Drainage is an essential prerequisite in peatland forest management, which generally, but not always, increases stand growth. Growth response depends on weather conditions, stand and site characteristics, management and biogeochemical processes. We constructed a SUSI-simulator (SUoSImulaattori, in Finnish), which describes hydrology, stand growth and nutrient availability under different management, site types and weather conditions. In the model development and sensitivity analysis, we used water table (WT) and stand growth data from 11 Scots pine stands. The simulator was validated against a larger dataset collected from boreal drained peatlands in Finland. In validation, SUSI was shown to predict WT and stand growth well. Stand growth was mainly limited by inadequate potassium supply, and in Sphagnum peats by low oxygen availability. Model application was demonstrated for ditch network maintenance (DNM) by comparing stand growth with shallow (−0.3 m) and deep ditches (−0.9 m): The growth responses varied between 0.5 and 3.5 m3 ha−1 in five years, which is comparable to experimental results. SUSI can promote sustainable peatland management and help in avoiding unnecessary drainage operations and associated environmental effects, such as increased carbon emissions, peat subsidence, and nutrient leaching. The source code is publicly available, and the modular structure allows model extension to cost–benefit analyses and nutrient export to water courses.

Abstract. Drained peatlands are one of the main sources of carbon dioxide (CO2) emissions globally. Emission reduction and, more generally, ecosystem restoration can be enhanced by raising the water table using canal or drain blocks. When restoring large areas, the number of blocks becomes limited by the available resources, which raises the following question: in which exact positions should a given number of blocks be placed in order to maximize the water table rise throughout the area? There is neither a simple nor an analytic answer. The water table response is a complex phenomenon that depends on several factors, such as the topology of the canal network, site topography, peat hydraulic properties, vegetation characteristics and meteorological conditions. We developed a new method to position the canal blocks based on the combination of a hydrological model and heuristic optimization algorithms. We simulated 3 d dry downs from a water saturated initial state for different block positions using the Boussinesq equation, and the block configurations maximizing water table rise were searched for by means of genetic algorithm and simulated annealing. We applied this approach to a large drained peatland area (931 km2) in Sumatra, Indonesia. Our solution consistently outperformed traditional block locating methods, indicating that drained peatland restoration can be made more effective at the same cost by selecting the positions of the blocks using the presented scheme.

Abstract. Peatlands are important natural sources of atmospheric methane (CH4) emissions. The production and emission of CH4 are strongly influenced by the diffusion of oxygen into the soil and of CH4 from the soil to the atmosphere, respectively. This diffusion, in turn, is controlled by the structure of macropore networks. The characterization of peat pore structure and connectivity through complex network theory approaches can give conceptual insight into how the relationship between the microscale pore space properties and CH4 emissions on a macroscopic scale is shaped. The evolution of the pore space that is connected to the atmosphere can also be conceptualized through a pore network modeling approach. Pore regions isolated from the atmosphere may further develop into anaerobic pockets, which are local hotspots of CH4 production in unsaturated peat. In this study, we extracted interconnecting macropore networks from three-dimensional X-ray micro-computed tomography (µCT) images of peat samples and evaluated local and global connectivity metrics for the networks. We also simulated the water retention characteristics of the peat samples using a pore network modeling approach and compared the simulation results with measured water retention characteristics. The results showed large differences in peat macropore structure and pore network connectivity between vertical soil layers. The macropore space was more connected and the flow paths through the peat matrix were less tortuous near the soil surface than at deeper depths. In addition, macroporosity, structural anisotropy, and average pore throat diameter decreased with depth. Narrower and more winding air-filled diffusion channels may reduce the rate of gas transport as the distance from the peat layer to the soil–air interface increases. The network analysis also suggests that both local and global network connectivity metrics, such as the network average clustering coefficient and closeness centrality, might serve as proxies for assessing the efficiency of gas diffusion in air-filled pore networks. However, the applicability of the network metrics was restricted to the high-porosity near-surface layer. The spatial extent and continuity of the pore network and the spatial distribution of the pores may be reflected in different network metrics in contrasting ways. The hysteresis of peat water content between wetting and drying was found to affect the evolution of the volume of connected air-filled pore space in unsaturated peat. Thus, the formation of anaerobic pockets may occur in a smaller soil volume and methanogenesis may be slower when the peat is wetting compared to in drying conditions. This hysteretic behavior might explain the hotspots and episodic spikes of CH4 emissions, and therefore, it should be taken into account in biogeochemical models.