基于升尺度方法的华北冬小麦区域生长模型初步研究 Ⅰ.潜在生产水平

A Preliminary Study on a Regional Growth Simulation Model of Winter Wheat in North China Based on Scaling-up Approach Ⅰ. Potential Production Level

作物生长模型是在田间尺度上开发的,而区域尺度上的作物生长信息更受决策部门的关注。作物模拟从单点研究发展到区域应用需要解决升尺度连接(Scalingup)等一系列技术问题。本文利用以经纬度为权重的IDW空间插值法对气象数据和与温度有关的作物参数进行空间插值;根据华北冬小麦的品种地带性分布特点进行了冬小麦品种参数的气候生态类型分区;利用冬小麦适宜播期温度指标,通过对实际温度的空间插值获得了播种日期的空间分布,初步解决了作物模型的升尺度问题。利用不同气候生态区域的代表站点资料对欧洲作物模型WOFOST进行了参数的适应性调整,较好地模拟了华北地区冬小麦主要发育期,生长模拟验证的误差基本在允许范围之内。在上述基础上,初步建立了潜在生产(水肥适宜)水平下华北冬小麦区域生长模拟模型,区域模拟检验表明,模拟发育期与实测发育日期的空间分布大致相符,模拟产量和实际产量的空间分布基本吻合。以上结论表明,本研究采用升尺度方法建立区域作物生长模型是可行的。本文可为水分胁迫条件下的区域作物生长模拟奠定基础。

Dynamic crop growth simulation models have been developed at a plot or a field scale. However, crop growth monitoring and yield predication at regional scale are concerned by decision makers. Modeling crop growth states at regional scale needs to obtain the value of parameters and/or initial conditions for each field. The objective of this paper was to establish a regional winter wheat growth simulation model by scaling-up WOFOST model developed by Wageningen Agricultural University, the Netherlands. Firstly, forcing variables (weather data) and parameters (related to temperature) of WOFOST were interpolated by IDW method; climate-ecologic type of winter wheat genetic parameters was demarcated according to geographic belt distribution of winter wheat cultivars in North China; by using appropriate temperature index of winter wheat sowing, spatial distribution of sowing date was estimated according to measured temperature. Secondly, WOFOST model was adjusted and validated by using field experiment data in various climate-ecological areas in North China, and simulated development stage and dry matter weight were satisfied (Fig.1, Fig.2). Thus, a regional winter wheat growth simulation model in potential production level (no water and nutrition limit) was developed in North China by scaling-up approach and parameters adjustment. Regional simulation tests showed that simulated development stage were nearly consistent with measured values in spatial distribution, and simulated and measured yields were identical in space (Fig.3, Fig.4). The results showed that the scaling-up approach to develop regional crop growth simulation model is feasible. This model can be a basis for the establishment of regional crop growth simulation in water stress conditions.