Year-round estimation of soil moisture content using temporally variable soil hydraulic parameters

Abstract

Soil moisture plays a key role in the hydrological cycle as it controls the flux of water between soil, vegetation, and atmosphere. This study is focused on a year‐round estimation of soil moisture in a forested mountain area using the bucket model approach. For this purpose, three different soil moisture models are utilised. The procedure is based on splitting the whole year into two complement periods (dormant and vegetation). Model parameters are allowed to vary between the two periods and also from year to year in the calibration procedure. Consequently, two sets of average model parameters corresponding to dormant and vegetation seasons are proposed. The process of splitting is strongly supported by the experimental data, and it enables us to variate saturated hydraulic conductivity and pore‐size characterisation. The use of the two different parameter sets significantly enhances the simulation of two (Teuling and Troch model and soil water balance model‐green–ampt [SWBM‐GA]) out of three models in the 6‐year period from 2009 to 2014. For these two models, the overall Nash‐Sutcliffe coefficient increased from 0.64 to 0.79 and from 0.55 to 0.80. The third model (the Laio approach) proved to be insensitive to parameter changes due to its insufficient drainage prediction. The variability of the warm and cold parameter sets between particular years is more pronounced in the warm periods. The cold periods exhibited approximately similar character during all 6 years.

Simulation of Long-Term Soil Hydrological Conditions at Three Agricultural Experimental Field Plots Compared with Measurements

“…At all three field plots, the best model performance for soil water contents was observed for the upper two soil compartments 0-30 and 30-60 cm with IA from 0.78 to 0.86, R 2 between 0.58 and 0.66 and RMSD at 0.02 cm 3 cm −3 (Table 4). In other agricultural experimental field studies, the comparison of simulated soil water contents with those measured by TDR resulted in IA-values between 0.34 and 0.96 and R 2 from 0.27 to 0.91, e.g., [16][17][18][19][20][21][22][23][24]. The model performance for pressure heads in terms of IA ranged from 0.11 up to 0.80, R 2 was from 0.10 to 0.56 and RMSD between 17 and 200 hPa ( Table 5).…”

“…Our 22 year dataset covered several vegetation periods with different crops and a wide range of wet, dry, cool and warm years and, thus, offer new opportunities for, e.g., model parametrization, model validation, analysis of soil water extraction by vegetation cover and model comparison as compared to other recent studies using similar measurement set ups with a focus on model validation with distinct shorter time periods and with a lower variation in vegetation or crop cover [13,[16][17][18][19][20][21][22][23][24].…”