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西北干旱区土壤含水量时空变化特征及土壤物理性质模拟试验研究

Spatial and Temporal Variations of Soil Water Content and Modeling of Soil Physical Properties in Arid Regions of Northwest China

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【Author in Chinese】 易小波

【Supervisor】 邵明安

【Author's Information】 西北农林科技大学, 环境科学, 2017, 博士

【Abstract in Chinese】 西北干旱区生态环境脆弱,区域内植被退化,土地沙化,土壤侵蚀严重。土壤水分是西北干旱区植物生长重要限制因子之一。充分认识西北干旱区内土壤水分时空变化规律,阐明土壤水分在干旱陆地生态系统中的意义,对干旱区生态维护以及水资源管理有重要的科学意义。本文以西北干旱区塔里木河下游和黄土高原南北样带为研究区,在不同空间尺度上(剖面-坡面-断面-样带)进行了大量的野外采样和实验观测,并结合室内化验分析,数学统计和尺度拓展等方法,系统研究了西北旱区土壤水分时空变化特征及其影响因素,探讨了不同空间尺度上土壤物理性质(容重,饱和导水率)的模拟与预测方法,对于评估影响植被恢复与生态重建的限制因子具有重要的参考价值。主要结果如下:(1)柽柳样方土壤含水量变化范围为5%~23%,属中等变异性。但除了近地下水位土壤层,其余层次的土壤含水量在时间上变化极小。土壤含水量与土壤质地高度相关,质地越细含水量越高。不同地下水埋深土壤水分剖面相似,且土壤含水量和地下水埋深二者关系并不明显。极端干旱区深根性植物特殊的用水策略导致了土壤水分独特的时间过程。我们认为在极端干旱区地下水—土壤—植物—空气系统中的水流处于稳态或者准稳态。因此,土壤含水量通常在时间上保持不变,而且在极端干旱区土壤含水量主要受土壤质地决定。(2)塔里木河下游地下水位和植被盖度随着离河道距离增加分别呈显著性对数和指数下降关系。不同质地对土壤持水性有显著差异,粉壤土的田间持水量(0.32g g-1)为沙土田间持水量(0.10g g-1)的3倍以上,前者的有效含水量约为后者的1.6倍。植被盖度受地下水位和土壤含水量的共同影响。胡杨和柽柳均具有适应极端干旱环境的能力,但二者用水策略不同。胡杨根系可以直接吸收地下水和土壤水,且在生长季有明显的水力提升现象;柽柳根系主要吸收地下水和近地下水位饱和土壤水。(3)塔河下游荒漠河岸林土壤含水量与离河道距离并没有显著线性规律。断面土壤含水量随着流域河道方向在逐渐减小。断面植被盖度随河段往下呈下降趋势。塔里木河下游“正质地效应”普遍存在。(4)在黄土高原地区,土壤干燥化程度存在明显的纬度地带性,且雨季前土壤干燥化指数的空间变异程度高于雨季后;经过雨季降水的补给,土壤干层在一定程度上得到修复,且中部地区的修复效果明显优于南部及北部地区;土壤干燥化指数剖面分布特征在雨季前、后的差异主要表现在浅层0-2.3 m土层,这主要归因于降水对浅层土壤水分的补给。(5)黄土高原南北样带0~20 cm深度土壤容重的变异为中等程度变异,20~40 cm为弱变异。状态空间方程转换系数表明,不同土层深度容重的影响因素不同,0~10cm主要为有机碳含量、黏粒和砂粒体积分数,10~20 cm为有机碳含量、黏粒和砂粒体积分数和降水量,20~40 cm为黏粒和砂粒体积分数、降水量和土地利用。状态空间模型的模拟效果均优于经典统计的多元逐步回归方程和传递函数方程,基于黏粒和砂粒体积分数、降水量和土地利用的状态空间模型可以解释样带20~40 cm容重92.3%的变异。一阶自回归状态空间模型可用于田间条件下土壤容重分布特征的预测。(6)黄土高原深剖面尺度土壤饱和导水率具有明显的空间变异性,变异程度为强变异经交叉检验,土壤饱和导水率可用球状模型进行较好拟合,变程为15m,且具有中等程度空间依赖性。研究所选取的5个可能影响因素中,饱和导水率、容重、有机碳、粉粒和黏粒在不同滞后距离上均具有空间自相关结构,滞后距离分别为8、4、8、1和2个采样间距。饱和导水率在不同的滞后距离下与有机碳和黏粒具有显著交互正相关关系,与容重和粉粒具有显著交互负相关关系。有机碳和粉粒是影响剖面尺度饱和导水率空间分布的主要因素,基于有机碳和土壤颗粒的状态空间方程对饱和导水率模拟效果较好,决定系数R2均在0.6以上,可用于田间条件下土壤饱和导水率分布特征的预测。

【Abstract】 Fragile ecological environment leads to serious problems in in arid regions of Northwest China,such as degeneration of vegetation,land desertification and soil erosion severely.Soil moisture is one of the key limiting factors controlling the growth of plants in arid regions.A better understanding of the temporal and spatial variations of soil moisture in arid regions is important for unraveling the role of soil moisture in the dryland ecosystems and will alo provide scientific value for the ecosystem maintenance and warer resource management.This study selects the lower reaches of Tarim River and North-South Transect of Loess Plateau as the study area,through the methods of combining field observation and laboratory analysis,typical statstatistic analysis and scale expansion,in order to investigate the temporal and spatial variations of soil moisture and its influencing factors,and to model and predict soil physical properties(bulk density,saturate soil hydraulic conductivity)at different spatial scales.These will have important values for evaluating the limiting factors of vegetation restoration and ecosystem reconstruction.The main results are as follows:(1)The soil moisture in the studied stand ranged from 5%~23%(g/g)and reavealed middle variability.Except in the layer close to the goundwater table,soil moisture in other layers varied little over time.Soil water contents were highly related to the soil texture,and soils exhibited higher water content when they had a higher clay fraction.The soil moisture profiles were similar even they had different groundwater depths,and there is no obvious relationship between soil water content and groundwater depth.The special water use strategies of phreatophytic species in the hyper-arid climate caused unique temporal soil moisture processes.We suggest that water flows in groundwater-soil-plant-atmosphere systems in hyper-arid regions are in steady or quasi-steady states.As a result,soil moisture generally remains constant over time,and the amount of water in the soil is mainly determined by soil texture in hyper-arid regions.(2)With the increase of the distance to the river channel,the groundwater level logarithmicly declined,and vegetation cover exponentially decreased,respectively.Soil textures had significantly impacts on soil water retention.The field capacity of silty loam(0.32 g g-1)was more than 3 folds of that of sandy soil(0.10 g g-1),and the effective water content of the former was 1.6 folds of the latter.The vegetation cover was controlled by the groundwater level and soil water content together.Populus euphratica and Tamarix has the ability to adapt to hyper-dry environment,but the water use strategies of them were different.Roots of Populus euphratica directly took up groundwater and soil water,and had the obvious hydraulic lift during the growing season.However,Tamarisk roots mainly absorbed groundwater and the saturated soil water in the layer near the groundwater level.(3)There was no significant linear relationship between the soil moisture and the distance to the river channel in the lower reaches of the Tarim River.The soil moisture content and vegetation cover in transects decreased gradually along with the direction of the river flow.The ―positive texture effect‖ was found in the lower reaches of the Tarim River,which meant higher vegetation cover occurred in soils with higher clay content.(4)The investigation of soil moisture content within 0~5 m profile across the North-South transect(86 sampling sites)on the Loess Plateau showed that soil desiccation had evident latitudinal zonality.The index of soil desiccation demonstrated higher variability before the rainy season than that after the rainy season.The water supply from precipitation alleviated soil dried layer,and this effect is more evident in the middle Loess Plateau than that in the south and north.The difference of soil desiccation index distribution in the soil profile befor and after rainy season occurred maily in the shallow layer(0~2.3 m),which is attributed to the water supply in the shallow layer by precipitation.(5)The investigation of spatial distribution of soil bulk density(BD)at different depths(0~10,10~20,20~40cm)across the North-South transect(86 sampling sites)on the Loess Plateau showed that the magnitude of BD variability in the 0~20 cm layer was moderate according to the coefficient of variations,while the BD variability in the 20~40 cm layer was weak.The key factors affecting the spatial distribution of BD differed among different soil depths.Soil organic carbon,clay and sand content were the key factors in the 0~10 cm layer;soil organic carbon,clay,sand and precipitation were the key factors in the 10~20 cm layer;while in the 20~40 cm layer,clay,sand,precipitation and land use were the key factors to affect the spatial distribution of BD along the transect in the study.State-space models were consistently more effective than multiple step wise regression functions and pedotransfer functions for estimating spatial distribution of BD.State-space model that included clay,sand,precipitation and land use showed the best simulation result,and the combination of such variables explained 92.3% of the total variation of BD.State-space models are recommended for studying spatial relations between soil bulk density and other variables on the Loess Plateau.(6)The investigation of spatial distribution of satuated hydraulic conductivity(Ks)in a layer with depth of 49 m at a vertical profile scale(96 sampling sites)in the southern Loess Plateau through classical statistics and first order autoregressive state-space modelling showed that Ks had evident spatial variability and the magnitude of Ks variability was strong.The degree of spatial dependence was moderate with range of 15 m.Ks,bulk density,organic carbon content,silt content,and clay content were auto-correlated at lag distance of 8,4,8,1,and 2 respectively.Ks had positive cross-correlations with organic carbon content and clay content,but had negative cross-correlation with bulk density and silt content.Organic carbon content and silt content were the key factoes affecting the spatial distribution of Ks on the sloping land.A combination of organic carbon content and soil particles was the best to explain the spatial variation of Ks(R2 > 0.6).The first order autoregressive state-space model is suitable for simulating the Ks distribution at the profile scale in the field.

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