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首页> 外文期刊>Irrigation and Drainage >Nested Validation of Aquacrop Model for Simulation of Winter Wheat Grain Yield, Soil Moisture and Salinity Profiles under Simultaneous Salinity and Water Stress
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Nested Validation of Aquacrop Model for Simulation of Winter Wheat Grain Yield, Soil Moisture and Salinity Profiles under Simultaneous Salinity and Water Stress

机译：同时盐分和水分胁迫下模拟冬小麦籽粒产量，土壤水分和盐分剖面的Aquacrop模型的嵌套验证

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摘要

Improvement of water management and water use efficiency at field scale is highly important under simultaneous salinity and water stress. The models that can translate the effects of different quantity and quality of water to crop yield, are useful tools for water management and improving water productivity (WP). AquaCrop (v4.0) simulates yield, water requirement, WP, soil water content and salinity under different conditions in the field, including water-limiting and different quality of irrigation water. This study was carried out as split plot design (factorial form) in Birjand, in the east of Iran, in order to evaluate the AquaCrop model. Treatments consisted of three levels of irrigation water salinity (S-1, S-2, S-3 corresponding to 1.4, 4.5, 9.6 dS m(-1)) as the main plot, two wheat varieties (Ghods and Roshan), and four levels of irrigation water amount (I-1, I-2, I-3, I-4 corresponding to 125, 100, 75, 50% water requirement) as subplot. The model was nested, calibrated and validated separately for each salinity treatment, and also simultaneously for all three salinity treatments. The overall model accuracy was higher for estimating soil moisture profile, as compared to soil salinity profile. For simulation of soil water content, the average values of RMSE, d, CRM and R-2 in both calibration and validation were 11.8%, 0.79, 0.05 and 0.61 respectively, while for simulation of soil salinity they were 24.4%, 0.72, 0.19 and 0.57 respectively. The AquaCrop successfully simulated yield, biomass and WP for two wheat varieties under salinity and water-limiting treatments with high accuracy. Average values of NRMSE, d, CRM, and R-2 for both calibration and validation of simulated grain yield were 7.1%, 0.97, 0.001 and 0.9 respectively, for the Roshan variety, while these measures were 8.2%, 0.98, -0.004 and 0.87 respectively, for the Ghods variety. Crop transpiration coefficient (Kc(Tr)), normalized crop water productivity (WP*), reference harvest index (HIO), volumetric water content at field capacity ((FC)), soil water content at saturation ((sat)), and temperature were the most sensitive parameters. Copyright (c) 2016 John Wiley & Sons, Ltd.
机译：在同时盐分和水分胁迫的情况下，改善田间规模的水资源管理和用水效率非常重要。该模型可以将不同数量和质量的水对作物产量的影响转化为水管理和提高水生产率（WP）的有用工具。 AquaCrop（v4.0）模拟田间不同条件下的产量，需水量，可湿性粉剂，土壤含水量和盐度，包括水限制和灌溉水的不同质量。为了评估AquaCrop模型，该研究在伊朗东部的Birjand进行了分割地块设计（原形）。处理包括三个水平的灌溉水盐度（S-1，S-2，S-3分别对应于1.4、4.5、9.6 dS m（-1））作为主要田地，两个小麦品种（Ghods和Roshan）和四个子级别的灌溉水量（I-1，I-2，I-3，I-4对应于125、100、75、50％的需水量）作为子图。对于每种盐度处理，分别对模型进行嵌套，校准和验证，对于所有三种盐度处理，也同时进行嵌套，校准和验证。与土壤盐度剖面相比，用于估算土壤湿度剖面的总体模型精度更高。对于土壤水分模拟，在校准和验证中，RMSE，d，CRM和R-2的平均值分别为11.8％，0.79、0.05和0.61，而对于土壤盐分模拟的平均值分别为24.4％，0.72、0.19和0.57。 AquaCrop成功地在盐度和水分限制条件下成功模拟了两个小麦品种的产量，生物量和可湿性粉剂。 Roshan品种的校准和验证模拟谷物产量的NRMSE，d，CRM和R-2的平均值分别为7.1％，0.97、0.001和0.9，而这些指标分别为8.2％，0.98，-0.004和Ghods品种分别为0.87。作物蒸腾系数（Kc（Tr）），归一化作物水分生产率（WP *），参考收获指数（HIO），田间持水量（FC），饱和土壤水含量（（sat））和温度是最敏感的参数。版权所有（c）2016 John Wiley＆Sons，Ltd.

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