基于水土保持的宜宾市土地利用空间重组

该文在GIS技术支持下分析了宜宾市水土流失与土地利用间的相互关系,以期为宜宾市土地利用空间重组提供战略思路。结果表明,水土流失多发生在自然因素与人类活动强度吻合较好的地方。因此,土地利用空间重组的目标即是通过土地利用的调整,规避生态敏感区或以能够逆向调节区域生态敏感性的方式利用土地,以有效的减缓水土流失。该文还提出了宜宾市土地利用空间重组的基本模式,即“结构调整+空间集聚”。     

Developments in land information systems: examples demonstrating land resource management capabilities and options

Land Information Systems (LIS) provide a foundation for supporting decision‐making across a broad spectrum of natural resource applications: agronomic, environmental, engineering and public good. Typically, LIS constitute a computerized database repository holding geospatial components, ‘mapping unit’ geometry and related georeferenced materials such as satellite imagery, meteorological observations and predictions and scanned legacy mapping. Coupled with the geospatial data are associated property, semantic and metadata, representing a range of thematic properties and characteristics of the land and environment. This paper provides examples of recent developments of national and regional LIS, presenting applications for land resource capabilities and management. These focus on the ‘Land Information System’ (LandIS) for England and Wales, and the ‘World Soil Survey Archive and Catalogue’ (WOSSAC) and consider Agricultural Land Classification in Wales, an Irish land and soil information system, and a scheme to optimize land suitability for application of palm oil biofertilizers in Malaysia. Land Information Systems support purposeful environmental interpretations, drawing on soil and related thematic data, offering insight into land properties, capabilities and characteristics. The examples highlight the practical transferability and extensibility of technical and methodological approaches across geographical contexts. This assessment identifies the value of legacy‐based natural resource inventories that can be interoperated with other contemporary sources of information, such as satellite imagery.     

Spatial distribution of soil organic matter in a coal mining subsidence area

ABSTRACT

Underground mining has caused drastic disturbances to regional ecosystems and soil nutrients. Understanding the three-dimensional (3D) spatial distribution of soil nutrients in mining area farmland is crucial for agricultural production and environmental management. However, few studies have reported the 3D spatial distribution of soil organic matter (SOM) in coal mining subsidence area. In our study, a sequential Gaussian simulation (SGS) algorithm was used to analyse the spatial distribution of SOM based on observations of 180 soil samples in the Zhaogu mine in China. The results showed that the SOM content had considerable variation in spatial distribution at different soil depths (0–20, 20–40, 40–60?cm) and decreased with the increase in soil depth. The spatial variability of surface organic matter was the largest, and the coefficient of variation was 29.38%, which was moderately mutated. The spatial distribution of SOM also varied among slope locations. The SOM content was higher upslope and downslope than on the middle slope. In addition, given a threshold, SGS can be used to calculate the probability that the organic matter content at any position is lower or higher than the given value. The research results provide a reference for land reclamation and precision agriculture.     

山东省土地适宜性空间分析及其优化配置研究

基于山东省自然、社会、经济统计资料及图形资料,运用GIS地理空间分析方法,对山东省土地适宜性进行评价,同时对区域土地资源自然质量指数、土地资源综合适宜度、相对适宜度进行研究。通过对适宜评价图和利用现状图的空间叠加,计算、分析了待调整土地资源的多度及重要值。以土地资源空间分析为基础,多度、重要值为依据,进行土地资源空间优化配置。结果表明,优化后农用地减少10994.82 hm²,林牧用地增加13083.56 hm²,未利用地减少1438.83 hm²。     

Spatial variability and temporal dynamics analysis of soil erosion due to military land use activities: uncertainty and implications for land management

Human activities, such as military off‐road vehicular traffic, disturb ground and vegetation cover of landscapes and increase potential rainfall related runoff and soil erosion. On military lands, soil erosion is of major concern in order to sustain training lands and thus there is a need for land condition maps for planning training activities and land management. In this study, we presented a conditional co‐simulation algorithm to generate annual time series maps of soil erosion status from 1989 to 2001 for an army installation. The spatial variability and temporal dynamics of land condition were analyzed. This algorithm modeled soil erosion as realizations of a random function by combining a set of permanent plot data and Landsat Thematic Mapper (TM) images. In addition to estimation maps of soil erosion status, we obtained the maps of uncertainties including the variance of each pixel estimate and the probability of poor land condition. The results and maps are useful tools for land managers and decision‐makers to guide military training programs and to generate management plans for sustaining training lands. Copyright © 2007 John Wiley & Sons, Ltd.     

黄土区不同土地利用方式坡面土壤含水率的空间变异性研究

为掌握不同土地利用方式下坡面土壤含水率的空间分布特征及其变异规律，利用经典统计学方法对黄土高原水蚀风蚀交错带草地和农地坡面土壤含水率的空间变异性进行了对比研究。结果表明：草地和农地的土壤含水率均值在同一土层深度下差异极显著，但二者在垂直方向、坡长方向的变异程度均为中等变异程度；草地和农地坡面土壤含水率的垂直变化特征不同，前者为降低型，后者在100 cm以上为波动型，以下为稳定型；草地和农地坡面土壤含水率均随坡长的增加呈波浪式变化规律，整体上有增加趋势；将坡面划分为5个坡长或将土层划分为4层以后，草地和农地坡面土壤含水率沿垂直方向、坡长方向的总体变化趋势均没有改变，但由于尺度的扩展获得了一些较大尺度上的水分信息。     

模拟降雨下黄土区草地灌木地土壤水分空间变化规律

利用黄土区燕沟流域42场模拟降雨下土壤水分观测数据,研究2种坡度的草地、灌木地在不同经营方式（原状地、刈割地、翻耕地）下的土壤水分对模拟降雨的响应。结果表明：1）在5次降雨补充下,依据土壤水分的标准差和变异系数指标,0-100cm土壤水分受土地经营方式影响表现为,原状草灌地土壤水分可划分为活跃层、次活跃层和相对稳定层,刈割地全剖面为相对稳定层,翻耕地可分为活跃层和相对稳定层。2）单次降雨事件则随降雨量增加,各经营方式下的水分活跃层逐渐变薄或消失,次活跃层变厚,而相对稳定层变薄,整个土壤剖面水分变化趋于一致。3）对于受高强度降雨补充的土壤水分变异性分层,建议采用更加灵敏的土壤水分标准差和变异系数判别标准：活跃层,标准差大于1.4,变异系数大于0.12;次活跃层,标准差1.4-0.9,变异系数0.12-0.08;相对稳定层,标准差小于0.9,变异系数小于0.08。4）坡度越小,土壤水分越高,坡度对草灌木地、刈割地的影响较翻耕地显著,且对50-100cm层水分影响远大于对表层0-50cm的影响。总之,降雨后土壤水分0-100cm层不断增加,且剖面土壤水分逐渐一致,土地经营方式、坡度因素对土壤水分变化强度和在不同深度土层中的表现有显著影响。     

基于土地利用和微地形的红壤丘岗区土壤水分时空变异性

在红壤丘岗区冬春两季,以网格采样法测定了红壤丘岗区一块包含茶地、旱地和林地的缓坡的地表层和深层土壤含水率,采用经典统计结合地统计方法分析了其空间变异特征。结果表明：单一土地利用下,林地土壤含水率明显高于茶地和旱地,整体采样区土壤水分变异系数明显大于单一土地利用。同一季节表层和深层土壤水分具有类似的变异趋势;土壤水分在不同利用下存在截然不同的变异特征。通过半方差分析发现,茶地－旱地交界区土壤水分空间变异低于其他地方;另一方面,茶地－旱地土壤水分不具备空间相关性。另外,采样区表现出明显的各向异性且季节性变化明显,在冬季,土地利用和微地形共同影响水分变异特征;而在春季,土地利用是土壤水分变异的主导因素。除茶地-旱地交界区冬季水分不具有空间相关性外,土壤水分整体上具有良好的变异特征和空间连续性,因此可以利用地统计学在整体采样区进行水分空间变异的研究。     

农田表层土壤养分空间变异特性研究

为给田间养分监测设施布设方法提供依据,在陕西杨凌选取2块农田,采用12 m×12 m嵌套6 m×6 m的采样方法,采集表层土壤（0～20 cm）养分数据,运用经典统计、地统计学结合Kriging插值方法,分析农田土壤养分空间变异特征。结果表明：冬小麦抽穗期与成熟期农田表层土壤全氮（TN）变异系数<10%,为弱变异,土壤有机质（SOM）、有效磷（AP）变异系数介于10%与100%之间,为中等变异,有效钾（AK）和铵态氮（NH4+-N）变异系数>100%,为强变异,成熟期硝态氮（NO3--N）由强变异转为中等变异。土壤养分最优半方差模型为球状模型,作物不同生育阶段,土壤养分空间相关性存在一定的差异,土壤SOM、TN块金系数<25%,空间相关性强烈,以结构性因素为主导;冬小麦抽穗期速效态养分块金系数介于25%与75%之间,空间相关性中等,随机性因素主导,成熟期<25%,空间相关性增强。采样密度由6 m×6 m变为12 m×12 m时,变异程度保持不变,土壤养分空间变异系数差值在0.04%～59.48%范围内,成熟期2号样地的AK除外,块金系数差值在0.065%～34.177%范围内,2种采样间距获得的土壤养分空间变异特征基本一致,建议选用12 m×12 m网格。     

Assessing scale effects on modelled soil organic carbon contents as a result of land use change in Belgium

This paper explores the influence of spatial scale on modelled projections of soil organic carbon (SOC) content. The effect of land use change (LUC) on future SOC stocks was estimated using the Rothamsted Carbon model for a small area of southern Belgium. The study assumed no management change and used a single climate change scenario. Three model experiments were used to identify how data scale affects predicted SOC stocks: (i) using European LUC datasets at a resolution of 10′ and assuming equal distribution of change within the study area, (ii) using more accurate regional data aggregated to the 10’ resolution, and (iii) using the regional data at a spatial resolution of 250 m. The results show that using coarse resolution (10′) data is inappropriate when modelling SOC changes in the study area as only the methods using precise data predict a change in SOC stocks similar to those reported in the literature. This is largely because of differences in model parameterisation. However, precisely locating LUC does not significantly affect the results. The model, using either pan‐European or region‐specific precise data predicts an average SOC increase of 1 t C ha^?1 (1990–2050), mainly resulting from afforestation of 13% of agricultural land.     

Assisting nonsoil specialists to identify soil types for land management: an approach using a soil identification key and toposequence models

Conventional soil survey information is often unclear except to specialists. An approach using soil toposequences and a soil identification key was used to aid the translation of soil survey information into a form suitable for a nonspecialist audience with a case study from Brunei. Soil Taxonomy was used to characterize the major soil types; however, to assist end users, a complementary special‐purpose soil classification system was developed in the form of a soil identification key using plain language terms in English that were also translated into Malay. Easily recognized soil features such as depth, colour and texture were used to categorize soils to match Soil Taxonomy classes. To complement the soil identification key, conceptual soil toposequence models presented the soil distribution patterns in a visual format that local land users understood. Legacy soil survey information along with a widespread distribution of 172 soil sites from 35 traverses in 16 study areas provided a dataset to develop and test soil toposequence models and the soil identification key which both proved reliable and robust. The approach demonstrated in Brunei could be applied to other countries and landscapes.     

雅鲁藏布江中游河岸交错带沙地土壤水分的空间异质性

土壤水分是制约西藏高寒河谷风沙化土地植物群落自然演替和人工促进植被恢复的重要因子之一,准确把握沙地土壤水分的分布状况,对指导正在进行的沙地植被恢复与重建具有重要实践意义。该文采用地统计学与GIS相结合的方法,以雅鲁藏布江中游河谷风沙化土地为对象,研究了河岸交错带沙地土壤水分的空间分布及不同类型沙地和沙丘部位的差异性。结果表明:1)试验地不同深度土壤含水率平均值为6.14%～14.20%,随着湿沙层深度的增加,土壤含水率平均值随之增大。各层土壤含水率均表现为强变异性。2)除0～20cm土壤含水率具有强烈的空间相关性外,其它各层土壤含水率具有中等的空间相关性。随着土层深度的增加,空间相关性减弱。不同深度土壤含水率的空间分布格局存在着较强的相关性,以20～40cm和40～60cm相关性最高。3)流动沙丘迎风坡和河滩地土壤含水率明显高于背风坡、沙砾地、沙丘顶。雅鲁藏布江河水丰枯变化、微地形和风沙运动则是造成不同类型沙地、沙丘部位土壤含水率差异的主要原因。     

沱江流域中游土壤有机质的空间变异特点及其影响因素

土壤有机质(SOM)是陆地生态系统中碳循环的重要源与汇[1-3]。其不仅能提高土壤肥力和生产力,且其对碳的固定也是人类应对大气CO2浓度升高的重要途径[4-5]。在区域尺度上,土壤有机质主要受气候、土地利用方式、地理因素如海拔高度、坡度和质地等差异的影响[6-9]。且不同自然地理条件和社会经济发展水平的区域,其土壤有机质的主要影响因素及其影响程度也会有所差异[10-12]。     

机器学习用于耕地土壤有机碳空间预测对比研究——以亚热带复杂地貌区为例

耕地土壤有机碳(SOC)是土壤质量的重要指标,也是生态系统健康的重要表征。当前机器学习(Machine Learning, ML)用于SOC数字制图日益热门,但不同算法在高空间分辨率SOC数字制图中的对比研究尚有欠缺。本研究以福建省东北部复杂地形地貌区为例,采用10m空间分辨率Sentinel-2影像数据,选取地形、气候、遥感植被变量为驱动因子,重点分析当前常用的机器学习算法——支持向量机(SupportVector Machine,SVM)、随机森林(RandomForest,RF)在SOC预测中的差异,并与传统普通克里格模型(Ordinary Kriging, OK)进行比较。结果表明:基于地形、遥感植被因子和气候因子构建的RF模型表现最佳(RMSE=2.004,r=0.897),其精度优于OK模型(RMSE=4.571, r=0.623),而SVM模型预测精度相对最低(RMSE=5.190, r=0.431);3种模型预测SOC空间分布趋势总体相似,表现为西高东低、北高南低,其中RF模型呈现的空间分异信息更加精细;最优模型反演得到耕地土壤有机碳平均含量为15.33 g·kg-1; RF模型和SVM模型变量重要性程度表明:高程和降水是影响复杂地貌区SOC空间分布的重要变量,而遥感植被因子重要性程度低于高程。     

野葛及百喜草对红壤坡地水土保持及土壤改良的效应

试验研究红壤坡地野葛水土保持和土壤改良效应结果表明,横峰野葛和百喜草可有效增大土壤持水量、土壤孔隙度和降低土壤容重,提高土壤pH值、有机质和N、P、K含量,减少土壤侵蚀量和径流量,水土保持和改良土壤效果明显,且野葛综合效果优于百喜草。     

菜地土壤剖面上重金属元素含量随时间的变化规律研究

在宜城镇蔬菜基地内选择种植时间为1a、5a、10a、15a、20a、45a的菜地序列,并选择周围的水稻田作为对照地,研究了菜地土壤中Hg、Cu、Zn、Cr、Pb 5种元素含量随种植时间的变化趋势。结果表明,在菜地的种植过程中,土壤中Hg、Cu、Zn、Cr和Pb 5种微量元素的含量有不断累积的趋势,应引起足够重视。以上元素含量随菜地利用时间的增加而累积的原因与菜地中大量投入的无机肥料（尤其是磷肥）、动物粪肥以及农药有关。此外,该文提出的土壤元素含量变化速率的概念,可以直观反映土壤中某一元素浓度的增加或减少的快慢,对预测土壤中元素浓度的变化趋势有参考价值。     

丘红壤坡耕地苎麻与花生水土保持效果对比研究

通过径流小区试验,进行了苎麻与花生水土保持效果的对比试验,重点分析降雨量、作物覆盖度、叶面积指数等农艺性状及冠层截留量与地表径流量的关系。试验从4月份作物种植后开始测定,7月底作物收获结束。结果表明,无论是地表拦蓄径流量,还是泥沙侵蚀量,苎麻处理都优于花生处理;与花生处理相比,苎麻处理的冠层截留量提高了22.9%~908.3%(p<0.01),土壤入渗率增加了16.2%~157.7%;红壤坡耕地径流量与降雨量呈显著正相关,与覆盖度和叶面积指数呈显著对数或指数负相关。     

黄河三角洲盐碱地不同利用方式土壤理化性质

为了缓解土壤盐碱性,保证土壤可持续利用,研究了黄河三角洲典型土地利用类型撂荒地、棉田、苜蓿地和梨园土壤理化性质.结果表明:棉田土壤容重较高,而孔隙度和毛管孔隙度低,由于棉田灌水压盐措施,抬高了地下水位,土壤返盐严重.苜蓿地由于管理粗放,对土壤扰动少,容重较低,孔隙度和毛管孔隙度较高,盐碱度较低;每年对苜蓿的采收显著降低了苜蓿地土壤有机质和养分含量,而豆科固氮菌的存在,使表层速效氮含量较高.梨园位于黄河三角洲土壤质地较好的区域,且有机肥料施用一定程度上缓解了土壤板结,盐碱度较低.撂荒地表层土壤理化指标均显著优于棉田,在退化土壤恢复中具有较好的效果.     

缓坡水平梯田土壤水分空间变异性

以江苏省扬州市区北部某梯田为例,分析了小于2°的缓坡水平梯田土壤含水率的空间变异特征,并针对缓坡水平梯田土壤含水率由较高田块到较低田块逐渐增加、同一级梯田内由内侧到外侧含水率逐渐减小的分布特征,提出了适合研究该种地形土壤含水率空间分布的有效方法,即趋势辅助克立格法(简记为KTAI)。该方法同时考虑了不同级梯田高程和同级田块内不同部位对土壤含水率的影响,用它对梯田土壤含水率进行插值,估计方差比传统的普通克立格法(简记为OK)大幅度降低,大大提高了估值精度,减轻了野外采样工作量,对于研究梯田土壤水分空间变异性具有重要意义,同时拓展了地质统计学理论在土壤水分空间变异性研究中的应用范围。     

黄土区采煤塌陷对土壤水力特性的影响*

通过对山西省平朔矿区塌陷区、原地貌和复垦区进行调查采样和实验室分析,研究采煤塌陷对土壤容重、含水量、田间持水量、饱和导水率和土壤崩解速率等指标的影响。结果表明:塌陷区土壤容重、含水量和田间持水量处于弱变异到中等变异区间,饱和导水率和崩解速率均为强变异;塌陷虽使土壤容重增加,但影响幅度不大;土壤含水量受塌陷影响规律不明显;田间持水量受塌陷影响明显(p0.05),较未受损地区降低6.2%~15.5%;在采煤塌陷的影响下,土壤饱和导水率和崩解速率显著增加(p0.05);复垦区土壤水力特性与原地貌没有显著差异(p0.05),且各层次之间差异性也不显著(p0.1)。