基于PEST的RZWQM2模型参数优化与验证

根据糯玉米-冬小麦田间喷灌试验不同处理结果,利用独立的自动参数估计软件PEST对RZWQM2模型进行参数优化,并分析了24个模型参数的综合敏感度。通过控制不同观测变量(土壤含水率、土壤氮素含量、作物叶面积指数、产量)模拟差异函数值在目标函数中的比重,优化目标方程,确定模型参数,并用田间试验数据对模型进行验证。结果表明,在不同观测变量的模拟差异函数值最接近条件下,冬小麦出叶间隔特性参数、冬小麦春化作用敏感特性参数及糯玉米出叶间隔特性参数等3个参数对模型整体模拟效果影响最大。相比试错法而言,基于PEST优化的RZWQM2模型能够更准确地模拟糯玉米-冬小麦轮作系统中水分、氮素及作物生长情况。     

Simulating water content, crop yield and nitrate-N loss under free and controlled tile drainage with subsurface irrigation using the DSSAT model

In southwestern Ontario, rain-fed crop production frequently fails to achieve its yield potential because of growing-season droughts and/or uneven rainfall distribution. The objective of this study was to determine if the Decision Support System for Agrotechnology Transfer (DSSAT) v4.5 model could adequately simulate corn and soybean yields, near-surface soil water contents, and cumulative nitrate-N losses associated with regular free tile drainage (TD) and controlled tile drainage with optional subsurface irrigation (CDS). The simulations were compared to observations collected between 2000 and 2004 from both TD and CDS field experiments on a Perth clay loam soil at the Essex Region Conservation Authority demonstration farm, Holiday Beach, Ontario, Canada. There was good model-data agreement for crop yields, near-surface (0-30 cm) soil water content and cumulative annual tile nitrate-N loss in both the calibration and validation years. For both TD and CDS, the CENTURY soil C/N model in DSSAT simulated water content and cumulative tile nitrate-N loss with normalized root mean square error (n-RMSE) values ranging from 9.9 to 14.8% and 17.8 to 25.2%, respectively. The CERES-Maize and CROPGRO-Soybean crop system models in the DSSAT simulated corn and soybean yields with n-RMSE values ranging from 4.3 to 14.0%. It was concluded that the DSSAT v4.5 model can be a useful tool for simulating near-surface soil water content, cumulative tile nitrate-N losses, and corn and soybean yields associated with CDS and TD water management systems.     

从群体到个体尺度——基于数据的DSSAT和GreenLab作物模型连接探索

作物模型的研究涉及作物生长发育的复杂过程,空间上从分子到细胞、组织、器官、个体、群体等不同尺度,时间尺度上可以从秒到年。基于不同的研究需求,切换作物模型尺度,可使得作物模型的适用性更广泛灵活。其中,如何从群体尺度的作物模型转入个体尺度的作物模型是本研究的内容。本研究基于四个玉米品种的两个处理（灌溉和雨养）的已有的实验数据和基于这些数据的DSSAT系统的模拟数据,校准功能结构模型GreenLab的参数,以计算结果一致为指标,探索不同空间尺度模型建立接口的方法,比较不同模型的特点。结果表明,GreenLab模型可以复现DSSAT系统的模拟数据和实际测量数据,进一步可以反演出各种器官之间生物量的分配并进行三维可视化展示。最后讨论了不同空间尺度模型结合的优势及应用领域。     

Influence of likelihood function choice for estimating crop model parameters using the generalized likelihood uncertainty estimation method

Proper estimation of model parameters is required for ensuring accurate model predictions and good model-based decisions. The generalized likelihood uncertainty estimation (GLUE) method is a Bayesian Monte Carlo parameter estimation technique that makes use of a likelihood function to measure the closeness-of-fit of modeled and observed data. Various likelihood functions and methods of combining likelihood values have been used in previous studies. This research was conducted to determine the effects of using previously reported likelihood functions in a GLUE procedure for estimating parameters in a widely-used crop simulation model. A factorial computer experiment was conducted with synthetic measurement data to compare four likelihood functions and three methods of combining likelihood values using the CERES-Maize model of the Decision Support System for Agrotechnology Transfer (DSSAT). The procedure used an arbitrarily-selected parameter set as the known “true parameter set” and the CERES-Maize model to generate true output values. Then synthetic observations of crop variables were randomly generated (four replicates) by using the simulated true output values (dry yield, anthesis date, maturity date, leaf nitrogen concentration, soil nitrate concentration, and soil moisture) and adding a random observation error based on the variances of corresponding field measurements. The environmental conditions were obtained from a sweet corn (Zea mays L.) experiment conducted in 2005 in northern Florida. Results showed that the method of combining likelihood values had a strong influence on parameter estimates. The combination method based on the product of the likelihoods associated with each set of observations reduced the uncertainties in posterior distributions of parameter estimates most significantly. It was also found that the likelihood function based on Gaussian probability density function was the best among those tested. This combination accurately estimated the true parameter values, suggesting that it can be used when estimating CERES-Maize model parameters for real experiments.     

日光温室不同栽培季节番茄的需水特性研究

【目的】研究日光温室不同栽培季节番茄(Lycopersiconesculentum Mill.)的需水特性,探明水分需求与环境条件、植株生长发育的关系,为精准灌溉提供依据。【方法】基于番茄对土壤含水率的生理需求,用称质量法和水量平衡法计算需水量,同时观测植株生长及环境因子变化,分析水分需求及其影响因素,构建了水分需求模型。【结果】冬春茬和秋冬茬番茄植株日需水量均呈先升高后降低趋势,秋冬茬需水高峰期出现时间早于冬春茬,但全生育期需水量低于冬春茬;冬春茬番茄日需水量变化主要与植株生长因素有关,包括叶面积和鲜生物量,而秋冬茬番茄日需水量与环境条件相关更密切,主要是日平均光强和空气相对湿度;分别建立冬春茬和秋冬茬番茄的日需水量模型,二者拟合效果均较好。【结论】冬春茬和秋冬茬番茄需水特性存在差异,主要影响因子分别源于植株生长状况和环境条件,冬春茬番茄需水特性主要与叶面积指数和鲜质量有关,而秋冬茬番茄主要与日均光照强度和空气湿度有关。     

根系带水质量模型参数灵敏度分析与标定的研究

利用收集的河南省新乡试验站田间试验数据对根系带水质量模型(ROOt Zone Water Quality Model,RZWQM)输入参数进行灵敏度分析和标定.结果表明,通过参数的灵敏度分析结果对RZWQM进行调参,节省参数校核时间,提高精度.参数标定后模拟值与实测值的对比显示,土壤含水量的模拟均方根差和平均相对误差分...     

RZWQM2模型对河北坝上地区大白菜模拟适用性评价

为明析根区水质模型(RZWQM2)对河北坝上地区蔬菜作物的适用性,以该地区膜下滴灌大白菜为研究对象,建立模型运行的气象、土壤及作物数据库,模拟2018年和2019年大白菜生育期内田间土壤水分动态变化、作物株高变化及最终产量,并通过实测值进行对比分析.结果表明:①经过对该模型参数的校准,得到各土层(20 cm、40 cm...     

土壤空间变异对水氮淋失和产量影响的模拟研究

基于CERES-Maize模型,研究了土壤空间变异和水文年型对半干旱地区土壤水氮淋失和玉米产量的影响.结果表明,土壤空间变异对作物产量和土壤水氮淋失的影响程度与降雨密切相关.丰水年水氮淋失量显著高于平水年和枯水年.降雨对作物产量和农田尺度水氮淋失的空间变异有明显影响,并能在一定程度上减弱土壤空间变异对产量和农田尺度水氮淋失的影响.随着土壤空间变异程度的增大,产量降低,产量的空间变异程度增加.水分渗漏和氮淋失量随土壤空间变异的增加呈增加趋势.当土壤黏粒和粉粒含量变异系数CV≥0.2时,在水氮管理中考虑土壤空间变异有利于提高作物产量,减轻水氮淋失.     

多因子胁迫下的西藏高原青稞生长动力学模拟

【目的】探究耦合气象、土壤水分和氮素状态对青稞生长的影响机理,构建西藏地区青稞生长动力学模型。【方法】于2016─2017年在拉萨市墨达灌区开展了试验研究,测定了青稞生育期气象参数、土壤水分和氮素质量浓度变化过程。基于日光合作用和呼吸作用模拟日干物质增长量,提出了开关因子计算青稞由发育生长到生殖生长的临界时间,根据叶面积指数变化和干物质质量平衡,以及青稞生育期干物质分配和转化关系发展了干物质日增长量分配关系,基于动态平衡原理,提出了气象条件、土壤含水率和氮素影响下的干物质胁迫关系。基于2016年观测值率定模型参数,模拟2017年青稞生长。【结果】模型在本地参数下,模拟结果与实测结果符合良好,Nash-Sutcliffe系数和相对均方根误差分别为0.84和0.05;变化条件下,能够达到较好的模拟精度,Nash-Sutcliffe系数和相对均方根误差分别为0.67和0.11。【结论】所提出的模型能够描述多因子胁迫条件下的青稞生长动力学机制,具有完备的物理机制。     

Diurnal changes in the water relations and transpiration of a soybean crop simulated during the development of water deficits

Summary A new model for transpiration of a soybean crop is formulated and solved numerically: the model specifically includes the water stored in the plant. It describes the changes in the daily course of transpiration, stomatal behaviour, leaf water potential and leaf temperature as water deficits develop. The calculated values of leaf water potential (Fig. 3) and transpiration (Fig. 5) compared well with measured values observed during the development of water deficits in a soybean crop growing on a grey cracking clay soil.     

Evaluation of the RZWQM for the Simulation of Water and Nitrate Movement in Level-Basin,Fertigated Maize

This study concerns the evaluation of the root zone water quality model (RZWQM) to simulate the seasonal water and nitrate movement in a level basin irrigated corn field under three different nitrogen (N) fertilizer treatments. The three N treatments, superimposed over a split basal dose applied before and at planting, were: a single broadcast application of 150 kg N/ha as urea (100% amidic form), a single fertigation application of the same N as UAN (50% amidic, 25% ammonium and 25% nitrate) with the first irrigation, and multiple UAN fertigations with three irrigations. Certain variety-specific maize crop parameters in the model were obtained by fitting these parameters to field data from the single fertigation treatment. The model was then evaluated on water and N results for the treatments. The model adequately simulated the water and nitrate transport for the season, with the seasonal averages of measured and predicted values differing by less than 5%. The most significant differences between measured and simulated water and nitrate occurred near the soil surface (15 cm depth), mostly during the days when the soil was extremely wet following irrigations. With the soil hydraulic properties estimated by simple means, the model tends to overestimate downward water fluxes and related nitrate transport through a compacted layer; however, it is found to be a useful tool to study the relative impacts of alter- nate nitrogen fertilizer and irrigation practices on root zone water quality.     

冬小麦生长及根系吸氮的动态模拟研究

建立了冬小麦生长、根系吸氮耦合模拟模型。冬小麦生长动态受到气象、土壤水分、氮肥等外界因素和作物吸氮能力等内在因素的影响 ,而作物吸氮量与干物质增长量和土壤水分、氮肥条件也有着密切的关系。模拟结果表明 :该模型能够较好的反映冬小麦生长动态、叶面积指数变化及作物吸氮过程     

Irrigation strategies to improve the water use efficiency of wheat-maize double cropping systems in North China Plain

Water is the most important limiting factor of wheat (Triticum aestivum L.) and maize (Zea mays L.) double cropping systems in the North China Plain (NCP). A two-year experiment with four irrigation levels based on crop growth stages was used to calibrate and validate RZWQM2, a hybrid model that combines the Root Zone Water Quality Model (RZWQM) and DSSAT4.0. The calibrated model was then used to investigate various irrigation strategies for high yield and water use efficiency (WUE) using weather data from 1961 to 1999. The model simulated soil moisture, crop yield, above-ground biomass and WUE in responses to irrigation schedules well, with root mean square errors (RMSEs) of 0.029 cm³ cm⁻³, 0.59 Mg ha⁻¹, 2.05 Mg ha⁻¹, and 0.19 kg m⁻³, respectively, for wheat; and 0.027 cm³ cm⁻³, 0.71 Mg ha⁻¹, 1.51 Mg ha⁻¹ and 0.35 kg m⁻³, respectively, for maize. WUE increased with the amount of irrigation applied during the dry growing season of 2001-2002, but was less sensitive to irrigation during the wet season of 2002-2003. Long-term simulation using weather data from 1961 to 1999 showed that initial soil water at planting was adequate (at 82% of crop available water) for wheat establishment due to the high rainfall during the previous maize season. Preseason irrigation for wheat commonly practiced by local farmers should be postponed to the most sensitive growth stage (stem extension) for higher yield and WUE in the area. Preseason irrigation for maize is needed in 40% of the years. With limited irrigation available (100, 150, 200, or 250 mm per year), 80% of the water allocated to the critical wheat growth stages and 20% applied at maize planting achieved the highest WUE and the least water drainage overall for the two crops.     

Evapotranspiration predictions: a comparison among GLEAMS,Opus, PRZM-2, and RZWQM models in a humid and thermic climate

Environmental fate models are increasingly used to evaluate potential impacts of agrochemicals on water quality to aid in decision making. However, errors in predicting processes like evapotranspiration (ET), which is rarely measured during model validation studies, can significantly affect predictions of chemical fate and transport. This study compared approaches and predictions for ET by GLEAMS, Opus, PRZM-2, and RZWQM and determined effects of the predicted ET on simulations of other hydrology components. The ET was investigated for 2 years of various fallow–corn growing seasons under sprinkler irrigation. The comparison included annual cumulative daily potential ET (ET_p), actual ET, and partitioning of total ET between soil evaporation (E_s) and crop transpiration (E_t). When measured pan evaporation was used for calculating ET_p (the pan evaporation method), Opus, PRZM-2, and RZWQM predicted 74, 65, and 59%, respectively, of the 10-year average ET reported for a nearby site. When the energy-balance equations were used for calculating ET_p (the combination methods), GLEAMS, Opus, PRZM-2, and RZWQM predicted 84, 105, 60, and 72% of the reported ET, respectively. The pan evaporation method predicted a similar amount of ET to the combination methods for bare soil, but predicted less ET when both E_s and E_t occurred. RZWQM reasonably predicted partitioning of ET to E_s, while GLEAMS and Opus over-predicted this partitioning. A close correlation between soil water storage in the root zone and ET suggests that accurate soil water content predictions were fundamental to ET predictions. ©     

InfoCrop: A dynamic simulation model for the assessment of crop yields,losses due to pests,and environmental impact of agro-ecosystems in tropical environments. I. Model description

The problems of agriculture in many tropical countries are gradually becoming more intense due to increasing food demand led by population growth, stagnation in farm productivity, mounting yield losses due to multiple pests, increasing vulnerability to global environmental changes and the need to reduce emission of greenhouse gases. Tools and techniques are needed to assist in developing strategies that can lead to higher food production, prevent crop production losses, and ensure minimal greenhouse gas emissions while maintaining soil fertility. Several dynamic models have been developed in recent past but most of these are generally strong either in soils and crops, or in greenhouse gases (GHG) emissions. Pest induced yield losses, a critical issue in the tropics, is not addressed in most models. InfoCrop, a generic dynamic crop model, has been developed to meet these specific requirements. It provides integrated assessment of the effect of weather, variety, pests, soil and management practices on crop growth and yield, as well as on soil nitrogen and organic carbon dynamics in aerobic as well as anaerobic conditions, and greenhouse gas emissions. The model considers the key processes related to crop growth, effects of water deficit, flooding, nitrogen management, temperature and frost stresses, crop–pest interactions, soil water and nitrogen balance and (soil) organic carbon dynamics. Its general structure relating to basic crop growth and yield is largely based on several earlier models, especially SUCROS series, and is written in Fortran Simulation Environment (FSE) programming language. The model has been validated for dry matter and grain yields of several annual crops, losses due to multiple diseases and pests, and emissions of carbon dioxide, methane and nitrous oxide in a variety of agro-environments. To increase the applications of model in research and development, an extremely simple menu driven version of InfoCrop has also been developed. The users of this version do not need any background in programming.     

不同水盐胁迫对番茄生长发育和产量的影响研究

【目的】探究番茄植株对不同水盐胁迫情景的响应,为合理制定盐碱化土壤下的灌溉制度提供科学依据。【方法】以粉欧宝番茄品种为研究对象,开展水盐对番茄生长发育影响的盆栽试验。试验采用完全随机布置,设置3个水分水平(W1-充分灌溉、W2-1/2的W1灌水量、W3-干旱复水)和2个盐分水平(S1-无盐和S2-0.3%含盐量),每个处理4个重复,测定了番茄耗水、干物质和产量指标,分析了不同水盐胁迫对番茄植株生长发育与产量的影响。【结果】与充分灌溉W1相比,W2水平的番茄植株耗水、干物质、植株含水率、叶质量、产量、单果质量显著减少。W3水平的植株耗水量和叶茎比显著减少,但单株干质量与鲜干比所受影响不大;单果鲜质量与干质量显著减小,但坐果率提高导致产量有所增加。盐分处理的番茄植株耗水量、单株干质量、鲜干比、叶茎比、果实总产量、单果鲜质量与干质量均小于无盐处理。水分胁迫显著影响叶片生长和单个果实发育,盐分胁迫抑制植株的生长发育及产量形成。【结论】干旱复水与无盐处理组合(W3S1)下番茄植株表现出了较好的生长发育状况和产量水平,可用于最优调亏灌溉制度的制定。     

RZWQM: Simulating the effects of management on water quality and crop production

The interactive use of experimentation and modeling is an efficient way to devise and test new agricultural management systems. The Root Zone Water Quality Model (RZWQM) is a comprehensive simulation model designed to predict the hydrologic response, including potential for groundwater contamination, of alternative crop-management systems. The model is one-dimensional (vertical into the soil profile) and integrates physical, biological and chemical processes. It simulates crop development and the movement of water, nutrients and pesticides over and through the root zone for a representative unit area of an agricultural field over multiple years. RZWQM allows for a variety of management practices: tillage; irrigation, fertilizer, manure and pesticide applications; tile drainage and crop rotations. Several significant validation efforts have shown the usefulness of RZWQM for evaluating and developing management scenarios.     

干旱区不同水盐处理对向日葵生理性状的影响研究

以美国油料向日葵G101为材料,研究在干旱区不同水盐处理对作物(油葵)的生理性状及产量形成的影响。结果表明:作物群体叶面积、叶片水势和产量随土壤含盐量的增加而呈下降趋势。在不同水盐处理下,轻度盐土结合(55%～65%)θfc的水分处理是适宜的。含水率在(65%～75%)θfc,含盐量在0.3%～0.5%时对油葵的生长及最终产量的形成影响不大,其叶面积指数、叶水势和产量与轻度盐土的分别相差5.90%、0.27MPa和5.92%。而含盐量超过0.5%时,高水分处理也对油葵的生长及最终产量的形成产生严重抑制,其产量是轻盐土的57.39%,低水分处理减产率达62.32%。     

气候变化条件下旱作玉米用水效率与单产变化趋势分析

以渭北旱塬合阳和长武2个试验站点为研究区域,通过多年的玉米田间试验数据评估CERES-Maize模型的适用性,再利用区域气候模式Reg CM4.0输出的气象数据对2050年前玉米单产及生产水足迹进行预测。结果表明:CERES-Maize模型可以很好地模拟雨养玉米产量和物候期,多数年份二者的绝对相对误差(Absolute relative error,ARE)在10%以内,CERES-Maize模型在渭北旱塬旱作农业区有很好的适用性。应用CERES-Maize模型模拟玉米生产水足迹,较传统水足迹计算方法得到的结果更为精确可靠。在RCP2.6气候情景下,随着温度升高和生育期有效降水量的增加,玉米产量呈上升趋势;在RCP8.5气候情景下,随着温度升高和生育期有效降水的减少,玉米产量呈下降趋势。气温上升幅度过大对玉米单产有明显的负面影响,降水与玉米用水效率呈正相关。为有效应对气候变化对旱作作物产量造成的负面影响,应采取减少温室气体排放量、增强土壤蓄水保墒能力、发展集雨补灌、筛选和培育节水抗旱新品种等措施。     

Measurements and simulations of heat and water balance components in a clay soil cropped with winter wheat under drought stress or daily irrigation and fertilization

Soil water and temperature dynamics were measured in a field experiment with winter wheat on a clay soil. There were four treatments: Control (C), receiving natural precipitation, drought (D), protected from rain by plastic screens during the growing season, daily irrigation (I) and daily irrigation and fertilization (IF). Treatments C, D and I received the nitrogen fertilizer as a single application of solid fertilizer in spring. In IF daily dressings of nutrients were supplied in the irrigation water. All treatments received 20 g Nm^–2. An associated experiment with a newly sown grass ley (L) that was irrigated and fertilized daily (total 5.6 g Nm ^–2) was also performed. Standard meteorological variables (air temperature and humidity, wind speed, precipitation, global radiation, and relative cloudiness) and crop development data (green area index, crop height, relative root distribution in depth) above and below ground were used as driving variables within a physically based dynamic model (SOIL) for simulating water and heat fluxes. Measured soil temperature and water content from one treatment (I) were used to tune the model parameters, tentatively set from literature data. Thereafter, water and heat fluxes in the other treatments were simulated using the same parameter values but with different crop-related measurements as driving variables for each treatment. Measured soil temperature and water content in C, D, IF and L could thus be used for validation of the simulations. The theory formulated in the model could accurately explain measured treatment differences in soil water and temperature dynamics. Since the soil-related parameters were identical in all treatments, the model was shown to be applicable over a wide range of moisture conditions.