红壤侵蚀区马尾松林下植被特征与土壤侵蚀的关系

针对南方花岗岩发育的红壤侵蚀区,在赣县大田乡选择5个低丘马尾松林,利用植物样方调查方法对样地的地形、土壤、植被、侵蚀沟进行调查和测量,基于获取的数据,利用统计学方法分析植被特征与土壤侵蚀的关系.结果表明：1）马尾松人工林郁闭度低,林木生长状况差,林地阳坡半阳坡植被总盖度仅为36.9％;2）林下灌草生物量低,物种丰富度、多样性、均匀度差,物种较为单一;3）林下植被以草本为主,草本以芒萁为主,其生物量占草本总生物量的75％以上;4）马尾松林下细沟、浅沟发育,土壤侵蚀严重,仅细沟、浅沟流失的土壤厚度达71.2 mm;5）不同坡位的侵蚀沟发育相关性显著,侵蚀沟与坡面的微环境差异明显,尤其是土壤密度和土壤水分差异显著;6）马尾松林下土壤侵蚀量对植被恢复具有抑制作用,但沟壑密度的发育能够提高灌草物种丰富度、多样性,以及促进灌草均匀性分布.     

黄土丘陵区典型沟道侵蚀诱发的CO2通量估算

以黄土丘陵区典型侵蚀沟道为对象,基于沟道剖面有机碳和¹³⁷Cs数据,采用碳库重分布模型估算了典型沟道侵蚀诱发的CO₂通量,并通过检验模型预测效率、解析影响因子,提出了模型校正的思路。结果表明:(1)在长期侵蚀作用下,沟道侵蚀区和沉积区均表现为剧烈的侵蚀效应,侵蚀区侵蚀速率介于30.99~46.44 mm/a,沉积区侵蚀速率介于34.20~37.88 mm/a,沉积区土壤流失速率略小于侵蚀区;(2)碳库重分布模型估算显示,侵蚀区与沉积区均表现为较强烈的碳源效应,侵蚀区CO₂通量介于18.41~28.44 g/(m²·a),沉积区CO₂通量介于22.19~29.25 g/(m²·a);(3)侵蚀部位、土壤容重、有机碳含量、侵蚀量、沟道平均坡度、植被地上部与地下部生物量共同解释了碳库重分布模型预测效率的变异特征(R²=0.68),其中侵蚀部位、侵蚀量、有机碳含量、土壤容重、植被地下部对预测效率有强驱动效应;(4)引入被忽略的植被新输入有机碳库参数,有望校正碳库重分布模型,提升模型预测效率。该研究结果明确了碳库重分布模型在沟道侵蚀区相比沉积区有更高的CO₂通量预测效率,为进一步提高模型的预测精度,可以考虑引入植被输入有机碳库作为校正参数。     

Landscape analysis of dynamic soil erosion in Subtropical China: A case study in Xingguo County, Jiangxi Province

As a case study on landscape pattern analysis of soil erosion change, Xingguo County in Jiangxi Province, China, was once one of the most severely eroded regions in Subtropical China. However, its soil erosion has been completely controlled in recent years. This county was historically full of forest as well as waterways that were well protected and soil erosion was seldom seen even by the mid-19th century. However, large areas of forest were destroyed after that period due to over-logging, which resulted in excessive erosion, bare hills, and mountains devoid of vegetation. Fortunately, soil erosion in Xingguo has been controlled gradually since 1982 after the county was appointed as 1 of the 8 Key National Level Erosion Control Regions. In this study, a raster (grid) soil erosion map was collected on the basis of soil erosion intensity maps from 1958, 1975, 1982 and 2000 with the aid of GIS software (ARC/INFO). Over 10 landscape indices were calculated using FRAGSTATS software for landscape pattern analysis. A set of free spatial statistics that address a fundamental problem in GIS, and soil erosion distribution patterns and their changes in the county were quantitatively analyzed at the landscape and class levels, respectively. Moreover, transformations of soil erosion types from 1958 to 1975, 1975 to 1982, and 1982 to 2000 were also calculated using the CROSSTAB module in IDRISI software. Results showed that at the landscape level, heterogeneity of soil erosion decreased. This was supported by decreasing tendencies of patch indices SHDI (Shannon’s diversity index), SHEI (Shannon’s evenness index), and IJI (Interspersion and juxtaposition index). This indicates that most of the severely eroded soil types were transformed into non-apparently eroded or slightly eroded types. Meanwhile, at the class level, a consistent pattern was found where the surface areas of non-apparently eroded or slightly eroded lands increased, and moderately, severely, very severely and extremely eroded lands deceased. In general, soil erosion in Xingguo County experienced three pronounced phases during the study periods: the exacerbation phase (1958–1975), the alleviation phase (1975–1982), and the overall alleviation phase (1982–2000). By the year 2000, 74.6% of total territory of this county was covered by land with no significant soil loss, indicating that severe soil erosion had been substantially controlled.     

新疆植被NDVI时空变化及定量归因

为揭示自然与非自然因素以及因素之间的交互作用对新疆植被覆盖变化的影响,以归一化植被指数(Normalized Difference Vegetation Index,NDVI)为植被覆盖状况表征指标,结合气候、地形、水文、土壤以及人为干扰等15种因子,采用线性趋势分析、随机森林和地理探测器模型,分析了2000—2018年新疆地区植被NDVI的时空演变特征,并对其空间分异的驱动力进行了定量探测。结果表明:新疆NDVI分布呈现北高南低、西高东低、山区高平原低的特点; 研究期间植被覆盖状况有明显改善,60.91%的植被区域NDVI呈增加趋势。土壤湿度的解释力最高(0.394),与耕地面积和潜在蒸散发共同主导植被NDVI的时空格局; 双因子的交互作用能以非线性方式增强对NDVI空间分布的解释力,其中,尤以土壤湿度和潜在蒸散发的交互作用影响力最强; 各因子存在促进植被生长的最适宜范围或特征,其中,NDVI空间变化基本与水分因素呈正相关,与辐射量、海拔呈负相关。总体上,土壤水分条件对新疆植被变化的影响更为直接,此外,适度的人类活动对植被恢复已有明显的促进作用。     

基于4种植被指数TVDI模型的三江平原土壤湿度反演

利用遥感手段监测土壤湿度有利于分析大尺度区域的土壤干湿状况。比对分析不同植被指数计算的温度植被干旱指数（TVDI）的精度能够提高TVDI反演土壤湿度的实际应用价值。以三江平原为研究区,基于2013年5—9月的四期MODIS影像,利用归一化植被指数（NDVI）、增强型植被指数（EVI）、修正土壤调节植被指数（MSAVI）、比值植被指数（RVI）分别计算TVDI,并以地面实测土壤湿度数据及降水数据进行精度验证。结果表明:（1）4种植被指数计算的TVDI与土壤湿度数据均具有一定的负相关关系,即TVDI值越高,土壤湿度值越低;（2）不同植被指数计算的TVDI在5月、6月、9月与土壤湿度回归分析的R²数值相近,均适合用来反演这3个时间段的土壤湿度,在7月份,相较于NDVI和RVI计算的TVDI结果（R²均在0.15左右）,基于EVI和MSAVI计算的TVDI （R²均在0.35左右）更适合反演该时期的土壤湿度;（3）5—9月期间,干旱现象主要发生在三江平原的中部及西南部,干旱程度主要为轻旱,东部及东北部在不同时期基本保持在正常或轻微湿润状态。     

退耕还林还草工程实施对洛河流域土壤侵蚀的影响

退耕还林还草工程是中国实施的重要生态环境建设与保护工程,对区域植被覆盖及土壤侵蚀产生重要影响。以洛河流域（陕北黄土高原部分）为研究对象,利用流域通用土壤侵蚀方程（RUSLE）,结合流域降雨、土壤类型、DEM、植被覆盖等数据,定量分析了2000—2010年退耕还林还草工程实施对流域土壤侵蚀的影响。结果表明:（1）洛河流域2000—2010年耕地面积减少,林地、草地面积增加,土地利用变化主要发生在2000—2005年;（2）洛河流域2000—2010年土地利用变化导致植被NDVI平均值增大,耕地变化区域植被NDVI值增加幅度高于耕地未变化区域,表明耕地变化区域植被NDVI增加对耕地区域总体植被NDVI值增加贡献较大;（3）降雨侵蚀力和退耕还林还草工程实施对土壤侵蚀具有明显的影响。受降雨侵蚀力增大影响,2000—2010年洛河流域土壤侵蚀呈增加趋势;不考虑降雨侵蚀力变化情况下,洛河流域土壤侵蚀呈减少趋势,反映出退耕还林还草工程实施对土壤侵蚀的减缓作用。     

粤西坡地土壤侵蚀特征及退化分析——以广东省郁南县大湾镇为例

坡地是广东省重要的土地资源,也是水土流失的策源地。研究坡地的土壤侵蚀及退化问题,对于坡地的可持续利用具有重要的意义。本文以广东省郁南县大湾镇为例,探讨了粤西典型坡地不同侵蚀区的侵蚀形态特征,以及土壤侵蚀所导致的坡地退化,分析了影响土壤退化的原因,并提出了退化坡地的整治措施。研究区以花岗岩发育的弱侵蚀强度为主,占总侵蚀面...     

红壤侵蚀退化坡面植被恢复过程中的水土保持效益演变

为探究花岗岩红壤侵蚀退化坡面植草措施实施中植被在不同生长阶段水土保持效益的演变规律，设置条带型（D1）、随机型（D2）、斑块型（D3）3种不同植草格局坡面，并以侵蚀退化裸地坡面（CK）作为对照开展试验，在天然降雨条件下监测整个植被生长过程中的坡面土壤侵蚀变化特征。结果表明：（1）植被的生长可显著提升坡面的水土保持能力，随着植被生长阶段的推进，坡面的产流产沙量明显下降，减流效益达20.74%~79.03%，减沙效益达97.42%~99.40%，但在不同降雨类型下，随着植被生长，坡面减流减沙效益表现出的递增变化规律具有差异。（2）植被生长能逐渐削弱降雨因素对坡面产沙的影响，使得坡面减沙率在不同雨型间的差异逐渐减小，最终稳定在一个较高水平，不同雨型间坡面减流率的差异在植被生长各时期皆较大。减流率、减沙率与植被生长时间二者之间存在对数函数关系，相关系数分别大于0.491和0.792。植被生长指标（分蘖数、盖度、株高）与坡面产流产沙量之间呈显著或极显著负相关关系。（3）从整个植被生长过程来看，3种植草格局的水土保持效益大小表现为D1>D3>D2，在植被生长的前期以及前中期，高植株密度的分布格局强于低植株密度分布格局，后期各格局差异较小。研究结果为南方红壤水土流失区严重侵蚀退化地植被恢复提供科学依据及技术支撑。     

Soil erosion risk assessment using GIS and CORINE model: a case study from western Shiraz,Iran

This study employs the Coordination of Information on the Environment (CORINE) model with geographic information system to assess soil erosion risk for restoring and protecting areas within the Bonrod Zangane watershed, western Shiraz, Iran. Actual soil erosion risk was determined by combining two main parameters including potential soil erosion risk and vegetation cover. The potential soil erosion risk was generated by integrating soil erodibility, erosivity and slope parameters. Soil texture, depth and stoniness layers were overlaid to form a soil erodibility map. Modified Fournier index and Bagnouls–Gaussen aridity index were integrated to generate the erosivity layer. The slope classes also were generated from digital elevation model. In order to estimate vegetative land cover, the normalized difference vegetation index (NDVI) was used. The raster-based layers were then integrated to produce erosion risk map. The results showed that 34.7% of the study area has high and only 31.4% of the study area has low soil erosion risk. It is concluded that CORINE model can be used to delineate the soil erosion risk and also to discriminate the potential soil erosion risk areas.     

区域水土流失植被因子的遥感提取

NDVI是区域土壤侵蚀评价的最佳植被因子。基于遥感影像TM数据提取了NDVI值并将其与土地利用信息同时集成于土壤侵蚀图的每个图斑,建立了包含多种因子的空间数据库。通过每个图斑林草地面积百分比和NDVI值的统计分析,建立了NDVI与植被盖度的线性关系。多重因子数据库和NDVI-植被盖度关系,可以为区域土壤侵蚀定量评价提供支持。     

Effect of vegetation cover on soil erosion in a mountainous watershed

We applied the Revised Soil Loss Equation (RUSLE) to assess levels of soil loss in a Geographic Information System (GIS). In this study, we used the k-NN technique to estimate vegetation cover by integrating Landsat ETM+ scenes and field data with optimal parameters. We evaluated the root mean square errors and significance of biases at the pixel level in order to determine the optimal parameters. The accuracy of vegetation cover estimation by the k-NN technique was compared to that predicted by a regression function using Landsat ETM+ bands and field measurements as well as to that predicted by the Normalized Difference Vegetation Index (NDVI). We used a regression equation to calculate the cover management (C) factor of the RUSLE from vegetation cover data. On the basis of the quantitative model of soil erosion, we explored the relationship between soil loss and its influencing factors, and identified areas at high erosion risk. The results showed that the k-NN method can predict vegetation cover more accurately for image pixels at the landscape level than can the other two methods examined in this study. Of those factors, the C-factor is one of the most important affecting soil erosion in the region. Scenarios with different vegetation cover on high-risk areas showed that greater vegetation cover can considerably reduce the loss of soil erosion. The k-NN technique provides a new method to estimate the C-factor for RUSLE erosion mapping. The quantitative model of different vegetation cover scenarios provides information on how vegetation restoration could reduce erosion.     

东北黑土区农林混合利用坡面土壤水分空间异质性及主控因素

针对黑土区坡面尺度上土壤水分在土地利用结构(从坡顶到坡脚,即沿着坡长方向,不同土地利用类型的排列方式)、土地利用类型(农地和林地)及地形要素的协同作用下的空间分异规律及影响机制尚不清楚的现状,以黑龙江省黑土区的农林混合利用典型坡面(克山县)为研究对象,应用植被数量生态学中的冗余分析方法(RDA)分析0~20、20~40、40~60 cm土壤水分剖面变异特征、不同土地利用结构下(农地-农地-农地-农地-农地,农地-农地-林地-林地-农地,农地-农地-林地-林地-林地,林地-林地-农地-林地-农地)坡面土壤水分异质性及其与环境因子的定量关系。结果表明:研究区坡面土壤含水率介于5.77%~45.57%,农地土壤含水率显著高于林地(P0.05),纵向上不同土地利用类型层间土壤含水率差异均不显著;土壤水分呈中等变异,纵向上农地各土层的变异系数(35.9%~39.6%)均高于林地(30.0%~36.5%),农林混合利用加强了土壤水分的空间变异程度;4种土地利用结构下,坡面土壤水分沿坡长方向呈不同的变化趋势,与土地利用镶嵌分布规律有关;冗余分析结果显示土地利用类型是影响黑土区坡面土壤水分异质性的主控因素,坡度次之,坡位和海拔高度对坡面土壤水分异质性也有影响。对于黑龙江黑土区坡面,需要结合土地利用结构配置等土地管理措施与不同的农业措施来防止坡面土壤侵蚀、提高东北区土壤肥力,实现经济效益、生态效益的协调统一。     

Sand Drift Potential in El-Khanka Area,Egypt

Wind erosion force vectors were computed from data of frequencyof occurrence of windspeed and direction based on the assumptionthat wind erosion is proportional to (windspeed)³× duration of exposure.The vertical distribution of eroded soil material wasmathematically described. The transition height betweensaltation and suspension could be identified and used tointegrate the two equations describing saltation and suspension.The soil avalanching process was studied by evaluating the horizontal changes of eroded soil material. The vertical andhorizontal distribution of eroded soil constituents, i.e.,particle size distribution, mean weight diameters, plantnutrients and heavy minerals content for selected wind stormswere also evaluated. Results revealed that soil constituents change considerably with the height and downwind distance.To assess the changes in soil properties due to wind erosion,surface soil samples were taken from the original eroded surfaceand from freshly accumulated drifts near the eroded field.Enrichment ratios were more than one for the fine fraction, organic matter, moisture retention, and chemical constituentsindicating a loss in their contents in the eroded field.     

Using SPOT images and field sampling to map burn severity and vegetation factors affecting post forest fire erosion risk

Runoff and erosion rates are known to increase substantially after a major forest fire. Erosion control measures therefore need to be put into place quickly after a large fire, and determining where to locate the measures requires accurate mapping of post fire erosion risk. Burn severity can be determined from field observations, but these are costly and time consuming. Satellite imagery is an alternative to quickly map burn severity for erosion mapping purposes. Post fire erosion decreases as forest vegetation recovers and this is related to both pre fire vegetation characteristics and soil properties. The objectives of this study were to test the use of SPOT multispectral images for mapping burn severity, pre fire vegetation density, and longer term (2.5 years) vegetation recovery. Indices tested include the Normalized Burn Ratio (NBR), Normalized Difference Vegetation Index (NDVI), Differenced Normalized Burn Ratio (dNBR), and Differenced Normalized Difference Vegetation Index (dNDVI). Indices were compared to field data gathered immediately after the fire and about 2.5 years later. The multi-temporal indices (dNBR and dNDVI) were more useful for burn severity mapping in the heterogeneous forest–scrubland–vineyard environment where bedrock and vineyard surfaces were confused with burned areas when using single images (NBR and NDVI). All of the post fire indices showed traces of the fire 2.5 years later; this was confirmed using Analysis of Variance where differences in indices were related to original ground cover (pine forest, mixed forest, mostly bedrock and vineyards) and the burn scar. Pre fire vegetation cover was less successfully mapped using the NDVI according to the initial field observations. Similarly, none of the post fire indices were able to distinguish differences in N–S vegetation recovery revealed by field measurements of understory vegetation height and cover; N facing slopes had deeper finer soils and these more favourable conditions led to greater vegetation growth than on S facing slopes and topslope convexities. It is suggested that relationships between topography and soil properties can be useful for mapping both soil erodibility and post fire vegetation recovery.     

基于Sentinel多源数据的农田地表土壤水分反演模型构建与验证

土壤水分是影响水文、生态和气候等环境过程的重要参数,而微波遥感是农田地表土壤水分测量的重要手段之一。针对微波遥感反演农田地表土壤水分受植被覆盖影响较大的问题,该文基于Sentinel-1和Sentinel-2多源遥感数据,利用Oh模型、支持向量回归(support vector regression,SVR)和广义神经网络(generalized regression neural Network,GRNN)模型对土壤水分进行定量反演,以减小植被影响,提高反演精度。结果表明:通过水云模型去除植被影响后的Oh模型反演精度有所提高。加入不同植被指数的SVR和GRNN模型的反演效果总体优于Oh模型,基于SVR模型的多特征参数组合(双极化雷达后向散射系数、海拔高度、局部入射角、修改型土壤调整植被指数)反演效果最优,其测试集相关系数和均方根误差分别达到了0.903和0.015 cm~3/cm~3,为利用多源遥感数据反演农田地表土壤水分提供了参考。     

福贡县土壤侵蚀时空变化及其影响因素分析

开展福贡县土壤侵蚀时空动态变化分析,对当地的水土流失防治和国土空间规划具有重要意义。研究基于降雨、土地利用、土壤和植被覆盖度等数据,采用GIS技术和RUSLE模型分析了福贡县2002年、2010年和2018年的土壤侵蚀时空变化和影响因素。结果表明:(1)福贡县土壤侵蚀强度主要以微度侵蚀和轻度侵蚀为主; 2002—2010—2018年平均土壤侵蚀模数不断下降,微度侵蚀面积不断增加,福贡县土壤侵蚀状况呈现改善趋势;(2)福贡县土壤侵蚀严重区主要分布在怒江两岸,近16 a福贡县74.73%以上的区域土壤侵蚀强度未发生改变,整体好转,表明退耕还林等工程实施对抑制土壤侵蚀强度有一定效果;(3)土地利用类型是福贡县土壤侵蚀的主要影响因子; 各因子解释力的大小依次为:土地利用类型、植被覆盖度、年均降雨量、海拔、坡度。海拔1 005～1 523 m、坡度>35°、年均降雨量1 482～1 671 mm、植被覆盖度<0.3、土地利用类型为未利用地的区域被识别为高风险侵蚀区。结合福贡县实际,坡耕地应为福贡县土壤侵蚀治理的重点区域。     

光学与微波遥感协同反演藏北表层土壤水分研究

表层土壤水分是定量干旱监测的重要参量,对干旱区生态环境具有十分重要的意义。在采用归一化植被指数阈值法划分地表覆盖类型的基础上,利用MODIS数据选择适用的光学遥感算法估算土壤水分基准值,以及利用风云三号B星搭载的微波成像仪(Fengyun-3B/MicrowareRadiationImagery,FY3B/MWRI)数据采用微波遥感算法反演土壤水分日变化量,最后构建藏北表层土壤水分协同反演的遥感模型并应用于区域土壤水分的估算。结果表明:光学遥感与微波遥感协同反演的土壤水分含量与实测数据呈显著相关,决定系数达到0.89,均方根误差为0.97,协同反演模型具有较高的反演精度,并且协同反演的结果优于单一遥感源的反演结果。该模型可以较好地适用于藏北地区表层土壤水分的动态监测。     

Monitoring the effects of land use and cover type changes on soil moisture using remote-sensing data: A case study in China's Yongding River basin

We used a radiation-transfer equation estimate of July surface temperatures (T_s) in China's Yongding River basin based on thermal infrared Landsat TM images from 1987 and 2005 and Landsat ETM+ images from 2000. Based upon the T_s–NDVI relationship space, we analyzed the scatterplot of T_s versus NDVI to calculate a temperature–vegetation dryness index (TVDI). We used a linear regression model between soil moisture and TVDI to estimate soil moisture to depths of 10 and 20 cm. We produced a land use and cover type map by classification of the Landsat images, and used the map to study the influence of land use and cover type changes on soil moisture. Some areas of farmland in 1987 had been converted into grassland by 2000, and soil moisture mainly increased, with increases ranging from 20 to 60%. From 2000 to 2005, most of the grassland in the northern part of the study area and some grassland in the central area were converted into farmland, and soil moisture decreased by up to 60%. Soil moisture decreased most obviously in areas where forest was converted into grassland, with decreases ranging from 60 to 100% in most areas.     

侵蚀区植被恢复过程中土壤有机碳稳定性的研究进展

探究土壤有机碳(SOC)的组成、来源和稳定性机制是深入认识陆地碳汇功能和应对气候变化的关键。"增加土壤碳汇"与"稳定现存土壤碳汇"都是提升陆地生态系统碳固持能力的重要方面,地位同等重要。与"增汇"研究成果丰硕相比,"稳汇"研究相对薄弱。侵蚀区进行植被恢复可以显著促进SOC积累,但由于侵蚀区存在碳素坡面侵蚀损失,其碳素积累效率低于其他生态系统类型区这一重要环节,导致目前有关侵蚀区及其水土保持植被恢复过程中SOC动态变化、稳定性及固持长期有效性等问题尚不清楚,微生物介导的SOC稳定机制尚未充分揭示。通过简要概括侵蚀区植被恢复过程中土壤碳素的积累效益和影响因素,综述植被恢复对土壤SOC及其活性组分稳定性的影响;在简要介绍土壤微生物在调控土壤碳素稳定性重要作用的基础上,梳理了基于微生物"碳泵"理论的土壤有机碳稳定性研究进展,特别是指出了随着植被恢复进程,侵蚀区土壤微生物介导的SOC动态变化,总结现有研究的不足。指出今后需要从研究对象(重点是西南石漠化区和南方红壤丘陵区)、研究内容(土壤微生物介导的SOC稳定状态和机制)、研究手段(借用微生物碳泵的理念,野外典型样地调查与室内培养手段相结合)和研究土层(20 cm以下深层次土壤)4个方面加强研究,以期对相关领域起到一定程度的推动作用。     

基于NDVI分区的全国草地生态系统覆盖区土壤水分遥感反演

为了建立土壤水分遥感反演模型,反演2016年全国草地生态系统土壤水分并分析其时空变化特征,通过结合表观热惯量(ATI)和温度植被干旱指数(TVDI)的混合模型反演2016年全国草地生态系统的土壤水分,并在实测数据与反演结果精度验证的基础上确定归一化植被指数(NDVI)阈值。结果表明:(1)NDVI≤0.2的像元区域,采用ATI模型反演精度较高; NDVI≥0.78的像元上,基于增强型植被指数(EVI)的TVDI反演精度较高; 0.2相似文献