predecessor mapcalc, PCRaster is optimized for dynamic modeling. The modeling
language also contains specialized routing algorithms to simulate matter flows
between pixels.
Spatial PCRaster models like LUCIA combine the landscape-scale representation of soil and vegetation classes in a map format, with parameters assigned to each
of these classes. During model initialization, parameters and maps are associated
using look-up tables; for example, the same value for the parameter subsoil clay
content is assigned to all related soil type pixels in the soil map. During the
following time-steps, each parameter is updated for each pixel based on the specific
model algorithms. Temporal data series such as weather data are read from time
series tables at every time step and are assigned to the respective pixels. LUCIA
requires soil, land cover and topographic (Digital Elevation Model (DEM)) maps,
as well as daily weather data such as rainfall, air and soil temperature, solar
radiation and reference evapotranspiration rates (ET0) (for a full description, we
refer to Marohn and Cadisch 2011). Soil and plant parameters required for model
initialization are grouped according to the modules described in the following
subsections.
10.2.3.1 Soil
Soil information represented in the LUCIA landscape is read from spatial soil maps
in a specific PCRaster-grid format. For each pixel, a specific soil is composed of
two horizons – top- and sub-soil, which have user-defined physical and chemical
properties. Within the physical category fall horizon thickness, bulk density and
texture, among others. Based on these parameters, plus soil organic matter content,
soil hydraulic properties (pore volume, field capacity and hydraulic conductivity,
among others) are derived based on the empiric pedo transfer functions developed
by Saxton and Rawls (2006). Soil chemical properties determine plant nutrient
supply and include total and available nitrogen, phosphorus and potassium.
10.2.3.2 Water Balance, Erosion and Deposition
Water enters the system in the form of rainfall, a part of which is intercepted and
evaporated from the plant canopy (Fig. 10.4). System losses occur as evapotranspiration, as drainage below the soil profile and as stream outflows from the watershed.
Topsoils and subsoils store water according to their pore volume and pore size
distribution, and rain water that has passed through the canopy (throughfall)
infiltrates the topsoil or, bypassing the soil matrix, goes directly into the subsoil.
The amount of infiltration depends on the rainfall intensity, as well as the level of
saturation and hydraulic conductivity of the topsoil. If the topsoil is saturated,
overflow occurs, and if rain intensity exceeds conductivity (both are expressed in
volume of water per time unit), surface runoff occurs (see Semmens et al. 2008 for
the infiltration concept used in LUCIA). Both processes then lead to soil erosion.
Infiltrated water can be stored in the topsoil or move into the subsoil (percolation)
10 Integrated Modeling of Agricultural Systems in Mountainous Areas
375
language also contains specialized routing algorithms to simulate matter flows
between pixels.
Spatial PCRaster models like LUCIA combine the landscape-scale representation of soil and vegetation classes in a map format, with parameters assigned to each
of these classes. During model initialization, parameters and maps are associated
using look-up tables; for example, the same value for the parameter subsoil clay
content is assigned to all related soil type pixels in the soil map. During the
following time-steps, each parameter is updated for each pixel based on the specific
model algorithms. Temporal data series such as weather data are read from time
series tables at every time step and are assigned to the respective pixels. LUCIA
requires soil, land cover and topographic (Digital Elevation Model (DEM)) maps,
as well as daily weather data such as rainfall, air and soil temperature, solar
radiation and reference evapotranspiration rates (ET0) (for a full description, we
refer to Marohn and Cadisch 2011). Soil and plant parameters required for model
initialization are grouped according to the modules described in the following
subsections.
10.2.3.1 Soil
Soil information represented in the LUCIA landscape is read from spatial soil maps
in a specific PCRaster-grid format. For each pixel, a specific soil is composed of
two horizons – top- and sub-soil, which have user-defined physical and chemical
properties. Within the physical category fall horizon thickness, bulk density and
texture, among others. Based on these parameters, plus soil organic matter content,
soil hydraulic properties (pore volume, field capacity and hydraulic conductivity,
among others) are derived based on the empiric pedo transfer functions developed
by Saxton and Rawls (2006). Soil chemical properties determine plant nutrient
supply and include total and available nitrogen, phosphorus and potassium.
10.2.3.2 Water Balance, Erosion and Deposition
Water enters the system in the form of rainfall, a part of which is intercepted and
evaporated from the plant canopy (Fig. 10.4). System losses occur as evapotranspiration, as drainage below the soil profile and as stream outflows from the watershed.
Topsoils and subsoils store water according to their pore volume and pore size
distribution, and rain water that has passed through the canopy (throughfall)
infiltrates the topsoil or, bypassing the soil matrix, goes directly into the subsoil.
The amount of infiltration depends on the rainfall intensity, as well as the level of
saturation and hydraulic conductivity of the topsoil. If the topsoil is saturated,
overflow occurs, and if rain intensity exceeds conductivity (both are expressed in
volume of water per time unit), surface runoff occurs (see Semmens et al. 2008 for
the infiltration concept used in LUCIA). Both processes then lead to soil erosion.
Infiltrated water can be stored in the topsoil or move into the subsoil (percolation)
10 Integrated Modeling of Agricultural Systems in Mountainous Areas
375