SPATIAL AND TEMPORAL VARIATIONS OF SOIL MOISTURE IN WEST-CENTRAL OKLAHOMA

From May 7 to August 13, 1985, soil moisture was measured at 12 study sites located along a 200-km east-west trending transect in west-central Oklahoma. Soil moisture was sampled at three depths at each site: 15 cm, 61 cm, and 91 cm. Study site location and the time (week) of data collection were analyzed through correlation and regression analysis in order to assess their impact on soil moisture variability measured at the three sampled depths. Along the transect for the study period, soil moisture increased with depth; soil moisture also increased with depth from west to east along the transect during the sample period. The correlation between the location of the sample site and soil moisture was weak at the 15 cm depth (0.48), but was stronger at greater depths (0.78 at 61 cm; 0.65 at 91 cm). The location of the study site along the transect explained 25% of the variation in soil moisture at a 15 cm depth; 62% at a 61 cm depth; and 51% at a 91 cm depth. The time (week variable) of data collection at each sample site was less useful in explaining the variability in soil moisture than site location. Time explains 15, 23, and 16% of the variability observed in soil moisture along the transect for the depths of 15, 61, and 91 cm, respectively. A combination of time and location variables, however, explained 46% of the variability in soil moisture for all three depths. The same time and location variables explained 55%, 76%, and 52% of the variability observed in soil moisture for the three individual depths: 15, 61, and 91 cm, respectively. Unusual precipitation events affected the transect throughout the study period and diminished the impact of location as a significant explanatory variable for describing variability in soil moisture.     

路南石林红壤微生物含量对土壤CO2浓度的影响

Lunan stone forest is a kind of typical karst in China, which is mainly developed underred soil. In the winter of 1999, three study sites were chosen in stone forest national park accordingto vegetation cover, geomorphologic location and soil types. CO2 concentration was measured withGastec pump at different depths of soil (20, 40, 60 cm) and at the same time soil samples weregathered and soil properties such as soil moisture, pH, soil organic content were analyzed and thetotal number of viable microbes were counted in laboratory. In the study, dependent variable waschosen as the mean soil log (PCO2), and soil properties were chosen as the independent variables.Multiple stepwise regression analysis showed that the total amount of microbes and soil moisture arethe best indicators of the CO2 production, with the equation LOG(PCO2) = - 0.039(TNM) - 0.056(Mo) + 1.215 accounting for 86% of the variation of the soil CO2 concentration, where TNM is thetotal number of microbes in the soil and Mo is the moisture of soil sample.     

Microbial production of CO2 in red soil in Stone Forest National Park

Lunan stone forest is a kind of typical karst in China,Which is mainly developed under red soil.In the winter of 1999,three study sites were chosen in stone forest national park according to vegetation cover,geomporphologic location and soil types,CO2 concentration was measured with Gastec punp at different dephts of soil (20,40,60cm) and at the same time soil samples were gatered and soil properties such as soil moisure,pH,soil organic content were analyzed and the total nmuber of viable microbes were counted in laboratory,In the study,dependent variable was chosen as the mean soil log(PCO2),and soil properties were chosen as the independent variables.Multiple stepwise regression analysis showed that the totla amount of microbes and soil moisture are the best indicators of the CO2 production,With the equation LOG(PCO2)=-0.039(TNM)-0.056 (Mo) 1.215 accounting for 86% of the variation of the soil CO2 concentration,where TNM is the total number of microbes in teh soil and Mo is the moisture of soil sample.     

Microbial production of CO2 in red soil in Stone Forest National Park

Lunan stone forest is a kind of typical karst in China, which is mainly developed under red soil. In the winter of 1999, three study sites were chosen in stone forest national park according to vegetation cover, geomorphologic location and soil types. CO2 concentration was measured with Gastec pump at different depths of soil (20, 40, 60 cm) and at the same time soil samples were gathered and soil properties such as soil moisture, pH, soil organic content were analyzed and the total number of viable microbes were counted in laboratory. In the study, dependent variable was chosen as the mean soil log (PCO2), and soil properties were chosen as the independent variables. Multiple stepwise regression analysis showed that the total amount of microbes and soil moisture are the best indicators of the CO2 production, with the equation LOG(PCO2) = - 0.039(TNM) - 0.056(Mo) + 1.215 accounting for 86% of the variation of the soil CO2 concentration, where TNM is the total number of microbes in the soil and Mo is the moisture of soil sample.     

PRELIMINARY ANALYSIS OF SPATIAL AND TEMPORAL DISTRIBUTION OF SOIL MOISTURE ON A DEFORESTED SLOPE

Soil moisture was measured over a four-month period at 31 sample points on a 1 ha clear-cut site on southern Vancouver Island. At each sample point measurements were collected at 10-cm intervals to the base of the soil profile. The data were used to determine spatial and temporal variations in soil moisture, and to infer the most likely mechanism(s) of soil-water movement vertically through the soil profiles and laterally across the site. All soils showed an increase in moisture content through the monitoring period. There was no strong tendency for moisture content to increase downslope along the topographic gradient. All soils exhibited an increase in soil moisture at depths of 20–30 cm, followed by a decline. This zone of increased soil moisture was correlated with the main root zone, and not with any textural contrasts. Topographic and textural influences on moisture movement through the soil matrix appear to be of minor importance. Moisture appears to follow paths dictated by root systems, which do not necessarily follow the microtopography. [Key words: soil moisture, soil matrix, macropores, topography, southern Vancouver Island, degraded dystric brunisols, dry coastal western hemlock forests.]     

毛乌素沙地南缘不同活性沙丘土壤水分时空变化

以毛乌素沙地南缘风沙活动区典型的不同活性沙丘(流动沙丘、半流动沙丘、固定沙丘)为研究对象,于2011、2012年4-10月,每月2次,利用烘干法对3种沙丘迎风坡、丘顶、背风坡底部的0~100 cm深度土壤水分进行定位监测,分析了3种沙丘土壤水分时空变化特征。结果表明:土壤水分含量总体表现为固定沙丘>半流动沙丘>流动沙丘。3种沙丘平均土壤水分含量大体上都表现为秋季 >春季 >夏季。3种沙丘背风坡底部土壤水分含量最高,其次是迎风坡,丘顶最低,且迎风坡和丘顶两年平均土壤水分含量差距不大。表层0~10 cm土壤水分含量季节之间差异最大,随深度增加,土壤水分季节变异系数减小。沙丘各部位土壤水分含量垂直变异系数总体变化趋势为从春季到夏季增加,从夏季到秋季减小。土壤水分含量在0~100 cm的垂直变异系数与土壤水分含量为负相关关系,水分含量越高,土壤水分在0~100 cm之间的变化幅度越小。研究区3种沙丘土壤含水量变化水分可分为4个时期:4-5月为春季缓慢积累期,6-8月为夏季消耗期,9-11月为秋季积累期,12月到次年3月为冬季稳定期。总体上,天然植被对水分的涵养效果大于其消耗,本区降水可以维持不同活性沙丘的天然植被生长。     

1983-2019年黑龙江省春季土壤湿度时空变化特征及影响因素

春季土壤湿度是影响东北粮食产量和品质的重要因素.在气候变暖的背景下,东北春季土壤湿度如何变化,鲜有研究.本文基于1983-2019年黑龙江省22个农业气象站的土壤湿度和气象观测资料,采用方差分析、突变分析及空间分析等方法,分析20世纪80年代以来黑龙江省春季土壤湿度的时空变化特征及其影响因素.结果 表明:1983-20...     

夏季不同土壤湿度和天气背景条件下绿洲土壤温湿特征的个例分析

 利用在甘肃省酒泉金塔地区开展的“绿洲沙漠能量和水分循环观测试验(JTEX)”获得的2005年5—7月的补充观测资料,分析了在不同土壤湿度和天气背景条件下的夏季绿洲农田土壤温、湿场特征。结果表明：一般来说,对于5—40 cm深度的土壤,随着深度的增加其湿度也随之增加。5 cm、10 cm的土壤湿度具有明显的日变化,且在中午时最为湿润;20 cm土壤湿度的日变化幅度小于上两层,变化趋势却与5 cm的相反;40 cm土壤湿度的日变化不明显。晴天浅层的土壤湿度日变化大于阴天。晴天个例中,土壤湿度较大时,5 cm土壤在白天比10 cm的湿润;当土壤较为干燥时,全天浅层土壤湿度都小于较深层的。各层土壤温度在一个中心值周围分布, 40 cm深度以上土壤温度均具有明显的日变化;土壤温度的极值出现时间滞后于地表温度,离地面的距离越大,峰值出现的时间比地表温度滞后的越长,且变化幅度越小。晴天的土壤湿度越小,浅层土壤湿度日变化幅度就越大,各层土壤温度也就越高。土壤深层基本不受天气情况的影响,但受灌溉的影响较大。     

SOIL CARBON DIOXIDE CONCENTRATIONS AND CLIMATE IN A HUMID SUBTROPICAL ENVIRONMENT

Soil carbon dioxide content, temperature, and moisture were measured biweekly for one year at Pigeon Mountain, GA. Levels of soil CO₂ ranged from 0.04% to 2.4% and were highest during the growing season, lowest during the winter. Soil temperature correlated positively with soil CO₂, accounting for 90% of CO₂ variation. Soil moisture variations decreased CO₂ concentration at times of high soil water content when CO₂ was flushed downward, and also at times of low soil moisture content when CO₂ production was inhibited. A predictive model of logistic form using 14-day means of daily actual evapotranspiration fit the data well (R²= 0.83). The model also tested well against soil CO₂ data acquired in the coastal plain at Rocky Point, NC. If actual evapotranspiration rates are known, the model permits estimation of soil CO₂ without preliminary field work, and can be used for studies of karst denudation, which require soil CO₂ data for seasonal and regional comparison of solution rates.     

黄土丘陵沟壑区不同深度土壤水分对降雨的响应及其稳定性

通过采用点面结合的方法,分析黄土高原地区降雨影响下不同深度土壤水分的时空变化,从土壤水分复杂的“变异性”中提取相对的“不变性”。结果表明:20 cm以上土壤水分无明显规律,难以表征不同植被类型或空间位置上的土壤水分差异;小于30 mm的降雨基本不会引起40 cm以下土壤水分明显波动;100 cm深处,各采样点的土壤水分能在一个稳定值上保持数月时间,在大于46 mm的强降雨之后出现阶梯式抬升,之后又保持稳定状态;越往土层深处,土壤水分时空稳定性越明显,能较好的表征各植被类型或空间位置上的土壤水分差异。该研究从土壤水分的稳定性角度进行分析,对黄土高原土壤水分的地面采样设计和时空预测具有实际应用价值。     

中国土壤湿度的时空变化特征

基于中国155个农业气象观测站1981-2010年逐旬土壤湿度资料,分析了全国和12个气候区域0~50 cm逐层的土壤湿度时空分布规律,采用趋势分析和Cramér-von Mises（CVM）方法探究了土壤湿度的变化趋势及突变性。结果表明：西南、江淮、东北、江南、江汉、黄淮和华南地区各层土壤湿度均高于全国平均值,内蒙古地区最低;随着深度增加,西南地区土壤湿度增加最明显,仅青藏高原地区土壤湿度减小。不同区域0~50 cm各层土壤湿度年变化和季节变化差异明显,并具有阶段性特征,大部地区深层土壤湿度高于浅层;总体上,新疆、华南、华北、青藏高原、东北、黄淮地区1981-2010年土壤湿度减小趋势显著,其中新疆地区减小最为明显。除江淮地区外,各区域土壤湿度均存在较为明显的年际差异,突变时段主要集中在20世纪80年代后期至90年代初期、90年代后期两个时间段。     

改进的热惯量模式及遥感土壤水分

本文提出一个考虑地表显热通量及潜热通量的热惯量模式。模式利用了地面定标的方法并充分利用了热象图的空间分布信息,因而较大幅度地提高了估算土壤水分含量的精度。     

A new approach to quantifying soil temperature responses to changing air temperature and snow cover

Seasonal snow cover provides an effective insulating barrier, separating shallow soil (0.25 m) from direct localized meteorological conditions. The effectiveness of this barrier is evident in a lag in the soil temperature response to changing air temperature. The causal relationship between air and soil temperatures is largely because of the presence or absence of snow cover, and is frequently characterized using linear regression analysis. However, the magnitude of the dampening effect of snow cover on the temperature response in shallow soils is obscured in linear regressions. In this study the author used multiple linear regression (MLR) with dummy predictor variables to quantify the degree of dampening between air and shallow soil temperatures in the presence and absence of snow cover at four Greenland sites. The dummy variables defining snow cover conditions were z = 0 for the absence of snow and z = 1 for the presence of snow cover. The MLR was reduced to two simple linear equations that were analyzed relative to z = 0 and z = 1 to enable validation of the selected equations. Compared with ordinary linear regression of the datasets, the MLR analysis yielded stronger coefficients of multiple determination and less variation in the estimated regression variables.     

腾格里沙漠东南缘不同固定程度沙地土壤表层水分时空变化遥感分析

土壤表层水分是固沙植被生长的主要水分来源,其时空变化格局决定了固沙植被的稳定性和演替方向。整合被动微波和光学数据的时空分辨率优势建立模型、反演土壤表层水分,可为不同固定程度沙地固沙植被稳定性评价提供科学依据。以腾格里沙漠东南缘为研究区,选取2003-2011年生长季(5-9月)AMSR-E土壤水分产品与MODIS数据,利用归一化植被指数NDVI、地表温度T_s,采用多元回归的方法,将空间分辨率为0.25°的AMSR-E土壤水分数据降尺度为每月的1 km平均表层土壤水分的时间序列数据,结合沙丘类型数据,分析了不同沙丘类型下土壤水分的时空异质性。结果表明:流动沙地的土壤水分空间分布与整个区域的差异性高于半固定沙地和固定沙地,而在极端干旱年份,研究区的整体分异不大,但同一类型间,固定沙丘空间差异明显高于半固定沙丘和固定沙丘;3种沙地类型表层土壤平均含水量在不同月份具有相似的变化规律,即土壤含水量5-9月呈抛物线形状,先下降后上升,7月达到最低,从同一月份不同沙地类型看,研究区表层土壤水分含量依次是固定沙地>半固定沙地>流动沙地;年际土壤水分在流动沙地和半固定沙地随降雨的变化而变化,而固定沙地基本不变。     

古尔班通古特沙漠南缘干季土壤水分含量空间异质性

土壤水分含量是荒漠植被发育的主要制约因子。对古尔班通古特沙漠南缘个体、群落、丘间地0~100 cm干季土壤水分含量的空间异质性进行分析。结果表明：（1）同尺度下,土壤水分含量随土层深度增加呈显著升高趋势,且表层土壤水分含量的变异系数高于其他土层。（2）个体尺度,梭梭树干基部周围土壤水分含量在垂直和水平方向存在格局分异。垂直方向,土壤水分含量随土层深度增加呈升高趋势。水平方向,随距树干基部距离增加,坡顶土壤水分含量呈升高趋势,坡中和坡底土壤水分含量呈降低趋势,但没有显著差异。（3）梭梭群落尺度上土壤水分含量异质性较强,且呈斑块状分布。（4）地形是影响丘间地尺度土壤水分含量空间分异的主要因素,形成坡底土壤水分含量最高、坡中次之、坡顶最低的空间分布格局。     

内蒙古温带半干旱羊草草原N2O通量及其影响因素

利用静态箱 -气相色谱法于 2 0 0 1～ 2 0 0 3年对内蒙古锡林河流域羊草草原进行了连续 2年的野外定位试验 ,获得羊草草原原状群落与土壤N2 O年排放通量分别在 3 91～ 4 71μgm- 2h- 1以及 5 5 0～ 10 0 3μgm- 2 h- 1范围内变动 ,证明内蒙古温带半干旱羊草草原生态系统是大气中N2 O的源 ;系统分析了羊草草原N2 O通量的季节变化、源汇特征以及关键的环境因子对草地N2 O通量的影响等 ,建立了N2 O通量与环境因子间的回归方程 ;并利用两年连续完整的观测数据对羊草草原N2 O年排放量进行了估算     

腾格里沙漠不同类型沙丘土壤水分含量与地形-植被因子关系研究

土壤水分是沙区主要的生态限制因子,其分布受气候、地形和植被等众多因素的影响。以腾格里沙漠沙坡头地区3种类型的沙丘（固定沙丘、半固定沙丘和流动沙丘）为研究对象,利用方差分析和冗余分析（RDA）等方法对沙丘不同部位和不同深度土壤水分的分布特征及其与地形-植被因子之间的关系进行了综合分析。结果表明：（1） 不同类型沙丘上0~300 cm的土壤水分随着深度的增加而增加,表层土壤水分的波动程度大于中层和深层。（2） 固定沙丘不同部位及不同深度的土壤水分之间没有明显的差异,半固定沙丘和流动沙丘迎风坡与丘底的土壤水分高于背风坡和丘顶。（3） 固定沙丘上的土壤水分受地形-植被因子的影响较半固定沙丘和流动沙丘小,影响固定沙丘土壤水分的主要因子有坡向、高差和灌木多度。（4） 地形-植被因子与研究区绝大多数半固定沙丘和流动沙丘的土壤水分均有负相关关系。研究揭示了腾格里沙漠土壤水分的分布规律及其与地形-植被因子的关系,对制定相应的防风固沙措施以及建立科学合理的植物固沙模式有积极的指导作用。     

固沙植被区典型生物土壤结皮类型下土壤CO2浓度变化特征及其驱动因子研究

对固沙植被区典型分布的藻类结皮、藓类结皮和流沙下不同深度的土壤气体采样,主要研究和讨论了不同类型生物土壤结皮下土壤CO2浓度的变化特征,及土壤温度和土壤水分对它的影响。结果表明,藻类结皮和藓类结皮在0~40 cm处的土壤空气CO2浓度平均值基本保持在600~1 100 μmol·mol-1之间,大于同一深度流沙下土壤CO2浓度值,但三者之间的差异并不显著。土壤温度与土壤CO2浓度呈正相关关系,且在表层相关性最强,具体表现为流沙>藓类结皮>藻类结皮。土壤水分对土壤CO2浓度的影响在表层0~5 cm为流沙>藻类结皮>藓类结皮,但在下层10~40 cm处为藻类结皮>藓类结皮>流沙。     

藏北高原土壤的温湿特征

通过藏北高原两个站点(D110和安多)土壤温湿特性的分析,表明浅层土壤温度的变化幅度明显的比深层的要大,而且浅层土壤温度受地表随机天气过程的影响较大。浅层(20cm)土壤在未冻结前湿度的变化幅度不但受形成降水的地表随机天气过程的影响,而且受其下层土壤湿度状况的影响。下层土壤湿度越小,浅层(20cm)土壤湿度的变化幅度越大。土壤湿度和土壤温度之间存在着明显的相互关系,土壤的湿度状况能够影响土壤温度变化的幅度和土壤温度变化的趋势。     

黄土丘陵小流域土壤水分空间预测的统计模型

在6个土层和10次土壤含水量测定的基础上,利用土地利用与地形等6类20个环境因子变量,建立了黄土丘陵区小流域土壤水分空间预测的6种多元线性回归模型,并提出了5类13个指标对模型进行了评价与比较。研究表明,各模型组之间的差异较大,以直接回归模型组为最优,PCA线性转换回归模型组次之,DCA非线性转换回归模型组最差。在每一组内,模型之间的差异相对较小,以变量全部入选模型稍优于变量逐步筛选模型。6种模型中,通用多元线性回归模型的拟合性最好、预测精度最高,但模型结构最为复杂、需要的环境因子最多;多元线性逐步回归模型不仅拟合性和无偏性方面很好,而且结构最为简单、需要的环境变量最少,因而为最优模型