关中平原农田土壤水力参数空间分异与模拟

土壤水力参数是土壤水分和污染物迁移等陆面过程数值模拟的重要基础参数。为探明关中平原农田土壤水力参数空间分异特征,建立空间分布预测模型,在关中平原网格布设124个样点,采集根层0-20 cm原状和扰动土壤样品,利用van Genuchten模型拟合获取土壤水分特征曲线,获得残余含水量(θr)、饱和含水量(θs)以及系数α和n等土壤水力参数。采用经典统计学、地统计学和结构方程方法分析了θr、θs、α和n的空间变异特征及影响因子,建立了水力参数传递函数预测模型。结果表明:θr和α为强变异,θs为中等变异,n为弱变异。θr、θs、α和n半方差函数最佳拟合模型分别为球状模型、指数模型、指数模型和球状模型。θs和n具有强烈的空间依赖性,变程分别为32.7,54.3 km;θr和α具有中等程度空间依赖性,变程均为52.8 km。土壤质地、容重、pH、有机质和海拔是影响土壤水力参数空间分布的主要因子。基于土壤理化性质和海拔建立的水力参数传递函数模型具有较好的模拟效果,可用于关中地区大尺度农田生态系统土壤水力参数的模拟预测。     

Detachment of road surface soil by flowing water

An agricultural watershed generally consists of two land use categories, farmland and the unpaved road or path networks with different traffic frequency and size. Road surfaces are quite different from farmland soil in physical properties, resulting in it's distinguish production transportation process. Hydraulic flume experiments were conducted with the flow discharges ranging from 1 to 5 L s^− 1 and the slope gradients ranging from 8.8% to 46.6% to simulate the soil detachment process on a road surface and to develop tools in order to calculate detachment rates occurring on that road surfaces. The results illustrate that road surfaces behave characteristically in the runoff detachment and sediment delivery process due to the difference in the bulk density and functions of agricultural soils. The soil detachment rate is closely related to flow depth, slope gradient and other hydraulic parameters such as shear stress, stream power and unit stream power. Multiple non-linear regression analyses indicate that detachment rates for all roads can be accurately predicted by power functions of flow depth and slope gradient. According to the experimental results, stream power was suggested as an indicator to estimate soil detachment rate instead of shear stress in soil erosion models. However, considering the simplicity and availability, power function of flow depth and slope gradient is also recommended to predict detachment rate on the road surfaces.     

土壤持水特性参数与土壤质地尺度关系的联合多重分形分析

Soil water-retention characteristics at measurement scales are generally different from those at application scales, and there is scale disparity between them and soil physical properties. The relationships between two water-retention parameters, the scaling parameter related to the inverse of the air-entry pressure (αvG, cm-1) and the curve shape factor related to soil pore-size distribution (n) of the van Genuchten water-retention equation, and soil texture (sand, silt, and clay contents) were examined at multiple scales. One hundred twenty-eight undisturbed soil samples were collected from a 640-m transect located in Fuxin, China. Soil water-retention curves were measured and the van Genuchten parameters were obtained by curve fitting. The relationships between the two parameters and soil texture at the observed scale and at multiple scales were evaluated using Pearson correlation and joint multifractal analyses, respectively. The results of Pearson correlation analysis showed that the parameter αvG was significantly correlated with sand, silt, and clay contents at the observed scale. Joint multifractal analyses, however, indicated that the parameter αvG was not correlated with silt and sand contents at multiple scales. The parameter n was positively correlated with clay content at multiple scales. Sand content was significantly correlated with the parameter n at the observed scale but not at multiple scales. Clay contents were strongly correlated to both water-retention parameters because clay content was relatively low in the soil studied, indicating that water retention was dominated by clay content in the field of this study at all scales. These suggested that multiple-scale analyses were necessary to fully grasp the spatial variability of soil water-retention characteristics.     

基于Markov链地统计模型的区域土壤性质研究进展

土壤水力学性质的空间变异对于区域土壤水分溶质循环模拟研究至关重要。基于Markov链的条件模拟是一种能融合多源信息技术的地统计学模拟方法,与传统插值法和基于变异函数的条件模拟相比有诸多优势。目前,该方法在土壤水力学性质空间变异性领域的研究并未全面展开。实现区域土壤水力学模型参数的随机模拟,对于实现区域土壤水分运动和溶质运移的随机模拟,分析土壤水力学性质空间变异性对土壤水分运动和溶质运移模拟结果的影响,特别是参数采样点变化对土壤水分运动和溶质运移结果影响的不确定性等研究都有重要意义。本文旨在综述基于Markov链的地统计学模拟在土壤学相关领域的研究进展,以期为区域模拟中面临的参数获取难题提供帮助,为区域农业生产管理,水分高效利用,农田生态环境保护提供科学依据。     

流域尺度土壤厚度的模糊聚类与预测制图研究

基于土壤厚度与景观位置和特征之间的关系,运用模糊c均值聚类(FCM)方法对西苕溪流域的土壤厚度分布进行了空间预测。选取高程、坡度、平面曲率、剖面曲率、径流强度系数和地形湿度指数6个地形因子进行模糊聚类,根据相应的聚类参数将流域地形组合分为8类。利用部分调查获得的土壤剖面数据,结合样点属性和专家经验为典型区赋值,最后由加权平均得到流域土壤厚度预测图。验证结果表明,FCM方法可以对地形因子组合进行有效合理的分级,其预测精度较高,模型的稳定性较好,是一种低成本高效率的制图方法。该方法在土壤厚度预测方面具有一定的可靠性。     

GENOTYPIC DIFFERENCES IN ROOT MORPHOLOGY AND PHOSPHORUS UPTAKE KINETICS IN BRASSICA NAPUS UNDER LOW PHOSPHORUS SUPPLY

Application of phosphorus (P) fertilizer is important in crop production because of the low bioavailability of phosphorus to plants in both acidic and calcareous soils. Although rapeseed (Brassica napus) is generally sensitive to P deficiency, different cultivars differ widely in this respect. Differences in P uptake and utilization between two rapeseed cultivars, one P-efficient (‘97081’) and one P-inefficient (‘97009’), were evaluated in solution culture by studying the changes in root morphology and parameters of P uptake kinetics in response to low-P stress. The P-efficient cultivar had lower Km and Cmin values and higher Vmax and developed longer and denser lateral root hair with greater number of root tips and branches under low-P stress, which resulted in a better developed root system and more efficient uptake of P. That, in turn, led to higher concentration and accumulation of P in the plants, culminating in higher biomass production. However, P utilization efficiency (biomass production per unit P accumulated in plant) of the P-efficient ‘97081’ was lower than that of ‘97009’ when P was deficient. These results suggest that P efficiency in rapeseed is due to a better developed root system as well as efficient uptake of P.     

基于CFD的养殖污水净化内循环流化床反应器结构优化

针对水产养殖污水净化对内循环流化床反应器的相关要求及流化状态下反应器结构、操作参数与相流体力学行为的密切关系,该文利用构建的描述不同结构、操作参数反应器气液两相流动的计算流体力学数学模型,分析了不同结构、操作参数下反应器液体流场、液体循环流量、气含率的变化规律,得到了对于内径200 mm、底部采用均孔布气盘的反应器,在表观气速为0.5~2.5 cm/s时,导流筒与反应器的内径比0.5,导流筒高度与反应器内径比6,导流筒下端到反应器底部距离50 mm,导流筒上端到液面距离100 mm为最优值;针对液体循环流量,使用相关数学模型求解理论值并与试验值进行比对,通过偏差分析探究了数学模型应用的局限性;使用MATLAB最小二乘法拟合了反应器在最优结构参数下表观气速与液体循环流量、气含率的关系,验证了拟合公式的精确性。该研究为内循环流化床反应器在水产养殖污水处理中的设计应用提供理论和技术参考。     

基于离散元的西北旱区农田土壤颗粒接触模型和参数标定

为了解决利用离散元法模拟土壤作业过程在预测农具阻力和土壤动态运动时存在失真等问题,整合延迟弹性模型(hysteretic spring contact model,HSCM)和线性内聚力模型(liner cohesion model,LCM)优势建立西北旱区农田土壤模型,以不同参数(静摩擦系数、动摩擦系数和内聚强度)组合下仿真得到的土壤仿真堆积角为响应值,基于Box-Behnken试验法建立回归模型,并根据该回归模型进行了参数预测并验证,对17组土壤仿真堆积角方差分析表明:静摩擦系数、动摩擦系数、动摩擦系数和抗剪强度的交互项、动摩擦系数的二次项对仿真堆积角的影响极显著;静摩擦系数和动摩擦系数的交互项、静摩擦系数的二次项对仿真堆积角的影响显著。使用预测的参数进行6种不同含水率土壤直接剪切仿真和试验对比可知,当含水率为1%~20%时,仿真与试验间的抗剪强度相对误差为1.18%~9.31%,仿真与试验间的内摩擦角相对误差为0.55%~4.07%。对仿真和试验鸭嘴插入阻力数据进行分析可知,仿真与试验曲线在入土距离处于0~50 mm期间时,但仿真入土阻力曲线波动较大,仿真和试验阻力走势基本一致,玉米直插穴播最深处50 mm处的仿真和试验入土阻力相对误差为0.928%,可利用此时的入土阻力分析直插鸭嘴结构对强度的影响。     

基于高光谱的冬油菜植株氮素积累量监测模型

为无损和定量研究高光谱技术在冬油菜植株氮素积累量(PNA,plant nitrogen accumulation)时空变化监测的适宜性及准确性,该文以两年田间氮肥水平试验为基础,采用单变量线性和非线性回归方法,建立基于特征光谱参数的冬油菜P NA高光谱估算模型。结果表明,采用比值光谱的方法可显著提高冬油菜冠层光谱反射率与PNA间的相关性,其最佳的波段组合为1 259 nm与492 nm处光谱反射率比值(R1259/R492),决定系数R2为0.85。高光谱参数间,以比值植被指数(RVI-5)、归一化光谱指数(NDSI)、线性内插法红边位置(REIP)、三角植被指数(TVI)、742 nm处一阶微分光谱值(FD742)和红边面积(SDR)等光谱参数与PNA相关性较好(平均R2和标准误SE分别为0.69和42.70),且以FD742表现最优(R2=0.79,SE=35.66)。精度分析结果显示,以光谱参数R1259/R492和FD742为自变量的指数方程模型作为高光谱监测油菜PNA的最佳模型,各生育期Noise Equivalent(NE)均较低且表现稳定,同时模型估测精度较高,R2分别为0.98和0.98,相对均方根误差RRMSE分别为0.73和0.72,相对误差MRE分别为14.42%和10.31%。该方法为快捷和精确评估冬油菜PNA提供了新的研究思路。     

基于无人机数码影像的冬小麦叶面积指数探测研究

叶面积指数(LAI)是评价作物长势的重要农学参数之一,利用遥感技术准确估测作物叶面积指数(LAI)对精准农业意义重大。目前,数码相机与无人机系统组成的高性价比遥感监测系统在农业研究中已取得一些成果,但利用无人机数码影像开展作物LAI估测研究还少有尝试。为论证利用无人机数码影像估测冬小麦LAI的可行性,本文以获取到的3个关键生育期(孕穗期、开花期和灌浆期)冬小麦无人机数码影像为数据源,利用数字图像转换原理构建出10种数字图像特征参数,并系统地分析了3个生育期内两个冬小麦品种在4种氮水平下的LAI与数字图像特征参数之间的关联性。结果表明,在LAI随生育期发生变化的同时,10种数字图像特征参数中R/(R+G+B)和本文提出的基于无人机数码影像红、绿、蓝通道DN值以及可见光大气阻抗植被指数(VARI)计算原理构建的数字图像特征参数UAV-based VARIRGB也有规律性变化,说明冬小麦的施氮差异不仅对LAI有影响,也对某些数字图像特征参数有一定影响;在不同条件(品种、氮营养水平以及生育期)下的数字图像特征参数与LAI的相关性分析中,R/(R+G+B)和UAV-based VARIRGB与LAI显著相关。进而,研究评价了R/(R+G+B)和UAV-based VARIRGB构建的LAI估测模型,最终确定UAV-based VARIRGB为估测冬小麦LAI的最佳参数指标。结果表明UAV-based VARIRGB指数模型估测的LAI与实测LAI拟合性较好(R2=0.71,RMSE=0.8,P0.01)。本研究证明将无人机数码影像应用于冬小麦LAI探测是可行的,这也为高性价比无人机遥感系统的精准农业应用增添了新成果和经验。