Gertner George, Wang Guangxing, Anderson Alan B
University of Illinois, Urbana, IL 61801, USA.
Environ Manage. 2006 Jan;37(1):84-97. doi: 10.1007/s00267-004-0152-4.
Determining a remeasurement frequency of variables over time is required in monitoring environmental systems. This article demonstrates methods based on regression modeling and spatio-temporal variability to determine the time interval to remeasure the ground and vegetation cover factor on permanent plots for monitoring a soil erosion system. The spatio-temporal variability methods include use of historical data to predict semivariograms, modeling average temporal variability, and temporal interpolation by two-step kriging. The results show that for the cover factor, the relative errors of the prediction increase with an increased length of time interval between remeasurements when using the regression and semivariogram models. Given precision or accuracy requirements, appropriate time intervals can be determined. However, the remeasurement frequency also varies depending on the prediction interval time. As an alternative method, the range parameter of a semivariogram model can be used to quantify average temporal variability that approximates the maximum time interval between remeasurements. This method is simpler than regression and semivariogram modeling, but it requires a long-term dataset based on permanent plots. In addition, the temporal interpolation by two-step kriging is also used to determine the time interval. This method is applicable when remeasurements in time are not sufficient. If spatial and temporal remeasurements are sufficient, it can be expanded and applied to design spatial and temporal sampling simultaneously.
在监测环境系统时，需要确定变量随时间的重新测量频率。本文展示了基于回归建模和时空变异性的方法，以确定在监测土壤侵蚀系统的永久样地上重新测量地面和植被覆盖因子的时间间隔。时空变异性方法包括利用历史数据预测半变异函数、对平均时间变异性进行建模以及通过两步克里金法进行时间插值。结果表明，对于覆盖因子，当使用回归模型和半变异函数模型时，预测的相对误差会随着重新测量之间时间间隔长度的增加而增大。在给定精度或准确性要求的情况下，可以确定合适的时间间隔。然而，重新测量频率也会因预测间隔时间而有所不同。作为一种替代方法，半变异函数模型的变程参数可用于量化近似重新测量之间最大时间间隔的平均时间变异性。该方法比回归和半变异函数建模更简单，但它需要基于永久样地的长期数据集。此外，还使用两步克里金法进行时间插值来确定时间间隔。当时间上的重新测量不足时，此方法适用。如果空间和时间上的重新测量足够，则可以将其扩展并应用于同时设计空间和时间采样。
