Journal
APPLIED SCIENCES-BASEL
Volume 11, Issue 2, Pages -Publisher
MDPI
DOI: 10.3390/app11020714
Keywords
depth functions; SCORPAN modelling; soil forming factors; forest soils; soil organic carbon; regionalisation; north-eastern lowlands; forest site mapping; Brandenburg
Categories
Funding
- Faculty of Forest and Environment of Eberswalde University for Sustainable Development 'Arbeitsgruppe Forschung'
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The study indicates that the combination of depth functions and SCORPAN modeling can provide soil data at arbitrary depth layers and help avoid depth gradients and uncertainty propagation. Analysis of the National Forest Soil Inventory data in Germany reveals that the depth to groundwater table and terrain parameters have a significant impact on soil organic carbon storage.
To cope with the challenges in forest management that are contemporarily caused by climate change, data on current chemical and physical soil properties are more and more necessary. For this purpose, we present a further amalgam of depth functions and SCORPAN modelling to provide data at arbitrary depth layers. In this concept, regionalisation is split up into the modelling of plot totals and the estimation of vertical distributions. The intended benefits by splitting up are: consistency between estimates on plot level and depth layer level, avoidance of artificial depth gradients, straightforward interpretation of covariates in the sense of pedogenetic processes, and circumnavigation of the propagation of uncertainties associated with separation between horizons during field sampling. The methodology was tailored to the circumstances within the north-eastern lowlands and the utilisation of current inventory data of the National Forest Soil Inventory (NFSI) in Brandenburg (Germany). Using the regionalisation of soil organic carbon (SOC) as an example, the application is demonstrated and discussed in detail. The depth to groundwater table and terrain parameters related to the catchment area were the main factors in SOC storage. The use of kriging did not improve the model performance. The relative depth gradients of SOC were especially distinguished by tree species composition and stand age. We suppose that interesting fields of application may be found in scenario-based modelling of SOC and when SOC serves as a basis for hydrological modelling.
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