Analysis of Water Stress Prediction Quality as Influenced by the Number and Placement of Temporal Soil-Water Monitoring Sites  

作　　者：Luan Pan Viacheslav I. Adamchuk Richard B. Ferguson Pierre R. L. Dutilleul Shiv O. Prasher 

机构地区：[1]Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, USA [2]Department of Bioresource Engineering, McGill University, Ste-Anne-de-Bellevue, Canada [3]Department of Plant Science, McGill University, Ste-Anne-de-Bellevue, Canada

出　　处：《Journal of Water Resource and Protection》2014年第11期961-971,共11页水资源与保护（英文）

摘　　要：In an agricultural field, monitoring the temporal changes in soil conditions can be as important as understanding spatial heterogeneity when it comes to determining the locally-optimized application rates of key agricultural inputs. For example, the monitoring of soil water content is needed to decide on the amount and timing of irrigation. On-the-go soil sensing technology provides a way to rapidly obtain high-resolution, multiple data layers to reveal soil spatial variability, at a relatively low cost. To take advantage of this information, it is important to define the locations, which represent diversified field conditions, in terms of their potential to store and release soil water. Choosing the proper locations and the number of soil monitoring sites is not straightforward. In this project, sensor-based maps of soil apparent electrical conductivity and field elevation were produced for seven agricultural fields in Nebraska, USA. In one of these fields, an eight-node wireless sensor network was used to establish real-time relationships between these maps and the Water Stress Potential (WSP) estimated using soil matric potential measurements. The results were used to model hypothetical WSP maps in the remaining fields. Different placement schemes for temporal soil monitoring sites were evaluated in terms of their ability to predict the hypothetical WSP maps with a different range and magnitude of spatial variability. When a large number of monitoring sites were used, it was shown that the probability for uncertain model predictions was relatively low regardless of the site selection strategy. However, a small number of monitoring sites may be used to reveal the underlying relationship only if these locations are chosen carefully.In an agricultural field, monitoring the temporal changes in soil conditions can be as important as understanding spatial heterogeneity when it comes to determining the locally-optimized application rates of key agricultural inputs. For example, the monitoring of soil water content is needed to decide on the amount and timing of irrigation. On-the-go soil sensing technology provides a way to rapidly obtain high-resolution, multiple data layers to reveal soil spatial variability, at a relatively low cost. To take advantage of this information, it is important to define the locations, which represent diversified field conditions, in terms of their potential to store and release soil water. Choosing the proper locations and the number of soil monitoring sites is not straightforward. In this project, sensor-based maps of soil apparent electrical conductivity and field elevation were produced for seven agricultural fields in Nebraska, USA. In one of these fields, an eight-node wireless sensor network was used to establish real-time relationships between these maps and the Water Stress Potential (WSP) estimated using soil matric potential measurements. The results were used to model hypothetical WSP maps in the remaining fields. Different placement schemes for temporal soil monitoring sites were evaluated in terms of their ability to predict the hypothetical WSP maps with a different range and magnitude of spatial variability. When a large number of monitoring sites were used, it was shown that the probability for uncertain model predictions was relatively low regardless of the site selection strategy. However, a small number of monitoring sites may be used to reveal the underlying relationship only if these locations are chosen carefully.

关 键 词：On-the-Go SOIL Sensing Variable-Rate IRRIGATION Electrical Conductivity SITE-SPECIFIC Water Management SOIL Matric Potential 

分 类 号：R73[医药卫生—肿瘤]