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Evaluation of the performance of the EPIC model for yield and biomass simulation under conservation systems in Cambodia

机译:柬埔寨保护系统下产量和生物质模拟史诗模型的性能评价

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Limited field studies have been performed to evaluate the impacts of conservation agriculture (CA) on crop yields and soil organic carbon sequestration in tropical conditions. In this study, we used the Environmental Policy Integrated Climate (EPIC) model to evaluate the impact of CA and conservation tillage (CT) on crop yields in tropical conditions for unique upland rice, soybean, and cassava cropping systems in Cambodia. New crop parameters were developed and tested for cassava, sesame, banana, sunn hemp, stylo, and congo grass. The results show that EPIC successfully replicated crop yields of soybean, upland rice, maize, and cassava based on R-2 statistics ranging from 0.62 to 0.88 and percent bias (PBIAS) values a &= 10%. However, it cannot be concluded that the model can accurately capture the biomass for all the individual crops due to limitations in the observed biomass data. The cassava and maize biomass were simulated satisfactorily, resulting in R-2 values of 0.81 and 0.75, respectively. However, the computed PBIAS for the biomass estimates of the two crops were & 25%. In contrast, the predicted rice and soybean biomass met PBIAS criteria (&= 23%) but resulted in weak R-2 statistics of &= 0.20, indicating inaccurate replications of the measured biomass. Similarly, the cover crop mean biomass and PBIAS statistics were acceptable but the R-2 values were not. Overall, the model tended to overestimate the measured crop biomass. No significant difference was found in the simulated crop yields between the CA and CT treatments. However, the predicted rice and soybean results reflect an increased yield trend over time for the CA treatments, versus no discernible trend for the cassava and maize yields.
机译:已经进行了有限的现场研究,以评估保护农业(CA)对热带条件下作物产量和土壤有机碳封存的影响。在这项研究中,我们利用环境政策综合气候(EPIC)模型来评估CA和保护耕作(CT)对柬埔寨独特旱稻,大豆和木薯种植系统的热带条件下的作物产量。为木薯,芝麻,香蕉,逊色星大麻,司机和刚果草进行了新的作物参数。结果表明,基于R-2统计量为0.62至0.88且百分比(PBIAS)值A& LT; LT; LT; LT; = 10%,史诗成功地复制了大豆,旱稻,玉米和木薯和木薯的作物产量。然而,不能得出结论,由于观察到的生物质数据中的限制,该模型可以精确地捕获所有单个作物的生物量。令人满意地模拟木薯和玉米生物质,导致r-2值分别为0.81和0.75。然而,对于两种作物的生物质估计的计算PBIA是& 25%。相反,预测的水稻和大豆生物量满足PBIAS标准(& = 23%),但导致&amp的弱R-2统计; = 0.20,表明测量的生物质的重复性不准确。同样,封面裁剪平均生物量和PBIAS统计是可接受的,但R-2值不是。总的来说,模型倾向于高估测量的作物生物质。在Ca和CT处理之间的模拟作物产量中没有发现显着差异。然而,预测的水稻和大豆结果反映了CA治疗的产量增加,而不是木薯和玉米产量的可辨别趋势。

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