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首页> 外文期刊>Climatic Change >Elevation dependence of winter wheat production in Eastern Washington State with climate change: A methodological study
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Elevation dependence of winter wheat production in Eastern Washington State with climate change: A methodological study

机译：华盛顿州东部冬小麦产量与气候变化的海拔依赖性：一种方法学研究

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Crop growth models, used in climate change impact assessments to project production on a local scale, can obtain the daily weather information to drive them from models of the Earth's climate. General Circulation Models (GCMs), often used for this purpose, provide weather information for the entire globe but often cannot depict details of regional climates especially where complex topography plays an important role in weather patterns. The U.S. Pacific Northwest is an important wheat growing region where climate patterns are difficult to resolve with a coarse scale GCM. Here, we use the PNNL Regional Climate Model (RCM) which uses a sub-grid parameterization to resolve the complex topography and simulate meteorology to drive the Erosion Productivity Impact Calculator (EPIC) crop model. The climate scenarios were extracted from the PNNL-RCM baseline and 2 x CO2 simulations for each of sixteen 90 km(2) grid cells of the RCM, with differentiation by elevation and without correction for climate biases. The dominant agricultural soil type and farm management practices were established for each grid cell. Using these climate and management data in EPIC, we simulated winter wheat production in eastern Washington for current climate conditions (baseline) and a 2 x CO2 'greenhouse' scenario of climate change. Dryland wheat yields for the baseline climate averaged 4.52 Mg ha(-1) across the study region. Yields were zero at high elevations where temperatures were too low to allow the crops to mature. The highest yields (7.32 Mg ha(-1)) occurred at intermediate elevations with sufficient precipitation and mild temperatures. Mean yield of dryland winter wheat increased to 5.45 Mg ha(-1) for the 2 x CO2 climate, which was markedly warmer and wetter. Simulated yields of irrigated wheat were generally higher than dryland yields and followed the same pattern but were, of course, less sensitive to increases in precipitation. Increases in dryland and irrigated wheat yields were due, principally, to decreases in the frequency of temperature and water stress. This study shows that the elevation of a farm is a more important determinant of yield than farm location in eastern Washington and that climate changes would affect wheat yields at all farms in the study. [References: 33]
机译：气候变化影响评估中使用的作物生长模型可以在本地范围内对生产进行计划，可以获取每日天气信息，以将其从地球气候模型中剔除掉。通用循环模型（GCM）通常用于此目的，可提供整个地球的天气信息，但通常无法描绘区域气候的细节，尤其是在复杂地形在天气模式中起重要作用的地方。美国西北太平洋地区是重要的小麦产区，其气候模式很难通过粗略的GCM解析。在这里，我们使用PNNL区域气候模型（RCM），该模型使用子网格参数化解决复杂的地形并模拟气象，以驱动侵蚀生产力影响计算器（EPIC）作物模型。从PNNL-RCM基线和RCM的16个90 km（2）网格单元中的每一个的2 x CO2模拟中提取了气候情景，并根据海拔进行了区分，而未对气候偏差进行校正。为每个网格确定了主要的农业土壤类型和农场管理实践。使用EPIC中的这些气候和管理数据，我们针对当前气候条件（基准）和2 x CO2“温室”气候变化情景模拟了华盛顿东部的冬小麦产量。研究区域内，基准气候下的旱地小麦平均产量为4.52 Mg ha（-1）。高海拔地区气温太低而无法使农作物成熟，单产为零。最高产量（7.32 Mg ha（-1））发生在中等高度，具有足够的降水和温和的温度。在2 x CO2的气候下，旱地冬小麦的平均产量增加到5.45 Mg ha（-1），明显偏暖和湿润。灌溉小麦的模拟产量通常高于旱地的产量，并且遵循相同的模式，但是对降水增加的敏感性当然较低。旱地和灌溉小麦单产的增加主要归因于温度和水分胁迫频率的降低。这项研究表明，与华盛顿东部的农场位置相比，农场的高低是决定产量的重要因素，而且气候变化将影响研究中所有农场的小麦产量。 [参考：33]

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