ISWC OpenIR  > 水保所知识产出(1956---)
坡面土壤水分时空变异的试验研究
贾玉华
Subtype博士
Thesis Advisor邵明安
2013-05
Degree Grantor中国科学院研究生院
Place of Conferral北京
Keyword土壤体积含水量 黄土高原 植被恢复 时空变异 空间格局
Abstract

土壤水是陆地水资源的重要组成部分,它作用于不同时空尺度下的水文、地
貌、气象和生态等各种自然过程。土壤水分含量的变化是各种尺度下水文循环和
水量平衡的关键过程。坡面是黄土高原典型的地形单元,它既是雨养农业的载体,
又是土壤侵蚀的主要发生地。以坡面为尺度研究土壤水分的变化,有助于明确黄
土高原土壤水分与植被的相互作用机制,可为该地区水土流失防治和植被恢复提
供理论支持,并为黄土高原覆被变化的效应评价提供参考。
陕西省神木县六道沟小流域地处黄土高原水蚀风蚀交错区,属于黄土高原向
毛乌素沙地过渡的生态脆弱区域。2003-2004 年,在一个远离侵蚀沟、坡度为
12-14°、坡向为西北方向的完整坡面上,建成四个大小为 5 m×61 m 的试验小区。
试验小区分别设计为柠条(Caragana Korshinskii Kom. )林地、苜蓿(Medicago
sativa Lin)草地、撂荒地和农地,每个小区安装了 11 根水平间距为 5 m、深度为
340-580 cm 不等的中子管。本文利用 2010-2012 年观测到的土壤水分数据,研究
了坡面土壤水分的时空变异规律,取得了以下试验成果:
1  四个小区土壤水分在垂直方向的变化趋势不同,水平方向的变化趋势相似
通常认为,土壤水分随时间的变化主要发生在 0-100 cm 的深度,该深度也是
植物根系主要部分集中分布的范围。通过垂直(0-100 cm)和水平两个方向上土
壤水分空间分布特征的研究,结果表明:(1)柠条林地和苜蓿草地剖面土壤上湿
下干,农地土壤上干下湿,撂荒地土壤含水量剖面分层性不太明显;(2)柠条林
地深层土壤在坡底和坡脚偏干,撂荒地坡下部不同深度土壤均偏湿,其它两个小
区土壤含水量随坡位波动较大;(3)垂直方向各小区土壤水分的强相关关系仅表
现在相邻深度之间,水平方向上各测点的剖面土壤含水量多数具有强相关关系,
小区土壤水分分布格局在垂直和水平方向均呈现一定的相似性;(4)在所考虑的
三个因素中,对平均土壤含水量的影响作用按相对大小排序依次是植被类型 > 剖面深度>坡位。
2 土壤水分空间格局的时间稳定性分析表明,最稳定的测点是低估小区平均
值的测点,小区尺度上苜蓿草地土壤水分的时间稳定性最高
土壤水分空间格局的时间稳定性分析表明,最稳定的测点是低估小区平均
值的测点,小区尺度上苜蓿草地土壤水分的时间稳定性最高
运用时间稳定性研究方法,对不同小区 0-100 cm 深度范围的土壤贮水量进行
分析,结果显示:(1)频率分布图中大多数测点,尤其是累积概率为 0.5 的测点,
在极端干湿条件下都不能保持相同的位置;(2)基于相对偏差分析,最稳定的测
点是低估小区平均值的测点,将最稳定点的测值校正后预测小区均值效果最好;
(3)通过各种方法选取的代表小区土壤水分均值的测点倾向于坡中或坡上的位
置,为随机取样策略的调整提供了一种新的思路:(4)苜蓿草地土壤水分时间稳
定性显著高于其它三个小区,植被恢复方式影响土壤水分时间稳定性可归因于植
被盖度和地上生物量的差异。
3 考虑土壤深度,影响土壤水分时间稳定性的因素按重要性排序依次为:植
被类型、土壤深度和湿润指数
考虑土壤深度,影响土壤水分时间稳定性的因素按重要性排序依次为:植
被类型、土壤深度和湿润指数
通过对土壤水分时间稳定性随剖面深度(0-100 cm)变化规律的研究,结果
发现:(1)Spearman 秩相关分析显示,柠条林地与农地剖面土壤水分时间稳定性
随深度增加而增加,苜蓿地先增加后减小,撂荒地在前三个测定日期不具有时间
稳定性特征,之后时间稳定性随深度呈增加趋势;(2)通过相对偏差法对每小区
各个深度鉴定了四种类型的代表性测点:极干点、极湿点、均值点和最稳定点;
极端干湿点在多个连续深度保持其代表性,而且其时间稳定性随深度增加;(3)
选定的三个影响土壤水分时间稳定性的因素在重要性上依次为:植被类型、土壤
深度和湿润指数;在所选取的土壤属性中,饱和导水率和容重对平均相对偏差及
其标准差分别具有显著的影响,土壤有机碳对平均相对偏差标准差也具有显著的
影响。(4)时间稳定性分析提高了对坡面土壤水分空间格局的认识。
4 将四个小区看作一个整体,坡面土壤贮水量的空间变异主要由结构性因素
引起,不同深度土壤贮水量在水平方向上的空间格局表现出巨大的差异
将四个小区看作一个整体,坡面土壤贮水量的空间变异主要由结构性因素
引起,不同深度土壤贮水量在水平方向上的空间格局表现出巨大的差异
坡面四个小区累计 44 个观测点,构成一个 24 m×60 m 的土壤水分观测网,
选取三个观测时间(2010 年 7 月、2011 年 7 月和 2012 年 7 月)、三个深度范围
的土壤贮水量(0-100 cm、100-200 cm 和 200-300 cm)进行空间变异分析,结果
表明:(1)坡面土壤贮水量因观测时间和深度范围不同而有显著性差异,土壤贮
水量为中等程度变异;(2)土壤贮水量半方差拟合以高斯模型为主,坡面不同测
定时间三个深度范围的土壤贮水量均表现出明显的空间自相关性,并呈现中等的空间依赖性,土壤贮水量的空间变异主要是由结构性因素引起,坡面土壤贮水量
空间自相关距离随深度减小,其变化范围为 14.7–18.4 m;(3)不同深度土壤贮
水量的空间格局差异巨大,与设置小区和实施植被恢复具有直接的关系,土壤水
分空间格局随时间变化发生了一定的改变,主要表现在干旱区域范围的明显扩展。
5  植被影响下小区剖面土壤水分的状况逐年变差, 10 cm 深度与其以下不同
深度土壤含水量的时间序列呈高度相关性
深度与其以下不同
深度土壤含水量的时间序列呈高度相关性
利用 0-340 cm 深度范围的土壤含水量进行时间动态分析,结果表明:(1)四
种植被类型下小区剖面土壤水分状况逐年变差,与生长季潜在蒸散量连续 3 年增
加有一定的联系;(2)四个小区中 10 cm 深度与其下深度不等土壤含水量的时间
序列呈高度相关性,柠条林地、苜蓿草地、撂荒地和农地可利用表层含水量预报
的深度范围分别为 20-70 cm,20-90 cm,20-50 cm 以及 20-70 cm;(3)土壤水分
方差与其均值的相关关系受植被类型、观测深度和观测时间影响,并不总是呈现
显著的正相关关系。
6 观测期内,柠条林地、苜蓿草地和撂荒地剖面土壤干层的干燥化程度在加
重,干层的厚度在加深
观测期内,柠条林地、苜蓿草地和撂荒地剖面土壤干层的干燥化程度在加
重,干层的厚度在加深
干层是黄土高原一种典型的土壤水文现象。利用各小区 580 cm 深度范围(每
小区 3 根中子管)的土壤含水量数据,分析四种植被类型影响下土壤干层的形成
特征和发育动态,结果表明:(1)按照最大入渗深度和最大耗水深度,可以按照
形成干层的功能将土壤剖面划分为降水补给层、干层和潜在干层;柠条林地的干
层形成于土壤剖面 100-580 cm 深度范围内;苜蓿草地干层上边界为 120 cm,下
边界低于 600 cm;撂荒地土壤干层在 160-440 cm 深度范围内;农地耗水深度高
于最大入渗深度,不具有形成干层的条件;(2)用体积含水量的形式表示田间持
水量,并将其值的 60%作为土壤稳定含水量,确定神木试验区土壤干层的水分上
限为 12%,并确定了神木试验区黄绵土土壤干层严重等级的划分标准; (3)与 2004
年植被建立之初相比较,在本试验确定的干层范围内,柠条林地土壤水分平均下
降率为 44.5%,苜蓿草地为 47.7%,撂荒地 17.5%,其中柠条林地和苜蓿草地土壤
水分平均下降率远远大于与其深度范围一致的农地,这一结果突出了土壤干层形
成过程中林草植被所起的主导作用;(4)把农地作为对照可消除其它 3 个小区干
层内的土壤蒸发量,以此得出植被建立后柠条林地、苜蓿草地和撂荒地土壤干层
每 20 cm 深度植被耗水 8.82 mm、9.68 mm 和 2.58 mm;3 种植被形成干层的能力
强弱顺序是:苜蓿草地>柠条林地>撂荒地;(5)土壤干层时间动态的研究结果表明,2010-2012 年之间,柠条林地、苜蓿草地和撂荒地剖面土壤干层的干燥化
程度在加重,干层的厚度在加深。试验期内,柠条林地形成了较稳定的极重度干
层;苜蓿草地的重度干层和中度干层都在加深,后者达到了 600 cm 以下;撂荒地
形成了中度干层,其轻度干层处于发展阶段。
关键词:土壤体积含水量;黄土高原;植被恢复;时空变异;空间格局

Other Abstract

Soil water is a main component of the terrestrial water resource. It participates in a
broad variety of natural processes (hydrological, topographical, climatic, ecological)
that act at different spatio-temporal scales. Change of soil water content is often the
center of hydrological cycle and water balance. Sloping loessial land is widely
distributed on the Loess Plateau, it not only supports the rain-fed agriculture, but also
functions in places suffering soil erosion. Research on changes of soil water content at
slope scale can help to understand the interrelations between soil water and vegetation
and provide theoretical guides for soil and water conservation as well as vegetation
restoration. Also, such research would improve the effects assessment of land cover
change induced by Grain for Green Project on the Loess Plateau.
This study was conducted on a loessial slope within the Liudaogou catchment of
Shenmu county in Shaanxi Province, China. The study area is located in the transitional
belt between the Loess Plateau and Mu Us desert. In 2003, four adjacent experimental
plots (5 m ×61 m) with different revegetation types (Korshinsk peashrub, i.e.
Caragana korshinskii Kom., purple alfalfa, i.e. Medicago sativa, natural fallow and a
grain crop of millet) were established on a uniform slope (12°- 14°) with a
northwestern aspect. The four plots had relatively intact surfaces and were located away
from eroded gullies. To facilitate measurement of soil water content, 11 aluminum probe
access tubes were installed at equal intervals of 5 m along the midline of each plot. In
July from 2010 to 2012, 15 measurement occasions of soil water content to a maximum
depth of 580 cm were taken. The data were collected to study the spatio-temporal  variability of soil water content on a loessial slope. The main conclusions were showed
as follow:
1 Soil moisture presented different vertical but similar horizontal trends in the
four vegetation type plots.
For soils of the Loess Plateau, large changes in soil water content occur within the
soil depth of 1 m at monthly and seasonal scales. Also, a significant fraction of roots is
located in the first meter soil layer at all times. In chapter 3, the distribution pattern of
soil moisture at depths from 10 cm to 100 cm was investigated and the main findings
were: (1) Soil moisture in upper layers was higher than that in lower layers in both KOP
(Korshinsk peashrub) and ALF (purple alfalfa) plots. In contrast, soil moisture trend in
MIL (cropland with millet) was opposite and NAF (natural fallow) had no similar trend
as the other three plots. (2) Soil was comparatively dry at deeper depth below the lower
parts of the KOP slope, and was moist at most depths in the counterpart of ALF plot. (3)
Strong correlations in soil moisture for adjacent soil layers, while horizontal correlation
was widely observed among soil profiles on the slope. (4) The importance of factors
influencing soil moisture was ranked as: vegetation types, soil depth and slope
positions.
2 Temporal stability analysis showed that the most stable points were those
that underestimated the mean SWS (soil water storage) of the plots and the
temporal stability was highest for ALF among all the four plots.
Temporal stability of SWS within 1 m depth was analyzed (chapter 4) using the
methods proposed by Vachaud et al. (1985). (1) According to the frequency distributions,
most measurement points did not maintain the same rank between the extreme soil
water conditions, especially for the points with probabilities of 0.5. (2) Based on the
relative difference analyses, the most stable points were those that underestimated the
mean SWS of the plots, and they were valuable for precisely estimating the mean SWS
of the experimental plots, especially when corrected by an equation incorporating
i

and
i
s . (3) the plot-average points derived from different ways tended to be on the
middle or above middle slope in the plots, which provided a practical alternative to
random sampling intended to find the representative points of the areal mean soil water
condition. (4) Results of Spearman rank correlation coefficients indicated that the  temporal stability was generally high for ALF, low for NAF, and lowest for MIL plots
while for KOP plots it was intermediate. Revegetation types thus had significant effects
on the temporal stability of SWS within the first meter of the soil profile. Revegetation
type in terms of its vegetation cover and aboveground biomass were the main factors
affecting the temporal stability of soil water.
3 Allowing for soil moisture temporal stability in profiles, vegetation type, soil
depth and the wetness index, in order of importance, had a significant effect on the
temporal stability of soil moisture.
Further research on temporal stability varying with soil depth (chapter 5) indicated
that: (1) temporal stability of the soil moisture profile expressed by Spearman rank
correlation coefficients generally increased with increasing depth in the KOP and MIL
plots, first increased and then decreased in the ALF plot and increased, but were
somewhat unstable on the first three measurement dates in the NAF plot. (2) Four types
of representative points, the driest, wettest, average moisture and most time-stable, for
various soil depths in the four plots were identified by a relative-difference technique.
Points with extreme moisture tended to remain representative at more depths than did
points with average moisture and increased in temporal stability with increasing soil
depth. (3) The correlation between MRDs and wetness index weakened with soil depth.
In contrast, the relationship of SDRD to the wetness index varied nonlinearly with soil
depth for all the plots. Vegetation type, soil depth and the wetness index, in order of
importance, had a significant effect on the temporal stability of soil moisture. Among
selected soil properties, saturated hydraulic conductivity and bulk density significantly
affected the MRD and SDRD. In addition, soil organic carbon had a significant effect
on SDRD. (4) Temporal stability analysis enhanced the recognition of spatial pattern of
soil moisture.
4 Merging the four plots as an integral slope, spatial variability of SWS was
mainly resulted from structural property, the spatial pattern of SWS in different
soil layers were different to a large extent.
Altogether 44 observation points in the four plots constitute a sampling grid of 24
m × 60 m. Using SWS data of three layers (0-100 cm, 100-200 cm and 200-300 cm) in
July of 2010, 2011 and 2012 and methods of classical statistics and geo-statistics,  chapter 6 reported the spatial variability of SWS. Results showed that: (1) the SWS was
significantly different among soil layers and observation times, the SWS had moderate
variability, and (2) Gaussian models was mainly fitted for semi-variance of SWS. The
SWS had moderate spatial dependence; spatial variability of SWS was mainly resulted
from structural property. The spatial autocorrelation distance decreased with decreasing
soil layers, ranging from 14.7-18.4 m. (4) Interpolation contour maps indicated SWS
spatial pattern were very different among the investigated soil layers, which could be
ascribed to the different vegetation restoration measures on the small area. Comparison
among different observation time indicated the dried areas expanded with time.
5 Soil moisture dynamics indicated a deteriorating water status under
influences of vegetation restoration, time series of soil moisture at 10 cm depth was
highly correlated to those in different depths for all the plots.
Soil moisture data from 10 cm to 340 cm were employed to analyze its temporal
dynamics (chapter 7). (1) Soil moisture status in all the plots deteriorated with time
increased, partly linked to the increase of potential evapotranspiration in the
corresponding periods for different year. (2) Time series of soil moisture at 10 cm depth
was highly correlated to those in different depths for all the plots. Soil moisture at
surface layer could be used to predict soil water content at other depths, i.e. 20 cm -70
cm for KOP, 20-90 cm for ALF, 20-50 cm for NAF and 20-70 cm for MIL. (3) soil
moisture variability increased with increasing soil water content, however, which was
interrupted by vegetation types, observational depths and time.
6 Soil drought aggravated in observational periods for soil moisture at a
maximum depth of 580 cm. Furthermore, the thickness of developed
dried-soil-layer (DSL) had been increased.
The DSL is a special hydrological phenomenon on the Loess Plateau. Three
observational points at a maximum depth of 580 cm in each plot were employed to
study DSL formation characteristics and its development dynamics in chapter 8. (1)
According to the maximum depth of infiltration and water consumption, functional
layers of DSL in soil profile were classified into precipitation recharge layer, DSL and
potential DSL. The DSL in KOP and NAF plot ranged from 100 cm to 580 cm, from
160 cm to 440 cm, respectively. The upper boundary of DSL in ALF plot was 120 cm, its lower boundary was beyond 580 cm. The MIL plot had not developed a DSL due to
water consumption was shallower than infiltration depth. (2) Field capacity in form of
volumetric soil water content was used to determine the threshold value of DSL, and
12% was recognized as the upper limit of DSL. Accordingly, the severity degree of DSL
was quantitively ranked. (3) Compared with the corresponding layers in 2004, mean soil
water content for DSL in 2010-2012 decreased by 44.5%, 47.7% and 17.5% for KOP,
ALF and NAF, respectively. Soil moisture drop in MIL plot was far below the level in
KOP and ALF, such result highlighted the dominant effects of vegetation in DSL
formation processes. (4) Regarding MIL as a control, the evapotranspiration could be
subtracted from other three plots. Since the plot established, SWS at every 20 cm
interval in present DSL consumed by vegetation were 8.82 mm, 9.68 mm and 2.58mm
for KOP, ALF and MIL, respectively. The ability of vegetation types to form DSL was
strong for ALF, average for KOP and weak for NAF. (5) The status of DSL in soil
profiles worsen in 2010-2012, the thickness of developed dried-soil-layer (DSL) had
been increased. Specifically, extremely severe DSL was formed in KOP plot, thickness
of severe and mediate DSL increased and reached to depth beyond our experiment,
meanwhile, mediate DSL formed in NAF and its light DSL was in process of
development.
Key Words: Volumetric Soil Water Content; the Loess Plateau; Vegetation
Restoration; Spatio-temporal Variability; Spatial Pattern 

Language中文
Document Type学位论文
Identifierhttp://ir.iswc.ac.cn/handle/361005/8972
Collection水保所知识产出(1956---)
Recommended Citation
GB/T 7714
贾玉华. 坡面土壤水分时空变异的试验研究[D]. 北京. 中国科学院研究生院,2013.
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