土壤热参数确定方法比较与修正

土壤热参数是分析研究土壤热传递的基本参数,寻求确定热参数简单方法是研究的热点问题.该文利用自行研制的土壤热特性试验系统,测定了4种质地土壤热特性,计算了不同质地土壤在不同含水率、不同容重情况下的热扩散率,进一步推导出不同情况下的导热率,并与Campbell经验公式计算的导热率进行比较,发现计算值与实测值相差较大,并对Campbell经验公式进行修正,同时对修正经验公式进行分析、检验,并讨论此经验公式的适用范围.结果显示在体积含水率小于20%的时候,修正经验公式可以用于计算导热率.     

基于土壤物理基本参数的土壤导热率模型

土壤物理基本参数是影响土壤导热率的重要因素,为了获取土壤的颗粒组成、有机质含量与土壤导热率计算模型中参数之间的关系,该文分析了陕西省9个地区的土壤质地对土壤导热率的影响,对不同土壤导热率估算模型的准确性进行评价,并在C?té-Konrad模型和Lu-Ren模型的基础上,建立了基于土壤物理基本参数的改进模型,结果表明:改进的C?té-Konrad模型与改进的Lu-Ren模型可以用来拟合不同质地的土壤导热率,且具有较好的拟合精度,决定系数R2均在0.92以上,相对误差(relative error,Re)均低于9.6%;对于砂粒含量或粉粒含量较高的土壤导热率,改进的C?té-Konrad模型模拟结果的均方根误差(root-mean-square error,RMSE)≤0.1183、R2≥0.9259以及Re≤9.55%,均优于C?té-Konrad模型、Lu-Ren模型和改进Lu-Ren模型;对于砂粒和粉粒含量均较低的土壤导热率,改进Lu-Ren模型模拟结果的RMSE≤0.0815、R2≥0.9326,Re≤8.21%,均明显优于其他3种模型。两种改进的模型分别建立了模型参数与颗粒组成、有机质含量之间的关系,能够更加详细描述土壤物理基本参数与导热率之间的关系,并且针对不同的土壤质地,选取合适的改进模型能够更加准确地计算土壤导热率。     

基于遗传算法的土壤水分运动参数识别

土壤水分运动参数的识别是研究土壤水分运动的基础。该文以反映土壤含水率实测值和计算值吻合程度的均方差最小为优化目标,以土壤导水率和扩散率经验参数上下限为约束条件,建立了土壤水分运动参数识别的优化计算模型。采用遗传算法和田间均质土壤一维非饱和运动数值计算相结合的方法,获得土壤导水率和扩散率经验参数最优值。经验证计算,土壤含水率实测值和计算值吻合程度较高,表明这一方法是可行的。     

不同土地利用方式峰丛坡地土壤入渗特征及其模拟

喀斯特峰丛坡地的水土过程基础研究相对短缺,阻碍了相关土壤水文机理认识和适合该区模型的构建。为探明峰丛坡地上土壤入渗性能及变化过程,提出适合峰丛坡地的土壤入渗模型,通过室内一维垂直入渗试验,研究了峰丛坡地上不同土地利用方式土壤的初渗率、稳渗率及平均入渗率,并利用Horton,Philip,Kostiakov及经验通用模型拟合其入渗过程并进行评价。结果表明:(1)峰丛坡地上灌木林地的土壤砂粒含量约占50%以上,土壤渗透性能较强,而梯田旱地黏粒含量较高、有机质含量低,土壤渗透性能较差。(2)不同土地利用土壤前期入渗率均较高,为1.33～3.17cm/min,随后入渗速率急剧下降82.2%～96.2%,在20min左右达到稳定入渗率。灌木林地的前期入渗率下降幅度最大,而裸石地和梯田旱地相对缓慢。(3)Horton模型适宜于描述喀斯特峰丛坡地的土壤入渗过程,Horton模型的初始入渗率和稳定入渗率与实测值较为接近,而Kostiakov和Philip模型的拟合值与实测值存在差距。本研究为进一步认识峰丛坡地土壤水分入渗机理及构建入渗模型提供了理论依据。     

基于伴随方程法的鱼饲料热特性参数反演

比热、导热率和导温系数是鱼饲料重要的热特性参数,其在干燥及冷却工艺参数的调整、饲料湿热传递仿真模拟研究中均有重要应用。为了探究鱼饲料的热特性,同时探究反演算法求解饲料热特性的适应性,该研究以草鱼（成鱼）膨化饲料为研究对象,建立基于伴随方程法的反演模型;利用自行搭建的热传导试验装置并配合红外热像仪（测温精度±0.1 ℃）,以获得饲料试样的温度分布规律;利用此数据可反演计算含水率为11%～17%的饲料在20～80 ℃温度范围内的比热、导热率和导温系数。使用差式扫描量热仪（Differential Scanning Calorimetry,DSC）和热特性分析仪分别测量饲料的比热和导热率,并计算导温系数,将此作为实测值;将反演算法所得值作为计算值。对二者进行线性拟合,决定系数R2均大于0.980,说明比热和导热率的计算值与实测值的误差较小,结果表明基于反演算法的鱼膨化饲料热特性参数测定方法是可行的。同时,结果表明,草鱼膨化饲料在11%～17%含水率和20～80 ℃温度范围内的比热为1.710～1.840 kJ/(kg?℃)。饲料比热随温度的增大而显著增大（P<0.05）。当含水率由11%增大至17%时,饲料的比热显著增加（P<0.05）,且呈线性规律。饲料的导热率为0.086～0.148 W/(m?K),当温度由20 ℃增大至80 ℃时,草鱼膨化饲料导热率显著增大（P<0.05）;含水率对其影响同样显著（P<0.05）。饲料的导温系数为5.701～10.003 m2/s,且受温度和含水率的影响均显著（P<0.05）。研究可为鱼饲料热特性参数的测定提供一种新思路。     

吸附性土壤溶质运移参数识别的粒子群-差分算法

非饱和土壤水分和溶质运移参数(导水率、扩散率、水动力弥散系数)的识别是进行数值模拟的关键.基于垂直一维非饱和吸附性土壤水分-溶质运移方程,以溴化钾为入渗溶液,分别以土壤含水率和溶质溶度的实测值与计算值标准差最小为优化目标,建立水分-溶质运移参数识别的多目标优化模型.应用权重系数法,将这一多目标优化问题转化为单目标优化问题,采用动态权重、异步时变学习因子的粒子群算法对模型求解.通过土柱实验,测定了220、380和780 min三组时刻的土壤含水率以及钾离子浓度的空间分布值,以前两组数据识别参数,第三组数据进行验证.结果表明入渗780 min权重系数为0.5时含水率以及钾离子浓度的计算值和实测值相关系数分别为0.977和0.952,标准差分别为0.007 4、2.369,实测值和计算值吻合较好,这表明粒子群识别水分和溶质运移参数是可行的.数值模拟表明,权重越大含水率实测和计算值的相关系数越大而浓度实测值和计算值的相关系数越小.     

基于粗糙度定标的IEM模型的土壤含水率反演

为研究基于粗糙度定标的模型进行土壤含水率反演的可行性,该文利用2幅不同时相的高级合成孔径雷达ASAR影像,以经验相关长度(lopt)代替相关长度l,实现对积分方程模型IEM(integral equation model)的粗糙度定标,以改进IEM模型对后向散射系数的模拟。在此基础上模拟了后向散射系数与土壤体积含水率(Mv)、lopt、均方根高度(hRMS)的关系,以组合粗糙度Zs(hRMS2/lopt)代替lopt与hRMS,建立土壤含水率反演的经验与半经验方法。对比2个不同时相的土壤含水率反演值与实测站点观测数据表明,经验方法下应用2004年8月18日、2004年8月24日2个时相的反演值与实测值的相关系数分别为0.785、0.837,半经验方法下则分别为0.900、0.863,表明半经验方法精度更好。该研究为利用两幅不同时相的ASAR影像获取两幅土壤含水率数据提供依据。     

棉花膜下滴灌土壤水盐运移规律数值模拟

通过棉花桶栽试验,获取棉花全生育期土壤蒸发蒸腾量以及土壤含水率、含盐量变化规律。以土壤水分运动基本方程和溶质运移对流-弥散方程为基础,在考虑棉花根系吸水和土壤蒸发蒸腾条件下,对膜下滴灌棉花全生育期时段内土壤中水盐运移规律进行了数值模拟,并与实测的土壤含水率和含盐量进行了对比分析。其结果显示:土壤表层和深层的土壤含水率和含盐量模拟值与实测值均存在不同程度的偏差,而中间层土壤含水率和含盐量的模拟值较接近实测值。因此,只要能够获得足够的精确的大田实测资料,就可以将该模型应用于棉花膜下滴灌土壤水盐运移规律的实际预测。     

质地对土壤热性质的影响研究

土壤热性质是水热迁移研究中的重要参数之一。根据非稳态条件下热流方程的差分解和实测土壤温度资料计算了不同质地土壤的热扩散率，并得出了质地影响下的土壤导热率关系式。研究结果表明，对特定土壤而言，土壤导热率与含水率之间可建立幂函数关系；砂粒、粉粒和粘粒含量对土壤热性质有不同程度的影响；不同质地土壤的热性质与土壤水吸力之间存在良好的定量关系；此外，含盐土壤的导热率可表示为浓度的幂函数关系。     

土壤初始含水率和降雨强度对黏黄土入渗性能的影响

为研究初始含水率和降雨强度对土壤入渗性能的影响,采用径流-入流-出流法和双环入渗法测量比较,采用不同降雨强度（20、40和60mm／h）和3种土壤含水率（2．60％、10．4％和19．5％）进行试验比较。结果表明：土壤入渗性能随着降雨强度的增加而降低,随着初始含水率的增加而降低;双环法测量的土壤初始入渗率随着含水率增加而增加,稳定入渗率则随着含水率的增加而降低。同时,通过Kostiakov、Horton和Philip入渗模型对试验结果进行回归分析,径流-入流-出流法测量结果均优于双环法测量结果,而且Horton入渗模型回归结果优于其他人渗模型。     

不同温度下的土壤热导率模拟

土壤热导率是研究陆地表层水热盐耦合运动的基本物理参数。由于水汽潜热传热在高温下的显著作用,高温下的土壤热导率显著高于常温值。该研究的目的是建立能够有效预测高温下土壤热导率的模型。在气体扩散定律的基础上,该文结合常温土壤热导率模型,提出了一个计算高温土壤热导率的新方法。并利用热脉冲技术实际测定了不同温度、不同含水率下的土壤热导率,对新模型进行了测试验证。结果表明,Cass等的水汽运移促进因子参数依赖于土壤质地,且存在较大的不确定性。经过对该参数修正后,建立的热导率模型均能够较好地模拟出高温下的土壤热导率。     

新疆包头湖灌区农田土壤水盐热特性空间变异特征

土壤作为高度变异体,其大尺度下的土壤水盐热分布特征具有空间变异性。为了探究大尺度下的土壤水、盐、热的空间分布特征及空间变异性,以新疆包头湖区域为例,采用经典统计学和地统计学相结合的方法,对土壤水盐热参数的空间分布特征进行分析。结果表明:土壤含水率、导热率及热容量均属于中等偏弱变异程度,土壤含盐量为强变异程度;土壤含水率、含盐量、导热率的半方差函数均可用高斯模型进行拟合,热容量的半方差函数可用指数函数进行拟合;含水率、含盐量、导热率、热容量同一深度各自变量之间均具有较强的空间依赖性,随机因素占总变异程度较低,最大相关距离在2 600~3 900 m。该研究为当地农业灌溉及精细农业的生产提供一定参考。     

利用热脉冲技术测量土壤表层含水率

准确测定表层土壤水分对陆地-大气间水热交换研究具有重要意义。由于对土壤结构影响轻微,热脉冲技术在原位监测含水率方面具有较大优越性,但目前田间应用集中在5 cm以下土层。该研究利用多针热脉冲传感器测定土壤容积热容量,然后基于热脉冲含水率法和热脉冲含水率变化法分别得到了3、9、21和39 mm的土壤含水率。结果表明,与烘干法含水率比较,热脉冲含水率变化法含水率在4个深度的均方根误差分别为0.022、0.006、0.004和0.006 m3/m3,均小于相应深度上热脉冲含水率法含水率的均方根误差。另外,热脉冲含水率变化法也降低了4个热脉冲传感器测定含水率的变异性。因此,热脉冲技术能够监测表层的土壤水分动态,表层土壤含水率的均方根误差在0.022 m3/m3以内。     

重庆北碚区土壤水热耦合模型研究

以南方的土壤和气候条件为背景,在裸露土壤的非恒温模型一维非饱和水流运动方程后增加根系吸水函数项得到作物地的土壤一维非饱和水流运动方程,与土壤中非稳态热流方程构成作物地的土壤水热耦合运移模型,联合初始边界条件,采用隐式差分法进行数值求解.结果表明：该水热运移耦合模型模拟值与实测值基本吻合,其拟合精度随土层深度增加而提高.     

日光温室栽培基质有效导热系数预测模型

栽培基质为固流两相组成的多组分材料,其导热系数是日光温室热环境营造过程中重要的热参数之一,在温室地面热量的传输中起着重要的作用。为了预测日光温室生产中栽培基质的有效导热系数,以珍珠岩、蛭石、炉渣、河沙、椰糠、泥炭及腐熟牛粪与花生壳8种常用单一基质为研究对象,首先利用干燥与饱和状态下基质有效导热系数的测试结果,通过复合材料有效特性混合模型的反向计算,确定了8种单一基质的固相导热系数,得到珍珠岩、蛭石、炉渣、河沙、椰糠、泥炭及腐熟牛粪与花生壳的固相导热系数分别为0.058、0.139、0.252、0.817、0.148、0.518、0.262及0.066 W/(m·K);其次,利用复配基质有效导热系数的实测结果,通过复合材料有效特性混合模型的正向与反向计算,明确了组成固相的各组分呈并联关系排列,并确定了复配基质中固相导热系数与基质各组分体积比例的关联;进一步将复配基质在不同饱和度下的有效导热系数实测值与基于6种复合材料导热系数模型理论计算值进行比较。结果表明：并联模型适用于复配基质有效导热系数的理论计算,构建了日光温室栽培基质有效导热系数的预测模型。采用实际生产中常用的4种育苗和栽培基质在不同饱和度下的有效导热系数对所建模型进行检验,模型预测值和实测值的平均相对偏差范围为0.42%～1.76%。基于并联模型构建的有效导热系数预测模型能够较为准确的计算日光温室栽培基质在不同饱和度下的有效导热系数。     

A new equation for the soil water retention curve

The soil water retention curve is a fundamental characteristic of unsaturated zone flow and transport properties. Recent studies show that an air‐entry value is needed in a soil water retention equation in order to provide a better prediction of relative hydraulic conductivity. A new equation considering the air‐entry value is proposed to describe the soil water retention curve. The performance of the proposed equation is contrasted with a well‐supported equation by comparing measured and calculated data for 14 soils, representing various soil textures, which range from sandstone to clay. Results show that the proposed equation provides adequate characterization of the soil water retention curves. The equation for predicting relative hydraulic conductivity is derived from the proposed soil water retention equation. An empirical equation for relative hydraulic conductivity is also used. Our results show that the agreement between the predicted and measured relative hydraulic conductivities is improved by the combinations of the proposed equation and the relative hydraulic conductivity equations. The proposed equation is mathematically simple and it can easily be implemented in unsaturated flow and multiphase flow numerical models.     

森林火灾对土壤热导率影响的实验和模型研究

An understanding of soil thermal conductivity after a wildfire or controlled burn is important to land management and post-fire recovery efforts. Although soil thermal conductivity has been well studied for non-fire heated soils, comprehensive data that evaluate the long-term effect of extreme heating from a fire on the soil thermal conductivity are limited. The purpose of this study was to evaluate the long-term impact of fire on the effective thermal conductivity of soils by directly comparing fire-heated and no-fire control soils through a series of laboratory studies. The thermal conductivity was measured for ten soil samples from two sites within the Manitou Experimental Forest, Colorado, USA, for a range of water contents from saturation to the residual degree of saturation. The thermal conductivity measured was compared with independent estimates made using three empirical models from literature, including the Campbell et al.(1994), Cté and Konrad(2005), and Massman et al.(2008) models. Results demonstrate that for the test soils studied, the thermal conductivity of the fire-heated soils was slightly lower than that of the control soils for all observed water contents.Modeling results show that the Campbell et al.(1994) model gave the best agreement over the full range of water contents when proper fitting parameters were employed. Further studies are needed to evaluate the significance of including the influence of fire burn on the thermal properties of soils in modeling studies.     

Assessment of some soil thermal conductivity models via variations in temperature and bulk density at low moisture range

Simulation of heat transfer in soil under steady and unsteady situations requires reliable estimate of soil thermal conductivity (λ) at varying environmental conditions. In the current work several soil thermal conductivity predicting models including I) de Vries, II) Campbell, III) combined de Vries and Campbell and IV) de Vries-Nobre were evaluated for the four soils of coarse sand, sandy loam, loam and clay loam textured at varying in temperature and bulk density at low moisture range. Thermal conductivities measured by the cylindrical probe method served as the reference for models assessment. Results showed that approximately same thermal conductivities obtained by the five methods at low moisture range (θ ≤ 0.05 m³/m³). Also the de Vries and de Vries-Campbell models produced accurate than Campbell and de vries-Nobre models. The accuracy of the two models increased with soil compaction but decreased with temperature rise. Campbell model showed more reliability at higher (311.16 and 321.16 K) temperatures; but its accuracy declined with soil compaction in current work. It seems that assuming needle shape for the soil particles is far away from the reality whereas assuming spherical shapes may be more realistic and produced more satisfactory prediction of thermal conductivity. The compaction would alter particle arrangement and may increase the contact area of particles; and then make them behave more or less spherical shape.it seems thermal conductivity in solid particles increase via increasing in temperature. Since a modified mineral shape factor, g_m, was developed as a combination between sphere and needle according to geometric mean particle diameter as well as bulk density and temperature as modifying factors. This factor increased the accuracy of de Vries-Nobre model up to 10.37%. Regarding nonlinear regression model, moisture content, bulk density, temperature and quartz content demonstrated significant effect on soil thermal conductivity in our investigation.     

Comparing the thermal conductivity of three artificial soils under differing moisture and density conditions for use in green infrastructure

Soil-based green infrastructure has the potential to improve building thermal performance and contribute to sustainable buildings. This study compares thermal conductivity response to soil moisture of three peat-free artificial soils to evaluate their potential use within green roofs and living walls. Thermal conductivity was measured with changing soil moisture and density. All soils showed higher thermal conductivity measures with increases in soil moisture. The ‘Biochar-coconut coir compost’ had the lowest thermal conductivity measures which displayed negligible response to density changes and exhibited the highest water holding capacity. When uncompacted, ‘FabSoil’ had low thermal conductivity measures, but when compacted, its measures were considerably higher. Results show the role of density on thermal performance will be soil type dependent. Overall, findings highlight the importance of considering substrate composition, density and suggest that peat-free artificial soil substrates that contain biochar, have a higher percentage organic matter content and a finer particle texture are likely to result in lower thermal conductivity and higher soil water holding capacity. The results also showed that ThetaProbe measures (volumetric) had a high equivalence to actual soil moisture content (gravimetric), across different soil types and soil bulk densities. This finding supports the use of ThetaProbe measures as an effective method for monitoring soil moisture; with the potential for integration into irrigation control systems for green infrastructure. The findings of this paper offer the potential to improve building thermal performance by informing soil substrate choice, irrigation control and load bearing requirements in the design of green infrastructure.