7
2017; Lai et al. 2016; Meusburger et al. 2012; Panagos et al. 2017a; Plangoen
et al. 2013).
Global climate change has taken a permanent place among the significant environmental problems being faced by the world community in recent decades
(Ibatullin et al. 2009). It is becoming one of the most significant environmental
issues of the twenty-first century (Campbell et al. 2011; Carter et al. 2015). The
temperature predictions for RCP4.5 show general warming in the Central Asian
region close to 2 °C (2021–2050 compared with 1961–1990) by the CMIP5, and the
heating tendency is more intensified for RCP8.5 (Immerzeel et al. 2013). Climate
change is expected to have a significant impact on the Central Asian region based on
global climate predictions (Unger-Shayesteh et al. 2013).
The modeling method is an ordinary and necessary way to predict the future
effects of climate change. Simulation studies are often based on erosion models and
global climate models (GCM). GCMs are commonly used to predict climatic characteristics under hypothetical or large-scale climate scenarios. Thus, these meteorological data for different scenarios act as input data for an erosion model to obtain
climate-altered variables associated with soil erosion.
Remote sensing and GIS methods are often used to obtain other necessary input
data for models. Several models with reliable results have been used in many forecasting or exploitation tasks or for planning. However, these models usually operate
according to the quantity and quality of the available data, which are unevenly distributed. In developed countries, data are highly available, but not in developing
countries, such as the former Soviet republics in Central Asia (Gafurov 2010).
Usually, data availability is minimal in a high-mountain region or in less-populated
areas, where continuous observations with daily time steps require incredibly high
costs and labor, which is not feasible for most developing countries. Central Asia is
one of those regions where data availability is minimal.
According to Kulikov (2018), for decades, Central Asia has remained a white
spot on the map of international science because of two reasons. First, since most of
the earlier scientific research was conducted in Soviet times, it was published in the
Russian language, and since the Soviet Union was a closed country, the publications
barely reached the English-speaking world. The second reason is because Central
Asia does not have sufficient resources to conduct large-scale systematic baseline
environmental studies.
Despite the importance and demand for studies on soil, vegetation, and climate,
the unfortunate economic situation in the region does not allow for a regular assessment of their condition (Kulikov 2018). However, the modern developments in the
field of GIS and RS and the availability of spatial data, together with the increase in
computing power, make this task less expensive. Fieldwork and ground data collection, along with laboratory work, are the most time-consuming parts of the study,
whereas auxiliary informational and analytical tools are now less significant due to
the generosity of their excellent suppliers. This allows the developing countries to
conduct a thorough assessment and regular monitoring of natural resources and
hazards.
1.3 Soil Erosion Processes and Models
2017; Lai et al. 2016; Meusburger et al. 2012; Panagos et al. 2017a; Plangoen
et al. 2013).
Global climate change has taken a permanent place among the significant environmental problems being faced by the world community in recent decades
(Ibatullin et al. 2009). It is becoming one of the most significant environmental
issues of the twenty-first century (Campbell et al. 2011; Carter et al. 2015). The
temperature predictions for RCP4.5 show general warming in the Central Asian
region close to 2 °C (2021–2050 compared with 1961–1990) by the CMIP5, and the
heating tendency is more intensified for RCP8.5 (Immerzeel et al. 2013). Climate
change is expected to have a significant impact on the Central Asian region based on
global climate predictions (Unger-Shayesteh et al. 2013).
The modeling method is an ordinary and necessary way to predict the future
effects of climate change. Simulation studies are often based on erosion models and
global climate models (GCM). GCMs are commonly used to predict climatic characteristics under hypothetical or large-scale climate scenarios. Thus, these meteorological data for different scenarios act as input data for an erosion model to obtain
climate-altered variables associated with soil erosion.
Remote sensing and GIS methods are often used to obtain other necessary input
data for models. Several models with reliable results have been used in many forecasting or exploitation tasks or for planning. However, these models usually operate
according to the quantity and quality of the available data, which are unevenly distributed. In developed countries, data are highly available, but not in developing
countries, such as the former Soviet republics in Central Asia (Gafurov 2010).
Usually, data availability is minimal in a high-mountain region or in less-populated
areas, where continuous observations with daily time steps require incredibly high
costs and labor, which is not feasible for most developing countries. Central Asia is
one of those regions where data availability is minimal.
According to Kulikov (2018), for decades, Central Asia has remained a white
spot on the map of international science because of two reasons. First, since most of
the earlier scientific research was conducted in Soviet times, it was published in the
Russian language, and since the Soviet Union was a closed country, the publications
barely reached the English-speaking world. The second reason is because Central
Asia does not have sufficient resources to conduct large-scale systematic baseline
environmental studies.
Despite the importance and demand for studies on soil, vegetation, and climate,
the unfortunate economic situation in the region does not allow for a regular assessment of their condition (Kulikov 2018). However, the modern developments in the
field of GIS and RS and the availability of spatial data, together with the increase in
computing power, make this task less expensive. Fieldwork and ground data collection, along with laboratory work, are the most time-consuming parts of the study,
whereas auxiliary informational and analytical tools are now less significant due to
the generosity of their excellent suppliers. This allows the developing countries to
conduct a thorough assessment and regular monitoring of natural resources and
hazards.
1.3 Soil Erosion Processes and Models