Abstract

Daily measurements of the water table depth are sometimes needed to evaluate the influence of seasonal water stress on Sphagnum recolonization in restored ombrotrophic peatlands. However, continuous water table measurements are often scarce due to high costs and, as a result, water table depth is more commonly measured manually bimonthly with daily logs in few reference wells. A literature review identified six potential methods to estimate daily water table depth with bimonthly records and daily measurements from a reference well. A new estimation method based on the time series decomposition (TSD) is also presented. TSD and the six identified methods were compared with the water table records of an experimental peatland site with controlled water table regime located in Eastern Canada. The TSD method was the best performing method (R2 = 0.95, RMSE = 2.48 cm and the lowest AIC), followed by the general linear method (R2 = 0.92, RMSE = 3.10 cm) and support vector machines method (R2 = 0.91, RMSE = 3.24 cm). To estimate daily values, the TSD method, like the six traditional methods, requires daily data from a reference well. However, the TSD method does not require training nor parameter estimation. For the TSD method, changing the measurement frequency to weekly measurements decreases the RMSE by 16% (2.08 cm); monthly measurements increase the RMSE by 13% (2.80 cm).

Highlights

  • Hydrological monitoring in ombrotrophic peatlands is used to understand the effect of the water table depth fluctuation on vegetation structure [1], which is mostly composed of Sphagnum species

  • The method architectures of general linear model (GLM), k-nearest neighbours (KNN), support vector machines (SVM), TREE, random forest (RF) and ADABOOST are shown in Figures A1 and A2 of Appendix A

  • For basins with a target water table depth of 10 cm (PC-10 and CC-10), the water table depth remained close to the surface for both years, with PC-10 having the least variation and a stable level

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Summary

Introduction

Hydrological monitoring in ombrotrophic peatlands is used to understand the effect of the water table depth fluctuation on vegetation structure [1], which is mostly composed of Sphagnum species. The presence of water in ombrotrophic peatland influences peat hydrophysical properties such as water storage capacity [13], hydraulic conductivity due to the surface subsidence [1,14] and drainable porosity [14,15]. It is a domino effect since any alteration of the hydrological regime can significantly affect peatland vegetation [16,17]

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