Environmental Engineering Reference
In-Depth Information
Table 7.6
Shares of the area of the different soil types (characterized by organic carbon content
in %, irst column) that fall in different categories of texture of topsoil (%)
OCTOP class
Coarse
Medium
Medium fine
Fine
Very fine
No mineral texture
0.1-1.23%
10
63
21
6
0
0
1.23-2.46%
23
43
15
17
1
0
2.46-3.94%
22
44
15
20
0
0
3.94-5.66%
25
58
14
3
0
0
5.66-8.86%
44
47
5
1
0
3
8.86-63.0%
48
39
1
2
0
10
No data
44
44
4
4
0
4
Total
29
48
12
9
0
2
For the texture in the topsoil (see Table
7.6
) there is a clear relationship with the
soil types (organic carbon content). The soil types with lower carbon content are
generally with a lower share of coarse soils and a higher share of medium fine and
fine textured soils. However, it is worth noting that for the most widespread texture
type, medium, the picture is more complex, with the soil types with 0.1-1.23% and
3.94-5.66% carbon content having the highest share of this texture category.
The largest share of non-mineral soils is, not surprisingly, found for the soil types
with highest carbon content. It is also worth noting that a high share of the areas
with no information on soil type are of the texture classes that are considered poor in
agronomic terms, with a very high percentage of medium and coarse textured soils.
Overall, looking at the three key variables, it is clear, firstly that almost two
thirds of the EU27+ is without identified obstacles. Secondly, the variables carbon
content and texture are clearly related. Thirdly, the fact that the information on
carbon content is available as continuous data as described above, gives this variable
an advantage compared to texture. Finally, as described earlier, the information on
carbon content is available in 1 km
2
grids, which is more suitable for mapping than
the other variables. Overall, it is thus clear that the selection of carbon content to
define the soil types and thus also to map the Seamzones seems justified.
One final remark on the processing of the data for SEAMLESS is, that the
selection of representative soil profiles tends to focus on the most dominant soil
profiles (Soil Typological Units). The original dataset with STUs holds information
on app. 5,300 sets of soil information. However, only 844 STUs, i.e. the dominant
ones with a dominant combination of soil texture and rooting depth per Seamzone,
have been chosen using the method described above. On average one set of soil
information from the STUs is used to describe 4.2 Seamzones. The distribution is
uneven as can be seen in Table
7.7
: half of the soil sets is used to describe one or
two Seamzones, whereas the 10% of the soil sets that is used most frequently is
used to describe ten or more Seamzones.
Already in the original data used to describe the soil characteristics the
heterogeneity of the soils across the EU is not fully described. The processing of
the data to Seamzones has increased this problem focusing on the most dominating
soils. However, due to the type of information on soil variables, mainly categorical
data, this is unavoidable.
