...
首页> 外文期刊>Journal of irrigation and drainage engineering >Long-Term Spatial and Temporal Maize and Soybean Evapotranspiration Trends Derived from Ground-Based and Satellite-Based Datasets over the Great Plains
【24h】

Long-Term Spatial and Temporal Maize and Soybean Evapotranspiration Trends Derived from Ground-Based and Satellite-Based Datasets over the Great Plains

机译:大平原基于地面和卫星的数据集得出的长期时空玉米和大豆蒸散趋势

获取原文
获取原文并翻译 | 示例

摘要

Estimation of evapotranspiration (ET) from any given crop is essential for agricultural water consumption analyses, hydrologic modeling, understanding vegetation response to climatic changes, and related studies. Even though it is a simplification of the complex physiological and surface energy balance relationships in accurately estimating ET, crop coefficient (K_c)-based estimation of crop ET is one of the widely used approaches. This study developed and evaluated crop-specific (maize and soybean) K_c versus normalized difference vegetation index (NDVI) relationships using satellite imagery data and observed crop ET fluxes. These models were used to estimate spatiotemporal K_c of maize and soybean using multiplatform satellite imagery to aid in computation of crop ET across these scales. Crop ET was characterized spatially (across the entire Great Plains) and temporally (1982-2013) and direction and magnitudes of trends were quantified. The study area comprises of 9 states and 834 counties, representing a total land area of 2,307,410 km~2, which is approximately 30% of the terrestrial area of the United States. The coefficient of determination (R~2), Nash-Sutcliffe modeling efficiency (NSE), and root mean square difference (RMSD) for K_c-NDVI models were 0.93, 87.5%, and 0.172, respectively, for maize and 0.76, 75%, and 0.20 for soybean, respectively, which denotes acceptable accuracy. Monthly and growing season maize and soybean ET was computed on a county basis for the study period using the developed monthly K_c values and reference ET, which was determined across 800 sites in the region. Maize ET in the region varied from 242 mm in Park County, Wyoming, to 942 mm in San Jacinto County, Texas. Soybean ET ranged from a minimum of 367 mm in Baca County, Colorado, to a maximum of 753 mm in Creek County, Oklahoma. The regional average magnitude of growing season maize and soybean ET was 651 and 564 mm, respectively. Spatial and temporal variability and trends in county-scale monthly and growing season maize and soybean ET were investigated for the period 1982 to 2013. For the majority of the maize and soybean growing counties, increasing trends in crop ET were detected, despite decreasing trends in reference ET. The significant positive trends in maize ET over the region ranged from 1.48 to 3.86 mm year~(-1), with an average of 2.65 mm year~(-1). For soybean, the significant positive trends varied from 0.88 to 4.13 mm year~(-1), with an average of 2.1 mm year~(-1). The analyses presented in this study inspire the use of satellite-derived indices to monitor crop development and water use to evaluate regional magnitudes of spatial and temporal ET. Furthermore, the spatial and temporal trend analysis for county-scale crop ET can be instrumental to make informed assessments, decisions, and forecasts about agroecosystem water resources management policy in the Great Plains region by state and federal agencies, producers, and other water resources associated professionals.
机译:估计任何给定作物的蒸散量(ET)对于农业用水量分析,水文模拟,了解植被对气候变化的响应以及相关研究都是必不可少的。尽管它简化了准确估算ET时复杂的生理和表面能平衡关系,但基于作物系数(K_c)的作物ET估算仍是广泛使用的方法之一。这项研究使用卫星图像数据和观察到的作物ET通量,开发并评估了特定作物(玉米和大豆)的K_c与归一化差异植被指数(NDVI)的关系。这些模型用于通过多平台卫星图像估算玉米和大豆的时空K_c,以帮助计算这些尺度上的作物ET。在空间上(整个大平原)和时间上(1982年至2013年)对作物ET进行了特征分析,并对趋势的方向和幅度进行了量化。研究区域由9个州和834个县组成,总土地面积为2,307,410 km〜2,约占美国陆地面积的30%。 K_c-NDVI模型的确定系数(R〜2),Nash-Sutcliffe建模效率(NSE)和均方根差(RMSD)对于玉米和玉米分别为0.93、87.5%和0.172。 ,对于大豆,则分别为0.20,这表示可接受的精度。使用所开发的每月K_c值和参考ET,在研究期间以县为基础计算了每月和生长季节的玉米和大豆ET,该值是在该地区的800个站点上确定的。该地区的玉米ET从怀俄明州帕克县的242毫米到德克萨斯州圣哈辛托县的942毫米不等。大豆ET的变化范围从科罗拉多州巴卡县的最小367毫米到​​俄克拉荷马州克里克县的最大753毫米。生长季玉米和大豆ET的区域平均幅度分别为651和564 mm。调查了1982年至2013年期间县级月度和生长期的玉米和大豆ET的时空变化和趋势。尽管玉米和大豆的增长趋势有所减少,但在大多数玉米和大豆种植县,农作物ET的趋势仍在增加。参考ET。该区域玉米ET的显着正趋势在1.48至3.86 mm年〜(-1)之间,平均为2.65 mm年〜(-1)。对于大豆而言,显着的正趋势从0.88 mm(〜-1)年(-1)变化,平均为2.1 mm(-1)年。这项研究中提出的分析启发了卫星衍生指标的使用,以监测作物生长和用水情况,以评估区域时空ET的大小。此外,县级作物ET的时空趋势分析可有助于对州和联邦机构,生产者以及其他与之相关的水资源对大平原地区农业生态系统水资源管理政策进行明智的评估,决策和预测。专业人士。

著录项

  • 来源
  • 作者单位

    Dept. of Biological Systems Engineering, Univ. of Nebraska-Lincoln, 18 L.W. Chase Hall, Lincoln, NE 68583;

    Dept. of Biological Systems Engineering, Univ. of Nebraska-Lincoln, 239 L.W. Chase Hall, Lincoln, NE 68583;

    School of Natural Resources and Dept. of Civil Engineering, Univ. of Nebraska-Lincoln, 311 Hardin Hall, Lincoln, NE 68583;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号