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基于吉林省观测土壤水分的WOFOST模型模拟研究
引用本文:刘维,王冬妮,侯英雨,何亮.基于吉林省观测土壤水分的WOFOST模型模拟研究[J].气象,2018,44(10):1352-1359.
作者姓名:刘维  王冬妮  侯英雨  何亮
作者单位:国家气象中心,北京 100081,吉林省气象科学研究所,长春 130062,国家气象中心,北京 100081,国家气象中心,北京 100081
基金项目:公益性行业(气象)科研专项(GYHY201506001)、国家自然科学基金项目(41705095)和国家气象中心作物模型业务应用创新团队共同资助
摘    要:利用吉林省白城站试验数据进行模型参数调整,通过独立的观测资料对生育期、叶面积指数、地上部分各器官生物量进行模拟验证与评价。以白城站和榆树站代表吉林省西部玉米种植区和中部黄金玉米带参数,利用农业气象观测站发育期资料、气象资料和经过质量控制后的逐日土壤水分自动站观测数据进行模拟。为了提高WOFOST模型模拟精度,将由模型通过降水量计算的土壤体积含水量替换为实测土壤水分计算的体积含水量,采用替换后的土壤体积含水量参与模型下一步运算,以此来模拟2001—2016年春玉米穗生物量变化状况,构建玉米土壤体积含水量改善率(PD)指标,来表征降水驱动和土壤水分驱动对作物模型模拟结果的影响。结果表明:(1)模型对白城站春玉米生育期、叶面积、地上部分总生物量和叶生物量较准确,而穗生物量模拟效果一般。(2)从代表站白城来看,穗生物量模拟值与降水量存在明显正相关,降水偏少的年份土壤模拟效果明显优于降水驱动。(3)从区域来看,以盐碱土为主的地区或降水量偏少的年型下土壤水分驱动效果优于降水驱动;在以黑土为主的区域或降水偏多的年型下,两者模拟效果基本接近。(4)总体来说,利用观测土壤水分替换降水量参与模型能够显著提高模型模拟精度。

关 键 词:WOFOST,土壤水分,春玉米,土壤体积含水量改善率
收稿时间:2017/11/25 0:00:00
修稿时间:2018/8/22 0:00:00

Simulation Research of WOFOST Model Based on Observed Soil Moisture Data in Jilin Province
LIU Wei,WANG Dongni,HOU Yingyu and HE Liang.Simulation Research of WOFOST Model Based on Observed Soil Moisture Data in Jilin Province[J].Meteorological Monthly,2018,44(10):1352-1359.
Authors:LIU Wei  WANG Dongni  HOU Yingyu and HE Liang
Abstract:The experimental data from Baicheng Station, Jilin Province, are used to calibrate the parameters in crop model WOFOST, and the independent observation data including development stages, leaf area index, biomass for each organ are adopted to verify and evaluate the adaption. The parameters from Baicheng and Yushu Stations represent the parameters in the western and central parts of Jilin Province. The developmental phase data, weather data and daily soil moisture data under optimization from automatic soil observation stations are used in the simulation of WOFOST model. To improve the simulation accuracy of WOFOST, the volume content of soil calculated based on precipitation is replaced by the volume content of soil calculated based on the observed soil moisture data, which was used in the next step computing of model to simulate the biomass from 2001 to 2016. The improvement rate of volume content of soil (PD) is constructed to analyze the different changes by using soil moisture data and precipitation data. The results showed that (1) the model simulation is more accurate for the growth period, leaf area, total biomass and leaf biomass of spring maize at Baicheng Station, while the simulation effect of spike biomass is general. (2) From the perspective of the typical Baicheng Station, there is a significant positive correlation between the simulated value of spike biomass and precipitation, and the simulation effect of soil in years with less precipitation is significantly better than that driven by precipitation. (3) Regionally speaking, the driving effect of soil moisture in regions dominated by saline alkali soil or with less precipitation years is better than that driven by precipitation. In the region where the soil type is backland and in the year with more precipitation, the simulation results of the two are similar. (4) In general, the WOFOST model can significantly improve the simulation accuracy by replacing precipitation with observed soil moisture.
Keywords:WOFOST  soil moisture data  spring maize  improvement rate of volume content of soil
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