ISWC OpenIR  > 水保所知识产出(1956---)
黄土丘陵区小流域土壤有效水时空变异 与动态模拟研究
高晓东
Subtype博士
Thesis Advisor吴普特
2013-05
Degree Grantor中国科学院研究生院
Place of Conferral北京
Keyword土壤有效水 时空变异 时间稳定性 坡沟关系 计算模型
Abstract

雨水资源利用是缓解黄土高原水土流失和干旱缺水的有效途径,土壤有效水是黄
土高原雨水资源化潜力的重要组成部分,也是该地区生态修复和农业生产的关键水资
源。土壤有效水受气象、土壤、地形、植被等因素影响呈现较强的时空变异性,其动
态变化规律和空间结构特征尚未深入了解。针对黄土丘陵区雨水资源高效利用的迫切
需求以及土壤有效水存在时空变异的客观事实,本论文以了解黄土丘陵区小流域土壤
有效水时空变异规律为主要研究目的,在水土流失严重的陕北清涧县园则沟流域进行
土壤水分定位观测(2009-2012 年)、土壤有效水参数测定、以及地形和植被现状调查
的基础上,借助经典统计学和地统计学等方法对园则沟小流域不同尺度(坡面、沟道
和小流域)土壤有效水时空变异规律、时间稳定性特征、空间结构及其季节性特征、
坡沟土壤有效水关系、土壤有效水计算模型等进行了研究,并与相应土壤水分时空变
异规律进行了对比分析,得到如下主要研究成果:
(1)小流域坡面和沟道土壤有效水及土壤水分均表现出明显的季节性特征和年
际特征。旱季土壤有效水和土壤水分以消耗为主,含水量较低;雨季以补充为主,含
水量较高。就年际特征而言,亚表层(20 cm 以下)土壤有效水与土壤水分从 2009
年到 2012 年呈递减趋势。土壤有效水与土壤水分空间变异性差异明显,二者标准差
虽然相似,但后者变异系数是前者的 1.5-2 倍。土壤有效水与土壤水分标准差随均值
增加呈现先增大而后降低的趋势,标准差极值对应的土壤含水量为 20%左右,对应的
土壤有效含水量为 10%左右。但二者均值与变异系数关系明显不同,其中土壤有效水
均值与变异系数呈指数负相关关系。值得注意的是沟道微地形(坡脊、沟坡地和汇水
道)显著影响土壤有效水与土壤水分空间分布,其中汇水道表层土壤含水量显著
(p<0.05) 高于沟坡地和坡脊。
(2)提出时间稳定性分析新指标 RMSE,结合其他指标分析了坡面和沟道土壤
有效水及土壤水分时间稳定性,结果表明土壤有效水与土壤水分均表现出较高时间稳
定性水平,但坡面和沟道时间稳定性特征存在差异。坡面土壤有效水与土壤水分时间稳定性相关性较高,土壤水分越稳定意味着土壤有效水也越稳定,但沟道不存在这种
特征。坡面土壤有效水时间稳定性还表现出明显的尺度性。在单一土地利用尺度上,
土壤有效水与土壤水分时间稳定性特征差异较小,而在流域坡面尺度上,土壤水分时
间稳定性显著高于土壤有效水。沟道微地形也影响土壤有效水与土壤水分时间稳定
性,坡脊土壤有效水与土壤水分时间稳定性水平显著(p<0.05)高于沟坡地和汇水道。
(3)提出扩展时间稳定性概念,即通过研究区外单个样点数据估算研究区土壤
有效水或土壤水分。然后采用此扩展时间稳定性分析,结合观测算子与随机组合等方
法,定量研究了小流域坡面和沟道土壤有效水关系。其中观测算子包括三种线性算子
(LRG、MRD 和 LRS)和一种非线性算子(CDF)。总体而言,扩展时间稳定性分析
和观测算子估算精度高于随机组合方法,但不同方法具有不同的应用前提。当有前期
土壤有效水数据时,扩展时间稳定性分析和观测算子法更适合该研究区;其中不同观
测算子表现差异较大,非线性观测算子估算精度最高,而线性算子时间传递性好。当
无前期土壤有效水数据时,随机组合方法能够获得一定精度的沟道土壤有效水,并且
发现从坡面随机选取 10 个样点的估算误差与所有 59 个样点估算误差仅有微弱差异。
(4)小流域土壤有效水半方差能够用地统计学球状模型较好拟合。半方差参数
呈现明显季节性特征:对于块金值,夏季>春季>秋季;对于变程:夏季>秋季>春季;
对于空间异质比,春季>秋季>夏季。表明夏季土壤有效水空间变异水平最低但其空
间依赖性最强。普通克里格插值方法能够较好地反映小流域土壤有效水空间结构。空
间分布特征总体表现为沟道土壤有效水高于坡面土壤有效水,阴坡高于阳坡,但这种
空间分布特征随季节发生变化。在春季和夏季,土壤有效水空间分布特征主要表现为
沟道高于坡面、阴坡高于阳坡;而在秋季,则主要表现为流域上下游高,而中游偏低
的分布特征,并且坡向对其影响减弱。
(5)基于数学方法与水量平衡原理分别构建了降雨-土壤有效水模型和土壤水量
平衡模型,并分别对小流域坡面和沟道土壤有效水及土壤水分进行了模拟。结果表明,
两类模型均能较好地模拟小流域坡面和沟道土壤有效水动态变化规律,并且估算精度
相当。鉴于降雨-土壤有效水模型形式简单,所需参数较少,因此更适合研究区土壤
有效水动态变化规律模拟。基于此模型,以 2010 年初始土壤有效储水量为初始值,
分别计算 25%、50%、75%和 95%降雨频率下的沟道、坡面和小流域土壤有效储水量
(空间平均值)。结果表明沟道各个降雨频率对应的有效储水量最低,为 102.4
mm-126.6 mm;坡面最高,为 113.9 mm-138.1 mm。
本论文基于长期观测数据,分析和探讨了黄土丘陵区小流域土壤有效水时空变异规律与动态模拟的一系列科学问题,深化了对该地区小流域尺度土壤有效水时空变异
规律、空间分布格局、坡沟土壤有效水关系、以及土壤有效水模型构建与模拟的科学
认识。本研究将为黄土丘陵区小流域雨水资源化潜力评价、雨水资源高效利用、以及
植被恢复提供科学理论依据。
关键词:土壤有效水;时空变异;时间稳定性;坡沟关系;计算模型

Other Abstract

Rainwater utilization is an effective means for relieving soil-water loss and water
shortage on the Loess Plateau. Available soil moisture (ASM) is one of the major
components of rainwater potential for the Loess Plateau, and it is also critical to the
ecological restoration and agriculture of this region. In fact, the ASM is highly variable in
space and time due to the influences of meteorology, soils, topography and vegetation.
However, the spatial-temporal features of ASM are not fully understood. In order to meet
the need for efficient use of rainwater in the hilly areas of the Loess Plateau, this
dissertation focused on the spatial-temporal variability of ASM in a catchment named
Yuanzegou catchment located in Northern Shaanxi province, based on soil moisture
datasets from 2009 to 2012 and other datasets relating to soils, topography and vegetation.
By coupling methods of classical statistics, geostatistics and modeling approaches, we
investigated: (1) the spatial-temporal variability of ASM across scales (hillslope, gully and
catchment) in the catchment; (2) the temporal stability characteristics of ASM at various
scales; (3) the spatial structure of ASM and its seasonal features at catchment scale; (4) the
quantitative relations of ASM between hillslopes and gullies; (5) the modeling of the
spatial-temporal variability of ASM. The main results were listed as follows:
(1) Apparent seasonal and inter-annual features were observed for ASM and soil
moisture (SM) in hillslopes and gullies. During dry seasons, ASM and SM showed
relatively low values, while they showed relatively high values in wet seasons. For
different years, ASM and SM at subsurface layers decayed gradually from 2009 to 2012.
The ASM showed different spatial variation features with SM. The coefficient of variance
for ASM was almost two times of that for SM although similar standard deviations were
observed for them. The standard deviation for ASM and SM increased first and then  decreased with the increase of mean water contents. The mean water content at which
standard deviation peaked was ~20% for SM and ~10% for ASM. However, the
relationship between mean water contents and coefficient of variance was different for SM
and ASM. It is worth noting that the micro-topography including ridges, plane surfaces and
pipes significantly affect the spatial distribution of ASM and SM, and pipes showed the
significantly (p<0.05) high SM values as compare to ridges and plane surfaces.
(2) A new metric for identifying time stability location, named RMSE was
introduced. Time stability of ASM and SM for hillslopes and gullies were analyzed by
using the new metric and others. The results showed that both ASM and SM showed
considerable time stability, whereas the time stability features for gullies and hillslopes
were different. For sampling points at hillslopes, the time stability degree of ASM was
positively correlated with that of SM, however, this was not observed at gullies. The time
stability of ASM for hillslopes behaved differently at various scales. At the land use scale,
ASM and SM showed very similar time stability features while SM showed stronger time
stability than ASM at catchment hillslope scale. The micro-topography also significantly
affected the time stability of ASM and SM, and ridges indicated significantly (p<0.05)
higher time stability than pipes and plane surfaces.
(3) We introduced the concept of extend time stability analysis, which denotes
estimating spatial mean soil moisture contents for a study site through soil moisture values
of one single sampling location away from the study site. Then we quantitatively analyzed
the relationship of ASM between hillslopes and gullies through extended time stability
analysis, observation operators and random combination analysis. In particular, three linear
methods (LRG、MRD and LRS) and one nonlinear method (CDF matching) were used for
defining observation operators. Overall, extended time stability analysis and observation
operators showed low estimation errors than random combination method. Nevertheless,
extended time stability analysis and observation operators are applicable only when
previous ASM datasets are available. For different observation operators, linear operators
showed better temporal transferability while nonlinear method had better estimation
accuracy. However, when no previous datasets are available, random combination method
could estimate spatial means with certain accuracy, and found that there is a limited gain in
estimation accuracy when more than 10 upland locations are randomly selected.  (4) The semivariance of ASM of the Yuanzegou catchment could be well fitted by
the spherical model. The semivariance parameter showed obvious seasonal feature in terms
of nugget, sill, range, and spatial heterogeneity ratio. For nugget, the decreasing order in
light of magnitude for various seasons is summer, spring and autumn; for range, the
decreasing order is summer, autumn and spring; and for spatial heterogeneity ratio, it is
spring, autumn and summer. This indicated that spatial variability of ASM was relatively
low in summer but the spatial correlations were strong. The mapping of ASM showed that
ordinary kriging method could relatively well characterize the spatial structure of ASM at
the catchment scale. Generally, gullies showed higher ASM than hillslopes, and for
hillslopes, north-face slopes had higher ASM than south-face slopes. The spatial structure
also differed seasonally. In autumn, ASM showed apparently different spatial structure as
compare to summer and spring.
(5) We developed two models, i.e., precipitation-ASM model and soil water balance
model, for ASM modeling. The results showed that these two models could reproduce
relatively well the temporal evolutions of ASM with similar estimation accuracies.
Considering the precipitation-ASM model is needs less inputs, we recommended this
model for ASM modeling in our study site. Based on precipitation-ASM model, we
calculated the ASM storage at different precipitation frequency for gullies, hillslopes and
catchment, with the initial ASM storage in 2010 as initial input. The results showed that
gullies had the lowest ASM storage independent of precipitation frequency with values of
102.4 – 126.6 mm, while hillslopes had the highest values, from 113.9 mm -138.1 mm.
These analyses improved the understanding of ASM spatial-temporal variations,
spatial structure of ASM, the quantitative relations of ASM between gullies and hillslopes,
and the modeling of ASM. The results of this dissertation could provide insights into the
calculation and evaluation of rainwater harvesting potential, the efficient use of rainwater,
and vegetation reconstruction on the Loess Plateau.
KEY WORDS: Available soil water, Spatial-temporal variability, Time-stability,
Hillslope-gully relations, Modelling

Language中文
Document Type学位论文
Identifierhttp://ir.iswc.ac.cn/handle/361005/8975
Collection水保所知识产出(1956---)
Recommended Citation
GB/T 7714
高晓东. 黄土丘陵区小流域土壤有效水时空变异 与动态模拟研究[D]. 北京. 中国科学院研究生院,2013.
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