土壤风蚀可蚀性研究进展评述

土壤风蚀可蚀性是土壤的内在属性,表征着土壤对风蚀发生发展的敏感程度,是土壤风蚀研究的重要基础性内容.现阶段,虽然土壤风蚀可蚀性研究已取得较大进展和丰硕成果,但仍有许多重要问题尚未解决.为继续推动和发展土壤风蚀可蚀性研究工作,在系统分析国内外研究进展的基础上,笔者围绕土壤风蚀可蚀性概念内涵、量化表达和动态特征3个焦点和热...     

基于Region Manager的北京土壤可风蚀性研究

在对北京市各种类型土壤进行调查的基础上,采用美国土壤学家D.W.Fryrear等人的计算土壤可蚀部分含量方程,计算北京主要土壤类型（亚类）表层的可蚀含量,建立了北京市可风蚀性数据库。用Region Manager地理信息系统制作北京土壤可风蚀性风分级图,并对北京地区主要土壤类型的可风蚀性进行分析与讨论,为正确评价北京土壤风蚀危害提供科学依据。     

土壤可蚀性研究进展综述

土壤可蚀性是表征土壤对降雨渗透能力及其对降雨和径流剥蚀、搬运敏感程度的一个综合指标,是反映土壤侵蚀的重要参数。介绍了国内外学者提出的土壤可蚀性指标,评述了直接测定法、公式法和诺谟图法的优缺点与应用范围;结合我国土壤可蚀性研究现状,介绍了我国土壤侵蚀严重区的典型土壤可蚀性指标值的最新研究成果,分析了我国土壤可蚀性研究的不足,指出应加强并完善土壤可蚀性指标、土壤可蚀性影响因子和土壤可蚀性计算方法的研究。     

水蚀过程的土壤可蚀性研究述评

土壤可蚀性是建立土壤侵蚀预报模型的重要参数,在土壤侵蚀研究中占有重要地位.该文基于土壤内在性质和侵蚀动力对土壤可蚀性评价指标与体系、土壤可蚀性的测定与计算方法以及土壤可蚀性动态变化等方面进行阐述,全面评述了目前国内外土壤可蚀性的研究进展,分析了当前土壤可蚀性研究存在的问题,指出了尚需加强的研究领域,包括土壤可蚀性评价指标体系、土壤可蚀性动态变化规律和土壤侵蚀机理研究等.     

豫东北黄泛区易风蚀性土壤特征

为分析不同土壤类型的性质、界定易风蚀性土壤类型并探索其特征，选取豫东北黄泛区为研究区域，采用野外取样、室内试验分析结合的方法测定土壤颗粒粒径、可蚀性因子K值等指标，界定区域易风蚀性土壤类型，并分析其空间分布特征。结果表明：（1）从土类看，豫东北黄泛区4种土类，以潮土为主，占区域面积的65.57%；从亚类看，共11种土壤亚类，以小两合土、沙土为主，占区域面积的59.76%。（2）土壤颗粒粒径组成上，沙土、草甸风沙土、盐化潮土、淤土等类型以砂粒为主；其余类型以粉粒为主。沙土、草甸风沙土、灌淤潮土、盐化潮土等类型易蚀颗粒含量较高，处于28.30%~31.36%范围内。草甸碱土、两合土、小两合土的土壤可蚀性因子K值相对较高，范围为0.038~0.041。（3）综合考虑易蚀颗粒含量≥25%和可蚀性属中等及以上2个指标，将沙土、草甸风沙土、灌淤潮土、盐化潮土、脱潮土界定为区域易风蚀性土壤。易风蚀性土壤面积占研究区的41.79%，主要分布在中牟县、祥符区、尉氏县等区域。研究结果可为黄泛区后续土壤研究及风蚀防治提供参考和科学依据。     

紫色丘陵区土壤可蚀性因子研究

土壤可蚀性是标准小区上单位降雨侵蚀力所引起的土壤流失量,具有明确的物理意义和简便的测定方法,是确定土壤流失量的重要指标,也是土壤预测预报模型的重要参数[1]。美国的《农业手册》(No·282,537和703)总结并提出了土壤侵蚀预报模型USLE和RUSLE[2-4]各个参数的计算方法。我国学者对土壤可蚀性进行了大量的研究,朱显谟[5]将土壤抗侵蚀性能分为抗冲性和抗蚀性,学者们[6-7]分别对土壤抗冲性和抗蚀性进行了研究。人工模拟降雨研究土壤可蚀性有效率高、可控性好的特点得到了广泛的运用。史学正等[8]用人工模拟降雨仪研究了亚热带土壤的可蚀性,于东升等[9]用不同人工模拟降雨方式研究了土壤可蚀性     

土壤可蚀性研究进展

土壤可蚀性(K值)是反映土壤侵蚀规律的重要指标,有关其研究成果已有大量研究论文报道。通过总结前人的研究成果,从土壤可蚀性评价指标的确定、空间变异性和不确定性以及研究方法等方面,介绍土壤可蚀性的研究进展。同时,指出了在今后的研究中需要形成统一的评价指标对土壤可蚀性进行评价,可利用泥沙平衡原理分析和验证可蚀性公式的适用程度,并建议建立K值数据库为水土流失监测、预报和治理提供参数基础。     

中国土壤可蚀性值及其估算

土壤可蚀性是评价土壤对侵蚀敏感程度的重要指标，也是进行土壤侵蚀预报的重要参数。本文运用野外观测资料，研究了我国不同水土流失区的土壤可蚀性值问题。根据实测资料，计算给出了一组土壤可蚀性实测值。并利用这组实测值。对我国土壤可蚀性估算问题进行了探讨。结果表明，国外现有的可蚀性估算模型不能直接应用于我国土壤的可蚀性计算，估算值明显大于实测值。但估算值与实测值之间存在有良好的线形关系。最后提出了我国不同地区及不同资料占有情况下的土壤可蚀性估算方法。本文研究结果可以直接用于我国土壤侵蚀预报中土壤可蚀性计算。     

不同退耕模式下土壤抗蚀性差异及其评价模型

土壤抗蚀性是评定土壤抵抗土壤侵蚀能力的重要参数之一,该文通过野外调查与室内分析相结合方法,在土壤理化性质综合分析的基础上,融入生物学指标,对川西低山丘陵区退耕桉树林、退耕杉木林、退耕茶园、退耕枇杷园和退耕撂荒地5种退耕模式下土壤抗蚀性进行了研究。结果表明：19个用于表征研究区土壤抗蚀性的指标可优化为>0.25 mm水稳性团聚体含量、平均质量直径、>0.25 mm团聚体破坏率、>0.5 mm团聚体破坏率、有机质含量及酸性磷酸酶6个指标;5种退耕模式下土壤抗蚀性综合指数大小依次为退耕杉木林＞退耕桉树林＞退耕枇杷园＞退耕茶园＞退耕撂荒地。在此基础上,应用6个优化指标构建了研究区不同退耕模式下土壤抗蚀性强、中等、弱3个等级的判别模型,模型总判别正确率为96.7%,具有较高的可信度。这为完善不同退耕模式下土壤抗蚀性评价指标体系和区域性土壤抗蚀性评价提供依据。     

基于粒度对比法的坝上农田风蚀与粉尘释放量估算

为了计算当前年内的农田风蚀量,该研究利用农田耕作层土壤粒度组成较均一,风蚀使表层可蚀性颗粒减少,不可蚀颗粒含量相对增加这一特点,通过比较一个风蚀季结束后,农田耕作层表层与下层可蚀性颗粒与不可蚀颗粒相对含量的变化,提出了一种估算当前年内土壤风蚀量和粉尘释放量的方法,并给出了风蚀量与粉尘释放量的计算公式。利用此方法对河北坝上地区主要农田类型土壤风蚀量和粉尘释放量进行计算。计算结果表明,2013年研究区农田风蚀量为960～5700 g/(m2·a),平均为2852.14 g/(m2·a),平均风蚀深度为0.21 cm/a,从强度上划分属于重度风蚀。农田平均粉尘释放量为768.16 g/(m2·a),约占农田平均风蚀量的29.00%。粉尘释放量与风蚀量之间有显著的线性相关关系,翻耕耙平地的风蚀量和粉尘释放量显著大于留茬地。该方法的估算结果与前人采用其他方法得到的结果以及实地观测得到的结果基本吻合。     

Effect of particle-size distribution on wind erosion rate and soil erodibility

Wind erosion is a serious problem, especially in arid and semi-arid regions. This study was conducted to assess the effects of wind speed as well as soil particle-size distribution on erosion rate (ER) using a wind tunnel. For this purpose, two clay loam soil samples (C2 and C10) in addition to a sandy clay loam (S2) were exposed to different wind velocities of 2, 9 and 18 m s^?1. The result showed that erosion rate increased significantly with increasing wind speeds. In addition, a critical diameter of 0.84 mm for soil particles was supported; for larger particles the changes in erosion rate were negligible. Furthermore, soil erodibility (K) was determined, which for S2, C2 and C10 was 57.73, 10.27 and 1.43, respectively. To predict soil erodibility, a power relationship as K = 3.382 MWD^?1.732 (R ² = 0.99) was established. The results indicated with increasing wind speed, the sensitivity of S2 remained constant, whereas C2 and C10 resisted wind speed. The finding of this research indicates the importance of particle-size distribution on wind erosion rate as well as soil erodibility.     

半干旱草原潜在土壤风力侵蚀空间格局研究

中国绝大多数的干旱半干旱地区遭受着严重的风力侵蚀。风蚀可导致土壤流失、肥力下降,最终导致土地荒漠化。半干旱草原区的荒漠化问题日益突出,由此带来的沙尘暴等灾害天气增多,给人们的生产生活带来诸多不便。从影响土壤风力侵蚀的风速、干燥度、植被盖度、地形起伏度、土壤可蚀性以及放牧压力6个方面出发,借助GIS技术,通过主成分分析研究半干旱草原区达茂旗土壤风力侵蚀的空间分布格局。结果表明:达茂旗潜在土壤风力侵蚀指数由南向北呈高—低—高趋势。达茂旗北部地区土壤风蚀主要受风速、干燥度和植被指数影响;中部地区风力侵蚀主要受地形起伏度的影响,地形起伏对风的消减作用增强,使得风力降低,加之该地区土壤可蚀性和干燥度相对较低,风力侵蚀指数低;南部土壤风力侵蚀主要受放牧压力影响,春季正是牧草返青季节,植被盖度低,且牲畜密度相对较大,放牧对草场的压力大,土壤风力侵蚀严重。风力侵蚀各影响因子的时空异质性是导致半干旱草原风力侵蚀空间异质性的主要原因。干旱草原风力侵蚀空间异质性的主要影响因素是风速、干燥度和植被指数,其次受地形和土壤可蚀性的影响,而放牧压力是半干旱草原区土壤风力侵蚀的主要人为因素之一。     

Wind tunnel test and Cs tracing study on wind erosion of several soils in Tibet

The soils of alpine meadows and alpine grassland steppes, aeolian soils, coarse-grained soils, and farm soils cultivated from alpine grasslands in Tibet are typical soils that are suffering from different degrees of soil erosion by wind. Based on field investigations, wind tunnel experiments, and a ¹³⁷Cs trace study, this work tested the erodibility of these soils by wind, simulated the protective functions of natural vegetation and the accelerative effects of damage by livestock, woodcutting, and cultivation on erosion, and estimated erosion rates from 1963 to 2001. The results indicated that alpine meadows have the strongest resistance to wind erosion, and that undamaged alpine meadow soils generally sustain only weak or no wind erosion. Alpine grassland steppes with good vegetation cover and little damage by humans exhibit good resistance to wind erosion and suffered from only slight erosion. However, soil erodibility increased remarkably in response to serious disturbance by livestock and woodcutting; wind erosion reached 33.03 t ha⁻¹ year⁻¹. The erodibility of semi-stabilized aeolian soil and mobile aeolian soil was highest, at 52.17 and 56.4 t ha⁻¹ year⁻¹, respectively. The mean erosion rates of coarse-grained soil with various levels of vegetation coverage and of farm soil were intermediate, at 45.85 and 51.33 t ha⁻¹ year⁻¹, respectively. Restricting livestock, woodcutting, and excessive grassland cultivation are the keys to controlling wind erosion in Tibet. In agricultural regions, taking protective cultivation and management to enhance surface roughness is a useful way to control wind erosion.     

沂蒙山区典型县土壤可蚀性K值空间变异研究

土壤可蚀性是一个相对概念,在时间、空间等方面呈现异质性特征,选取蒙阴县和沂水县为研究区域,采用EPIC模型中K值计算方法,以地统计学原理为指导,基于Arc GIS地统计模块,探讨了沂蒙山区典型县土壤可蚀性空间分布特征,为区域土壤侵蚀评价提供数据支撑。结果表明:(1)研究区土壤可蚀性K值变化范围为0.1057~0.3776,属中等变异,以中低可蚀性土壤分布最广;在分布最广的粗骨土土类中,石灰岩钙质粗骨土K值最大,为中高可蚀性土壤,存在较大的侵蚀危险性。(2)蒙阴县西北部区域为低可蚀性土壤,中部和东南部为中可蚀性及以上土壤;沂水县土壤主要为中低可蚀性,而南部、西北及东北部存在中高及高可蚀性土壤;两县相接区域土壤为中可蚀性及以上土壤。(3)同一土类而不同土地利用呈现异质性特征,不同土地利用K值大小依次为园地耕地林地草地。(4)随着海拔高度增大,土壤可蚀性K值呈逐渐减小趋势。     

利用~(137)Cs技术研究土壤可蚀性的时空变异(英文)

土壤可蚀性的研究变异性是当代土壤侵蚀预测预报研究的核心。本综述了土壤可蚀性变异性研究的进展及存在的问题,提出了利用＾１３７Ｃｓ法定量测定土壤可蚀性时空变异的新技术。     

青藏高原土壤可蚀性K值的空间分布特征

土壤可蚀性反映了土壤对水力侵蚀作用的敏感性,是进行土壤侵蚀评价和预报的重要参数。收集了青藏高原1 255个典型土壤剖面资料,采用模型计算和面积加权分析方法确定了每一个土壤亚类的土壤可蚀性K值,结合青藏高原1∶100万土壤类型图,分析了青藏高原土壤可蚀性K值的空间格局特征。结果表明,青藏高原土壤可蚀性K值平均为0.230 8,低可蚀性、较低可蚀性、中等可蚀性、较高可蚀性和高可蚀性土壤面积分别占该区面积的5.60%,18.23%,24.35%,44.02%和7.80%。土壤可蚀性以中等可蚀性和较高可蚀性为主,二者分布面积之和达1.77×106 km2,占青藏高原总面积的68.37%;较高可蚀性、高可蚀性土壤主要分布在青藏高原中西部的羌塘高原、柴达木盆地和横断山区的低海拔河谷中。青藏高原土壤可蚀性K值具有明显的垂直分异特征,在横断山区最为显著,土壤可蚀性随海拔高度升高而降低。不同海拔高度的水热分异影响了土壤的理化特性,进而决定了青藏高原土壤可蚀性的垂直分带特征。     

Regional modeling of wind erosion in the North West and South West of Iran

About two-thirds of the Iran’s area is located in the arid and semiarid region. Lack of soil moisture and vegetation is poor in most areas can lead to soil erosion caused by wind. So that the annual suffered severe damage to large areas of rich soils. Modeling studies of wind erosion in Iran is very low and incomplete. Therefore, this study aimed to wind erosion modeling, taking into three factors: wind speed, vegetation and soil types have been done. Wind erosion sensitivity was modeled using the key factors of soil sensitivity, vegetation cover and wind erodibility as proxies. These factors were first estimated separately by factor sensitivity maps and later combined by fuzzy logic into a regional-scale wind erosion sensitivity map. Large areas were evaluated by using publicly available datasets of remotely sensed vegetation information, soil maps and meteorological data on wind speed. The resulting estimates were verified by field studies and examining the economic losses from wind erosion as compensated by the state insurance company. The spatial resolution of the resulting sensitivity map is suitable for regional applications, as identifying sensitive areas is the foundation for diverse land development control measures and implementing management activities.     

东北典型黑土区剖面粒径分布特征及其可蚀性研究

为了更好的了解黑土区土壤剖面粒径分布以及可蚀性因子特征,本研究以东北典型黑土区鹤北流域为研究区,利用沉降法对不同土地利用方式下土层表面至母质的土壤样品进行粒径分布规律研究,并基于粒径及有机碳分布特征,计算了土样的可蚀性K值,最后对土壤可蚀因子K与WEPP模型中土壤的细沟间侵蚀因子(Inter- rill Erodibility)K_i、细沟侵蚀因子(Rill Erodibility)K_r和临界剪切力因子(Critical Shear)Tc进行相关分析。结果表明:(1)不同剖面下土壤粘粒含量逐层变化不大。而粉粒含量呈现出随土层深度增加而含量减少,砂粒呈现出随土层深度增加而含量增大;(2)除人工林外,其余6个剖面土壤可蚀性因子K值均表现出随土层深度增加而含量增大的趋势;(3)对农地剖面土样分析发现,可蚀性因子K值与细沟侵蚀因子K_r呈极显著正相关,与临界剪切力因子Tc呈极显著负相关,而与细沟间侵蚀因子K_i的正相关性略有降低。     

Uncertainty and Sensitivity Analyses of the Modified Wind Erosion Equation for Application in Canada

The wind erosion equation (WEQ) was used for several decades for predicting soil loss by wind erosion, but few systematic studies on the uncertainty of predicting wind erosion have been conducted. Several researchers found that WEQ is not accurately representing soil erosion and under‐represents soil erodibility that consequently results in WEQ underestimations. WEQ was modified under Canadian conditions for the National Agri‐Environmental Health Analysis and Reporting Program, referred as (WEQ‐NAHARP). The model, input, and parameter uncertainties that control model efficiency were used to analyze the local and universal uncertainties for WEQ‐NAHARP. One and ninety‐nine percentiles were used as lower and upper boundaries of uncertainty bound when using general likelihood uncertainty estimation for estimating the uncertainty of WEQ‐NAHARP's prediction. The soil erodibility (I ), climate factor (C ), and soil surface roughness factor (K ) were found as the three most sensitive factors in predicting wind erosion in WEQ‐NAHARP. The vegetation cover factor (V ) was discovered not sensitive to the prediction model as it is less than 1,000 kg ha⁻¹ and became very sensitive as V ‐value is greater than 5,000 kg ha⁻¹ . Field length along the prevailing wind erosion direction (L ) and V have lower local sensitivity indexes than the other three factors. WEQ‐NAHARP underestimated wind erosion rate of Pampas, Argentina, and overestimated at Washington State, USA. This probably reflected the nature of WEQ‐NAHARP's behavior, which had a great uncertainty of its prediction. The model appears to underestimate total annual soil loss for coarse soil and overestimate annual soil loss for finer soil. Copyright © 2017 John Wiley & Sons, Ltd.