Table 1. Total precipitation and mean air temperature for June to August in 2017 and 2019 and long-term averages (2000–2019). The data for Hirvas have been calculated using the kriging interpolation method. | ||||

Month, Annual | June | July | August | Annual |

Precipitation (mm) | ||||

Hirvas 2017 | 56 | 81 | 54 | 490 |

Hirvas 2019 | 86 | 14 | 97 | 572 |

Rovaniemi 2000–2019 | 64 (19–125) | 79 (15–152) | 70 (7–178) | 639 (422–874) |

Temperature (°C) | ||||

Hirvas 2017 | 11.8 | 15.6 | 12.8 | 1.7 |

Hirvas 2019 | 13.7 | 14.8 | 13.4 | 1.6 |

Rovaniemi 2000–2019 | 12.5 | 16.1 | 13.4 | 1.8 |

Table 2. Thickness of peat layer, volume of stand, depth of ditch and degree of decomposition of peat according to the type of mineral soil under the peat layer. The soil types are saSi = clay silt, siHkMr = silt sandy moraine, HkMr = sand moraine, srHkMr = gravel sand moraine, Hk = sand. | |||||||||||||

Soil | N | Peat layer, cm | Volume of stand, m^{3 }ha^{–1} | Depth of ditch, cm | Degree of decomposition of peat | ||||||||

Mean | Min | Max | Mean | Min | Max | Mean | Min | Max | Mean | Min | Max | ||

saSi | 5 | 49 | 41 | 57 | 102 | 45 | 174 | 28 | 23 | 34 | 4.0 | 2 | 7 |

siHkMr | 12 | 42 | 23 | 70 | 110 | 40 | 181 | 36 | 20 | 44 | 4.7(10) | 3 | 7 |

HkMr | 25 | 40 | 27 | 70 | 108 | 11 | 181 | 40 | 19 | 55 | 2.9(22) | 1 | 5 |

srHkMr | 4 | 38 | 21 | 53 | 85 | 23 | 133 | 42 | 13 | 52 | 2.0 | 2 | 5 |

Hk | 7 | 38 | 26 | 61 | 92 | 55 | 158 | 42 | 18 | 56 | 3.0 | 2 | 5 |

Table 3. The average groundwater levels (in cm) on measurement days according to soil types in 2017 and 2019. Precipitation is the sum of the precipitation in the week preceding the measurement. The soil types are saSi = clay silt, siHkMr = silt sandy moraine, HkMr = sand moraine, srHkMr = gravel sand moraine, Hk = sand. | ||||||||||

Year 2017 | ||||||||||

Soil | Group | N | 28. June | 6. July | 12. July | 20. July | 27. July | 3. Aug | 10. Aug | 16. Aug |

saSi | Silty | 5 | 14 | 14 | 18 | 13 | 20 | 20 | 26 | 28 |

siHkMr | Silty | 12 | 15 | 16 | 25 | 16 | 26 | 28 | 36 | 39 |

HkMr | Sandy | 25 | 18 | 19 | 36 | 20 | 36 | 38 | 44 | 46 |

srHkMr | Sandy | 4 | 16 | 16 | 27 | 18 | 27 | 27 | 36 | 34 |

Hk | Sandy | 7 | 20 | 23 | 36 | 24 | 36 | 38 | 43 | 41 |

Rain, mm | 29 | 26 | 5 | 34 | 5 | 22 | 10 | 12 | ||

Year 2019 | ||||||||||

Soil | Group | N | 19. June | 26. June | 3. July | 10. July | 17. July | |||

saSi | Silty | 5 | 18 | 14 | 18 | 21 | 27 | |||

siHkMr | Silty | 11 | 17 | 14 | 19 | 24 | 34 | |||

HkMr | Sandy | 25 | 28 | 19 | 30 | 37 | 47 | |||

srHkMr | Sandy | 3 | 22 | 16 | 22 | 26 | 38 | |||

Hk | Sandy | 7 | 28 | 23 | 31 | 36 | 44 | |||

Rain, (mm) | 19 | 37 | 11 | 6 | 4 | |||||

Rain = Previous week’s rainfall | ||||||||||

N = Number of plots |

Table 4. Tested explanatory variables for the linear mixed effects model. The parameters of distributions (continuous variables) or the frequencies (numbers of observations in the longitudinal data) and the proportions of the categories (categorical variables) are presented in the table. | ||||

Variable | Mean | Median | Minimum | Maximum |

Continuous variables: | ||||

Groundwater level, cm (response) | 27.35 | 24.00 | 8.00 | 65.00 |

Volume of stock, m^{3} ha^{–1} | 108.20 | 111.60 | 10.50 | 181.00 |

Measurement, nr. | 3.93 | 4.00 | 1.00 | 8.00 |

Rainfall (during week), mm | 16.89 | 12.00 | 3.70 | 37.20 |

Temperature (during day), °C | 14.04 | 13.90 | 10.20 | 16.90 |

Peat decomposition, scale 1–8 | 3.34 | 3.00 | 1.00 | 7.00 |

Altitude, m a.s.l. | 83.02 | 82.83 | 80.40 | 86.64 |

Ditch depth, cm | 35.82 | 35.00 | 13.00 | 56.00 |

Depth of peat layer, cm | 41.44 | 39.00 | 21.00 | 70.00 |

Categorical variables: | ||||

Peat type | wooden-sphagnum peat: 85% (515), wooden-carex peat 15% (91) | |||

Mineral soil type | Silty: 31% (190), Sandy: 69% (416) |

Table 5. Parameter estimates and tests of a general linear mixed effects model (Gaussian) for the groundwater level. Std. err. denotes the standard error of the estimates, df denotes the degrees of freedom, t-values are the test values for the parameter estimates, and p is the statistical significance level. R^{2} for the marginal model was 68.4% and that for the conditional model was 81.4%. | |||||

Variable | Coefficient | Std. err. | df | t-value | p |

Fixed effects: | |||||

Intercept | 13.791 | 4.905 | 511.000 | 2.812 | 0.005 |

Peat type, carex-sphagnum peat, ref. wooden-carex peat | –0.155 | 0.064 | 83.000 | –2.412 | 0.018 |

Volume of timber stock, m^{3} ha^{–1} | 0.002 | 0.001 | 83.000 | 2.973 | 0.004 |

Rainfall (during the period week), mm | –0.014 | 0.001 | 511.000 | –26.370 | 0.000 |

Measurement, nr | 0.083 | 0.005 | 511.000 | 16.044 | 0.000 |

Mineral soil type, sandy, ref. silty | 1.110 | 0.233 | 83.000 | 4.761 | 0.000 |

Depth of peat layer, cm | –0.367 | 0.134 | 83.000 | –2.748 | 0.007 |

Ditch depth, cm | 0.003 | 0.002 | 83.000 | 1.928 | 0.057 |

Altitude, m.o.s.l. | –0.133 | 0.060 | 83.000 | –2.220 | 0.029 |

Mineral soil type*Depth of peat layer | –0.025 | 0.006 | 83.000 | –4.105 | 0.000 |

Depth of peat layer*Altitude | 0.004 | 0.002 | 83.000 | 2.713 | 0.008 |

Random effects (variances) and phi (AR1 correlation structure), 95% confidence limits in the parenthesis: | |||||

Random year effect | 1.509e-2 (0.079e-2–0.289) | ||||

Random sample point effect | 1.354e-2 (0.593e-2–3.092e-2) | ||||

Residual | 4.092e-2 (3.206e-2–5.223e-2) | ||||

Phi | 0.511 (0.377–0.623) |