• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文学位 >Digital terrain analysis and simulation modeling to assess spatial variability of soil water balance and crop production.
【24h】

Digital terrain analysis and simulation modeling to assess spatial variability of soil water balance and crop production.

机译：数字地形分析和模拟模型可评估土壤水分平衡和作物产量的空间变异性。

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Terrain characteristics and landscape position control soil physical properties. They often modify environmentally sensitive processes such as leaching, erosion and sedimentation, as well as dynamic factors affecting crop production. The likelihood of soils becoming saturated increases at the base of slopes and in the depression where there is a convergence of both surface and subsurface flow. The objective of this study was to combine a conventional, one-dimensional soil water balance model with a terrain analysis model to evaluate the hydrological and agricultural processes occurring on sloping land surfaces. A new digital terrain model, TERRAE-SALUS was developed to study and model how the terrain affects the vertical and lateral movement of water occurring on the land surface and in the shallow, subsurface regimes. This study evaluated the capability of TERRAE-SALUS applied at a field scale with rolling terrain where the soil water content was measured. The model was able to partition the landscape into an interconnected series of element network from a grid DEM. TERRAE-SALUS was evaluated using three different scenarios to gain a better understanding of the factors affecting the runoff-runon processes. The high elevation point consistently showed lower water contents compared to the upper and lower saddles and depressions. The subsurface lateral flow was highest on the saddles between two peaks, indicating the correct performance of the model in predicting the contribution of water from the elements located on the peaks. The RMSE between measured and simulated soil water content varied from 0.22 cm to 0.68 cm. A second experiment was carried out applying the crop simulation model CROPGRO in combination with remote sensing data to evaluate the ability of the model to identify factors responsible for the yield variation in a spatially variable landscape. Results from this study showed that the combination of crop simulation modeling and remote sensing can identify management zones and causes for yield variability, which are prerequisites for zone-specific management prescription.
机译：地形特征和景观位置控制着土壤的物理性质。它们经常修改对环境敏感的过程，例如淋溶，侵蚀和沉淀以及影响作物生产的动态因素。在斜坡的底部和地面和地下流都汇合的洼地中，土壤饱和的可能性增加。这项研究的目的是将常规的一维土壤水平衡模型与地形分析模型相结合，以评估在倾斜土地表面上发生的水文和农业过程。开发了一种新的数字地形模型TERRAE-SALUS，以研究和建模地形如何影响陆地表面和浅层，地下状态下水的垂直和横向运动。这项研究评估了TERRAE-SALUS在田间规模和起伏地形中的应用能力，该地形用于测量土壤含水量。该模型能够将景观从网格DEM划分为相互连接的一系列元素网络。使用三种不同的方案对TERRAE-SALUS进行了评估，以更好地了解影响径流-径流过程的因素。与上，下鞍和洼地相比，高海拔始终显示出较低的水含量。在两个山峰之间的鞍座上，地下侧向流量最高，表明该模型在预测山峰上各元素的水贡献方面具有正确的性能。测得的土壤水分与模拟的土壤水分之间的均方根误差介于0.22 cm至0.68 cm之间。使用作物模拟模型CROPGRO结合遥感数据进行了第二项实验，以评估该模型识别空间可变景观中导致产量变化的因素的能力。这项研究的结果表明，作物模拟模型和遥感技术的结合可以确定管理区域和产量变化的原因，这是制定特定区域管理规定的前提。

著录项

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