基于不同PTF_S的流域尺度土壤持水特性空间变异性分析

利用点估计模型、线性回归模型、非线性回归模型和人工神经网络模型等四种PTFS分别预测大沽河流域90个土壤样本的田间持水量(θ-30 kPa)和凋萎含水量(θ-1 500 kPa),借助传统统计学和地统计学方法对其空间变异性进行了比较分析。传统统计学分析认为非线性回归模型预测的效果最好,无论是实测值还是估计值,所有土壤样本θ-30 kPa的变异系数总是小于θ-1 500 kPa,两者均属于中等变异性;地统计学分析表明实测值和预测值的θ-30 kPa和θ-1 500 kPa均存在不同程度的块金效应,且θ-30 kPa总是表现出较θ-1 500 kPa更强烈的空间相关性,通过分析θ-30 kPa和θ-1 500 kPa的半方差函数模型参数,发现人工神经网络模型最能真实地反映试验区土壤持水特性的空间变异性特征。     

参数模型在壤土类土壤颗粒大小分布中的应用

颗粒大小分布是土壤的基本物理性质之一 ,可以用来预测其它难以直接测定的土壤性质。采用参数模型描述土壤的颗粒大小分布有许多优点。本文利用河南封丘地区三种壤土类土壤共 30 0个样本的颗粒分析资料 ,研究了五种参数模型的适用情况。结果表明 ,包含四个参数的Fred4P模型对三种土壤颗粒大小分布的模拟效果最为理想 ;三参数的Fred3P和MLog模型对砂壤土的描述效果较差 ,对另外两种质地土壤的模拟效果与Fred4P模型相当。四参数的Gomp模型计算误差大于Fred3P和MLog模型。在这五种参数模型中 ,MVG模型的误差最大 ,不能精确描述封丘地区壤土类土壤的颗粒大小分布。     

小麦根系长度的估算方法与参数分析

构建小麦根系伸长过程的动态模型,并对模型参数进行定量分析,可为植株形态建成模拟和可视化显示提供关键技术。根据根系生长发育的基本结构单元,利用根系与地上部叶片生长之间的同伸关系,以生长度日为时间尺度,建立了小麦初生根、节根与分枝根发生过程的模型;通过计算不同类型根系的生理年龄,建立了不同类型根系发育阶段预测模型;以线性方程为基础,建立了不同类型根的伸长过程模型,并实现了对总根长变化过程的动态模拟。利用独立的试验资料对所建模型进行了检验,结果显示模型对小麦总根长和主轴数量的模拟值与观测值的均方根差分别为370.68 cm和1.27个,相对误差分别为0.27和0.16;对模型参数的灵敏性分析表明,模拟结果对参数变化的响应比较适中,可以较好地反映小麦根系长度和拓扑结构的动态变化过程。     

用MatLab确定土壤水分特征曲线参数

土壤水分特征曲线是定量研究土壤水运动的重要参数。目前,土壤物理学家普遍采用vanGenuchten模型(简称VG模型)来描述土壤水分特征曲线(h-θ曲线),本文讨论了如何确定模型参数的方法。根据中国科学院栾城试验站大田土壤剖面所采土样实测土壤负压h和土壤含水率θ数据,VG模型中的参数利用MatLab非线性拟合函数来确定,通过用四参数模型计算,计算的θ值与实测的θ值拟合较好,误差相对较小。通过长江河口地区土样检验表明,用MatLab方法确定VG模型参数,计算值与实测值拟合也较好,且计算值与实测值的残差平方和范数<0.001。     

新安江模型和人工神经网络的耦合应用

提出了一种集成人工神经网络的概念性水文模型,该模型是一种半分布式概念性水文模型,考虑了降雨的空间变异性,流域特征的不均匀性等因素对径流过程的影响。采用遗传算法进行概念性模型参数优选,同时考虑雨量站的空间分布,利用GIS和DEM数据进行流域单元划分;对于每个子流域,考虑模型输入参数和降雨资料的空间分布特性,进行产流计算;在径流演算过程中,利用人工神经网络的非线性映射方法代替传统概念模型中线性叠加方法计算整个流域的出口流量过程。以半湿润的淮河上游支流的大坡岭流域为例,对模型的可行性进行验证,并与单一的新安江模型的结果进行了比较。验证结果表明,集成人工神经网络技术和新安江模型的耦合模型有较好的模拟和预报结果。     

土壤侵蚀模拟的高维指数非线性模型及参数辨识方法研究

针对常规土壤侵蚀经验统计模型适用性不强、模拟精度不佳等问题,对灰色离散序列高阶动态模型进行合理扩展,建立了多变量高维指数非线性模型,通过MATLAB寻优,实现了非线性模型中参数的搜索--辨识.该模型具有信息包容量丰富、信息开发利用潜力大、适用范围广等特点.人工降雨条件下的坡耕地土壤侵蚀模拟结果表明:模型有效系数>0.91.平均误差率<6.2%,模拟精度较高.     

高斯一牛顿法在滑坡预测预报模型参数优化中的应用

对滑坡预测预报的非线性模型,在估计其参数时,传统的方法是将非线性模型在参数的近似值处展开成泰勒级数,并仅取至一次项,然后再应用线性模型参数估计理论进行参数估计。因线性化时略去了二阶及二阶以上的各高次项,所以必然会产生模型误差。介绍了高斯牛顿法的基本原理,并以洒勒山新滑坡为例,在建立该滑坡灰色GM（1,1）模型和Verhulst模型的基础上,运用高斯-牛顿法对两个非线性模型的参数进行优化。计算结果表明,参数优化后各模型的预测精度比优化前各模型的精度有显著提高。说明采用高斯-牛顿法优化非线性模型参数是提高滑坡预测预报精度的一种有效且切实可行的方法。     

基于电学参数的苹果可溶性固形物含量预测

为实现苹果可溶性固形物含量的无损检测，该研究提出了一种长短期记忆编解码和多层感知机（LSTMED-MLP,long short-term memory encoder-decoder-multi-layer perceptron）融合的介电特征预测方法。在0.158～3 980 kHz频率范围内的9个频率点下，采用介电谱测量仪获取300个富士苹果的电学参数，其中每个频率点对应15项电学参数，即每个苹果对应135项电学特性参数，之后通过苹果基因组学理化分析方法，获取可溶性固形物含量；根据电学参数与可溶性固形物含量，构建苹果关键基因组学参数的回归预测模型。为简化模型输入，提取样本变量特征，使用主成分分析（principal component analysis,PCA）和LSTMED模型，提取每个样本的40项特征值，作为非线性回归模型多层感知机（MLP）和XGBoost的输入，建立可溶性固形物含量预测模型。试验结果表明，LSTMED具有更好的适用性，且LSTMED-MLP模型的预测效果最好，在校正集和预测集上，决定系数分别为0.95和0.90，均方根误差分别为0.77和0.84，且对不同种...     

基于CT图像的土壤孔隙结构三维重建及水力学性质预测

为了更好地了解土壤孔隙结构对水分运动过程的影响机制,该文利用黄淮海平原原状潮土CT扫描图像,通过数字图像分析和计算机重建技术对孔隙结构进行三维重建,根据图像分析获得的孔隙大小分布和连通性等形态学参数建立了用于描述孔隙尺度结构特征对水分运动影响机制的网络模型,据此预测了样本尺度(样本体积为385.84cm3)的土壤水力学性质。结果表明,模型预测的水力学性质和实测值基本吻合,变化趋势基本一致,二者的决定系数达0.94以上。结果表明相关网络模型可以较好地模拟孔隙尺度的水分运动过程,可用于预测土壤的非饱和水力学性质。     

基于GA的GRNN高光谱遥感反演冬小麦叶片氮含量模型的建立与验证

基于人工神经网络理论,针对高光谱遥感中数据冗余问题,本文建立了基于遗传算法(GA)的广义回归神经网络(GRNN)模型,利用回归分析问题中参数筛选方法,对表征冬小麦叶片全氮的光谱参数进行了筛选,并和线性回归方法对比,线性回归方法的均方根误差(RMSEP):在冬小麦叶片氮含量为34.0g kg-1~62.5g kg-1预测范围内,逐步回归模型为14.4g kg-1,后向选择为11.8g kg-1,而广义回归神经网络为3.40g kg-1。说明神经网络方法所筛选到的光谱参数更能反映小麦叶片全氮含量,且神经网络模型预测精度高。     

基于遗传算法的人工神经网络模型在冬小麦根系吸水模型中的应用

基于土壤水分与冠部数据,应用遗传算法优化人工神经网络模型的权值,将获得的冬小麦根长密度分布应用于根系吸水模型中,并进行了水分数值模拟,水分模拟效果整体较好,表明应用该方法可以为根系吸水模型提供准确的根系参数,并且较为方便,这对于根系吸水模型的建立及应用有着重要的意义。     

应用GIS和神经网络方法进行泥石流危险度评价的研究——以云南省为例

应用了GIS和神经网络方法,根据云南省31年的降水数据和DEM数据,以该省典型的区域为样本训练神经网络,以县、市行政区域为评价单元,对云南省泥石流的危险度进行了评价。结果表明,所采用的网络能够很好地收敛,用训练好的网络对全省125个县市的样本进行测试,结果表明网络能较好的对样本做出评价,而且评价结果与其他方法进行评价的结果较一致,达到了设计网络所预期的目的。     

Modelling Sonchus arvensis root biomass allocation to below-ground shoot and fine root growth

Below-ground (bg) shoot emergence rates of Sonchus arvensis are dependent on temperature and root weight. However, it is unknown to what extent this is due to a root depletion rate that depends on initial root weight, or due to differences in resource allocation to fine root and bg shoot growth. To resolve this, we retrieved data from an experiment in which plants were grown in the dark at constant temperature (4°C, 8°C, and 18°C) and harvested prior to or at shoot emergence. A dynamic mass-balance model, in which biomass of the initial root was allocated to bg shoot and fine root daily growth, and where respiration took place from all tissues, was used. The relative depletion rate of root biomass (RDR; d^?1) and fraction of the depleted biomass allocated to bg shoots (SFRR) were estimated and calibrated to observed biomass. The RDR increased with initial root weight and temperature and SFFR was highest for light roots and lowest for heaviest roots, whereas the rest was allocated to fine root biomass. The length-to-biomass ratio of bg shoots decreased with initial root weight. Under between-year weather variations (2004–2010), the reduction in root biomass during the coldest April–May was simulated to be over 12 days delayed compared with the warmest spring. The influence of biomass allocation on bg shoot elongation of heavier roots was thus stimulated by a larger fraction of root biomass being depleted, but counteracted by a smaller fraction of it allocated into bg shoot elongation, compared with lighter roots. The complexity of shoot emergence based on root depletion estimates may be a reason why predictions based on only an accumulated root weight-specific temperature sum, as proposed by a previous study, are expected to be less uncertain than those based on root depletion estimates.     

水分胁迫对冬小麦生长后效影响的模拟研究

以Logistic方程为基础框架，建立了具有土壤水分胁迫后效影响的作物生长模型，实现了胁迫后效影响在生长模型中的定量化。利用模型模拟了小麦冠根干物质积累动态。经与实测值相比较，模拟与实测值吻合良好，表明所建模型结构合理，为作物水分关系模拟提供了一种新方法。所建模型不仅可以模拟单调上升的生长过程，也可模拟先上升后下降的过程，具有一定普适性。模型中的时变和非时变参数，都具有明确的物理意义。对冠根两种不同动态过程的后效影响参数对比显示，胁迫对冠生长的后效影响明显大于对根系的后效影响，表明对水分胁迫较敏感的生长过程，胁迫对它的后效影响也较大。     

苗期土壤含水率变化对冬小麦根、冠生物量累积动态的影响

为合理进行冬小麦生长过程的适时水分调控，该文对不同生育期土壤含水率对冬小麦根冠影响的试验进行分析。采用的试验包括5种水分处理，即苗期充分供水，其它生育期进行中度胁迫(FB)、重度胁迫(FC)处理和从苗期开始的中度水分胁迫(SB)、重度水分胁迫(SC)处理以及全生育期充分供水的对照处理。试验结果表明：苗期土壤含水率对冬小麦根、冠的生物量，生物量的累积速率产生不同影响，使全生育期内根、冠占植株总量的比例和根冠比发生改变。当苗期水分改变时，生育初期，根、冠均没有明显响应，但到播后16 d，播后20 d，根、冠生物量分别随胁迫程度的增加而减小(FB>SB，FC>SC)；在播后28 d，SB和SC的根系质量累积速率超过对应FB和FC处理，且苗期受胁迫处理的冬小麦在生殖生长阶段所维持的根系大于苗期不受胁迫处理的根系；冠的累积速率则在播后28 d和35 d也出现SB>FB，SC>FC的结果，到播后42 d，SB、SC的冠质量分别超过对应的FB、FC的冠质量。在此过程中，根、冠生物量占总质量的比例发生改变，根表现为SB>FB，SC>FC；冠在营养生长阶段FB>SB，FC>SC，在生殖生长期SB达到最大；相应根冠比改变。     

Spatial prediction of soil nutrient in a hilly area using artificial neural network model combined with kriging

It is widely recognized that using correlated environmental factors as auxiliary variables can improve the prediction accuracy of soil properties. In this study, a radial basis function neural network (RBFNN) model combined with ordinary kriging (OK) was proposed to predict spatial distribution of four soil nutrients based on the same framework used by regression kriging (RK). In RBFNN_OK, RBFNN model was used to explain the spatial variability caused by the selected auxiliary factors, while OK was used to express the spatial autocorrelation in RBFNN prediction residuals. The results showed that both RBFNN_OK and RK presented prediction maps with more details. However, RK does not always obtain mean errors (MEs) which were closer to 0 and lower root mean square errors (RMSEs) and mean relative errors (MREs) than OK. Conversely, MREs of RBFNN_OK were much closer to 0 and its RMSEs and MREs were relatively lower than OK and RK. The results suggest that RBFNN_OK is a more unbiased method with more stable prediction performance as well as improvement of prediction accuracy, which also indicates that artificial neural network model is more appropriate than regression model to capture relationships between soil variables and environmental factors. Therefore, RBFNN_OK may provide a useful framework for predicting soil properties.     

Root growth and nutrient element status of creeping bentgrass cultivars differing in heat tolerance as influenced by supraoptimal shoot and root temperatures

This study was designed to determine and compare root growth and nutritional responses of creeping bentgrass cultivars that differ in heat tolerance to differential, supraoptimal, shoot and root temperatures. Shoots and roots of ‘Penncross’ (heat sensitive) and ‘L‐93’ (heat tolerant) were exposed to four air/soil temperature regimes (20/20°C‐control, 20/35°C, 35/20°C, and 35/35°C) in water baths and growth chambers. Exposing roots to supraoptimal root temperature (35°C) while maintaining shoots at normal temperature (20°C) or particularly at 35°C reduced root fresh weight, root number, and contents of nitrogen (N), phosphorus (P), and potassium (K) in shoots and roots and accelerated root death for both cultivars. High root temperature had greater detrimental effects on root growth and nutrient element accumulation than high shoot temperature for both cultivars. A low root temperature at supraoptimal shoot temperature improved root growth, reduced root mortality; and increased N, P, and K contents in shoots and roots. Among the three nutrient elements, K was the most sensitive to changes in root temperature. L‐93 generally maintained higher fresh weight and number of roots and higher N, P, and K contents in shoots and roots, particularly K in roots, under high root (20/35°C) or shoot/root (35/35°C) temperatures. The results indicated that root growth and nutrient element accumulation, particularly of K, played an important role in creeping bentgrass tolerance to heat stress imposed on shoots by high air temperature or to roots by high soil temperatures. The enhanced root growth and nutrient element relations with a low root temperature at supraoptimal ambient temperatures could lead to the improved shoot growth in cool‐season grasses observed under these conditions.     

CO2浓度倍增、增温和轻度干旱对冬小麦根系生长和氮素吸收的影响

  【目的】  根系是作物氮素吸收的主要器官,研究CO₂浓度倍增和增温对根系生长和氮素吸收的影响,为应对气候变化提供科学的养分管理策略。  【方法】  以冬小麦(Triticum aestivum L.)为材料,在人工气候室内进行盆栽试验。设置对照(大气CO₂浓度400 μmol/mol+正常环境温度,CK)、CO₂浓度倍增(CO₂浓度800 μmol/mol+正常环境温度,ECO₂)、增温4℃ (CO₂浓度400 μmol/mol+增温4℃,ETem)和CO₂浓度倍增+增温4℃ (CO₂浓度800 μmol/mol+增温4℃,ECO₂+ETem) 4种气候情景,每种气候情景设置充分供水(80%田间持水量)和轻度干旱(60%田间持水量) 两个水分条件。调查了冬小麦根系生长(根生物量、根冠比、总根长、根总表面积和根总体积)和氮素吸收的情况,分析冬小麦氮素吸收与根系生长的关系。  【结果】  1) CO₂浓度倍增对冬小麦各生育期根系生长均无显著影响,而增温4℃和轻度干旱显著抑制了开花和灌浆期的根系生长。2) CO₂浓度倍增、增温、轻度干旱共同作用均显著抑制了冬小麦根系生长,其中增温和轻度干旱对根系生长具有协同抑制作用。3) CO₂浓度倍增显著降低了冬小麦灌浆期根氮含量,而对地上部氮含量无显著影响;增温4℃显著增加了冬小麦各生育期根氮含量和地上部氮含量;轻度干旱增加了根氮含量和地上部氮含量,且仅对地上部氮含量有显著影响;CO₂浓度倍增与增温交互作用仅对根氮含量增加有显著促进作用;增温与轻度干旱交互作用对根氮含量和地上部氮含量增加均有显著促进作用;CO₂浓度倍增与轻度干旱交互作用,以及CO₂浓度倍增、增温和轻度干旱三者交互作用对根氮含量和地上部氮含量增加均无显著影响。4)根氮积累量及地上部氮积累量均与根系形态指标对CO₂浓度倍增、增温、轻度干旱及其交互作用的响应具有相同变化特征,且根氮积累量和地上部氮积累量与各生育期根系形态指标有显著正相关关系。  【结论】  在本试验条件下增温和轻度干旱对冬小麦根系生长具有较强的抑制作用,且二者对根系生长具有协同抑制作用;CO₂浓度倍增对冬小麦各生育期根部和地上部氮素吸收的影响总体不显著,而增温和轻度干旱对根部和地上部氮含量增加均有一定的促进作用,对根部和地上部氮积累量增加均有抑制作用,增温是影响氮素吸收的主导因子。     

Nitrogen Use Efficiency in Cacao Genotypes

Cacao (Theobroma cacao L) is mostly grown on soils with low natural fertility. On such soils nitrogen (N) is one of the most yield limiting nutrients for cacao. Information is lacking on N use efficiency in cacao. A greenhouse experiment was conducted to evaluate growth response and N use efficiency by two cacao genotypes. The genotypes used were TSH-565 and ICS-9 and N rates adapted were 0, 120, 240, 360, and 480 mg N /pot. In both genotypes, increasing levels of applied N improved growth (stem girth, dry weight of shoot and roots and shoot/root ratio), and concentration and uptake of N. Genotypes differed significantly for stem girth and ICS -9 produced greater stem girth compared with TSH-565. Nitrogen uptake had a linear relationship with root dry weight of the two genotypes. In both genotypes, increasing levels of applied N overall increased N-uptake efficiency (NEFF = N concentration in shoot x shoot/root), but decreased N-use efficiency by shoot and roots (NUE = g dry matter of shoot or root/mg N) and N-use efficiency of carbohydrate (NUEC = mg of total carbohydrates in shoot/mg of N in shoot). Both genotypes responded differently to applied N, despite the existence of close genetic relatedness between them. The method used here appears to be suitable method for identification of cacao genotypes that are efficient in uptake and utilization of N.     

有机肥与种植密度对旱作玉米根系生长及功能的影响

在大田条件下研究了基施有机肥及3种种植密度（60,75,90千株/hm2）对旱作玉米根系生长和功能的影响。结果表明,在大喇叭口期,基施有机肥显著降低了30—100cm土层内的根长与根表面积,但对根干重影响不显著;由于基施有机肥处理地上部生物量更大,因而显著降低了根冠比;种植密度对该时期根系生长的影响较小。在蜡熟期,基施有机肥限制了30—100cm土层及1/4行间、行间与膜下位置的根系分布,但对根冠比的作用不显著。该时期根长、根表面积及根干重均有随密度增加而减少的趋势,该趋势在0—30cm土层和株上位置表现显著;种植密度的增加也降低了根冠比。有机肥延缓根系衰老作用不明显,其根系导水率与不基施有机肥处理无显著差异;而在种植密度增加情况下,单位根系表面积吸水功能的提高弥补了根量减少带来的损失,表现出一定的适应性。