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1.
不同灌水水平下CROPGRO棉花模型敏感性和不确定性分析 总被引：1，自引：0，他引：1
基于过程的作物模型使用大量的品种和土壤参数来模拟作物生长和土壤水分变化。对于新的作物品种或新的环境,这些参数往往需要重新率定,然而许多参数难以通过实测获得。敏感性分析(sensitivity analysis,SA)可以量化模型输入参数对模型输出的影响,通过筛选出敏感性较大的参数进行率定,而把敏感性较小的参数设为固定值,可以极大简化参数率定过程,提高工作效率和模型模拟精度。为了给DSSAT-CROPGRO-Cotton模型应用于新疆地区进行棉花灌溉制度优化提供本地化的模型参数,对该模型进行了敏感性分析和不确定性分析。该文依据新疆石河子的棉花大田试验资料,应用Morris法和扩展傅里叶幅度敏感性检验(extend Fourier amplitude sensitivity test,EFAST)法对DSSAT-CROPGRO-Cotton模型3个灌水处理(60%ETC、80%ETC和100%ETC,ETC为作物蒸发蒸腾量crop evapotranspiration)下6个输出结果(初花天数、成熟天数、籽棉产量、地上干物质量、最大叶面积指数和蒸发蒸腾量)对于品种和土壤参数进行敏感性分析,并比较了2种方法的相关关系,最后对EFAST法的输出结果进行不确定性分析。相关分析结果显示,对于地上干物质量和最大叶面积指数,Morris法和EFAST法相关性介于0.87~0.93,对于模型结果成熟天数、籽棉产量和蒸发蒸腾量,2种方法相关性介于0.66~0.81。敏感性分析和不确定性分析结果显示,模型模拟灌水处理对初花天数无明显差异,且模拟初花天数和最大叶面积指数存在参数敏感性过于单一现象。模型参数敏感性随土层而不同:对于成熟天数,40~80 cm土壤参数的敏感性更强;对于地上干物质量和蒸发蒸腾量,80~120 cm土壤参数的敏感性更强,这可能是由于该地区气候干旱,下层土壤水分充足程度直接影响作物受到水分胁迫的程度,进而影响作物生长发育和蒸发蒸腾量。模型输出结果最大叶面积指数和蒸发蒸腾量存在一定程度的高估。该研究可提高CROPGRO-Cotton模型在新疆地区的模拟效率和模拟精度。 相似文献
2.
基于遥感和AquaCrop作物模型的多同化算法比较 总被引：1，自引：0，他引：1
为了研究不同数据同化方法在AquaCrop(FAO Crop model to simulate yield response to water)模型模拟作物地上生物量(above ground biomass,AGB)、冠层覆盖度(canopy cover,CC)和产量过程的效率,以冬小麦为研究对象,利用2012-2013、2013-2014和2014-2015年冬小麦田间试验数据,将标定的Aqua Crop生长模型与遥感光谱信息相结合开展同化技术分析,应用粒子群优化(particle swarm optimization,PSO)、模拟退火(simulated annealing,SA)和复合型混合演化(shuffled complex evolution,SCE-UA)3种数据同化算法,以不同生育期、不同水分处理和不同氮肥水平的AGB和CC为双变量开展多同化算法的模拟分析,对3种数据同化算法的运算效率和同化结果进行对比分析。结果表明:1)3种数据同化算法达到的应度值0.26时,SCE-UA同化算法用时最少(833 s),SA数据同化算法用时最多(1433 s),表明SCE-UA同化算法效率最优,SA数据同化算法效率最低;2)不同生育期的同化结果,AGB的同化精度随着生育期的推进而降低,AGB的模拟值在拔节期和挑旗期高于实测值,被高估,在开花期和灌浆期被低估,总的AGB被低估;CC在拔节期和挑旗期被低估,在开花期和灌浆期被高估,总的CC被低估;3)不同水分处理的同化结果,AGB普遍被低估,CC在雨养(W0)条件下被高估,在正常灌溉(W1)和过量灌溉(W2)条件下被低估;产量均被低估;4)不同氮肥水平,AGB的模拟精度随着施N量的增加而降低,并且普遍被低估,CC普遍被高估,产量均被低估。以上结果表明,PSO、SA和SCE-UA 3种数据同化算法均能有效模拟冬小麦的AGB、CC和产量,其中SCE-UA数据同化算法无论在运算效率还是同化结果的精度上均优于PSO和SA数据同化算法。 相似文献
3.
基于MCMC方法的WOFOST模型参数标定与不确定性分析 总被引：1，自引：0，他引：1
为探究作物生长模型参数的自动标定技术及其不确定性分析方法,该研究以郑州农业气象试验站为试验点,利用融入了snooker更新(snooker update)的DE-MC(differential evolution Markov chain,差分进化马尔科夫链)方法实现对WOFOST(world food studies)作物生长模型的参数标定和不确定性定量评价。snooker更新增加了DE-MC算法中候选样本的多样性,从而实现利用更少的并行链对多维参数空间进行有效采样,较适合于WOFOST模型参数众多的特性。结果表明:相比于模型默认值,采用MCMC(Markov chain Monte Carlo,马尔科夫链-蒙特卡洛)标定后的参数,叶面积指数(leaf area index,LAI)模拟精度可提高51.40%~53.07%,产量模拟精度提高8.25%~8.88%。标定参数中,SPAN、SLATB070、SLATB040、AMAXTB130和SLATB00的后验分布可近似为高斯分布,其中SPAN的不确定性最低。带入后验参数集合进行模型,LAI在三叶期至返青期之间以及拔节期至抽穗期之间模拟的不确定性较大;产量模拟的不确定性随时间不断增大,至乳熟期前后达到稳定。该方法能够实现对多参数复杂作物生长模型的参数标定和不确定性分析,对作物模型参数估计及提高模拟精度具有重要作用。 相似文献
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干旱脆弱性评价作为干旱风险评估和灾损评估的重要环节,在保障国家粮食安全和农业可持续发展中具有重大意义。该文以中国5大玉米种植区为研究区域,以其中241个主要玉米种植城市为基本单元,采用扩展傅里叶幅度检验法选取出2个敏感参数(作物冠层形成后到衰老之前的作物系数和参考收获指数),并在此基础上对AquaCrop作物模型进行逐市的参数标定。利用参数标定后的模型对不同灌溉条件下玉米受到的水分胁迫及相应情景下的产量进行模拟计算,分别建立了5个玉米种植区对应的干旱脆弱性曲线。结果表明:5个区域的脆弱性曲线拟合结果均为S形曲线,当干旱强度指标达到0.2附近时,产量损失率开始迅速增加;当干旱强度指标达到0.6左右时,产量损失率接近最大值。拟合函数的决定系数R^2分别在0.47~0.98之间,曲线拟合结果较好,在中国区域性玉米干旱脆弱性研究与干旱风险评估领域具有一定的理论与应用价值。 相似文献
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《Communications in Soil Science and Plant Analysis》2012,43(22):2899-2912
ABSTRACTAquaCrop applies an automatic calibration procedure through semi-quantitative approach to determine degree of soil fertility stress on crop production and water productivity. The objective of this study was to assess this capability of AquaCrop to simulate maize grain yield and biomass production, canopy cover and soil water content in the root zone under different nitrogen (N) applications in a semi-arid environment. The field experiments were conducted at the research farm located in Tehran, over the 2015 and 2016 growing seasons. Five N treatments were investigated including no nitrogen (N0), 50(N1), 100(N2), 150(N3) and 200 kg N. ha?1 (N4) for each year. Calibration was carried out using the data of N0 and N4 in 2015 and validation in the field was performed with remaining data. The results indicated that the range of relative root-mean-square error (RRMSE), coefficient of determination (R2) and mean bias error (MBE), for estimating final biomass production were obtained as 5.16%, 0.966, 0.28 ton. ha?1, and for final grain yield were 14.64%, 0.939, 0.56 ton. ha?1, respectively. The AquaCrop simulated canopy cover and biomass production development with RRMSE of 16.23–24.12% and 6.09–32.39%, respectively. The performance of the model for simulating soil water content was also good with RRMSE< 10.78%. Over all, these results confirmed that the AquaCrop model could be an applicable tool for managing maize production under different N stresses in a semi-arid environment. 相似文献
6.
基于全局敏感性分析和贝叶斯方法的WOFOST作物模型参数优化 总被引：12，自引：7，他引：5
作物模型参数的敏感性分析、标定和验证可以提高模型的效率和精准度,进而为模型应用做好准备工作。该研究结合参数全局敏感性分析方法以及贝叶斯后验估计理论的马尔科夫蒙特卡洛(Markov Chain Monte Carlo,MCMC)方法,以华北栾城站三年的冬小麦观测数据(叶面积和地上生物量)为参照,对WOFOST模型的55个品种参数进行了敏感性分析、筛选和优化。发现:1)对叶面积影响较大的参数为:生育期为0、0.5、0.6和0.75时的比叶面积、生育期为1.5时的最大光合速率、叶面积指数最大增长率;对地上干物质影响较大的参数为:生育期为1.5时的最大光合速率、生育期为0时的比叶面积、35℃时叶面积的生命周期、生育期为0时的散射消光系数、生育期为1.8时的最大光合速率、储存器官的同化物转换效率。2)潜在和雨养产量水平下,最大叶面积和地上生物量对参数的敏感性差异不大。3)马尔科夫蒙特卡洛方法(MCMC)可以对WOFOST模型品种参数较好地优化;设计的3种校正-验证方案中,第1种方案(用1998-1999年作为校正年份,1999-2000年,2000-2001年作为验证年份)模拟效果最好。4)优化后的参数,模型对潜在产量水平模拟较好,一致性指数均大于0.9,相对均方根误差小于20%;而对有水分胁迫的雨养情况下比潜在产量水平的模拟结果差,表明模型对水分胁迫的模拟不足。该研究为WOFOST模型区域应用和模型调整优化提供科学理论依据。 相似文献
7.
Ali vahdati Ebrahim Amiri Ali Akbar Ebadi Ali Faramarzi 《Communications in Soil Science and Plant Analysis》2020,51(16):2137-2146
ABSTRACT The present study was conducted to assess the ability of AquaCrop model in predicting of grain and biological yield of rice genotypes in water management. A two-year field experiment was conducted at the experimental farm of the Iranian Rice Research Institute in Rasht, Iran from 2016 to 2017. The experiment was established in a split-plot design with two irrigation management (continuous submergence and end season water stress) as the main plot, fourth rice genotypes as the sub-plot and three replications. The goodness-of-fit between observed and simulated grain yield and final biomass was assessed by means of the coefficient of determination (R 2), the absolute and normalized root mean square errors (RMSE). The RMSEn of predicting grain yield at calibration and evaluation stages was in the range of 6–12% and 6–8% for biological yield. The results indicated that AquaCrop model is suitable to predict grain yield and biological yield of rice genotypes in northern Iran. AquaCrop model can be used to determine optimization strategies to improve the water consumption of rice genotypes. 相似文献
8.
不同气候区和不同产量水平下APSIM-Wheat模型的参数全局敏感性分析 总被引：5，自引：5，他引：5
量化作物模型的参数敏感性和模拟结果的不确定性对模型的标定和应用具有重要意义。为了探讨小麦生长模型(APSIM-Wheat)在不同气候区和不同产量水平下参数的敏感性,以及由于参数造成模拟结果的不确定性,以华北栾城、黄土高原长武、四川盐亭和新疆乌兰乌苏4个不同气候区下的典型冬小麦生产地为分析对象,运用扩展傅里叶幅度检验法(extended Fourier amplitude sensitivity test,EFAST)的全局敏感性分析方法,量化了小麦生长模型(APSIM-Wheat模型)在3种产量水平下(潜在、雨养和实际产量)的开花期、成熟期、产量、生育期的蒸散(evapotranspiration,ET)对品种、土壤和生化等33个参数的敏感性和不确定性。发现:1影响开花期和成熟期较为敏感的参数依次是:始花期积温、出苗到拔节积温、春化指数、光周期因子、灌浆期积温;2影响产量较敏感的参数依次为:春化指数、出苗到拔节积温、每茎谷粒质量、潜在灌浆速率、光周期指数、最大谷粒质量和辐射利用效率(radiation use efficiency,RUE);影响生育期蒸散较为敏感的参数依次为:春化指数、出苗到拔节积温、光周期指数、始花期积温;3不同产量水平下,参数敏感性差异不大,4个不同气候类型下的冬小麦开花期、成熟期、产量和生育期的蒸散对参数的敏感性基本一致;4不同气候区下,开花期和成熟期对模型参数敏感性差异很小,但产量和生育期的蒸散对参数敏感性有差异。该研究为APSIM-Wheat模型的区域应用和模型调参提供了科学指导依据。 相似文献
9.
Ruzica Stricevic Aleksandar Simic Alpaslan Kusvuran Marija Cosic 《Archives of Agronomy and Soil Science》2017,63(9):1301-1313
Given that the optimal sowing rate and inter-row spacing of Italian ryegrass raised for seed have not been determined, the objective of this research was to assess the effect of crop density on biomass and seed yields under different climate conditions, applying the AquaCrop model. The data came from experiments conducted under moderate continental climate conditions at Stitar (Serbia) and Mediterranean climate conditions at Cukurova (Turkey). At Stitar, there were three different inter-row spacings (high (Sd), medium (Sm) and low (Sw) crop densities), while at Cukurova there was only high crop density (Sn). In the calibration process, the initial canopy cover, canopy expansion and maximal canopy cover were adapted to each crop density, while the other conservative parameters were adjusted to correspond to all climate conditions. Calibration results showed a very good match between measured and simulated seed yields; the values of the coefficient of determination (0.922). The biomass simulation was very good for Cukurova (R2 = 0.97), but somewhat poorer for Stitar (R2 = 0.72). Other statistical indicators were high such as Willmott index of agreement of both the calibrated and validated data sets, for both study areas >0.916 and normalized root mean square error in the range from 9–18%. The AquaCrop model was found to be more reliable for Italian ryegrass biomass and seed yield predictions under mild winter climate conditions, with adequate water supply, compared with moderate climate and water shortage conditions. 相似文献
10.
HSPF在热带沿海流域水文模拟中的应用 总被引：1，自引：1，他引：0
[目的] 探究HSPF模型在热带沿海流域的适用性和不确定性，为该模型在不同流域和地区的应用提供科学参考。[方法] 以位于热带沿海地区的三亚河流域为例，建立HSPF模型，选取2017-2019年径流量对模型进行率定和验证；通过Morris筛选法分析了水文过程中8个参数的敏感度，并与国内外研究不同流域的参数敏感度相对大小进行对比；同时利用MC-LHS方法对不同降雨量下模型的不确定性进行分析。[结果] HSPF模型能够很好地模拟研究区域实际的水文过程，率定期和验证期的NSE分别为0.93和0.98，相对误差（Re）分别为0.87%和0.21%；地下水日消退系数为最敏感参数，而下层土壤蒸发系数和地下水出流中进入深层的比例对径流模拟的影响几乎可以忽略。[结论] 参数敏感度相对大小体现空间差异性。模型模拟的不确定性与降雨量之间的相关性明显。降雨量越大，模型模拟的不确定性和置信区间就越大，模型就越不稳定。 相似文献
11.
12.
M. van Oijen D.R. CameronK. Butterbach-Bahl N. Farahbakhshazad P.-E. JanssonR. Kiese K.-H. RahnC. Werner J.B. Yeluripati 《Agricultural and Forest Meteorology》2011,151(12):1609-1621
Four different parameter-rich process-based models of forest biogeochemistry were analysed in a Bayesian framework consisting of three operations: (1) Model calibration, (2) Model comparison, (3) Analysis of model-data mismatch.Data were available for four output variables common to the models: soil water content and emissions of N2O, NO and CO2. All datasets consisted of time series of daily measurements. Monthly averages and quantiles of the annual frequency distributions of daily emission rates were calculated for comparison with equivalent model outputs. This use of the data at model-appropriate temporal scale, together with the choice of heavy-tailed likelihood functions that accounted for data uncertainty through random and systematic errors, helped prevent asymptotic collapse of the parameter distributions in the calibration.Model behaviour and how it was affected by calibration was analysed by quantifying the normalised RMSE and r2 for the different output variables, and by decomposition of the MSE into contributions from bias, phase shift and variance error. The simplest model, BASFOR, seemed to underestimate the temporal variance of nitrogenous emissions even after calibration. The model of intermediate complexity, DAYCENT, simulated the time series well but with large phase shift. COUP and MoBiLE-DNDC were able to remove most bias through calibration.The Bayesian framework was shown to be effective in improving the parameterisation of the models, quantifying the uncertainties in parameters and outputs, and evaluating the different models. The analysis showed that there remain patterns in the data - in particular infrequent events of very high nitrogenous emission rate - that are unexplained by any of the selected forest models and that this is unlikely to be due to incorrect model parameterisation. 相似文献
13.
为探究内蒙古河套灌区玉米生长适宜的水肥管理方案,开展了不同灌水与施肥水平玉米田间试验。利用田间实测数据对AquaCrop模型进行了率定与验证,以此为基础,采用AquaCrop模型模拟分析了不同灌水和施肥条件下玉米产量和水分利用效率的变化规律。结果表明:(1)模型率定和验证过程中冠层覆盖度和生物量模拟值与实测值的R~2分别介于0.74～0.99,0.87～0.99;NRMSE分别介于4.55%～12.32%,5.77%～27.07%;E_(NS)分别介于0.90～0.99,0.85～0.99;各处理产量模拟值与实测值间R~2分别为0.99,0.97;NRMSE分别为4.59%,3.42%,E_(NS)分别为0.95,0.97;水分利用效率模拟值与实测值间R~2分别为0.81,0.86;NRMSE分别为6.75%,13.85%,E_(NS)分别为0.96,0.83。说明AquaCrop模型在河套灌区具有很好的适用性。(2)利用校验后的模型模拟了不同施肥水平下灌水量变化对玉米产量和水分利用效率的影响,当灌水量达270 mm后,继续增加灌水量,玉米产量和水分利用效率基本保持不变,甚至有所降低。(3)以稳产高效为目标,中肥条件下,灌水270 mm时玉米产量和水分利用效率均为各灌水量中的最优值。因此,推荐灌水270 mm、施肥375 kg/hm~2为研究区保障玉米稳产高效的最优灌溉施肥组合。 相似文献
14.
为探究省力化栽培模式下库尔勒香梨园适宜的灌溉制度，依据4种灌溉定额(3 750,5 250,6 750,8 250 m3/hm2)条件下2年香梨的田间试验数据，通过冠层覆盖度、土壤含水量和蒸散强度(ETa)和产量指标，确定AquaCrop模型参数。设置不同灌水场景，综合考虑产量、水分利用效率和灌溉水利用效率，利用AquaCrop模型优化香梨灌溉制度。结果表明：Y2W3处理产量高出其余处理3.87%～16.86%,Y2W1处理水分利用效率高出其余处理2.88%～27.20%;AquaCrop模型模拟与试验地实测结果的决定系数(R2)、均方根误差(RMSE)、标准均方根误差(NRMSE)、拟合度指数(d)和Nash效率系数(NSE)评价指标表明，冠层覆盖度R2变化范围为0.89～0.93,土壤含水量d为0.92～0.98,ETa的RMSE为1.06～1.61 mm/d; AquaCrop模型预测15种不同场景，灌溉定额7 200 m3/h... 相似文献
15.
AquaCrop模型在西北胡麻生物量及产量模拟中的应用和验证 总被引：2，自引：0，他引：2
为了预测水分和养分对胡麻籽粒产量、生物量与水分生产率的影响,使用FAO研发的水分驱动作物模型AquaCrop对胡麻在不同灌溉与氮磷水平下的生长情况进行模拟和验证。试验分别于2011年、2012年在甘肃省榆中县良种场进行,试验设置4个灌溉水平,3个氮水平,3个磷水平。模型性能的评价采用模型效率(E)、决定系数(R2)、均方根误差(RMSE)和平均绝对误差(MAE)等统计指标。分析结果表明:AquaCrop模型校正的籽粒产量和生物量在不同灌溉与氮磷水平处理下的预测误差统计值为:0.97E0.99,0.11RMSE0.33,0.11 t·hm 2MAE0.42 t·hm 2,与2012年的试验观察数据(0.96E0.99,0.11RMSE0.42,0.11 t·hm 2MAE0.39 t·hm 2)基本一致;同时,群体覆盖(CC)与生物量的模拟结果与测定值也非常拟合。AquaCrop模型在充分灌溉处理下预测胡麻产量,比非充分灌溉处理下具更高的准确性。因而,水分驱动模型AquaCrop在西北胡麻区不同的灌溉与田间管理措施下有较高的模拟精确性,具有广阔的应用前景和价值。 相似文献
16.
On the Use of Different Efficiency Criteria for the Validation of a Heavy Metal Balancing Tool 总被引：1，自引：0，他引：1
The validation of metal balancing tools is usually based on the comparison of simulated versus observed data. In our study, we applied a set of different relative and absolute criteria to evaluate the performance of the model Assessment Tool for Metals in Soils. In this process, the uncertainty of the model output and the sensitivity of model parameters were also assessed. The study includes data from 123 agricultural used top soils which are characterized by the application of different fertilizers (mineral and farmyard fertilizers, sewage sludge) resulting in diverse metal inputs into the soil. Although the most common validation criteria (coefficient of determination, error ratio between prediction and observation) indicated a good model performance in predicting the metal contents over a simulation period, the absolute measure (mean absolute difference between prediction and observation) showed that the informational value of the validation results was limited for several sites. Therefore sites with short simulation periods and/or low metal inputs are not suitable for validation, because the model uncertainty covers the metal concentration changes. Excluding such sites from the validation statistics led to evaluable and quite better validation results. Although the calculated output uncertainty was low, a further reduction can be realized by improving the database for the identified sensitive parameters (initial soil metal content and fertilizers metal concentration). 相似文献
17.
根系水质模型中土壤与作物参数优化及其不确定性评价 总被引：9，自引：5，他引：4
农业系统模型参数优化存在很高的不确定性,是模型应用研究的重点和难点。该研究利用自动优化程序PEST(parameter estimation software)对根系水质模型(root zone water quality model,RZWQM)中土壤参数(土壤水力学参数和根系生长参数)和作物遗传参数进行了优化,结果表明PEST优化模拟结果明显优于传统试错法的校正结果,且具有较高的参数优化效率。模型参数优化不确定性评价表明校正数据和参数初始值的选择、土壤水力学参数估算方法、不同类型参数间的相互作用以及优化目标方程(误差来源计算)都明显影响模型模拟结果。以上过程中土壤水力学参数优化值差异较小,但其土壤水分特征曲线却明显不同。通过以上评价分析提高了RZWQM相关参数优化结果的可靠性及其模拟功能,降低了模型参数优化的不确定性,为PEST优化其他模型参数提供了重要支持。 相似文献
18.
中国不同水稻生长环境下ORYZA(v3)模型参数全局敏感性分析 总被引：3，自引：1，他引：2
中国水稻种植分布广、气候跨度大，水稻生长环境差异较大。ORYZA(v3)模型被广泛用于水稻生长模拟，但不同环境下该模型参数敏感性的时空特征尚不清楚。该研究选取了位于中国16个水稻种植亚区的18个典型站点，分别采用EFAST（Extended Fourier Amplitude Sensitivity Test）方法对模型中16个作物参数进行30 a（1986－2015年）全局敏感性分析，分析了参数敏感性与气象因子的相关性。结果表明，模型参数敏感性在不同生育阶段、不同稻作制度、以及不同站点之间均存在较大的差异，尤其在高海拔或具有特殊气候类型的地区的参数敏感性明显异于其他地区；模型中叶面积相对生长速率最大值（RGRLMX）、颖花生长系数（SPGF）和最大单粒重（WGRMX）的敏感性受环境的影响最大；各参数的敏感性与日均最低气温、日均最高气温、积温具有显著相关性，但由于海拔、纬度等因素的综合影响，模型参数敏感性在空间上不随纬度或海拔的变化呈现单一的变化趋势；RGRLMX在大理、牡丹江等站点出现单参数极度敏感的现象，揭示了模型的结构可能存在一定缺陷，在容易受低温冷害影响的地区应用时具有一定的局限性。 相似文献
19.
《Communications in Soil Science and Plant Analysis》2012,43(14):1692-1705
This study tests the potential of near infrared reflectance spectroscopy (NIRS) for predicting soil fertility and management history from topsoil (0–10 cm deep) spectra. Soil fertility was assessed by measuring the growth of a test plant, and soil management history was determined through inquiries with farmers. Moreover, NIRS predictive value was compared with that of a group of topsoil parameters: total carbon and nitrogen, nitrate, potential respiration and denitrification, and microbial biomass. Modelling used partial and modified partial least square regressions to ensure comparisons between predictions by NIRS versus by soil parameters. Soil fertility and management history were well predicted by NIRS (Q2 = 0.78 and R2 = 0.89 both; Q2 and R2 are cross-validation and calibration coefficients of determination, respectively), as were the soil parameters (Q2 = 0.79–0.92 and R2 = 0.86–0.98). Soil fertility and management history were more accurately predicted by NIRS than by the set of soil parameters. 相似文献
20.
农业生产管理系统模型输入参数多,参数率定过程十分耗时费力,大大限制了其推广应用。该研究以华北平原2 a的冬小麦-夏玉米田间试验观测数据为基础,使用PEST(parameter estimation)参数自动优化工具对土壤-作物-大气系统水热碳氮过程藕合模型(soil water heat carbon and nitrogen simulator,WHCNS)的土壤水力学参数、氮素转化参数和作物遗传参数进行自动寻优,同时计算分析模型参数的相对综合敏感度,并将优化结果与土壤实测水力学参数和试错法的模拟结果进行比较。参数敏感度分析结果表明,18个模型参数的相对综合敏感度较高,其中土壤水力学参数普遍具有较高的敏感度,以饱和含水率敏感度最高;作物参数中,作物生长发育总积温和最大比叶面积具有较高的综合敏感度;而氮素转化参数的敏感度远低于土壤水力学参数和作物参数。评价模型模拟效果的统计性指标(均方根误差、模型效率系数和一致性指数)表明,PEST法比实测水力学参数的模拟精度有所提高,其中土壤含水率、土壤硝态氮含量、作物产量和叶面积指数的均方根误差分别降低了61.8%、23.5%、73.6%和23.3%。同时PEST法比试错法对土壤水分和作物产量的模拟精度也有较大提高,但对土壤氮素和叶面积指数的模拟精度提高不明显。由于该方法大大节约了模型校准时间,在较短的时间内获得了明显高于试错法的模拟精度,因此PEST软件在WHCNS模型参数自动优化中是一个值得推广的工具。 相似文献