of samples slowed down for 20–40 cm depth, but fluctuated for 0–20 cm depth. The predicted SOC maps based on the representative samples exhibited higher accuracy, especially for soil depth 20–40 cm, as compared to those based on legacy soil data. Multi-grade representative sampling could be an effective sampling strategy at a regional scale. This sampling strategy, combined with the fuzzy membership-based mapping approach, could be an optional effective framework for regional soil property mapping. A more detailed and accurate soil parent material map and the addition of environmental variables representing human activities would improve mapping accuracy.     

Estimating soil ammonium adsorption using pedotransfer functions in an irrigation district of the North China Plain

Extensive use of chemical fertilizers in agriculture can induce high concentration of ammonium nitrogen(NH4⁺_-N) in soil. Desorption and leaching of NH4⁺_-N has led to pollution of natural waters. The adsorption of NH4⁺_-N in soil plays an important role in the fate of the NH4⁺_-N. Understanding the adsorption characteristics of NH4⁺_-N is necessary to ascertain and predict its fate in the soil-water environment, and pedotransfer functions(PTFs) could be a convenient method for quantification of the adsorption parameters. Ammonium nitrogen adsorption capacity, isotherms, and their influencing factors were investigated for various soils in an irrigation district of the North China Plain. Fourteen agricultural soils with three types of texture(silt, silty loam, and sandy loam) were collected from topsoil to perform batch experiments. Silt and silty loam soils had higher NH4⁺_-N adsorption capacity than sandy loam soils.Clay and silt contents significantly affected the adsorption capacity of NH4⁺_-N in the different soils. The adsorption isotherms of NH4⁺_-N in the 14 soils fit well using the Freundlich, Langmuir, and Temkin models. The models’ adsorption parameters were significantly related to soil properties including clay,silt, and organic carbon contents and Fe²⁺ and Fe³⁺ ion concentrations in the groundwater. The PTFs that relate soil and groundwater properties to soil NH4⁺_-N adsorption isotherms were derived using multiple regressions where the coefficients were predicted using the Bayesian method. The PTFs of the three adsorption isotherm models were successfully verified and could be useful tools to help predict NH4⁺_-N adsorption at a regional scale in irrigation districts.     

非无菌覆土对药用菌生长的影响

Ten different casing soils were collected from two soils at two depths (0.2 and 2.0 m below soil surface) to examine the relationships between the physical properties of non-axenic casing soil and yield,number and weight of the medicinal mushroom Agaricus blazei ss.Heinemann.The results showed that soil clay content and bulk density were negatively correlated with the mushroom yield,respectively,but soil silt content and water-holding capacity were found to be positively correlated with the yield.The number of mushrooms was negatively correlated with soil water-holding capacity but positively correlated with soil clay,bulk density and porosity.The weight of mushroom was positively correlated with the content of soil fine sand and negatively correlated with the contents of soil coarse sand,total sand and clay.Neither soil depth nor different soil combinations affected the yield and number of mushrooms,but the mushroom weight was affected by the soil combinations and soil depth,so interplay in the fructification process with the physical characteristics of casing is complicated.     

土壤矿物吸附和土壤团聚体对土壤有机碳含量的影响研究

Soil organic carbon (SOC) can act as a sink or source of atmospheric carbon dioxide; therefore, it is important to understand the amount and composition of SOC in terrestrial ecosystems, the spatial variation in SOC, and the underlying mechanisms that stabilize SOC. In this study, density fractionation and acid hydrolysis were used to assess the spatial variation in SOC, the heavy fraction of organic carbon (HFOC), and the resistant organic carbon (ROC) in soils of the southern Hulunbeier region, northeastern China, and to identify the major factors that contribute to this variation. The results showed that as the contents of clay and silt particles (0--50 μm) increased, both methylene blue (MB) adsorption by soil minerals and microaggregate contents increased in the 0--20 and 20--40 cm soil layers (P < 0.05). Although varying with vegetation types, SOC, HFOC, and ROC contents increased significantly with the content of clay and silt particles, MB adsorption by soil minerals, and microaggregate content (P < 0.05), suggesting that soil texture, the MB adsorption by soil minerals and microaggregate abundance might be important factors influencing the spatial heterogeneity of carbon contents in soils of the southern Hulunbeier region.     

平原区土壤质地的反射光谱预测与地统计制图

基于地统计方法的土壤属性制图通常需要大量的采样与实验室测定。本研究提出利用可见光近红外(visible-nearinfrared spectroscopy,VNIR)光谱技术测定替代实验室测定,并与地统计方法相结合预测土壤质地的空间变异。通过建立砂粒(0.02 mm),粉粒(0.002~0.02 mm),黏粒(0.002 mm)含量的VNIR光谱预测模型,将模型预测得到的质地数据和建模点实测质地数据一同用于地统计分析和Kriging插值制图。以江苏北部黄淮平原地区为案例的研究结果表明,砂粒、粉粒、黏粒含量的预测值和实测值的均方根误差(RMSE)分别为8.67%、6.90%3、.51%,平均绝对误差(MAE)分别为6.46%、5.60%、3.05%,显示了较高的预测精度。研究为快速获取平原区土壤质地空间分布提供了新的可能的途径。     

紫色土流失土壤的颗粒特征及影响因素

土壤可蚀性是影响坡面水蚀过程的内在因素,与土壤质地,土壤有机质等理化性质密切相关.本研究利用田间人工模拟降雨观测资料,分析了侵蚀过程中流失土壤颗粒组成的变化.结果表明:(1)在次降雨过程中,流失土壤颗粒组成不断变化.随着降雨的进行,细砂含量逐步增加,而粉粒含量基本不变,黏粒含量逐渐减小;(2)雨强是影响流失土壤颗粒组成的重要因素.随雨强增加,细砂含量呈逐步增大的趋势,而粉粒与黏粒含量均逐步下降;(3)坡度对流失土壤颗粒组成影响比较复杂.随坡度增加,细砂含量先增大后减小,粉粒与黏粒含量先减小后增大;在20°坡度时,细砂含量最大,粉粒与黏粒含量最小.     

基于高时间分辨率农田土壤湿度观测的绿洲农业区土壤质地制图

Due to the almost homogeneous topography in low relief areas, it is usually difficult to make accurate predictions of soil properties using topographic covariates. In this study, we examined how time series of field soil moisture observations can be used to estimate soil texture in an oasis agricultural area with low relief in the semi-arid region of northwest China. Time series of field-observed soil moisture variations were recorded for 132 h beginning at the end of an irrigation event during which the surface soil was saturated. Spatial correlation between two time-adjacent soil moisture conditions was used to select the factors for fuzzy c-means clustering. In each of the ten generated clusters, soil texture of the soil sample with the maximum fuzzy membership value was taken as the cluster centroid. Finally, a linearly weighted average was used to predict soil texture from the centroids. The results showed that soil moisture increased with the increase of clay and silt contents, but decreased with the increase of sand content. The spatial patterns of soil moisture changed during the entire drying phase. We assumed that these changes were mainly caused by spatial heterogeneity of soil texture. A total of 64 independent samples were used to evaluate the prediction accuracy. The root mean square error (RMSE) values of clay, silt and sand were 1.63, 2.81 and 3.71, respectively. The mean relative error (RE) values were 9.57% for clay, 3.77% for silt and 12.83% for sand. It could be concluded that the method used in this study was effective for soil texture mapping in the low-relief oasis agricultural area and could be applicable in other similar irrigation agricultural areas used in this study.     

鄱阳湖沙山地区沙化土地特征及成因分析

鄱阳湖沙山地区土地沙化属于南方荒漠化的一种典型类型,是在湖滨沙质阶地的基础上形成的,它既有别于北方的土地沙漠化,又区别于南方其它类型的荒漠化.基于野外调查的基础上对该地区土地沙化特征进行描述,同时从历史背景、当代气候特征以及鄱阳湖水位变化等几个方面对沙化的成因进行了分析.分析结果表明:(1)目前该地区土地沙化趋于变好态势;(2)历史上的海平面变化及气候特征成为鄱阳湖沙山形成的主要因素,而沙山又为该地区当代土地沙化提供了丰富的物质来源.(3)当代气候特征下,流水及固定风向的长期侵蚀为土地沙化提供了动力因素,而鄱阳湖水位的周期性变化,为土地沙化的物质循环提供了有利的环境.总的来说,鄱阳湖沙山地区的土地沙化是在历史地质地貌变迁、当代气候条件、湖泊变化以及人为活动等因素的共同作用下形成的独具特色的亚热带土地荒漠化.     

沂蒙山区桃园棕壤斥水性对理化性质的空间响应

以沂蒙山区典型土地利用桃园棕壤为例,在分析降雨前后桃园棕壤斥水性与理化性质空间变异的基础上,探讨了棕壤斥水性对土壤含水量、有机质含量和土壤质地的空间响应特征。按照1 m×1 m网格等间距测定降雨前后土壤实际斥水性与含水量,同时采集表层0~3 cm土壤样品,分析其有机质含量与砂粒、粉粒、黏粒含量,并借助经典统计学、地统计学与空间自相关理论对土壤斥水性及理化性质进行空间格局与空间相关性分析。结果表明:沂蒙山区桃园棕壤的斥水程度强烈,雨后斥水性显著降低;降雨前后棕壤斥水性均具有中等变异水平和较强的空间自相关性,且呈指数模型分布,各向异性显著。受结构变异和随机变异作用,斥水性空间格局沿耕作方向呈条带状分布,在其垂直方向上最小变程为1.4 m。土壤质地是影响棕壤斥水性空间变异的主要因素,斥水性与粉粒含量呈空间正相关,与砂粒和黏粒含量呈空间负相关,相关程度粉粒砂粒黏粒;棕壤斥水性与含水量呈空间负相关,相关度雨前较弱,雨后显著。     

王茂沟流域淤地坝系土壤颗粒与有机碳分布特征研究

为了研究黄土高原丘陵沟壑区坝系坝地土壤颗粒与有机碳的分布特征,以陕北绥德县王茂沟小流域为研究对象,选取了47个土壤剖面,采集土样940个,分析了分形维数、粗化度、有机碳与各粒径组成之间的关系。结果表明:（1）研究区坝地的土壤粒径分布中,粉粒含量占主导地位,依次为砂粒、黏粒;（2）王茂沟坝地土壤颗粒的分形维数在2.674~2.829之内变化,垂直剖面上变化很微小,坝前、坝中、坝后土壤颗粒分形维数分别为2.803 3,2.783 6,2.795 8;（3）王茂沟坝地土壤质地粗化度在0.27~0.58,平均值为0.44,坝前（0.40） < 坝后（0.45） < 坝中（0.46）;（4）坝地土壤颗粒在0.05~0.002 mm和 < 0.002 mm范围内与土壤颗粒的分形维数成极显著正相关,在2.0~0.05 mm范围内与土壤颗粒的分形维数成极显著负相关;坝地土壤有机碳与粉粒和黏粒呈正相关,与细砂粒和极细沙粒含量呈负相关。     

土壤及泥沙颗粒组成与养分流失的研究

利用自然降雨影响下的农田为试验样地,分析了降雨前后土壤颗粒组成与养分含量的变化,探讨了流失泥沙颗粒组成与养分的变化特征。结果表明,在降雨后,西瓜地与油菜地表土颗粒组成呈现粘粒与粉粒含量减少,砂粒含量相对增加的趋势;土壤养分含量都有不同程度的下降,其中水解氮与速效磷下降的幅度很大,西瓜地与油菜地水解氮降雨后降幅分别为9.67%和7.99%,速效磷的降幅分别为9.20%和8.76%;全氮养分降幅很小,西瓜地与油菜地分别为2.17%和1.54%;流失泥沙细小颗粒含量与养分含量随时间基本都呈降低的变化趋势,并且细小颗粒含量与携带流失的养分含量有显著甚至极显著的正相关性;流失泥沙具有富集粘粒和富集养分的特性,油菜地与西瓜地粘粒富集率分别为1.23和1.20,两样地全氮与速效磷的富集率都在1.3以上,而全磷和水解氮富集率基本处在1.1-1.3之间。     

雨强对华北土石山区坡面侵蚀及其颗粒富集过程的影响

为研究雨强对华北土石山区坡面侵蚀过程和泥沙颗粒分布规律的影响,采用室内人工模拟降雨试验,以华北土石山区2种典型土壤为研究对象,在4种雨强(30,60,90,120mm/h)条件下,分析了径流的变化过程和侵蚀泥沙的颗粒组成及其颗粒富集率的变化规律。结果表明:(1)随着雨强从30mm/h增大至120mm/h,黄土性褐土和石灰性褐土的产流时间均逐渐减小,分别缩短了79%和85%;(2)在60,90,120mm/h雨强条件下,黄土性褐土的径流强度和泥沙浓度均随降雨时间先减小后增大,而后趋于稳定状态,石灰性褐土仅在120mm/h雨强条件下出现相似规律;(3)当雨强从30mm/h增大至120mm/h,黄土性褐土泥沙流失朝粗颗粒化发展,侵蚀泥沙的砂粒和粗粉粒含量分别增加了86%和21%,而石灰性褐土的变化不明显;(4)在降雨初始阶段,粒径较小的黏粒和细粉粒明显富集,而粒径较大的粗粉粒和砂粒不易流失,但随着降雨历时的延长,不同粒径泥沙颗粒的富集率趋于1,这种现象在大雨强下表现得尤为明显。     

沙柳沙障对沙丘土壤颗粒粒径及分形维数的影响

统计分析了库布齐沙漠流动沙丘、设置沙柳活沙障和死沙障沙丘的土壤颗粒粒径分布、分形维数及其与土壤砂粒(>0.05 mm)、粉粒(0.05~0.002 mm)和黏粒(<0.002 mm)含量的关系。结果表明:与流动沙丘相比,设置沙障沙丘的粉粒和黏粒含量增加,且随着土层的加深而表现为下降趋势,不同部位则均呈沙丘下部>上部>中部的趋势。土壤颗粒分形维数因设置沙障而呈增大趋势,且表现为活沙障沙丘>死沙障沙丘>流动沙丘;垂直分布上,设置沙障沙丘的土壤分形维数随土层加深而逐渐减小,而流动沙丘表现为表层与下层大而中层小的特征,沙丘不同部位的分形维数则均表现为沙丘下部>上部>中部。土壤颗粒分形维数大小与土壤质地的细粒化有一致的变化趋势,且与砂粒含量呈极显著负相关关系,而与黏粒含量、粉粒含量呈极显著正相关关系。<0.05 mm粒径物质含量的增加和>0.05 mm粒径物质含量的降低共同导致了土壤颗粒分形维数在设置沙障后的增大。     

典型黑土区耕作土壤质地遥感时间窗口及影响因素分析

了解黑土区耕作土壤质地的空间分布对于黑土区农业精准管理以及耕地保护至关重要。遥感技术是快速获取土壤质地空间分布的有效方法。该研究以黑龙江省友谊农场耕地为研究对象,评估研究区土壤质地遥感反演的最佳时间窗口并分析其影响因素。筛选覆盖研究区的2019-2021年25幅Sentinel-2影像,将每幅影像的波段和构建的光谱指数输入随机森林模型,建立土壤质地遥感反演模型,比较不同时期影像反演土壤质地的模型精度,确定土壤质地遥感反演的最适宜影像,并分析造成反演土壤质地精度变化的原因,获取友谊农场土壤质地空间分布。结果表明：1）友谊农场反演土壤质地的最佳时间窗口为4月下旬至5月中旬;2）在25幅Sentinel-2影像中,2020年5月7日反演粉粒和砂粒的模型精度最高（粉粒的R2为0.785,均方根误差为6.697%;砂粒的R2为0.776,均方根误差为8.296%）;2019年5月3日反演黏粒的模型精度最高（R2为0.776,均方根误差为1.6%）;3）不同时期的Sentinel-2影像对土壤质地反演的准确性有很大的影响,而土壤含水量和秸秆覆盖是造成不同时期土壤质地预测精度差异的重要原因。研究为确定土壤质地遥感反演的最佳时间窗口、实现区域尺度土壤质地制图提供关键技术。