A flexible approach to managing variability in grain yield and nitrate leaching at within-field to farm scales

We up-scaled the APSIM simulation model of crop growth, water and nitrogen dynamics to interpret and respond to spatial and temporal variations in soil, season and crop performance and improve yield and decrease nitrate leaching. Grain yields, drainage below the maximum root depth and nitrate leaching are strongly governed by interaction of plant available soil water storage capacity (PAWC), seasonal rainfall and nitrogen supply in the water-limited Mediterranean-type environment of Western Australia (WA). APSIM simulates the interaction of these key system parameters and the robustness of its simulations has been rigorously tested with the results of several field experiments covering a range of soil types and seasonal conditions in WA. We used yield maps, soil and weather data for farms at two locations in WA to determine spatial and temporal patterns of grain yield, drainage below the maximum root depth and nitrate leaching under a range of weather, soil and nitrogen management scenarios. On one farm, we up-scaled APSIM simulations across the whole farm using local weather and fertiliser use data and the average PAWC values of soil type polygons. On a 70 ha field on another farm, we used a linear regression of apparent soil electrical conductivity (EC_a) measured by EM38 against PAWC to transform an EC_a map of the field into a high resolution (5 m grid) PAWC map. We then used regressions of simulated yields, drainage below the maximum root depth and nitrate leaching on PAWC to upscale the APSIM simulations for a range of weather and fertiliser management scenarios. This continuous mapping approach overcame the weakness of the soil polygons approach, which assumed uniformity in soil properties and processes within soil type polygons. It identified areas at greatest financial and environmental risks across the field, which required focused management and simulated their response to management interventions. Splitting nitrogen applications increased simulated wheat yields at all sites across the field and decreased nitrate leaching particularly where the water storage capacity of the soil was small. Low water storage capacity resulted in both low wheat yields and large leaching loss. Another management option to decrease leaching may be to grow perennial vegetation that uses more water and loses less by drainage.Paper from the 5th European Conference on Precision Agriculture (5ECPA), Uppsala, Sweden, 2005     

基于APSIM模型的旱地春小麦生育期的播期和耕作效应分析

为对不同播期和耕作条件下旱地春小麦生育期进行准确预测,利用甘肃省定西市安定区凤翔镇安家沟村2015-2016年大田试验数据及研究区1971-2017年气象数据,通过穷举试错法校准APSIM模型的相关参数,再用相关性分析检验,进而基于模型模拟数据分析播期和耕作措施对旱地春小麦生育期的影响.结果表明,春小麦全生育期及各生育...     

补灌量和覆盖量变化对旱地春小麦叶面积指数的影响

免耕覆盖中补灌量和秸秆覆盖量变化对叶片生长有较大影响,以甘肃省定西市安定区1979—2019年历史气象数据为基础,运用APSIM模型对补灌量与覆盖量耦合变化时旱地春小麦的叶面积指数进行模拟,并采用方差分析、二次多项式回归、单因素分析等方法,研究补灌量和覆盖量对旱地春小麦叶面积的影响机制。结果表明：在试验设计范围内,旱地春小麦叶面积指数随着补灌量变化在分蘖—拔节期呈开口向下的二次抛物线先增后减变化,补灌量在252.09 mm时春小麦叶面积指数出现最大值为1.83,其他各个时期均呈开口向上的二次抛物线递增变化。随着秸秆覆盖量变化,叶面积指数在出苗—分蘖期,呈开口向下的二次抛物线先增后减变化,试验设计范围内秸秆覆盖量为2397.09 kg/hm²时春小麦叶面积指数出现最大值为0.59,分蘖—拔节期呈开口向下的二次抛物线递增变化;其他各个时期均呈开口向上的二次抛物线递增变化。相同阶段下,补灌量每增加50 mm,春小麦叶面积指数最大增幅13.95%;秸秆覆盖量每增加1000 kg/hm²,春小麦叶面积指数最大增幅3.7%。补灌量对春小麦叶面积指数的影响...     

华北平原不同降水年型和作物种植模式下的产量和耗水模拟

华北平原是中国重要的粮食生产基地,在国家粮食产业中地位较高,但长期灌溉造成了华北平原地下水资源的严重亏损,地下水位持续下降。该研究利用APSIM模型对华北平原1986－2015年不同种植模式下的产量和耗水情况进行模拟研究,为华北平原调整作物种植模式、农业水资源管理以及农业发展政策的制定提供科学依据。研究结果表明：APSIM模型能够较好地模拟冬小麦和夏玉米的生育期、产量及水分利用特征,其中生育期模拟结果的误差在5 d之内,产量、ET和下渗量模拟结果的R2均在0.84以上,表明该模型在华北平原具有较好的适用性;在华北平原地区,冬小麦-夏玉米一年两熟种植模式（M2Y1）年均产量（13 445 kg/hm2）最高,但耗水量（724 mm）也是最大,水分亏损（233 mm）最为严重;一年一熟种植模式（M1Y1）年均耗水量（534 mm）较小,水分亏损量（43 mm）最少,但产量（9 215 kg/hm2）较低;两年三熟种植模式（M3Y2）兼顾产量和耗水,在保证一定产量的前提下减少了耗水量,产量耗水综合效果最好,适合在华北平原推广实行。此外,该研究对栾城站丰水年、平水年和枯水年等不同降水年型下的3种种植模式产量耗水特征进行了对比分析,研究表明在华北平原降水资源对于作物生长有重要意义,年降水量越大,作物产量越高,水分亏损量越少。     

Yield benefits of triticale traits for wheat under current and future climates

Triticale often out-yields wheat in both favourable and unfavourable growing conditions. Observed traits suggested for the higher yields in triticale include greater early vigour, a longer spike formation phase with same duration to flowering, reduced tillering, increased remobilization of carbohydrates to the grain, early vigorous root growth and higher transpiration use efficiency. To quantify the impact of these traits systematically across seasons and contrasting rainfall regions and soil types, these triticale traits were introduced into a wheat model (APSIM-Nwheat). The impact of each individual trait and their full combination was analysed in a simulation experiment for three Mediterranean growing environments, two contrasting soil types and long-term historical weather data. The simulated impact of these traits was compared with measured impacts from a range of field experiments across several environments. Simulated responses of various crop characteristics including yield, were in general similar to responses observed in wheat-triticale comparison field experiments across a large range of growing conditions. The simulation analysis indicated that the yield response to the incorporation of the triticale traits into wheat was positive, in both low and high yielding growing conditions, similar to measured differences, but the simulated benefit was on average lower than the range observed in data of triticale and wheat. This suggests that other traits might also be involved in higher-yielding triticale, or the magnitude of some of the traits may be underestimated in field experiments due to ‘trait by environment’ interactions. The simulation results suggest the highest yield benefit can be achieved from increasing transpiration use efficiency in wheat, but early vigour, remobilization of stem carbohydrates and early root growth also contribute positively to a yield increase in the different growing environments. The yield benefits from the triticale traits increased in the future climate change scenario in particular on soils with high water-holding capacity from contributions of increased early vigour, remobilization of stem carbohydrates and transpiration use efficiency, and remained stable on the lighter soils.     

基于APSIM模型旱地春小麦产量对温度和CO2浓度升高的响应

为了探索气候变化对旱地春小麦生长的影响机理,在田间试验的基础上通过调试APSIM模型参数,并对模型进行检验,用APSIM模型模拟7个温度水平和7个CO2浓度水平组合设计下的春小麦产量,并采用二次多项回归和通径分析研究春小麦产量对温度和CO2浓度升高的响应。结果表明:当温度不变,CO2浓度每升高100 mol·mol-1,春小麦平均增产4.9%,最大增产可达到14.6%;春小麦产量随CO2浓度升高呈递增型二次抛物线变化,但春小麦产量会出现报酬递减。当CO2浓度不变时,温度每升高1℃,春小麦平均减产6.1%,最大减产幅度高达14.2%;春小麦产量随温度升高呈递减型二次抛物线变化。温度和CO2浓度同时升高对春小麦产量存在正的协同作用,但温度对春小麦产量负效应大于CO2浓度对春小麦产量的正效应。温度和CO2浓度同时升高会对旱地春小麦产量形成不利。     

基于APSIM模型的旱地小麦和豌豆水肥协同效应分析

为探索水肥协同作用对作物产量影响的机制和规律,在田间试验的基础上调试APSIM模型参数,并对模型进行检验,然后用该模型模拟近30多年来研究区的小麦/豌豆产量,并采用多元回归方法分析了施N量(X1)、生育期降水量(X2)和休闲期降水量(X3)对小麦/豌豆模拟产量的协同效应.结果表明,APSIM模型可以准确用来模拟小麦和豌...     

室内模拟实验研究中国北方不同管理方式对土壤固碳潜力的影响

Soil has been identified as a possible carbon(C) sink for sequestering atmospheric carbon dioxide(CO_2).However,soil organic carbon(SOC) dynamics in agro-ecosystems is affected by complex interactions of various factors including climate,soil and agricultural management practices,which hinders our understanding of the underlying mechanisms.The objectives of this study were to use the Agricultural Production Systems sIMulator(APSIM) model to simulate the long-term SOC dynamics under different management practices at four long-term experimental sites,Zhengzhou and Xuzhou with double cropping systems and Gongzhuling and Uriimqi with single cropping systems,located in northern China.Firstly,the model was calibrated using information from the sites and literature,and its performance to predict crop growth and SOC dynamics was examined.The calibrated model was then used to assess the impacts of different management practices,including fertilizer application,irrigation,and residue retention,on C dynamics in the top 30 cm of the soil by scenario modelling.Results indicate a significant SOC sequestration potential through improved management practices of nitrogen(N) fertilizer application,stubble retention,and irrigation.Optimal N fertilization(N_(opt)) and 100%stubble retention(R100) increased SOC by about 11.2%,208.29%,and 283.67%under irrigation at Gongzhuling,Zhengzhou,and Xuzhou,respectively.Soil organic carbon decreased rapidly at(U|¨)rumqi under irrigation,which was due to the enhanced decomposition by increased soil moisture.Under rainfed condition,SOC remained at a higher level.The combination of N_(opt) and R100 increased SOC by about 0.46%under rainfed condition at Uriimqi.Generally,agricultural soils with double cropping systems(Zhengzhou and Xuzhou) showed a greater potential to sequester C than those with single cropping systems(Gongzhuling and(U|¨)r(u|¨)mqi).     

Modeling long-term soil carbon dynamics and sequestration potential in semi-arid agro-ecosystems

Long-term soil carbon (C) dynamics in agro-ecosystems is controlled by interactions of climate, soil and agronomic management. A modeling approach is a useful tool to understand the interactions, especially over long climatic sequences. In this paper, we examine the performance of the Agricultural Production Systems sIMulator (APSIM) to predict the long-term soil C dynamics under various agricultural practices at four semi-arid sites across the wheat-belt of eastern Australia. We further assessed the underlying factors that regulate soil C dynamics in the top 30 cm of soil through scenario analysis using the validated model. The results show that APSIM is able to predict aboveground biomass production and soil C dynamics at the study sites. Scenario analyses indicate that nitrogen (N) fertilization combined with residue retention (SR) has the potential to significantly slow or reverse the loss of C from agricultural soils. Optimal N fertilization (N_opt) and 100% SR, increased soil C by 13%, 46% and 45% at Warra, Wagga Wagga and Tarelee, respectively. Continuous lucerne pasture was the most efficient strategy to accumulate soil C, resulting in increases of 49%, 57% and 50% at Warra, Wagga Wagga and Tarlee, respectively. In contrast, soil C decreases regardless of agricultural practices as a result of cultivation of natural soils at the Brigalow site. Soil C input, proportional to the amount of retained residue, is a significant predictor of soil C change. At each site, water and nitrogen availability and their interaction, explain more than 59% of the variation in soil C. Across the four sites, mean air temperature has significant (P < 0.05) effects on soil C change. There was greater soil C loss at sites with higher temperature. Our simulations suggest that detailed information on agricultural practices, land use history and local environmental conditions must be explicitly specified to be able to make plausible predictions of the soil C balance in agro-ecosystems at different agro-ecological scales.     

基于APSIM模型的不同施肥处理下春玉米产量模拟及气候敏感性分析

以平凉市泾川县大田试验为基础,利用农业生产系统模拟模型,探究不同类型施肥处理对春玉米产量的影响以及气候变化对春玉米产量影响的敏感性差异,分析APSIM模型对模拟该地区春玉米产量的适应性。结果表明,APSIM模型对该区域春玉米产量的模拟效果较好,决定系数(R²)介于0.934～0.975,归一化均方根误差(NRMSE)介于6.073%～9.758%,模型一致性指标(D)介于0.952～0.987。模型敏感分析显示,年平均温度是模拟不同施肥处理下春玉米产量的敏感参数,其变化程度对模拟结果影响较大,不同施肥处理(CK、N、NP)下的敏感指数分别为0.533 2、0.558 7和0.568 2。