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在黑河上游八宝河流域建立自动化、时空协同、智能观测的生态水文无线传感器网络,实现分布式的地面观测,对于定量刻画流域尺度时空异质性较强的生态水文要素的动态特征及其不确定性具有重要意义。在观测网设计过程中,节点的空间布局将直接影响到无线传感器网络的观测水平。为准确捕捉流域内关键生态水文要素的时空变异性和场分布,探讨了一种基于回归克里格模型的空间采样布局优化方法,并以地表温度观测网优化为例,应用到八宝河流域生态水文无线传感器网络布局方案设计中。研究结果表明,该优化方法同时考虑了目标变量与环境变量之间的相关关系以及残差在空间上的自相关特征,可以同时优化目标变量的地理空间和属性空间。优化后的无线传感器网络可以较好地捕捉流域内生态水文要素的时空动态特征。
The establishment of automatic, spatiotemporal coordination and intelligent observation of eco-hydrological wireless sensor networks in the Babao River basin in the upper reaches of the Heihe River to achieve distributed ground observation is of great significance to quantitatively characterize the dynamic characteristics of eco-hydrological elements with large temporal and spatial heterogeneity in the basin scale Certainty is of great importance. In the process of observing network design, the spatial layout of nodes will directly affect the observation level of the wireless sensor network. In order to accurately capture the spatio-temporal variability and field distribution of key eco-hydrological elements in the basin, a spatial sampling layout optimization method based on regression kriging model was discussed. Taking the optimization of surface temperature observation network as an example, Ecology and hydrology wireless sensor network layout design. The results show that the optimization method considers both the correlation between target variables and environmental variables and the spatial autocorrelation of residuals, and can simultaneously optimize the geospatial and attribute space of the target variables. The optimized WSN can better capture the spatio-temporal dynamic characteristics of eco-hydrological elements in the basin.