Mr Yurij M. Dmytruk, Yurіy Fedkovych Chernіvtsі Natіonal Unіversіty, Ukraine. Global Symposium on Soil Erosion (GSER19), 15 - 17 May 2019 at FAO HQ.

1. Models erosion as methodical basis
combating its manifestations in Ukraine
Yuriy Dmytruk, Vasyl Cherlіnka, Yurіy Fedkovych Chernіvtsі Natіonal Unіversіty, Ukraine
INTRODUCTION
The water and wind erosion heading the list of
destructive phenomena concerning of the
soils. The emergence and development of
processes of water erosion is one of the most
urgent problems for the environment of
Ukraine. Erosion is a leading factor in the loss
of the fertile soil layer, that is, its degradation
as a natural and economical resource. It is
relevant even for relatively arid areas, since
the storm-like nature of the precipitation
implies the immediate emergence of
temporary water streams, which determine
the appearance of linear erosion elements. A
detailed analysis carried out by soil scientists
in Ukraine has shown that the combination of
negative factors has a positive dynamic
(Baljuk et al., 2010).
а) b)
Fig. 1. Geographical location of the research area within
Ukraine (a), Chernivtsi region (b)
The foundation of modern advances in the
field of combining erosion models with
geoinformation systems has already been laid,
and these results are theoretical basis for the
practical realization of spatial analysis and
modeling.
MATERIALS AND METHODS
Data processing was carried out with the use
of GIS GRASS (GRASS Development Team,
2017). As object of research, a fragment of the
territory of Ukraine (Fig. 1a) was selected, in
particular the Kitsman district of the
Chernivtsi region (Fig. 1b), is confined to the
Dniester-Prut watershed (Northern Bukovina)
with contrasting geomorphological
conditions.
To create simulation models of soil cover, we
used the Cherlinka script (2017c, d, b) written
on the R-statistic, which includes a number of
adaptations for solving set tasks and
implements 14 basic types of predicative
algorithms. This work used Random Forests,
its implementation in the R ranger package
(Wright and Ziegler, 2017). Based on the
analysis of the DEM (GRASS Development
Team, 2017), we simulated and evaluated the
potential risks of erosion phenomena using
the SIMWE model (Mitas and Mitasova,
1998; Mitasova and Mitas, 2001; Hofierka et
al., 2002; Fernandes et al., 2017). The
parameters of the model were chosen
according to Koko data (2011).
For comparing we are given by erosion
modeling on the example of the typical region
of Ukraine, which is average for all
parameters. As we see (Figure 2a, Table 1),
only 60.3% of its territory is covered by soil
surveys.
MAIN RESULTS
To fill the gaps, we used the Random Forest
algorithm, which them we obtained a
predicative soil map with κ = 87.4% (Fig. 2b).
This allowed us to use these predictive data
for the expansion of the official assessment of
the territory's erosion. If we calculate erosion
only according to official data (we recall that
the data are 60-30 years old), then in general
it is 15862 ha or 26% of the area of the district
(Fig. 2c, Table 1). If we estimate the erosivity
of the soil to give a predicative soil map, then
we see that the erosivity increases by 224%,
with strongly eroded soils occupying almost 2
times more areas (Fig. 2d, Table 1). The area
of the sedimented soils remained at the
previous level. In contrast to the previous
approach the definition of the number of
eroded areas, the next approach is based on a
mathematical model experiment. Simulation
of water erosion based on SIMWE model
showed interesting results.
First of all, it is clearly observed that erosion
processes are timed to the relief of the territory.
Further simulation, allowed to obtain a
complete picture of erosion hazard (Fig. 2e).
This figure shows that the location of eroded
soils on the official maps do not really have the
necessary precision, since they do not take into
account many of the moments associated with
the progress of real erosion processes.
CONCLUSIONS
It has been shown that the existing data on the
development of soil erodibility in Ukraine are
outdated, incomplete and have numerous
errors. An advanced version of the evaluation of
this data, i.e. filling gaps in researches through
predicative soil modeling, although possible,
but can’t be too precise due to incomplete
reliability of the source data. Our research
confirms the effectiveness of using GRASS GIS
and the model of water erosion-deposition
SIMWE for a more correct assessment of the
phenomenon of erosion. This is a prerequisite
for the development of a system of anti-erosion
measures at a qualitatively higher level. It also
allows assessing different scenarios and
strategies to combat the manifestations of
erosion processes. Such an approach is scalable
for the entire territory of Ukraine and may be
recommended for a more accurate assessment
of the risks of erosion.
Tab. 1: Differences between official and model data on soil erosion
Fig. 2. Soil resources of the region of research: map of agro-industrial groups of
soil (a); predicative soil map (b); eroded soils according to official data (c); eroded
soils according to the predicative map (d); erosion-deposition map from SIMWE,
kg∙m-2∙s-1 (e)
a)
d)
b)
c) e)