•SOM contents decreased significantly between 1998 and 2018 in the layer 30–100 cm.•Decrease of SOM content was shown for mineral soils under cropland, 0–30 cm.•Decrease of SOC stocks in mineral ...soils under agriculture was calculated.•Choice for geomatching or classmatching is relevant in estimation for subareas.
Changes in soil organic matter (SOM) content and soil organic carbon (SOC) stock in the 0–30 cm and 30–100 cm soil layers between 1998 and 2018 in the Netherlands were estimated by repeated sampling of 1152 locations in the Soil Sampling Programme (SSP). These locations were selected following a stratified simple random sampling design. We discuss various barriers we met: restricted accuracy of information on soil bulk density, uncertainties due to positional errors, differences in sampling support, and changes in laboratory analysis methods since 1998. Domains of interest such as mineral soils were defined either on the basis of the stratification of the SSP sample (geomatching) or on the basis of soil profiles observed at the selected locations (classmatching). The mean SOM content changed significantly in the 30–100 cm layer (-17.68 gkg-1) in the entire area of interest (non-built-up area in the Netherlands) between 1998 and 2018 (at a 5% significance level). A decrease in SOM content between 1998 and 2018 could be shown for the 0–30 cm layer in mineral soils under cropland if classmatching was applied (at a 5% significance level), but no change could be shown in this layer in the remaining domains of interest, whether geomatching or classmatching were applied. For the 30–100 cm layer in mineral soils, significant changes in mean SOM content were shown by classmatching: −8.59 gkg-1 under cropland and −4.75 gkg-1 under grassland. The calculations indicate that SOC stocks decreased between 1998 and 2018 in both the 0–30 cm and the 30–100 cm layer of mineral soils under both cropland and grassland. The accuracy of the bulk density data needs to be improved in future measurements to increase the accuracy of calculations of the SOC stock changes.
Validation of a new gamma ray soil bulk density sensor Pepers, Karin H. J.; Egmond, Fenny; Koomans, Ronald ...
European journal of soil science,
July–August 2024, 2024-07-00, 20240701, Volume:
75, Issue:
4
Journal Article
Peer reviewed
Open access
Soil compaction and soil bulk density are key soil properties affecting soil health and soil ecosystem services like crop production, water retention and purification and carbon sequestration. The ...standard method for soil bulk density measurements using Kopecky rings is very labour intensive, time consuming and leaves notable damage to the field. Accurate data on bulk density are therefore scarce. To enable large‐scale data collection, we tested a new portable gamma ray sensor (RhoC) for in situ field and dry bulk density measurements up to 1 m depth. In this first validation study, measurements with the RhoC‐sensor were compared with classic ring sampling. Measurements were made in two agricultural fields in the Netherlands (a sandy clay loam and a sandy soil), with large variation in subsoil compaction. At 10 locations within each field, three soil density profiles were made. Each profile comprised six depth measurements (every 10 cm from 10 to 60 cm depth) using the RhoC‐sensor and Kopecky rings, resulting in 30 pairwise profiles and 180 measurements in total per field. At an average soil density of 1.5 g/cm3, the relative uncertainty was 9% for the Kopecky rings and 15% for the RhoC‐sensor. Because the RhoC‐sensor is easy and quick to use, the higher relative uncertainty can easily be compensated for by making additional measurements per location. In conclusion, the RhoC‐sensor allows a reliable quantitative in situ assessment of both field and dry bulk density. This provides the much‐needed possibility for rapid and accurate assessment of soil compaction. The acquisition of this data supports the calculation of soil organic carbon stocks and is indispensable for (national) soil monitoring, to assess soil health and to inform sustainable land management practices for sustained or improved soil health and provision of soil ecosystem services, such as requested in the proposed EU Directive on Soil Monitoring and Resilience.
In response to the growing societal awareness of the critical role of healthy soils, there has been an increasing demand for accurate and high-resolution soil information to inform national policies ...and support sustainable land management decisions. Despite advancements in digital soil mapping and initiatives like GlobalSoilMap, quantifying soil variability and its uncertainty across space, depth and time remains a challenge. Therefore, maps of key soil properties are often still missing on a national scale, which is also the case in the Netherlands. To meet this challenge and fill this data gap, we introduce BIS-4D, a high-resolution soil modeling and mapping platform for the Netherlands. BIS-4D delivers maps of soil texture (clay, silt and sand content), bulk density, pH, total nitrogen, oxalate-extractable phosphorus, cation exchange capacity and their uncertainties at 25 m resolution between 0 and 2 m depth in 3D space. Additionally, it provides maps of soil organic matter and its uncertainty in 3D space and time between 1953 and 2023 at the same resolution and depth range. The statistical model uses machine learning informed by soil observations amounting to between 3815 and 855 950, depending on the soil property, and 366 environmental covariates. We assess the accuracy of mean and median predictions using design-based statistical inference of a probability sample and location-grouped 10-fold cross validation (CV) and prediction uncertainty using the prediction interval coverage probability.
PDF
