SAR Data Assimilation for Crop Biomass Simulation Based on Crop Growth Model

Biomass from SAR data was assimilated into crop growth model to describe relationship between crop biomass and crop growth time to improve estimation accuracy of biomass. In addition, inverse model was established in order to estimate biomass according to relationship between biomass and backscattering coefficients from SAR data. Based on cost function, parameters of growth model were optimized as per conjugate gradient method, minimizing the differences between estimated biomass and inversion values from SAR data. The results indicated that the simulated biomass using the revised growth model with SAR data was consistent with the measured one in time distribution and even higher in accuracy than that without SAR data. Hence, the key parameters of crop growth model could be revised by real-time growth information from SAR data and accuracy of the simulated biomass could be improved accordingly.

Studies on crop growth modelling and simulation models in China

There is a close relationship between agricultural production and environmental meteorological conditions. In the study of the correlation between them, the simulation models are paid more attention to the crop growth. In this paper the development of the studies on the crop growth dynamic simulation model in China is briefly reviewed. The relationships between meteorological conditions and each process of crop growth (such as photosynthesis, respiration, accumulation and distribution of assimilation products and growth of leaf area) are studied and simulated basing on the results from field experiments. Preliminary models for rice, wheat, maize and soybean have been developed, and some investigations about modelling methods, procedures and parameters in simulation models are made.

Spatial-time continuous changes simulation of crop growth parameters with multi-source remote sensing data and crop growth model

本文将遥感信息与作物模型同化实现作物生长参数的时空域连续模拟,进而监测生长参数的时空域变化。首先将作物模型WOFOST(World food studies)与冠层辐射传输模型PROSAIL耦合构建WOPROSAIL模型,利用微粒群算法(PSO)通过最小化从CCD数据获取的土壤调节植被指数观测值SAVI(soil adjusted vegetation index)与耦合模型得到的模拟值SAVI’之间差值优化作物模型初始参数。通过MODIS数据反演实现参数的区域化,并将区域参数作为优化后作物模型输入参数驱动模型逐像元计算生长参数,实现生长参数的时空域连续模拟与监测,最终建立区域尺度遥感-作物模拟同化框架模型RS-WOPROSAIL。结果表明:同化模型解决了作物模型模拟空间域和遥感信息时间域的不连续问题。模型模拟的叶面积指数(LAI)、穗重(WSO)、地上总生物量(TAGP)等生长参数较好地体现了水稻生长状况时空域变化,研究区水稻模拟产量与实际产量的误差为27.4%。

Retrieving crop leaf area index by assimilation of MODIS data into a crop growth model

Leaf area index (LAI) is an important parameter in monitoring crop growth. One of the methods for retrieving LAI from remotely sensed observations is through inversion of canopy reflectance models. Many model inversion methods fail to account for variable LAI values at different crop growth stages. In this research, we use the crop growth model to describe the LAI changes with crop growth, and consider a priori LAI values at different crop growth stages as constraint information. The key approach of this research is to assimilate multiple canopy reflectance values observed at different growth stages and a priori LAI values into a coupled crop growth and radiative transfer model sequentially using a variational data assimilation algorithm. Adjoint method is used to minimize the cost function. Any other information source can be easily incorporated into the inversion cost function. The validation results show that the time series of MODIS canopy reflectance can greatly reduce the uncertainty of the inverted LAI values. Compared with MODIS LAI product at Changping and Shunyi Counties of Beijing, this method has significantly improved the estimated LAI temporal profile.

DYNAMIC MODEL OF CROP GROWTH SYSTEM AND NUMERICAL SIMULATION OF CROP GROWTH PROCESS UNDER THE MULTI-ENVIRONMENT EXTERNAL FORCE ACTION

According to the biomechanic theory and method, the dynamic mechanism of crop growth under the external force action of multi_environment factors (light, temperature,soil and nutrients etc.) was comprehensively explored.Continuous_time Markov(CTM) approach was adopted to build the dynamic model of the crop growth system and the simulated numerical method. The growth rate responses to the variation of the external force and the change of biomass saturation value were studied. The crop grew in the semiarid area was taken as an example to carry out the numerical simulation analysis, therefore the results provide the quantity basis for the field management. Comparing the dynamic model with the other plant growth model, the superiority of the former is that it displays multi_dimension of resource utilization by means of combining macroscopic with microcosmic and reveals the process of resource transition. The simulation method of crop growth system is advanced and manipulated. A real simulation result is well identical with field observational results.

Simulation and Validation of Rice Potential Growth Process in Zhejiang Province of China by Utilizing WOFOST Model

A crop growth model of WOFOST was calibrated and validated through rice field experiments from 2001 to 2004 in Jinhua and Hangzhou, Zhejiang Province. For late rice variety Xiushui 11 and hybrid Xieyou 46, the model was calibrated to obtain parameter values using the experimental data of years 2001 and 2002, then the parameters were validated by the data obtained during 2003. For single hybrid rice Liangyoupeijiu, the data recorded in 2004 and 2003 were used for calibration and validation, respectively. The main focus of the study was as follows： the WOFOST model is good in simulating rice potential growth in Zhejiang and can be used to analyze the process of rice growth and yield potential. The potential yield obtained from the WOFOST model was about 8100 kg/ha for late rice and 9300 kg/ha for single rice. The current average yield in Jinhua is only about 78% （late rice） and 70% （single rice） of their potential yield. The results of the simulation also showed that the currant practice of management at the middle and late growth stages of rice should be reexamined and improved to reach optimal rice growth.

Calibration and validation of SiBcrop Model for simulating LAI and surface heat fluxes of winter wheat in the North China Plain

The accurate representation of surface characteristic is an important process to simulate surface energy and water flux in land-atmosphere boundary layer.Coupling crop growth model in land surface model is an important method to accurately express the surface characteristics and biophysical processes in farmland.However,the previous work mainly focused on crops in single cropping system,less work was done in multiple cropping systems.This article described how to modify the sub-model in the SiBcrop to realize the accuracy simulation of leaf area index(LAI),latent heat flux(LHF)and sensible heat flux(SHF)of winter wheat growing in double cropping system in the North China Plain(NCP).The seeding date of winter wheat was firstly reset according to the actual growing environment in the NCP.The phenophases,LAI and heat fluxes in 2004–2006 at Yucheng Station,Shandong Province,China were used to calibrate the model.The validations of LHF and SHF were based on the measurements at Yucheng Station in 2007–2010 and at Guantao Station,Hebei Province,China in 2009–2010.The results showed the significant accuracy of the calibrated model in simulating these variables,with which the R2,root mean square error(RMSE)and index of agreement(IOA)between simulated and observed variables were obviously improved than the original code.The sensitivities of the above variables to seeding date were also displayed to further explain the simulation error of the SiBcrop Model.Overall,the research results indicated the modified SiBcrop Model can be applied to simulate the growth and flux process of winter wheat growing in double cropping system in the NCP.

Growth simulation and yield prediction for perennial jujube fruit tree by integrating age into the WOFOST model

Mathematical models have been widely employed for the simulation of growth dynamics of annual crops,thereby performing yield prediction,but not for fruit tree species such as jujube tree(Zizyphus jujuba).The objectives of this study were to investigate the potential use of a modified WOFOST model for predicting jujube yield by introducing tree age as a key parameter.The model was established using data collected from dedicated field experiments performed in 2016-2018.Simulated growth dynamics of dry weights of leaves,stems,fruits,total biomass and leaf area index(LAI) agreed well with measured values,showing root mean square error(RMSE) values of 0.143,0.333,0.366,0.624 t ha^-1 and 0.19,and R2 values of 0.947,0.976,0.985,0.986 and 0.95,respectively.Simulated phenological development stages for emergence,anthesis and maturity were 2,3 and 3 days earlier than the observed values,respectively.In addition,in order to predict the yields of trees with different ages,the weight of new organs(initial buds and roots) in each growing season was introduced as the initial total dry weight(TDWI),which was calculated as averaged,fitted and optimized values of trees with the same age.The results showed the evolution of the simulated LAI and yields profiled in response to the changes in TDWI.The modelling performance was significantly improved when it considered TDWI integrated with tree age,showing good global(R2≥0.856,RMSE≤0.68 t ha^-1) and local accuracies(mean R2≥0.43,RMSE≤0.70 t ha^-1).Furthermore,the optimized TDWI exhibited the highest precision,with globally validated R2 of 0.891 and RMSE of 0.591 t ha^-1,and local mean R2 of 0.57 and RMSE of 0.66 t ha^-1,respectively.The proposed model was not only verified with the confidence to accurately predict yields of jujube,but it can also provide a fundamental strategy for simulating the growth of other fruit trees.

Effects of Crop Growth and Development on Land Surface Fluxes

In this study, the Crop Estimation through Resource and Environment Synthesis model （CERES3.0） was coupled into the Biosphere-Atmosphere Transfer Scheme （BATS）, which is called BATS CERES, to represent interactions between the land surface and crop growth processes. The effects of crop growth and development on land surface processes were then studied based on numerical simulations using the land surface models. Six sensitivity experiments by BATS show that the land surface fluxes underwent substantial changes when the leaf area index was changed from 0 to 6 m2 m-2. Numerical experiments for Yucheng and Taoyuan stations reveal that the coupled model could capture not only the responses of crop growth and development to environmental conditions, but also the feedbacks to land surface processes. For quantitative evaluation of the effects of crop growth and development on surface fluxes in China, two numerical experiments were conducted over continental China： one by BATS CERES and one by the original BATS. Comparison of the two runs shows decreases of leaf area index and fractional vegetation cover when incorporating dynamic crops in land surface simulation, which lead to less canopy interception, vegetation transpiration, total evapotranspiration, top soil moisture, and more soil evaporation, surface runoff, and root zone soil moisture. These changes are accompanied by decreasing latent heat flux and increasing sensible heat flux in the cropland region. In addition, the comparison between the simulations and observations proved that incorporating the crop growth and development process into the land surface model could reduce the systematic biases of the simulated leaf area index and top soil moisture, hence improve the simulation of land surface fluxes.

Dynamic modeling of mineral contents in greenhouse tomato crop

Tomato is one the most important vegetables worldwide and mineral nutrition in tomato crops is considered as the second most important factor in crop management after water availability. Mathematical modeling techniques allow us to design strategies for nutrition management. In order to generate the necessary information to validate and calibrate a dynamic growth model, two tomato crop cycles were developed. Several mineral analyses were performed during crop development to determine the behavior of N, P, K, Ca, Mg and S in different organs of the plant. Regression models were generated to mimic the behavior of minerals in tomato plants and they were included in the model in order to simulate their dynamic behavior. The results of this experiments showed that the growth model adequately simulates leaf and fruit weight (EF > 0.95 and Index > 0.95). As for harvested fruits and harvested leaves, the simulation was less efficient (EF < 0.90 and Index < 0.90). Simulation of minerals was suitable for N, P, K and S as both, the EF and the Index, had higher values than 0.95. In the case of Ca and Mg, simulations showed indices below 0.90. These models can be used for planning crop management and to design more appropriate fertilization strategies.

基于SEBAL模型的陆浑灌区生育期内实际蒸散发研究

【目的】探索基于遥感技术和能量平衡模型建立准确快捷评估灌区高空间分辨率蒸散发值的方法。【方法】基于SEBAL模型,利用Landsat-8遥感影像和气象数据估算了作物生育期内陆浑灌区的实际蒸散发值,验证了能量平衡模型在陆浑灌区的适用性,进而分析了陆浑灌区实际蒸散发的时空演变特征。【结果】SEBAL模型模拟值与蒸散发产品(v 1.5)的相关系数在0.8以上,SEBAL模型模拟值与站点实测值的相关系数在0.96以上。生育期内,2—5月实际蒸散发值逐月增加,作物种植区实际蒸散发值大于林区,实际蒸散发高-高聚类点主要分布在作物种植区;6—7月实际蒸散发出现年内最高值106.52 mm,林区实际蒸散发值大于作物种植区,实际蒸散发高-高聚类点主要分布在林区;8—9月实际蒸散发值整体开始降低,实际蒸散发高-高聚类点数量减少,并向东北地区收缩。【结论】SEBAL模型利用遥感卫星影像等数据可以得到准确的高空间分辨率地表实际蒸散发估算结果,在灌区尺度具有强适用性。

作物生长模型(CropGrow)研究进展

农业信息技术是基于信息技术与农业科学的交叉融合而形成的新兴技术,催生了数字农业和智慧农业的快速发展。作物生长模型作为其核心内容之一,可以动态模拟作物生长发育过程及其与气候因子、土壤特性和管理技术之间的关系,从而有效克服传统农业生产管理研究中较强的时空局限性,为不同条件下的作物生产力预测预警与效应评估等提供量化工具。本文重点介绍笔者团队在作物生长模型的构建与应用方面形成的总体技术方法、最新研究进展及未来发展思考。通过20多年系统深入的探索和实践,本团队以小麦、水稻等作物为主要对象,以"生理机制解析-模型算法构建-生产力动态预测-效应定量评估-模拟平台研发"为主线,综合运用系统分析、动态建模、虚拟现实、情景模拟及决策支持等方法,开展了作物生长模型CropGrow的构建与应用研究。首先,利用系统分析方法与动态建模技术,构建了机理性与预测性兼备的综合性作物生长模型(CropGrow),包括阶段发育与物候期、器官发生与建成、光合生产与物质积累、同化物分配与产量品质形成、养分动态、水分平衡以及作物三维形态建成与虚拟显示等子模型,可数字化、可视化表征不同条件下作物生长发育与生产力形成过程;然后,结合地理信息系统(GIS)和遥感(RS)技术,构建了基于模型、GIS和RS有效耦合的区域作物生产力预测技术;进一步量化了气候变化、品种更新、土壤改良、措施优化对区域作物生产力形成的影响,拓展了适宜方案生成、理想品种设计、气候效应评估、耕地利用评价以及农业政策制定等应用技术;最后,运用构件化程序设计思想,基于作物生产数据库、作物模型构件库等,集成开发了基于模型的数字化、可视化作物生长模拟系统与决策支持平台,实现了数据管理、参数优化、生长模拟、遥感耦合、区域预测、方案设计、效应评估、安全预警、产品发布等综合功能。未来作物模拟研究将在完善基础数据库的基础上,进一步提升预测能力、量化基因效应、拓展智能决策、耦合多功能模型等,为粮食生产的预测预警、情景效应的量化评估、生产管理的智能决策、作物品种的优化设计等提供数字化支撑,对于保障国家粮食安全和推进数字农业发展具有重要意义。

基于数据同化系统的作物产量预测研究进展

数据同化系统融合了遥感数据和作物生长模型的优势,是实时监测农业生产状况的有力手段。本文在简要介绍作物产量遥感估测方法的基础上,重点对数据同化算法的发展情况、多源遥感数据在数据同化上的应用潜力、数据同化系统的不确定性以及数据同化系统的尺度效应4方面进行论述。并且针对农业应用现状,提出未来应充分挖掘多源遥感数据、多作物生长模型集合和数据算法的优势,最终实现以机理模型为纽带的作物估产模式,并为制定田间管理策略、规划粮食产业布局和制定进出口贸易政策提供有力的数据和技术支撑。

AquaCrop作物模型研究和应用进展

AquaCrop是由国际粮农组织(FAO)开发并向全球免费推广的一款新的作物生长模型,自从2009年发布以来,已经受到各国研究者的重视,而国内对该模型的应用尚处于起步阶段。为国内同仁更深入的了解该模型以及在中国的进一步验证和应用该模型提供有用的背景和参考信息,对模型原理、模型计算方案、模型应用现状和存在问题进行介绍和探讨。众多研究结果证明,AquaCrop模型有很好的模拟精度,可以辅助灌溉管理决策等。AquaCrop作为一个新发展的模型,其适应性还有待进一步验证,研究领域也有待进一步拓宽。

膜下滴灌水源矿化度对棉花生长的影响及AquaCrop模拟

利用微咸水灌溉是缓解干旱区灌溉淡水资源短缺的有效途径。为探讨膜下滴灌水源矿化度对棉花植株体内盐分累积、生长及产量的影响,该研究开展了2 a(2020-2021年)测坑试验,共设置6个灌溉水矿化度,分别为1、2、3、4、5和6 g/L,分析了棉花生育期内不同土层盐分累积规律,构建了不同矿化度水源膜下滴灌棉花的AquaCrop作物生长模型。结果表明:1)不同矿化度水源膜下滴灌棉花土壤盐分在40~60 cm土层积累量达到峰值,80~100 cm土层盐分积累较少。不同矿化度水源膜下滴灌棉花2 a末40~60 cm土层盐分分别累积44.29%、42.68%、43.40%、34.92%、35.69%、39.32%。2)灌溉水源矿化度为3~4 g/L时棉花生长指标和产量优于其他处理,且不会造成盐分累积过高,灌溉水源矿化度为4 g/L与1 g/L相比棉花各生长指标和产量受到影响较小,综合考虑棉花适宜灌溉水源为3~4 g/L之间。3)通过构建AquaCrop作物生长模型模拟冠层覆盖度、地上干物质量模拟值与实测值的决定系数大于等于0.812,标准均方根误差不大于24.1,一致性指数不小于0.984,模拟效果较好。棉花产量模拟值与实测值的相对误差RE小于9.28%,可见AquaCrop作物生长模型能较好地模拟不同矿化度水源膜下滴灌棉花生长发育过程,可用于产量预测和农业水资源优化管理。研究结果可为干旱区咸水资源膜下滴灌技术可持续利用提供依据。

作物生长模型研究现状与展望

作物生长模型由最初的作物生长发育模型发展到农业决策支持模型,在科学研究、农业管理、政策制定等方面发挥着越来越重要的作用。本文首先回顾了作物生长模型的发展过程,并按照模型主要驱动因子,将作物生长模型分为土壤因子、光合作用因子和人为因子驱动3类并分别进行了归纳阐述;然后对典型的模型分别从模型模块、时空尺度、可模拟的作物类型等方面进行列表式对比;并对作物生长模型在气候变化评估、生产管理决策支持、资源管理优化等方面的应用,以及面临的极端条件、复杂农业景观和模型复杂度等挑战进行了总结,在此基础上认为遥感数据同化和孪生农场是其发展方向。

基于同化植被净初级生产力的区域玉米产量估测

为了评价植被净初级生产力NPP作为同化变量提高区域玉米产量估测精度的有效性及其应用于区域玉米产量估测的潜力,选择黑龙江省双鸭山市友谊农场玉米种植区为研究对象,以WOFOST为作物生长动态模型,分别以叶面积指数LAI和植被净初级生产力NPP为同化变量,选用MODIS LAI和NPP产品为遥感观测数据,开展基于遥感观测数据与作物生长模型同化的区域玉米产量估测研究。重点比较了分别以叶面积指数LAI和植被净初级生产力NPP为同化变量的区域玉米产量估测结果精度。结果表明,相较以叶面积指数LAI为同化变量的区域玉米产量估测统计结果(均值为7755 kg/hm^(2),标准差为1303 kg/hm^(2)),以植被净初级生产力NPP为同化变量的区域玉米产量估测统计结果(均值为9214 kg/hm^(2),标准差为190 kg/hm^(2))与研究区域统计结果(均值为8970 kg/hm^(2))更为接近,但在表现玉米产量空间异质性方面稍显不足。以植被净初级生产力NPP为同化变量开展区域作物产量估测是一种可行的数据同化策略,具有较大的应用潜力。

基于磁化微咸水灌溉的作物生长发育特征和产量研究——以青河县为例

为提升高海拔地区微咸水利用效率,以青河县试验区种植的玉米、向日葵和马铃薯为对象,对比分析了磁化微咸水处理对各作物生长发育和产量的影响,进一步研究了磁化微咸水灌溉的向日葵生长模型,分析其生长特征与花盘直径的关系。结果表明:与常规灌溉大田试验相比,研究区3种作物生长发育特征值均显著增大,各作物产量分别提高了28.90%、18.27%和8.19%;磁化微咸水处理的向日葵生长发育各特征指标间相关性很强,建立了向日葵花盘直径关于其特征的多元线性回归模型,拟合系数R 2为0.942;在高海拔地区磁化微咸水灌溉能有效增强作物的生长发育特征,并提高其产量。研究结果可为高海拔灌区推广磁化微咸水设备提供理论依据。

不同矿化度水源膜下滴灌棉田土壤水盐动态和作物生长模拟

为构建适用于干旱区膜下滴灌条件的土壤水盐动态分布和棉花生长模型,基于2020—2021年的田间试验,经过对SWAP模型的土壤、土壤水力功能和作物生长等模块进行率定和验证,对灌溉水矿化度为1、2、3、4、5、6 g·L^(-1)时的土壤水盐分布特征、作物生长过程和干物质累积分配进行数值模拟。结果表明:(1)土壤含水率与土壤含盐量的模拟精度以20~100 cm土层较好,0~20 cm土层模拟精度较差,其中土壤含水量的模拟效果优于土壤含盐量;随着灌溉水源矿化度的增加,土壤含水率和含盐量的模拟误差逐渐变小。(2)不同矿化度水源膜下滴灌棉花叶面积指数模拟效果较好(R2=90.72%,RMSE=0.35 cm^(2)·cm^(-2),NRMSE=8.73%,IOA=0.98)。(3)不同矿化度水源膜下滴灌棉花茎干物质累积量模拟效果较好(R2=89.08%,RMSE=6.12 g,NRMSE=23.16%,IOA=0.96)。研究结果表明,SWAP模型可以较好地对不同矿化度水源膜下滴灌的土壤水盐动态分布和棉花生长过程进行模拟。

耕作模式对红壤坡耕地典型作物不同生育期土壤入渗特性的影响

以南方红壤区典型作物玉米为试验作物,设置顺坡垄作(Downslope ridge tillage,DT)、横坡垄作(Cross-slope ridge tillage,RT)、传统耕作(Conventional tillage,CT)、覆膜耕作(Plastic mulching tillage,PM)4种耕作模式试验小区,利用环刀法测定土壤入渗速率和累积入渗量,探析了耕作模式对红壤坡耕地作物不同生育期土壤入渗特性的影响,同时还对5种典型入渗模型在红壤坡耕地上的适宜性进行了评价。结果表明:(1)作物不同生育期土壤入渗速率和累积入渗量曲线差异明显,RT、PM的土壤入渗过程变化相对较大,而CT、DT的土壤入渗过程变化相对较小;(2)总体来看,RT、PM初始入渗率较大,且入渗速率变化较大,而DT、CT初始入渗率较小,入渗速率变幅也较小,饱和导水率总体表现为CT>RT>PM>DT;(3)不同耕作模式下的土壤初始入渗率与土壤容重呈负相关,与土壤有机质呈正相关,而稳定入渗率和饱和导水率则与土壤全氮含量呈正相关;(4)5种入渗模型均可较好地对不同耕作模式的红壤坡耕地土壤入渗过程进行拟合,其中Horton模型的拟合效果总体最优。研究结果可为红壤坡耕地降雨径流调控和坡耕地水土流失防治提供理论依据。