农田水利工程治理天津市土壤盐渍化的效果

为研究农田水利工程治理盐渍化的效果,以天津市为例,结合ArcGIS9.3与试验分析方法,分析说明农田水利建设对土壤盐渍化改良的作用。结果表明,1982-2008年,盐渍土面积由49.40×104hm2,降低到32.42×104hm2,18.76%的盐渍土完全脱盐化,其他土壤盐化程度也大大降低;2006-2010年,来自于盐渍土的新增耕地面积减少了2.54×104hm2,但有1.11×104hm2的沟渠转换成耕地;0~60 cm内的滨海盐渍土剖面中,排水体系完善的耕地,69.81%以上在轻度盐化以下,而排水体系较差的荒地,40%以上为盐土,仅14.85%在轻度盐化以下。1982-2005年,易形成盐渍化的土壤面积由65.55×104hm2,减少到49.60×104hm2,减少区域与盐渍化降低区的分布区域一致。因此,农田水利建设是通过改良盐渍土的形成环境,从而达到治理盐渍化的效果。对于沟渠分布过密的脱盐化地区,可将部分废弃沟渠纳入宜耕后备资源中,通过土地整治促进农田集中连片,进而推进高标准农田建设。     

中国盐渍土研究的发展历程与展望

盐渍土在我国广泛分布,西北、华北、东北及沿海是我国盐渍土的主要集中分布地区,耕地中也有大量盐渍化土壤分布。盐渍土是我国最主要的中低产土壤类型之一,人类活动对其作用明显。本文回顾了我国盐渍土研究工作的发展历程,分析了我国目前盐渍土相关研究工作的现状和近期主要研究工作进展,并结合目前国内外相关研究的前沿和热点问题,提出了我国盐渍土研究的展望。建议重点进行土壤盐渍化评估和预警、土壤水盐运移过程及其模拟、植物与土壤盐分相互作用机制、土壤水盐优化调控、盐碱障碍治理与修复和盐渍化的生态环境效应等方面的研究。     

盐渍土壤特征及改良措施研究进展

全球盐渍土壤面积大、分布广，且近年来在自然和人为因素等综合影响下，土壤盐渍化进程加速。盐渍化对土壤环境以及作物生长发育造成严重不良影响，盐渍土壤改良对改善土壤环境、提高作物生产力尤为重要。我国盐渍土壤占世界盐渍土壤面积近1/10，盐渍土壤复垦和土壤盐渍化防治已成为我国农业可持续发展的当务之急。因此，采取适当且具有成本优势的措施缓解盐渍土壤对作物生长的影响，已成为我国农业技术发展的重要需求。本文总结了盐渍土壤特征，从降盐措施、改良及培肥措施、生物应对措施3个方面综述了盐渍土壤改良途径，为进一步开展盐渍土壤改良研究提供理论支撑。     

黄河三角洲中重度盐渍土棉田水盐运移规律研究

为充分利用黄河三角洲中重度盐渍土资源,通过前期微咸水压盐(2 g/L),选取中度(3.10～3.90 g/kg)和重度(4.60～5.70 g/kg)盐渍土,研究了不同程度盐渍化土壤棉花种植下土壤剖面水盐运移规律。研究结果表明:微咸水压盐后可以使剖面盐分处于相对均匀分布状况;覆盖促进了棉花对膜下水分的吸收利用,中度盐渍土棉花在苗期和蕾期主要耗水层为0～40 cm土壤表层,重度盐渍土棉花主要耗水层为0～30 cm土壤表层,后期由于作物生长引起深层水分(60～100 cm)消耗,且中度盐渍土深层水分吸收要高于重度盐渍土;生育期内中度盐渍土盐分上下土层波动范围为0.80～2.00 g/kg,重度盐渍土为2.00～5.60 g/kg,膜下土壤含盐量均要低于膜外土壤含盐量,至收获期中度、重度盐渍土剖面平均脱盐率分别为62.40%和55.83%,棉花产量分别为2 129.76 kg/hm2和823.66 kg/hm2。     

秸秆覆盖对盐渍化土壤水盐影响的试验研究

研究了不同秸秆覆盖量处理对盐渍化土壤蒸发量、含水率及含盐量动态变化的影响。结果表明,（1）随着秸秆覆盖量增加,土壤蒸发量逐渐减少,当秸秆覆盖量为7 500 kg/hm2时,日蒸发量减少幅度趋于稳定。（2）秸秆覆盖量为10 500,7 500,4 500,1 500 kg/hm2时,蒸发抑制率依次为80.54%,79.01%,62.45%,37.93%。（3）随着秸秆覆盖量增加,不同土层含水率逐渐增加。当秸秆覆盖量为7 500 kg/hm2时,0—10 cm土层含水率达到最大值,比对照实验增加了9.28%;0—10 cm土层含盐量下降幅度最大,含盐量减少了3.21%。因此,秸秆覆盖盐渍土壤能够减少土壤水分蒸发损失,提高水分利用效率,抑制盐渍化土壤可溶性盐分的表聚作用,对改良盐渍化土壤具有显著效果。     

民勤绿洲膜果麻黄周围土壤盐分分布规律研究

以民勤绿洲膜果麻黄为研究对象,对其生境土壤的盐渍化类型、盐渍化程度及其盐分离子的空间分布规律进行了研究。结果表明,膜果麻黄生境土壤盐渍化程度总体以轻度盐渍化及轻度盐渍化以下为主。在垂直方向上土壤盐渍化程度随土层的加深而加重,土壤盐分含量呈明显的底聚分布特征;在水平方向上,膜果麻黄有一定的聚盐效果。在距膜果麻黄树干30 cm处,剖面0~60 cm土层土壤在轻度盐渍化以下,60~100 cm土层土壤轻度盐渍化;在距膜果麻黄树干60 cm处,剖面0~40 cm土层土壤在轻度盐渍化以下,40~100 cm土层土壤轻度盐渍化;在距膜果麻黄树干90 cm处,剖面0~80cm土层土壤在轻度盐渍化以下,80~100 cm土层土壤轻度盐渍化。而在距膜果麻黄树干30 cm处,0~10 cm土层为亚氯盐渍土,10~40 cm土层为亚硫酸盐渍土,40~80 cm土层为亚氯盐渍土,80~100 cm土层为氯盐渍土;在距膜果麻黄树干60 cm和90 cm处,0~60 cm土层为亚氯盐渍土,60~100 cm土层为氯盐渍土。同时各土层土壤阳离子以Na+为主,占到了对应土层阳离子摩尔质量的47.54%~82.57%;各土层土壤阴离子以Cl-为主,占到了对应土层阴离子摩尔质量的58.65%~84.84%,土壤盐分主要是氯化钠。     

干旱区盐渍土介电常数特性研究与模型验证

常用的土壤介电模型一般都是针对非盐渍化土壤提出来的,对于干旱区盐渍化土壤,模型对于介电常数虚部的描述与实际测量情况有一定差距。为了更好地深入研究干旱区盐渍化土壤介电常数特性,该文选择盐渍土介电模型(修正的含水含盐土壤Dobson介电模型)作为典型研究区盐渍化土壤介电常数的基础模型,模拟分析土壤介电常数对模型参数的响应,在野外实测数据的支持下验证了盐渍土介电模型的适用性。研究结果表明:1)在低频区域(0.5相似文献   

盐渍土时空变化信息的图谱可视化分析

针对盐渍土动态变化监测中,无法实现变化信息的定位可视化表达问题,该文应用地学信息图谱的分析理念,提出了表达盐渍土类型变化的时空复合单元,探讨了盐渍土时空变化信息的图谱可视化表达方法。以盐渍化比较严重的银川平原为研究区,利用2000、2004和2009年3a的卫星遥感图像,进行了土壤盐渍化遥感制图,在GIS技术支持下,获取了2000-2004年、2004-2009年2个时段的盐渍土时空变化信息图谱,实现了盐渍土时空变化信息的可视化表达。为定位分析盐渍土演化的驱动机制提供了一种新的方法。     

中国盐渍土研究：历程、现状与展望

盐渍土研究是以盐渍土和盐渍生境作为主要研究对象，以盐渍土和盐渍化的发生与演变过程、环境要素和人类活动对盐渍化的影响与作用机制、盐渍土的治理、改良和利用的理论与技术为主体的研究领域。我国盐渍土面积巨大、种类繁多，盐渍化问题突出，对农业生产和生态环境造成不同程度的影响。我国科学家提出的盐渍土“水盐调控”“水盐平衡”，“淡化肥沃层”和“障碍消减”等理论与技术方法，为发展农业生产、提高土地产能、保障粮食安全、拓展耕地资源等发挥了积极作用。近期我国在土壤盐渍化演变过程的监测与多源数据融合、土壤水盐运移过程模拟与尺度转换、盐渍农田养分循环与减损增效、盐渍障碍的生态消减、盐渍障碍微生物修复、盐渍农田灌排优化管理与边际水安全利用等方面取得了积极的进展和成果。建议今后深入开展盐渍土精准控盐的高效和安全用水、土壤盐渍障碍的绿色消减与健康保育、盐渍农田养分库容扩增与增碳减排、土壤盐渍化与区域生态的耦合响应和协同适应等方面的理论与技术研究。应面向农业、资源、生态、环境等领域和行业，致力于拓展理论和新技术的研究，为国家农业升级、粮食安全、耕地保护、生态安全、高质量发展发挥重要作用。本文回顾了我国盐渍土研究工作的...     

田块尺度苏打盐渍土盐化和碱化空间变异特征

土壤盐渍化是松嫩平原农业发展和生态环境安全面临的主要问题之一.据统计,目前松嫩平原土壤盐渍化面积约327万hm^2,占平原总面积的21%左右.研究表明：盐渍土的盐分含量和化学特征常具有高度的空间变异性.盐渍土的这种空间变异性是由土壤的非均质性和各种随时空变化的外在因素引起的.这些外在因素包括浅埋深地下水、微地貌、季节性渍涝、人类活动等.定量描述苏打盐渍土盐分空间变异特征不仅有助于理解各种外在因素在土壤盐渍化过程中的作用,深化对土壤发生盐渍化机制的认识,而且将为苏打盐渍土的改良和治理提供必要的基础数据.     

Model-Based Integrated Methods for Quantitative Estimation of Soil Salinity from Hyperspectral Remote Sensing Data:A Case Study of Seffected South African Soils

Soil salinization is a land degradation process that leads to reduced agricultural yields. This study investigated the method that can best predict electrical conductivity (EC) in dry soils using individual bands, a normalized difference salinity index (NDSI), partial least squares regression (PLSR), and bagging PLSR. Soil spectral reflectance of dried, ground, and sieved soil samples containing varying amounts of EC was measured using an ASD FieldSpec spectrometer in a darkroom. Predictive models were computed using a training dataset. An independent validation dataset was used to validate the models. The results showed that good predictions could be made based on bagging PLSR using first derivative reflectance (validation R2 = 0.85), PLSR using untransformed reflectance (validation R2 = 0.70), NDSI (validation R2 = 0.65), and the untransformed individual band at 2257 nm (validation R2 = 0.60) predictive models. These suggested the potential of mapping soil salinity using airborne and/or satellite hyperspectral data during dry seasons.     

反射光谱估算滨海土壤黏粒含量

探明反射光谱估算土壤黏粒含量的成因是实现黏粒含量测定、提高估算精度的基础。该文以江苏省滨海平原的150个土壤样品为研究对象,将测得的原始光谱数据进行平滑、一阶导数、连续统去除和倒数等数据变换,采用逐步多元线性回归(stepwise multiple linear regression,SMLR)和偏最小二乘回归(partial least squares regression,PLSR)方法估算黏粒含量,并在此基础上分析建模的影响波段,探讨反射光谱估算土壤黏粒含量的成因。结果表明,连续统去除光谱数据的SMLR分析估算精度最高,建模集和验证集决定系数分别为0.941和0.750。360~900、1 800~2 490 nm是黏粒含量的重要建模影响波段,该建模影响波段主要包括铁离子(410 nm附近)、土壤有机质(500~800 nm)、层状硅酸盐中的结晶水(1 900 nm附近)、绿泥石和蛭石等黏土矿物(2 325 nm)的吸收特征波段;PLSR分析表明,1 400 nm附近回归系数出现的双峰特征源于高岭石的双峰吸收。黏粒中的黏土矿物、黏粒对铁离子的吸附特性以及黏粒与有机质的高度相关性是实现反射光谱估算滨海土壤黏粒含量的原因。     

基于差异化光谱指数的盐渍土水分含量预测——以滨海盐土为例

以滨海盐土为研究对象,通过添加不同浓度的盐溶液并模拟蒸发过程,获取不同含水、含盐量的土壤样品,并测定土壤光谱和土壤含水量,分别运用光谱指数法和偏最小二乘回归法(PLSR)对土壤含水量进行预测。结果表明：由2027 nm和1878 nm构建的土壤水分差异化光谱指数(NDMI2027,1878)是预测土壤水分的最优指数,且适用于任何等级的盐渍化土壤,其建模集和验证集的预测结果均优于PLSR方法,验证集R2达0.99,RMSE仅为21.84 g/kg,可比较准确地预测盐渍化土壤的含水量。     

辽宁省黄土状母质发育土壤有机质含量高光谱预测模型的构建

  目的  建立辽宁省黄土状母质发育土壤有机质含量的高光谱预测模型,以便快速获取土壤样品的有机质含量。  方法  对省域内黄土状母质发育土壤进行了样品采集,获取样品有机质含量和高光谱数据;选择原始光谱及其一阶微分、二阶微分、倒数对数、倒数对数一阶微分、倒数对数二阶微分6种光谱变换数据作为自变量,与土壤有机质含量进行相关分析,选取特征波段,分别建立多元逐步线性回归（SMLR）、偏最小二乘回归（PLSR）和主成分回归（PCR）3种土壤有机质高光谱线性预测模型,并进行了支持向量机（SVM）方法的非线性模型拟合。  结果  土壤有机质含量与其光谱反射率呈负相关关系,对光谱进行不同的数学变换,可以提高土壤有机质含量与光谱反射率的相关性,其中一阶微分和二阶微分的提升效果最佳;相同光谱数据在不同模型中建模精度存在显著差异,以原始光谱反射率一阶微分为自变量的PLSR模型精度最高,建模集和验证集的决定系数（R2）分别为0.958和0.976;3种线性方法建立的最佳预测模型的检验精度为:PLSR > SMLR > PCR。  结论  PLSR模型是辽宁省黄土状母质发育土壤有机质含量的最佳高光谱预测模型,且基于特征波段的建模效果优于全波段;SVM非线性模型的预测精度较低。     

基于不同光谱变换的土壤盐含量光谱特征分析

跟踪初生盐渍土壤的微生物修复实验,采用同步实测得土壤盐含量和光谱数据,详细分析了基于34种光谱变换,修复过程中盐渍土的光谱特征。对于选取的6种光谱变换,采用全波段(400~1650 nm)和分析获得的最佳敏感波段分别建立了土壤盐含量的光谱反演PLSR(partial least squares regression)模型。研究表明,光谱变换处理使土壤盐含量与平滑后的光谱反射数据的相关性明显增强,且最佳敏感波段范围进一步聚焦。本研究得到最佳光谱变换为导数变换,基于全波段的土壤盐含量预测模型以SGSD变换效果最好,与原始光谱相比,模型的r、RMSEP分别从0.537和1.928改善到0.823和1.256。而SGSD(Log R)是基于最佳波段所建立的盐含量预测模型的有效光谱变换方法,该研究为进一步实现盐渍土中盐含量快速定量分析提供了方法和数据参考。     

Pedotransfer functions for predicting bulk density of coastal soils in East China

Soil bulk density (BD) is an important physical property and an essential factor for weight-to-volume conversion. However, BD is often missing from soil databases because its direct measurement is labor-intensive, time-consuming, and sometimes impractical, particularly on a large scale. Therefore, pedotransfer functions (PTFs) have been developed over several decades to predict BD. Here, six previously revised PTFs (including five basic functions and stepwise multiple linear regression (SMLR)) and two new PTFs, partial least squares regression (PLSR) and support vector machine regression (SVMR), were used to develop BD-predicting PTFs for coastal soils in East China. Predictor variables included soil organic carbon (SOC) and particle size distribution (PSD). To compare the robustness and reliability of the PTFs used, the calibration and prediction processes were performed 1 000 times using the calibration and validation sets divided by a random sampling algorithm. The results showed that SOC was the most important predictor, and the revised PTFs performed reasonably although only SOC was included. The PSD data were useful for a better prediction of BD, and sand and clay fractions were the second and third most important properties for predicting BD. Compared to the other PTFs, the PLSR was shown to be slightly better for the study area (the average adjusted coefficient of determination for prediction was 0.581). These results suggest that PLSR with SOC and PSD data can be used to fill in the missing BD data in coastal soil databases and provide important information to estimate coastal carbon storage, which will further improve our understanding of sea-land interactions under the conditions of ongoing global warming.     

滩涂土壤有机质含量的反射光谱估算

Rapid determination of soil organic matter (SOM) using regression models based on soil reflectance spectral data serves an important function in precision agriculture. “deviation of arch”(DOA)-based regression and partial least squares regression (PLSR) are two popular modeling approaches to predict SOM. However, few studies have explored the accuracy of the DOA-based regression and PLSR models. Therefore, the DOA-based regression and PLSR were applied to the visible near-infrared (VNIR) spectra to estimate SOM content in the case of various dataset divisions. A two-fold cross-validation scheme was adopted and repeated 10 000 times for rigorous evaluation of the DOA-based models in comparison with the widely used PLSR model. Soil samples were collected for SOM analysis in the coastal area of northern Jiangsu Province, China. The results indicated that both modelling methods provided reasonable estimates of SOM, with PLSR outperforming DOA-based regression in general. However, the performance of PLSR for the validation dataset decreased more noticeably. Among the four DOA-based models, the linear model of the DOA provided the best estimation of SOM and a cutoff of SOM content (19.76 g kg^-1), and the performance for calibration and validation datasets was consistent. As the SOM content exceeded 19.76 g kg^-1, SOM became more effective in masking the spectral features of other soil properties to a certain extent. This work confirmed that reflectance spectroscopy combined with PLSR could serve as a non-destructive and cost-efficient way for rapid determination of SOM when hyperspectral data were available. The DOA-based model, which requires only 3 bands in the visible spectra, also provided SOM estimation with acceptable accuracy.     

基于光谱吸收特征的土壤含水量预测模型研究

为了定量分析土壤含水量与反射光谱特征之间关系,并为土壤含水量速测提供理论依据。以黑土作为研究对象,测定实验室光谱反射率,利用去包络线方法提取反射光谱特征指标,建立土壤水分含量高光谱预测模型。结果表明:黑土含水量与1 420 nm、1 920 nm附近吸收谷的主要光谱特征(吸收谷深度、宽度、面积)呈显著正相关;1 920 nm附近吸收谷可作为黑土土壤水分的特征吸收谷,由其光谱特征参数预测黑土含水量;以1 920 nm附近吸收谷面积为自变量建立的一元线性回归模型预测精度高,输入量少,可以作为土壤含水量速测仪器研制的理论依据。     

Proximal soil sensing of soil texture and organic matter with a prototype portable mid‐infrared spectrometer

Recent advances in semiconductor technologies have given rise to the development of mid‐infrared (mid‐IR) spectrometers that are compact, relatively inexpensive, robust and suitable for in situ proximal soil sensing. The objectives of this research were to evaluate a prototype portable mid‐IR spectrometer for direct measurements of soil reflectance and to model the spectra to predict sand, clay and soil organic matter (SOM) contents under a range of field soil water conditions. Soil samples were collected from 23 locations at different depths in four agricultural fields to represent a range of soil textures, from sands to clay loams. The particle size distribution and SOM content of 48 soil samples were measured in the laboratory by conventional analytical methods. In addition to air‐dry soil, each sample was wetted with two different amounts of water before the spectroscopic measurements were made. The prototype spectrometer was used to measure reflectance (R) in the range between 1811 and 898 cm^?1 (approximately 5522 to 11 136 nm). The spectroscopic measurements were recorded randomly and in triplicate, resulting in a total of 432 reflectance spectra (48 samples × three soil water contents × three replicates). The spectra were transformed to log₁₀ (1/R) and mean centred for the multivariate statistical analyses. The 48 samples were split randomly into a calibration set (70%) and a validation set (30%). A partial least squares regression (PLSR) was used to develop spectroscopic calibrations to predict sand, clay and SOM contents. Results show that the portable spectrometer can be used with PLSR to predict clay and sand contents of either wet or dry soil samples with a root mean square error (RMSE) of around 10%. Predictions of SOM content resulted in RMSE values that ranged between 0.76 and 2.24%.     

基于相似光谱匹配预测土壤有机质和阳离子交换量

土壤可见光-近红外波段光谱(350~2 500 nm)包含了大量的土壤属性信息,相同类型的土壤具有相似的光谱曲线特征,但相似光谱曲线是否具有相似的属性含量?探讨此问题可为土壤光谱库的应用提供依据,从而最终服务于快速获取土壤信息技术体系的构建。该研究以安徽宣城为研究区,根据母质、地形特征和土地利用等信息,采集91个典型土壤剖面,共含400个土壤发生层样品,测定了有机质(soil organic matter,SOM)和阳离子交换量(cation exchange capacity,CEC)含量,同时采用VARIAN公司的Cary 5000分光光度计测定了土壤光谱,并将光谱数据变换为反射率(R)、反射率一阶导数(FDR)和吸收度(Log(1/R))3种形式。该文采用光谱角(spectral angle mapper,SAM)、偏最小二乘回归(partial least square regression,PLSR)和SAM-PLSR(spectral angle mapper-partial least square regression,SAM-PLSR)3种方法预测土壤SOM和CEC。SAM方法是通过对测试集104个光谱曲线与参考集的296个光谱曲线进行相似性计算,并以此实现土壤SOM和CEC含量的预测。SAM-PLSR方法以SAM算法下的匹配结果作为建模样本建立PLSR模型和进行预测分析。结果表明,具有相似光谱曲线的土壤具有相似的SOM和CEC含量,SAM算法下相似光谱匹配可直接预测SOM(R2=0.78,RPD=2.17)和CEC(R2=0.82,RPD=2.41)。PLSR方法可很好地预测SOM(R2=0.87,RPD=2.77)和CEC(R2=0.87,RPD=2.59);相较之下,SAM-PLSR方法不仅可以更加准确预测SOM(R2=0.89,RPD=3.00)和CEC(R2=0.91,RPD=3.06),而且大大减少了建模样本的数量。该研究使可见光-近红外光谱可更加高效地用于土壤属性分析,并为土壤光谱数据库的建设及应用提供技术参考。