渭干河绿洲不同土地利用类型土壤盐分的变化特征分析

土壤盐分的动态分析与监测,是实现盐渍化土地科学管理与利用的必要前提。运用GIS技术,结合地统计学方法,分析了渭干河绿洲土壤盐渍化的分布格局,探讨了不同土地利用类型下土壤盐分的变化规律。结果表明：土壤盐分离子含量随土层深度增加而减少,CO^2-₃和HCO₃^-变化不明显,整个剖面表现为：Na⁺+K⁺>Ca²⁺>Mg²⁺,SO^2-₄>Cl^->HCO₃^->CO^2-₃,具有中-强变异性,除了HCO₃^-、CO^2-₃和Ca²⁺外,其他盐分离子变异系数随深度增加而减小。不同土地利用类型的土壤含盐量具有显著差异垂向分布,耕地、荒地和草地、林地分别呈现为平均型、表聚型和底聚型盐分剖面,且各类型表层土壤（0～40 cm）含盐量依次为荒地（38.42 g·kg^-1）>草地（16.30 g·kg^-1） > 耕地（5.37 g·kg^-1） > 林地（4.62 g·kg^-1）。渭干河绿洲土壤属于重盐土类型,自然因素（蒸降比和地下水波动等）是土壤盐渍化的形成条件,而人为干扰（土地利用方式、灌排、施肥等）则促进了土壤盐渍化的发展。     

不同环境背景下的艾比湖区域土壤水盐差异性特征研究

由于不同的环境背景下环境机制不同,所以导致了水盐（主要指水分、盐分）空间变异存在很大差异,在此背景下分析艾比湖地区含水量与含盐量空间变异,有助于更加合理的了解土壤含水量与含盐量一体化规律。以艾比湖为中心把艾比湖区域分为三个靶区：绿洲、荒漠、湖区,运用统计学方法,分析三个区域的土壤水分、盐分差异性特征。结果表明：绿洲、荒漠、湖区这三个区域表层土壤盐分积聚严重,其含盐量大小依次为：荒漠→绿洲→湖区,而含水量却相反;绿洲、荒漠和湖区土壤含盐量的变异系数均在85%～150%之间,属高强度变异,含水量变异系数均介于55%～75%之间,属中强度变异。说明荒漠区域盐分含量的水平分布不均匀,空间异质性较强;而水分含量的水平相对较为均匀,空间异质性较弱。绿洲、荒漠、湖区土壤层10～20 cm与20～40 cm土壤层含盐量的存在显著性相关性（p<0.01）,即绿洲的相关系数0.913,荒漠的相关系数0.966,湖区的相关系数0.941,绿洲与湖区土壤表层与亚层含水量存在显著性相关性（p<0.01）相关系数分别为0.851 和0.908。说明绿洲与湖区土壤层0～10 cm与10～20 cm土壤含水量存在水分转移现象,荒漠区域这种现象不明显,可能与沙漠炎热地表环境和土壤性质等因素有关。研究结果揭示了艾比湖地区不同环境背景下秋季的土壤含水量与含盐量分布特征,为艾比湖地区农作物灌溉管理及土壤盐渍化治理提供了科学依据。     

干旱区绿洲荒漠带土壤水盐异质性及生态环境效应研究——以黑河中游张掖绿洲为例

对黑河中游地区典型绿洲的土壤含水量与含盐量分析表明,在无灌溉情况下,绿洲及绿洲边缘过渡带表层土壤含水量水平分异明显,由绿洲区的20%左右递减到绿洲荒漠生态过渡带的2.9%。绿洲荒漠带土壤水分变化反映了人类利用绿洲水资源的程度,在绿洲地下水资源开发过度和绿洲边缘人类活动剧烈的区域均存在着生态裂谷,对绿洲生态系统的稳定极为不利。绿洲荒漠带土壤可溶性盐分含量的水平分异表现为绿洲土壤可溶性盐分含量比绿洲荒漠生态过渡带和荒漠区低;绿洲界外区不同荒漠类型土壤含盐量变化不同,在绿洲外围沙质荒漠区,土壤含盐量较低,在绿洲外围砾质荒漠（戈壁）区,土壤含盐量明显高于绿洲区;荒漠区土壤含盐量的垂直变化表明,含盐量最高的聚集层一般不在表层,而在40～60 cm的亚表层。受土壤水盐分异的影响,绿洲外围荒漠植被类型出现分异,从高位绿洲到中位绿洲,外围区荒漠植被的耐旱性和耐盐性均增加。     

新疆铁干里克绿洲水文过程对土壤盐渍化的影响

在对塔里木河下游绿洲地表灌溉水和地下水水质特征及土壤盐分实测分析的基础上,探讨了地表水、地下水过程及其对土壤盐渍化的影响。结果显示：塔里木河下游绿洲灌区地表水矿化度与土壤表层0～50cm盐分含量呈显著正相关,与50～100cm土层含盐量相关性不显著;地下水埋深与土壤盐分含量密切相关,0～50cm表层土壤盐分含量随地下水埋深的增加而下降,其中0～20cm下降幅度最大。当地下水埋深较浅时,绿洲内土壤含盐量高,呈T型分布,盐分表聚性强,土壤盐分含量随土壤深度的增加呈下降趋势;当地下水埋深较深时,绿洲内土壤盐份呈菱形分布,中层土壤盐分高,且地下水矿化度和土壤盐分分布转折点均为6.0m。据此推断,6m是地下水盐分积聚和表层土壤盐分积累停止的临界地下水埋深。     

不同环境背景下的艾比湖区域土壤水盐差异性特征研究北大核心CSCD

由于不同的环境背景下环境机制不同,所以导致了水盐(主要指水分、盐分)空间变异存在很大差异,在此背景下分析艾比湖地区含水量与含盐量空间变异,有助于更加合理的了解土壤含水量与含盐量一体化规律。以艾比湖为中心把艾比湖区域分为三个靶区:绿洲、荒漠、湖区,运用统计学方法,分析三个区域的土壤水分、盐分差异性特征。结果表明:绿洲、荒漠、湖区这三个区域表层土壤盐分积聚严重,其含盐量大小依次为:荒漠→绿洲→湖区,而含水量却相反;绿洲、荒漠和湖区土壤含盐量的变异系数均在85%~150%之间,属高强度变异,含水量变异系数均介于55%~75%之间,属中强度变异。说明荒漠区域盐分含量的水平分布不均匀,空间异质性较强;而水分含量的水平相对较为均匀,空间异质性较弱。绿洲、荒漠、湖区土壤层10~20 cm与20~40 cm土壤层含盐量的存在显著性相关性(p<0.01),即绿洲的相关系数0.913,荒漠的相关系数0.966,湖区的相关系数0.941,绿洲与湖区土壤表层与亚层含水量存在显著性相关性(p<0.01)相关系数分别为0.851和0.908。说明绿洲与湖区土壤层0~10 cm与10~20 cm土壤含水量存在水分转移现象,荒漠区域这种现象不明显,可能与沙漠炎热地表环境和土壤性质等因素有关。研究结果揭示了艾比湖地区不同环境背景下秋季的土壤含水量与含盐量分布特征,为艾比湖地区农作物灌溉管理及土壤盐渍化治理提供了科学依据。     

开都河流域下游绿洲表层土壤盐分空间变异特征分析——以焉耆县为例

针对目前干旱区广泛存在的绿洲土壤次生盐渍化问题,基于GIS和地统计学方法,研究开都河流域下游绿洲焉耆县表层土壤的盐分空间变异特征。结果表明:1)0~10cm、10~20cm和20~30cm三层土壤盐分的半方差函数模型均符合高斯模型;随着土壤采样深度的增加,其空间变程递增,C0+C均为50%,属于中等空间相关性。2)土壤盐分在水平方向上,0~5g/kg(非盐化和轻盐化)呈片状分布,而5g/kg(中度、重度盐化和盐土)呈斑块状分布在中部和低洼地区;在垂直方向上,0~10cm土壤盐分含量最高,且随着土层深度的增加,土壤盐分递减。     

灌区间盐分变迁与耕地安全特征——以三工河流域农业绿洲为例

针对目前绿洲内部土壤盐渍化问题,以新疆三工河流域农业绿洲为研究区,运用遥感、GIS和地统计学相结合的方法研究了0~20 cm土层盐分动态特征与发展趋势。结果表明:流域空间上土壤盐分的理论变异函数拟合符合指数模型,F检验达到极显著水平。Kriging差值及其与同期的土地利用类型图叠加运算表明,整个绿洲区南部阜康灌区耕地土壤盐化面积及盐渍化作用小于北部绿洲阜北灌区,耕地土壤盐分具有显著的局地地带性分布特征,随绿洲耕地南北方向距离的增加土壤盐渍化作用增强。另外南部绿洲耕地农业灌溉具有明显的脱盐作用,随时间尺度的延长,盐渍化作用减弱;而北部绿洲土壤盐渍化作用加强,表现为积盐作用。绿洲受盐害作用的区域主要为北部(阜北灌区)绿洲,通过空间概率模型预测,在长时间范围内,土壤盐渍化依旧是制约北部绿洲耕地生产力的主要因素。通过联合运用变异函数分析、线性回归分析和空间概率分析方法的优势,有效识别了三工河流域农业绿洲空间土壤盐渍化的变化特征与变化趋势,对于认识流域空间单元土壤盐分的变迁具有重要意义。     

基于热红外光谱的干旱区土壤盐分监测研究

土壤盐渍化是新疆最常见的土地退化过程,已经严重威胁到了当地的农业生产、生态稳定和经济发展。通过对渭库绿洲土壤含盐量和土壤热红外光谱分析,探讨了土壤含盐量与热红外发射率之间的定量关系。结果表明：（1）盐渍化土壤的发射率随着含盐量的变化而发生变化,当土壤盐分增加时,发射率也随之增大。（2）土壤含盐量与热红外发射率光谱数据相关性在8.5～9.5 μm波段范围内表现尤为显著,相关系数超过0.8,最高为0.90,对应波段范围9.259～9.271 μm。（3）运用回归模型一阶导数变换形式下建模效果和预测精度都是最优的,R²达到了0.899,RMSE最小为1.734。热红外光谱技术可以反演土壤含盐量,为利用热红外遥感识别土壤盐分信息提供技术支撑。     

基于MSAVI-WI特征空间的新疆渭干河-库车河流域绿洲土壤盐渍化研究

土壤盐渍化是造成干旱区土地荒漠化及生态恶化的重要原因,及时获取大尺度高精度土壤盐渍信息是防治工作的基础。选取新疆塔里木盆地北缘渭干河—库车河流域三角洲绿洲为研究区,利用Lansat-TM数据与野外实测数据分析盐渍化土壤与修改型土壤调整植被指数(MSAVI)、湿度指数(WI)之间的关系,在此基础上提出了MSAVI-WI特征空间概念,构建了土壤盐渍化遥感监测指数模型(MWI)。结果表明:MWI与土壤表层含盐量相关性较高,其相关性为0.844,精度高于土壤盐渍监测常用的盐分指数与实测数据的相关性。MWI能较好的反映盐渍化土壤地表植被及土壤水分的组合变化,具有明确的生物物理意义,并且特征参量简单,理论上易于理解,实践上易于实现,MWI模型的构建有利于干旱区大尺度土壤盐渍化定量监测与评价工作的开展。     

塔里木河中游典型绿洲盐渍化土壤的反射光谱特征

研究盐渍化土壤的光谱特性是利用遥感技术实现在区域尺度上进行土壤盐渍化监测和评价的工作基础, 是建立地面数据和遥感数据关系的桥梁。本文以塔里木河中游典型绿洲--渭干河-库车河三角洲绿洲为研究对象, 采用光谱学技术以及多元统计相结合的方法, 研究干旱区典型绿洲盐渍化土壤的反射光谱特征。首先, 对光谱数据进行预处理(去噪、剔除水分吸收波段), 以便消除仪器本身噪声及外界条件的影响, 并且计算了部分盐渍地样本的光谱吸收特征参数, 说明相同程度的盐渍化土壤具有相似的吸收特征;其次, 研究盐渍化土壤的反射光谱与盐分因子(八大离子、电导率(EC)、含盐量(salt content)、pH、总溶解固体(TDS)等) 之间的关系, 并选择具有代表性的盐分因子与野外实测光谱数据建立定量回归模型, 通过多元线性回归分析得出含盐量、SO₄^2-、TDS、EC与原始光谱数据的相关性分别是0.746、0.908、0.798 和0.933, 达到了理想的效果。本研究对于干旱区典型绿洲盐渍土的光谱特征研究有着重要指示意义, 为发展和完善中国盐渍土理化特征的可见光-近红外反射光谱分析理论奠定科学积累, 并进一步为干旱区土壤盐渍化、沙漠化灾害等环境恶化问题的解决提供新的科学技术手段。     

三工河流域中上游绿洲土壤盐化的时空动态

针对绿洲内部土壤盐渍化发生的现状,以三工河流域中上游阜康绿洲为研究区,运用遥感与GIS技术,结合地统计学方法研究了0—20 cm土层盐分动态特征及其主导因素。结果表明:①研究区各种景观类型间转移剧烈,区域绿洲化作用强于荒漠化; ②通过对1982年和2005年土壤盐分的理论模型拟合,符合球形模型,并且F检验达到极显著水平; ③Kriging插值及其与同期的绿洲景观类型图叠加运算表明,土壤盐渍化具有向北推进的趋势,南部绿洲土壤盐化程度减弱,北部绿洲土壤盐渍化程度加重;④农业灌溉具有一定的洗盐作用,使得南部绿洲土壤盐化程度减轻;北部绿洲,由于地下水作用,使得土壤盐化程度加重。     

An integrated methodology for assessing soil salinization, a pre-condition for land desertification

Soil salinization is mainly an arid-zone problem leading to land desertification. It reduces soil quality and limits the growing of crops. The control of this problem involves inventorying, mapping, and monitoring soil salinity, which requires cost-effective, rapid, and reliable methods for determining soil salinity in the field, and rapid, specific data-processing methods. This paper shows the usefulness of an integrated methodology involving a hand-held electromagnetic sensor (Geonics-EM38) and the ESAP (Electrical conductivity or salinity, Sampling, Assessment and Prediction) software for assessing, predicting, and mapping soil salinity. The salinity of a 0.45-ha surface-irrigated plot was analysed by reading the EM38 at 161 locations, and by employing the ESAP software for calibrating the sensor, and predicting and mapping soil salinity at multiple depths. To calibrate the EM38 sensor, the electrical conductivity of the saturation extract (ECe) of 57 soil samples taken at 19 points was measured. The multiple linear regression (MLR) calibration model predicted ECe from EM38 readings with R² ranging from 0.71 to 0.95 for the multiple-depth profile. Furthermore, the MLR calibration model provided field range average estimates of soil salinity. Fifty-seven percent of the field had ECe values above 4 dS m⁻¹. The salinity levels and distribution in the root zone identified areas with inverted profiles, which revealed drainage problems. The integrated method presented is a breakthrough in the ability to accurately and rapidly assess soil salinity in agricultural lands.     

An integrated methodology for assessing soil salinization,a pre-condition for land desertification

Soil salinization is mainly an arid-zone problem leading to land desertification. It reduces soil quality and limits the growing of crops. The control of this problem involves inventorying, mapping, and monitoring soil salinity, which requires cost-effective, rapid, and reliable methods for determining soil salinity in the field, and rapid, specific data-processing methods. This paper shows the usefulness of an integrated methodology involving a hand-held electromagnetic sensor (Geonics-EM38) and the ESAP (Electrical conductivity or salinity, Sampling, Assessment and Prediction) software for assessing, predicting, and mapping soil salinity. The salinity of a 0.45-ha surface-irrigated plot was analysed by reading the EM38 at 161 locations, and by employing the ESAP software for calibrating the sensor, and predicting and mapping soil salinity at multiple depths. To calibrate the EM38 sensor, the electrical conductivity of the saturation extract (ECe) of 57 soil samples taken at 19 points was measured. The multiple linear regression (MLR) calibration model predicted ECe from EM38 readings with R² ranging from 0.71 to 0.95 for the multiple-depth profile. Furthermore, the MLR calibration model provided field range average estimates of soil salinity. Fifty-seven percent of the field had ECe values above 4 dS m⁻¹. The salinity levels and distribution in the root zone identified areas with inverted profiles, which revealed drainage problems. The integrated method presented is a breakthrough in the ability to accurately and rapidly assess soil salinity in agricultural lands.     

基于表观电导率与实测光谱的干旱区湿地土壤盐分监测

以新疆艾比湖滨盐渍化土壤为对象,利用磁感应电导仪和光谱仪测得的盐渍土表观电导率和可见光/近红外光谱数据,选取与EM38解译的土壤盐分相关性最好的光谱变换形式和特征波长,分别建立多元逐步回归、偏最小二乘回归和支持向量回归的土壤盐分监测模型。结果表明：（1）表观电导率两种模式相结合建立的盐分含量解译模型的拟合优度达到0.91,即在该区域内电磁感应技术可用于土壤盐分含量的间接监测。（2）一阶微分处理优于二阶微分,经一阶微分变换后的光谱可以较好地预测土壤盐分含量。（3）3种建模方法中,支持向量回归的建模精度最高,偏最小二乘回归和多元逐步回归次之。干旱区湖滨湿地土壤盐分含量的估测模型宜选取基于平滑后的原始一阶微分光谱数据建立的支持向量回归模型。     

Changes in Soil Salinity in the Ekhiin-Gol Oasis (Mongolia) According to Monitoring Data of 1977 and 2001

IntroductionNatural oases in the Gobi Desert arespecific ecosystems forming in the zones offresh(or slightly saline)groundwater dischargeconfined to tectonic faults[1].Until recently,theirenvironmental peculiarities remained poorlystudied.Before the 1980s,the only data on thenatural oases in the Transaltai Gobi and theirvegetation conditions were published by LavrenkoandYunatov[2].More ample and versatile data on the oasesecosystems were obtained by the Soviet-MongolianBiological Expeditio…     

Geostatistical analysis of variations in soil salinity in a typical irrigation area in Xinjiang, northwest China

Characterizing spatial and temporal variability of soil salinity is tremendously important for a variety of agronomic and environmental concerns in arid irrigation areas. This paper reviews the characteristics and spatial and temporal variations of soil salinization in the Ili River Irrigation Area by applying a geostatistical approach. Results showed that:(1) the soil salinity varied widely, with maximum value of 28.10 g/kg and minimum value of 0.10 g/kg, and was distributed mainly at the surface soil layer. Anions were mainly SO_4~(2-) and Cl~-, while cations were mainly Na~+ and Ca~(2+);(2) the abundance of salinity of the root zone soil layer for different land use types was in the following order: grassland cropland forestland. The abundance of salinity of root zone soil layers for different periods was in the following order: March June September;(3) the spherical model was the most suitable variogram model to describe the salinity of the 0–3 cm and 3–20 cm soil layers in March and June, and the 3–20 cm soil layer in September, while the exponential model was the most suitable variogram model to describe the salinity of the 0–3 cm soil layer in September. Relatively strong spatial and temporal structure existed for soil salinity due to lower nugget effects; and(4) the maps of kriged soil salinity showed that higher soil salinity was distributed in the central parts of the study area and lower soil salinity was distributed in the marginal parts. Soil salinity tended to increase from the marginal parts to the central parts across the study area. Applying the kriging method is very helpful in detecting the problematic areas and is a good tool for soil resources management. Managing efforts on the appropriate use of soil and water resources in such areas is very important for sustainable agriculture, and more attention should be paid to these areas to prevent future problems.     

干旱内流区尾闾绿洲土壤积盐的动态特征

运用遥感与GIS技术,结合地统计学方法研究了三工河流域下游阜北绿洲近23 a来表层土壤(0～20 cm)盐分动态特征及其主导因素。结果表明:①研究区景观类型间相互转换频繁,区域绿洲化进程的同时,荒漠化也在加重,并且绿洲化进程强于荒漠化; ②通过对1982年和2005年土壤盐分的理论模型拟合,符合指数模型,并且,F检验达到极显著水平; ③Kriging插值及其与同期的绿洲景观类型图进行叠加运算表明,在自然和人为作用下,区域土壤盐化程度加重,高盐区面积增加,低盐区面积减少,土壤盐分在20 g·kg-1以上的分布面积增加了15.36%,而在5～10 g·kg-1范围减少43.85%; ④水库输水灌溉是引发区域地下水位抬升的直接因素,间接导致土壤盐渍化程度的加重。     

Growth, ionic and osmotic relations of an Allenrolfea occidentalis population in an inland salt playa of the Great Basin Desert

Variation in growth, physiology and ionic relations patterns of Allenrolfea occidentalis, a perennial halophyte of dry habitats, was studied under field conditions from May 1996 to November 1997. An A. occidentalis community has a characteristic soil pH of 7·3–8·3. During the two years, the population was exposed to great variations in soil salinity, from 29 to 146 dS m⁻¹, and soil moisture, ranging from drought (9·2%) to wet (19%). The salt concentrations were significantly higher in the surface soil layers than in the subsurface layers. Seasonal changes in dry weight are directly related to soil salinity stress. Allenrolfea occidentalis had greater growth and biomass production under saline conditions. Na⁺and Cl⁻ions were accumulated in plant tissues in much greater amounts than K⁺, Ca²⁺, and Mg²⁺. Soil salinities were significantly reduced at the end of the growing season. Water potentials of the shoots decreased significantly with increasing salinity. The plant (F_v/F_mratio) was more affected by salinity and irradiation levels during the summer period.     

Remote Sensing Inversion for Simulation of Soil Salinization Based on Hyperspectral Data and Ground Analysis in Yinchuan,China

The Pingluo area, as an experimental study area in Yinchuan, has been subjected to major environmental degradation due to soil salinization problems. Soil salinization is one of the main problems of land degradation in arid and semiarid regions. In the present study, remote sensing was integrated with mathematical modeling to evaluate soil salinization adequately. To detect soil salinization, soil water content and electrical conductivity of soil samples were analyzed. The reflectance of soil samples was measured using a spectrometer (SR-3500) with 1024 bands. Indices of soil salinity, vegetation and drought were analyzed using Landsat images over the study area. Based on Landsat images, physicochemical analysis, reflectance of sensitive bands for soil salinization and environmental indices, canopy response salinity index (CRSI), perpendicular drought index (PDI) and enhanced normalized difference vegetation index (ENDVI), a new model was established for simulation and prediction of soil salinization in the study area. Correlation analyses and multiple regression methods were used to construct an accurate model. The results showed that green, blue and near-infrared light was significantly correlated with soil salinity and that the spectral parameters improved this correlation significantly. Therefore, the model was more effective when combining spectral parameters with sensitive bands with modeling. After mathematical transformation of soil reflectance, the correlations of bands sensitive to soil salinization were 0.739 and 0.7 for electrical conductivity and water content, respectively. After transformation of vegetation reflectance, the correlation coefficient of soil salinity became 0.577. After inversion of the model based on soil hyperspectral and water content, the significance became 0.871 and 0.726, respectively, which can be used to predict soil salinity and water content. The spectral soil salinity model had a coefficient of 0.739 for soil salinity prediction. Among the salinity indices, the CRSI was selected as the most significant, with R² of 0.571, whereas the R² for PDI reached only 0.484. Among the vegetation indices, the ENDVI had the highest response to soil salinity, with R² of 0.577. After scale conversion, the correlation percentages between CRSI and measured soil salinity and between ENDVI and measured soil salinity increased to 16.2% and 8.5%, respectively. Following the correlation between PDI and soil water content, the percentage of correlation increased to 11.6%. The integration of hyperspectral remote sensing, ground methods and an inversion method for salinity is a very important and effective technique for rapid and nondestructive monitoring of soil salinization.

     

民勤绿洲不同土地利用类型下土壤水盐的空间分布特征分析

以石羊河流域下游——民勤绿洲为研究区域，通过野外采样、实地调查和实验分析，对不同土地利用类型下（耕地、林地、草地、湿地、盐碱地、撂荒地和荒漠）土壤的水盐特征进行研究，结果表明研究区土壤含水率整体偏低，范围为5.35%~20.58%，土壤含盐量的平均值为47.02 g·kg^-1，盐渍化程度严重。土壤含水率和含盐量表现为中等变异性，说明其易受到气候、地形、水文地质以及人为活动的影响。不同土地利用类型下土壤水盐的垂直分布差异显著，土壤含水率在垂直方向上的变化特征较为复杂，但含盐量在垂直方向上主要表现为“表聚型”和“振荡型”。民勤绿洲各土层土壤水盐的水平分布均呈条带状分布,土壤含水率整体表现出西高东低，南高北低，而土壤含盐量则表现出相反的趋势。