Integrated hydrological modelling for predicting spatiotemporal variability of water table depths in Danish peatlands

It is well known that artificially drained peatlands are net greenhouse gas (GHG) sources to the atmosphere. In peatlands, the depth of the groundwater table i.e. the water table depth (WTD), is an important driver of carbon dioxide (CO₂) and methane (CH₄) emissions.

Integrated hydrological models simulating transient unsaturated and saturated subsurface flow in peatlands, allow mapping of the spatiotemporal variability of WTD and thereby the impact on GHG on daily, seasonal, and inter-annual timescales. Thereby, hydrological modelling of peatlands has the potential to assist more accurate estimates of GHG emissions compared to the simple default IPCC emission factors and/or long-term average WTD estimates used in prevalent national GHG inventories.

Here we apply physically-based 3D modelling of the WTD to a highly monitored peatland, as a case-study representing common drained and degraded peatland soils in Denmark. The catchment scale model is based on an advancement of the National Hydrological Model of Denmark running in the numerical simulation tool MIKE-SHE/MIKE-Hydro.

We identify the main processes governing peatland WTD dynamics in the model and develop a novel parameter calibration scheme focusing on WTD dynamics. We use objective functions tailored to timeseries of WTD by combining individual components of a modified version of the Kling-Gupta Efficient (KGE) with low- and highpass filters to separate the WTD signal into seasonal patterns and short-term precipitation responses. Using the Pareto Archived Dynamically Dimensioned Search (PADDS) algorithm to obtain the pareto front enables post-weighting of objective functions for optimal tradeoff analysis. The model is calibrated at 100m scale and a forward run with the optimal parameter values demonstrate mapping of WTD dynamics and statistics for potential use in GHG inventories at 20m scale.

Those achievements will lead to more robust representation of peatland hydrology in hydrological models and will facilitate analysis of hotspots and hot moments in GHG emissions and enable scenario-based analysis of climate change and management impacts on WTD dynamics in peatlands. This will support the Danish rewetting strategies and better upscaling of GHG emissions for the national inventories.