非均匀土壤区域SVAT模型中土壤水动力学参数的整合研究

荷兰Cabauw地区一个 10km×10km区域内的四种主要土壤的水动力学参数用一种实验室直接测定法 (Wind氏蒸发法 )和两种间接方法 (“分段土壤推导函数”、“连续土壤推导函数”)确定 ,而该区域水动力学特性参数的整合则采用两组方案 (聚合土壤参数法和有效土壤参数法 )进行。一个SVAT模型的模拟输出结果———感热通量、潜热通量与实测数据的比较分析表明 :(1)对于用“分段土壤推导函数”确定的土壤水动力学参数的区域整合 ,以“逆模拟法”(有效土壤参数法 )较为可行 ,其模拟感热、潜热的精确性接近参比方案 (“模拟 平均法”) ;(2 )对于实验室直接测定的参数 ,则以几何平均vanGenuchten Mualem经验公式参数的方案 (聚合土壤参数法 )为佳 ;(3)对于“连续土壤推导函数”推导的水动力学参数 ,几何平均土壤组分方案 (聚合土壤参数法 )和“逆模拟法”方案 (有效土壤参数法 )二者均可得到优于参比方案 (“模拟 平均法”)的模拟结果 ,其中以前者最佳 ;(4 )所有区域化参数整合方案中 ,以水平几何平均区域内实验室直接测定的参数的方案最优 ;同时 ,“连续土壤推导函数”法的土壤组分几何平均方案的模型输出精确性接近该最优方案     

一个新的植被参数化方案研究

为定量描述土壤－植被－大气连续体的热量及水分交换,建立了以有效比湿等为基础且具普适性的植被参数化方案－－１种等温大叶模式。利用拉萨、狮泉河和南京３个试验站的气象观测资料验证并由此计算的感热通量和潜热通量以及净辐射量、土壤温度等观测结果进行比分析表明,该植被参数化方案成功地反映了下垫面的水、热传输特征。     

一个新的植被参数化方案研究

为定量描述土壤-植被-大气连续体的热量及水分交换,建立了以有效比湿等为基础且具普适性的植被参数化方案——1种等温大叶模式。利用拉萨、狮泉河和南京3个试验站的气象观测资料验证并由此计算的感热通量和潜热通量以及净辐射量、土壤温度等观测结果进行对比分析表明,该植被参数化方案成功地反映了下垫面的水、热传输特征。     

青海湖2种高寒嵩草湿草甸湿地生态系统水热通量比较

基于涡度相关技术,研究了2015年青海湖2种高寒嵩草湿草甸湿地生态系统水热通量的特征。结果表明:(1)2015年青海湖高寒藏嵩草和小嵩草湿草甸湿地生态系统日平均水汽通量分别为1.74,0.99mm,年水汽通量分别为633.3,362.1mm。(2)青海湖2种高寒嵩草湿草甸湿地生态系统感热、潜热和净辐射日变化均呈单峰曲线,感热和潜热月平均日变化最大值出现的时间均晚于净辐射。藏嵩草湿草甸湿地生态系统感热月均日变化最大值最大为179.06W/m~2,最小为46.02W/m~2;潜热最大为312.55W/m~2,最小为30.58 W/m~2;小嵩草湿草甸湿地生态系统感热月均日变化最大值最大为161.86 W/m~2,最小为31.60 W/m~2;潜热最大为215.44 W/m~2;最小为14.08 W/m~2。(3)通过波文比分析发现,2种高寒嵩草湿草甸湿地生态系统生长季能量分配以潜热为主,非生长季小嵩草湿草甸湿地生态系统能量分配以感热为主,藏嵩草湿草甸湿地生态系统则较为复杂。藏嵩草湿草甸湿地生态系统全年能量平衡率为0.82,小嵩草湿草甸湿地生态系统为0.89,增加土壤热通量项能改善能量平衡状况。     

SiB2模型在黄灌区的应用探讨

SiB2(simple biosphere model Version 2)是用来模拟生态系统通量较为理想的国外模型,为了探讨其在我国黄河灌区的适用性及利用遥感数据驱动模型的可行性,并用其来研究该地区农田能量收支情况,以位山灌区为研究试点,利用位山实验站1a左右的观测数据对模型进行了验证分析,模拟结果表明:SiB2模型能够较好地模拟位山试验站农田的能量通量、CO2通量及地表温度,净辐射、潜热通量、感热通量、CO2通量与地表温度的模拟值与观测值吻合较好,线性相关系数R分别为0.988,0.714,0.607,0.677与0.933,其中净辐射模拟效果最好,感热通量偏差较大。另外,利用遥感MODIS LAI数据驱动SiB2模型表明,除净辐射外,模拟效果很差,因此在站点尺度遥感LAI(叶面积指数,leaf area index)产品不适合驱动SiB2模型。     

若尔盖高原高寒草甸地表能量交换和蒸散研究

若尔盖高原高寒草甸生态系统是青藏高原能量和水分循环的重要组成部分,但该地区地面水热通量观测数据非常缺乏。本研究基于涡动相关法,于2013年11月1日−2014年10月31日,利用三维超声风温仪和红外开路二氧化碳/水汽分析仪在若尔盖高原一典型高寒草甸开展周年通量观测,以揭示其地表能量交换和蒸散特征及影响因素。结果表明：高寒草甸地表能量通量各组分呈显著的日变化和季节变化特征,净辐射通量、感热通量、潜热通量和土壤热通量的年均值分别为94.5、21.0、51.8和1.2Wm−2。非生长季感热稍占优势,生长季潜热占绝对主导地位,波文比全年平均值为0.70,能量平衡闭合率年平均值为0.77。辐射是感热通量的主要气象影响因子,潜热通量则受温度、辐射和饱和水汽压差共同影响。日蒸散量变化范围为0.12～5.09mmd−1,全年平均值为1.82mmd−1。非生长季蒸散主要受土壤表面导度因子控制,生长季则由辐射主导,土壤和植被表面导度因子为次要影响因素。在季节尺度上,蒸散的变化取决于降水分布,全年降水和蒸散量分别为682.7mm和673.6mm,其中生长季分别占全年总量的84%和82%。6−7月降水匮乏抑制了蒸散,此时土壤储水成为蒸散的主要水源,从全年看,降水基本都以蒸散的方式返回大气。与青藏高原上同类观测研究相比,地表能量通量和蒸散都有相似的季节变化趋势,但观测到的年平均波文比和年蒸散量最大,气温、降水、地表植被等因素的共同作用导致这一结果。研究数据可作为地面验证资料,用于若尔盖地区陆面模式参数化方案的优化和卫星遥感反演资料的校验。     

湄公河流域农业干旱主要影响因素分析和预估

以湄公河流域作为模拟试验区域,采用区域气候模式RegCM3为模拟工具,单向嵌套全球海气耦合模式ECHAM5/MPI-OM当代(1980-2009年)和SRES A1B情景下未来(2010-2039年)的输出结果,以根系层土壤含水量为代表性指标,对试验区月尺度农业干旱进行了预估。基于地表能量平衡,系统分析了降水、蒸发、地表温度等农业干旱主要影响因素与区域气候模式模拟的大气环流、地表感热通量、地表潜热通量、地表净通量之间的联系和变化规律,从气陆间能量和水汽通量平衡角度,对农业干旱发生机理进行了初步识别。预估结果表明:未来春末(6月)和秋末(10月)湄公河流域温度增加、土壤含水量减少较为明显;同时,在这个时段试验区蒸发旺盛和降水减少的趋势,有可能导致湄公河流域局部地区农业干旱的发生。     

苏南地区典型作物冠层阻力参数及潜热通量的模拟

准确测算和模拟农田潜热通量对农业生产有着重要意义。该研究基于波文比能量观测系统对苏南地区夏玉米和冬小麦生育期内潜热通量进行连续观测,采用Katerji-Perrier（KP）和Todorovic（TD）两种方法来确定Penman-Monteith（P-M）模型中冠层阻力参数,探究两种冠层阻力参数子模型的估算误差及成因。结果表明：冬小麦生育期内主要气象因子呈现相似变化趋势,净辐射日均值呈现出波动上升趋势。两种冠层阻力参数子模型对冬小麦潜热通量模拟均取得良好的模拟效果,模拟R2不小于0.84,纳什系数不小于0.86,但KP模型精度稍高于TD模型。KP模型对冬小麦和夏玉米潜热通量均有高估,而TD模型高估了夏玉米潜热通量,饱和水汽压差是影响KP和TD两种冠层阻力参数子模型误差的主要因素,且饱和水汽压差越大绝对误差越大。研究为当地农业用水管理提供科学依据。     

青藏高原高寒金露梅灌丛湍流热通量交换与分配特征及其环境影响机制

青藏高原重要植被类型之一高寒灌丛的湍流热通量交换是局地微气候特征和植被物候事件的主要调控因素,但其时间格局与分配特征及环境影响机制尚不明确。以青藏高原东北隅的高寒金露梅(Potentilla fruticosa)灌丛为研究对象,基于涡度相关系统连续观测的湍流热通量,研究该生态系统显热通量和潜热通量交换与分配的特征及潜在环境调控过程。结果表明(1)全年逐时显热通量和逐时潜热通量的平均日变化均表现出单峰型特征,最大值出现在13:30左右。在非生长季(11月-翌年4月)、生长初期(5月)和生长季末期(10月),热量交换以显热通量为主,而在生长季中期(6-9月)则以潜热通量居多;(2)显热通量呈现出双峰型季节特征,最大峰和次高峰分别出现在4月中旬和10月上旬。潜热通量为单峰型季节变化,最大值在7月下旬;(3)湍流热通量的逐时、逐日变异均主要受控于太阳短波辐射;(4)波文比呈现出U型季节变化,而解耦系数、蒸散比例表现为钟型季节变化,热量分配指标在非生长季和生长季分别受控于土壤表层温度和增强植被指数。高寒金露梅灌丛的热量交换主要受控于太阳辐射,热量分配则受下垫面温度和植被覆盖影响。     

神府东胜煤田弃土弃渣体径流水动力学特性研究

[目的]对神府煤田开发建设过程中造成的弃土弃渣体的径流水动力学特性进行研究,并分析土壤剥蚀率与各水动力学参数之间的关系。[方法]采用野外模拟降雨试验方法。[结果](1)弃土弃渣体的土壤剥蚀率Dr随雨强增大显著线性递增;(2)雷诺数Re总体上随着雨强增大而增大,随降雨历时先增大后保持稳定;佛罗德数Fr受雨强影响不显著,在产流0~12min内波动较大,随后在某一常数附近上下波动;阻力系数f随降雨历时呈递增趋势,受雨强影响不显著,次降雨平均阻力系数f大小表现为:沙少石多弃渣体弃土体沙多石少弃渣体;(3)各下垫面土壤剥蚀率Dr与水流剪切力、水流功率P之间均呈显著的线性函数关系。[结论]研究区不同类型下垫面次降雨径流水动力学参数变化各具特点,土壤剥蚀率与各水动力学参数之间存在显著相关关系。     

基于单一和集合土壤转换函数模型对土壤含水量的模拟性能分析

土壤转换函数(Soil pedotransfer function,PTF)是一种高效获取土壤水力参数的方法。由于土壤具有很强的空间异质性,确定最优PTF模型成为模拟土壤含水量的关键。为此,以海河流域3个实验场地(密云站、大兴站、馆陶站)为研究区,采用7种常用的单一PTF模型预测土壤水力参数作为HYDRUS-1D的模型参数,求解Richards方程获得土壤含水量,并与实测土壤含水量进行比较,评价了常用单一PTF模型预测的土壤水力参数对土壤含水量的模拟性能。此外,采用3种方法构建集合PTF模型,评价了集合PTF模型对土壤含水量的模拟性能。结果表明：基于van Genuchten方程构建的单一PTF作为模型参数模拟土壤含水量的均方根误差最小;而其中Rosetta3模型表现更优。在集合PTF模型中,基于遗传算法加权法构建的模型表现最好。集合PTF模型预测土壤水力参数可以较好的捕捉多个单一PTF预测土壤水力参数的整体趋势,弥补单一PTF在某些情况下模拟误差较大的不足。     

Estimating the water retention curve from soil properties: comparison of linear, nonlinear and concomitant variable methods

The unsaturated soil hydraulic functions involving the soil–water retention curve (SWRC) and the hydraulic conductivity provide useful integrated indices of soil quality. Existing and newly devised methods were used to formulate pedotransfer functions (PTFs) that predict the SWRC from readily available soil data. The PTFs were calibrated using a large soils database from Hungary. The database contains measured soil–water retention data, the dry bulk density, sand, silt and clay percentages, and the organic matter content of 305 soil layers from some 80 soil profiles. A three-parameter van Genuchten type function was fitted to the measured retention data to obtain SWRC parameters for each soil sample in the database. Using a quasi-random procedure, the database was divided into “evaluation” (EVAL) and “test” (TEST) parts containing 225 and 80 soil samples, respectively. Linear PTFs for the SWRC parameters were calculated for the EVAL database. The PTFs used for this purpose particle-size percentages, dry bulk density, organic matter content, and the sand/silt ratio, as well as simple transforms (such as logarithms and products) of these independent variables. Of the various independent variables, the eight most significant were used to calculate the different PTFs. A nonlinear (NL) predictive method was obtained by substituting the linear PTFs directly into the SWRC equation, and subsequently adjusting the PTF parameters to all retention data of the EVAL database. The estimation error (SSQ) and efficiency (EE) were used to compare the effectiveness of the linear and nonlinearly adjusted PTFs. We found that EE of the EVAL and the TEST databases increased by 4 and 7%, respectively, using the second nonlinear optimization approach. To further increase EE, one measured retention data point was used as an additional (concomitant) variable in the PTFs. Using the 20 kPa water retention data point in the linear PTFs improved the EE by about 25% for the TEST data set. Nonlinear adjustment of the concomitant variable PTF using the 20 kPa retention data point as concomitant variable produced the best PTF. This PTF produced EE values of 93 and 88% for the EVAL and TEST soil data sets, respectively.     

Applicability of site-specific pedotransfer functions and rosetta model for the estimation of dynamic soil hydraulic properties under different vegetation covers

Background, Aims, and Scope  During the last decades, different methods have been developed to determine soil hydraulic properties in the field and laboratory. These methodologies are frequently time-consuming and/or expensive. An indirect method, named Pedotransfer Functions (PTFs), was developed to predict soil hydraulic properties using other easily measurable soil (physical and chemical) parameters. This work evaluates the use of the PTFs included in the Rosetta model (Schaap et al. 2001) and compares them with PTFs obtained specifically for soils under two different vegetation covers. Methods  Rosetta software includes two basic types of pedotransfer functions (Class PTF and Continuous PTF), allowing the estimation of van Genuchten water retention parameters using limited (textural classes only) or more extensive (texture, bulk density and one or two water retention measurements) input data. We obtained water retention curves from undisturbed samples using the ‘sand box’ method for potentials between saturation and 20 kPa, and the pressure membrane method for potentials between 100 and 1500 kPa. Physical properties of sampled soils were used as input variables for the Rosetta model and to determine site-specific PTFs. Results  The Rosetta model accurately predicts water content at field capacity, but clearly underestimates it at saturation. Poor agreement between observed and estimated values in terms of root mean square error were obtained for the Rosetta model in comparison with specific PTFs. Discrepancies between both methods are comparable to results obtained by other authors. Conclusions  Site-specific PTFs predicted the van Genuchten parameters better than Rosetta model. Pedotransfers functions have been a useful tool to solve the water retention capacity for soils located in the southern Pyrenees, where the fine particle size and organic matter content are higher. The Rosetta model showed good predictions for the curve parameters, even though the uncertainty of the data predicted was higher than for the site-specific PTFs. Recommendations and Perspectives  The Rosetta model accurately predicts the retention curve parameters when the use is related with wide soil types; nevertheless, if we want to obtain good predictors using a homogenous soil database, specific PTFs are required. ESS-Submission Editor: Prof. Zhihong Xu, PhD (zhihong.xu@griffith.edu.au)     

夹砂层土壤Green-Ampt入渗模型的改进与验证

对于土层夹砂结构,湿润锋穿过砂层上界面时,入渗率变为稳渗率。为确定各因素下夹砂层土壤的稳渗率,在Green-Ampt入渗模型基础上,引入导水度系数(小于1)来量化上层土壤的导水程度,建立了改进的夹砂层土壤Green-Ampt入渗模型。采用HYDRUS-1D软件,模拟了不同土壤质地、初始含水率、压力水头、砂层埋深和砂层厚度条件下的稳渗过程,根据模拟结果分析了夹砂层土壤的入渗规律及其影响因素,稳渗率主要受土壤质地、压力水头和砂层埋深的影响。在相同压力水头、初始含水率和砂层厚度下模拟获得不同砂层埋深的稳渗率,并采用改进的Green-Ampt入渗模型拟合,求得导水度系数和进水吸力值。分析发现导水度系数变化较小,为简化计算,取其平均值0.95。在此基础上,提出了由土壤物理特性参数进气值倒数估算进水吸力的计算公式。利用秦王川地区的夹砂层土壤积水入渗试验及已有文献资料验证所建模型的有效性,结果表明所建模型待定参数少,计算误差基本在5%以内,且试验设计较简单,可为农田水分管理及工程防渗技术提供理论依据。     

Predicting unsaturated hydraulic conductivity of soil based on some basic soil properties

Soil hydraulic conductivity is a crucial parameter in modeling flow process in soils and deciding water management. In this study, by combining the non-similar media concept (NSMC) to the one-parameter model of Brooks and Corey, a new NSMC-based model for estimating unsaturated hydraulic conductivity of various soils was presented. The main inputs are soil bulk density, particle-size distribution, soil water retention characteristic and saturated hydraulic conductivity of soil. The results indicated that the NSMC-based model could generally more accurately predict unsaturated hydraulic conductivity of soils, as compared to four one-parameter models and van Genuchten–Mualem model. This study, by introducing NSMC, provided a new way to incorporate soil physical heterogeneity into soil hydraulic simulation, and hence NSMC-based approach is expected to improve efficiency of the existing models in the simulation of soil water flow.     

A review on parameterization and uncertainty in modeling greenhouse gas emissions from soil

The efficacy of mathematical modeling as a tool for estimating greenhouse gas (GHG) emissions from soil depends on the uncertainty. Systematic evaluation of various sources of uncertainties in GHG emission models is limited. This paper reviews the state-of-the-art knowledge on the parameterization and uncertainty analysis of soil GHG emission models. Major recommendations and conclusions from this work include: (a) uncertainties due to model parameters and structure can be quantified by combining the Bayesian theorem and the Markov Chain Monte Carlo (MCMC) method; (b) uncertainty due to event-based model input may also be assessed by regarding each event as a latent variable; however, the necessity of the simultaneous evaluation of uncertainties from model input, parameters, and structure might be negotiable because strong correlations may exist between input errors and model parameters; (c) uncertainty analysis is essential for a successful model parameterization by reducing both the number of undetermined parameters and the parameter space; and (d) model parameterization (calibration) should be conducted on multiple sites towards multiple objectives. Case studies were presented for comparing the model uncertainties of the denitrification components of four models, DAYCENT, DNDC, ECOSYS, and COMP. The methods discussed in this paper can help to evaluate model uncertainties and performances, and to offer a critical guidance for model selection and parameterization.     

基于土壤传递函数的土壤持水特性间接估计及其空间变异性研究

A total of 107 soil samples were taken from the city of Qingdao,Shandong Province,China.Soil water retention data at 2.5,6,10,33,100,300,and 1 500 kPa matric potentials were measured using a pressure membrane apparatus.Multiple linear regression (MLR) was used to develop pedotransfer functions (PTFs) for single point estimation and van Genuchten parameter estimation based on readily measurable soil properties,i.e.,MLR-based point (MLRP) PTF and MLR-based parametric (MLRV) PTF.The double cross-validation method was used to evaluate the accuracy of PTF estimates and the stability of the PTFs developed in this study.The performance of MLRP and MLRV PTFs in estimating water contents at matric potentials of 10,33,and 1 500 kPa was compared with that of two existing PTFs,the Rawls PTF and the Vereecken PTF.In addition,geostatistical analyses were conducted to assess the capabilities of these PTFs in describing the spatial variability of soil water retention characteristics.Results showed that among all PTFs only the Vereecken PTF failed to accurately estimate water retention characteristics.Although the MLRP PTF can be used to predict retention characteristics through traditional statistical analyses,it failed to describe the spatial variability of soil water retention characteristics.Although the MLRV and Rawls PTFs failed to describe the spatial variability of water contents at a matric potential of 10 kPa,they can be used to quantify the spatial variability of water contents at matric potentials of 33 and 1 500 kPa.     

土壤水力特性的空间尺度效应研究进展

研究土壤水力特性的空间尺度效应,在生态水文模拟和农业水肥精准管理方面具有重大意义。水力特性空间变异研究方法主要有统计法、随机模拟法、土壤转换函数法和分形理论法;由于土壤中物理、化学和生物等过程作用的尺度不同,导致其空间变异方式亦不相同,当前主要采用地统计学、谱分析、多重分形和小波分析等方法研究水力特性的尺度效应。研究过程中仍有一些问题需解决,其中尺度转换始终是非常重要的问题,并且要与GIS等技术相结合。