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Users may define the amount of nitrate and organic nitrogen contained in humic substances for all soil layers at the beginning of the simulation. If the user does not specify initial nitrogen concentrations, SWAT+ will initialize levels of nitrogen in the different pools.
Initial nitrate levels in the soil are varied by depth using the relationship:
3:1.1.1
where is the concentration of nitrate in the soil at depth (mg/kg or ppm), and is the depth from the soil surface (mm). The nitrate concentration with depth calculated from equation 3:1.1.1 is displayed in Figure 3:1-3. The nitrate concentration for a layer is calculated by solving equation 3:1.1.1 for the horizon’s lower boundary depth.
Organic nitrogen levels are assigned assuming that the C:N ratio for humic materials is 14:1. The concentration of humic organic nitrogen in a soil layer is calculated:
Nitrogen in the fresh organic pool is set to zero in all layers except the top 10 mm of soil. In the top 10 mm, the fresh organic nitrogen pool is set to 0.15% of the initial amount of residue on the soil surface.
While SWAT+ allows nutrient levels to be input as concentrations, it performs all calculations on a mass basis. To convert a concentration to a mass, the concentration is multiplied by the bulk density and depth of the layer and divided by 100:
Table 3:1-1: SWAT+ input variables that pertain to nitrogen pools.
The three major forms of nitrogen in mineral soils are organic nitrogen associated with humus, mineral forms of nitrogen held by soil colloids, and mineral forms of nitrogen in solution. Nitrogen may be added to the soil by fertilizer, manure or residue application, fixation by symbiotic or nonsymbiotic bacteria, and rain. Nitrogen is removed from the soil by plant uptake, leaching, volatilization, denitrification and erosion. Figure 3:1-1 shows the major components of the nitrogen cycle.
Nitrogen is considered to be an extremely reactive element. The highly reactive nature of nitrogen results from its ability to exist in a number of valance states. The valence state or oxidation state describes the number of electrons orbiting the nucleus of the nitrogen atom relative to the number present in an electronically neutral atom. The valence state will be positive as the atom looses electrons and will be negative as the atom gains electrons. Examples of nitrogen in different valence states are:
The ability of nitrogen to vary its valence state makes it a highly mobile element. Predicting the movement of nitrogen between the different pools in the soil is critical to the successful management of this element in the environment.
Figure 3:1-2: SWAT+ soil nitrogen pools and processes that move nitrogen in and out of pools.
The fate and transport of nutrients and pesticides in a watershed depend on the transformations the compounds undergo in the soil environment. SWAT+ models the complete nutrient cycle for nitrogen and phosphorus as well as the degradation of any pesticides applied in an HRU.
The following five chapters review the methodology used by SWAT+ to simulate nutrient, pesticide, bacteria, and carbon processes in the soil.
3:1.1.2
where is the concentration of humic organic nitrogen in the layer (mg/kg or ppm), and is the amount of organic carbon in the layer (%). The humic organic is partitioned between the active and stable pools using the following equations:
3.1.1.3
3:1.1.4
where is the concentration of nitrogen in the active organic pool (mg/kg), is the concentration of humic organic nitrogen in the layer (mg/kg), is the fraction of humic nitrogen in the active pool, and is the concentration of nitrogen in the stable organic pool (mg/kg). The fraction of humic nitrogen in the active pool, , is set to 0.02.
3:1.1.5
where is the nitrogen in the fresh organic pool in the top 10 mm (kg N/ha), and is material in the residue pool for the top 10 mm of soil (kg/ha).
The ammonium pool for soil nitrogen, , is initialized to 0 ppm.
3:1.1.6
where is the concentration of nitrogen in a layer (mg/kg or ppm), is the bulk density of the layer (Mg/m), and is the depth of the layer (mm).
| Variable Name | Definition | Input File |
|---|---|---|
SWAT+ monitors five different pools of nitrogen in the soil (Figure 3:1-2). Two pools are inorganic forms of nitrogen, NH4+ and , while the other three pools are organic forms of nitrogen. Fresh organic N is associated with crop residue and microbial biomass while the active and stable organic N pools are associated with the soil humus. The organic nitrogen associated with humus is partitioned into two pools to account for the variation in availability of humic substances to mineralization.
SOL_NO3
: Initial NO3 concentration in soil layer (mg/kg or ppm)
.chm
SOL_ORGN
: Initial humic organic nitrogen in soil layer (mg/kg or ppm)
.chm
RSDIN
: Material in the residue pool for the top 10mm of soil (kg ha-1)
.hru
SOL_BD
: Bulk density of the layer (Mg/m)
.sol
SOL_CBN
: Amount of organic carbon in the layer (%)
.sol
Nitrogen is allowed to move between the active and stable organic pools in the humus fraction. The amount of nitrogen transferred from one pool to the other is calculated:
3:1.2.3
is the amount of nitrogen transferred between the active and stable organic pools (kg N/ha), is the rate constant (1×10), is the amount of nitrogen in the active organic pool (kg N/ha), is the fraction of humic nitrogen in the active pool (0.02), and is the amount of nitrogen in the stable organic pool (kg N/ha). When is positive, nitrogen is moving from the active organic pool to the stable organic pool. When is negative, nitrogen is moving from the stable organic pool to the active organic pool.
Mineralization from the humus active organic pool is calculated:
3:1.2.4
where is the nitrogen mineralized from the humus active organic pool (kg N/ha), is the rate coefficient for mineralization of the humus active organic nutrients, is the nutrient cycling temperature factor for layer , is the nutrient cycling water factor for layer is the amount of nitrogen in the active organic pool (kg N/ha).
Nitrogen mineralized from the humus active organic pool is added to the nitrate pool in the layer.
The complexity of the nitrogen cycle and nitrogen’s importance in plant growth have made this element the subject of much research. The nitrogen cycle is a dynamic system that includes the water, atmosphere and soil. Plants require nitrogen more than any other essential element, excluding carbon, oxygen and hydrogen. Nitrogen is modeled by SWAT+ in the soil profile and in the shallow aquifer.
Nitrification is the two-step bacterial oxidation of to .
step 1: (Nitrosomonas)
step 2: (Nitrobacter)
Ammonia volatilization is the gaseous loss of that occurs when ammonium, , is surface applied to a calcareous soil or when urea, (, is surface applied to any soil.
surface applied to a calcareous soil:
step 1:
step 2:
Urea surface applied to any soil:
step 1:
step 2:
SWAT+ simulates nitrification and ammonia volatilization using a combination of the methods developed by Reddy et al. (1979) and Godwin et al. (1984). The total amount of nitrification and ammonia volatilization is calculated, and then partitioned between the two processes. Nitrification is a function of soil temperature and soil water content while ammonia volatilization is a function of soil temperature, depth and cation exchange capacity. Four coefficients are used in the nitrification/volatilization algorithms to account for the impact of these parameters. Nitrification/volatilization occurs only when the temperature of the soil layer exceeds 5°C.
The nitrification/volatilization temperature factor is calculated:
if 3:1.3.1
where is the nitrification/volatilization temperature factor, and is the temperature of layer (°C).
The nitrification soil water factor is calculated:
if 3:1.3.2
if 3:1.3.3
where is the nitrification soil water factor, is the soil water content of layer on a given day (mm HO), is the amount of water held in the soil layer at wilting point water content (mm HO), and is the amount of water held in the soil layer at field capacity water content (mm HO).
The volatilization depth factor is calculated:
3:1.3.4
where is the volatilization depth factor, and is the depth from the soil surface to the middle of the layer (mm).
SWAT+ does not require the user to provide information about soil cation exchange capacity. The volatilization cation exchange factor is set to a constant value:
3:1.3.5
The impact of environmental factors on nitrification and ammonia volatilization in a given layer is defined by the nitrification regulator and volatilization regulator. The nitrification regulator is calculated:
3:1.3.6
and the volatilization regulator is calculated:
3:1.3.7
where is the nitrification regulator, is the volatilization regulator, is the nitrification/volatilization temperature factor, is the nitrification soil water factor, and is the volatilization depth factor.
The total amount of ammonium lost to nitrification and volatilization is calculated using a first-order kinetic rate equation (Reddy et al., 1979):
3:1.3.8
where is the amount of ammonium converted via nitrification and volatilization in layer (kg N/ha), is the amount of ammonium in layer (kg N/ha), is the nitrification regulator, and is the volatilization regulator.
To partition between nitrification and volatilization, the expression by which is multiplied in equation 3:1.3.8, is solved using each regulator individually to obtain a fraction of ammonium removed by each process:
3:1.3.9
3:1.3.10
where is the estimated fraction of nitrogen lost by nitrification, is the estimated fraction of nitrogen lost by volatilization, is the nitrification regulator, and is the volatilization regulator.
The amount of nitrogen removed from the ammonium pool by nitrification is then calculated:
3:1.3.11
and the amount of nitrogen removed from the ammonium pool by volatilization is:
3:1.3.12
where is the amount of nitrogen converted from to in layer (kg N/ha), is the amount of nitrogen converted from to in layer (kg N/ha), is the estimated fraction of nitrogen lost by nitrification, is the estimated fraction of nitrogen lost by volatilization, and is the amount of ammonium converted via nitrification and volatilization in layer (kg N/ha).
Decomposition is the breakdown of fresh organic residue into simpler organic components. Mineralization is the microbial conversion of organic, plant-unavailable nitrogen to inorganic, plant-available nitrogen. Immobilization is the microbial conversion of plant-available inorganic soil nitrogen to plant-unavailable organic nitrogen.
Bacteria decompose organic material to obtain energy for growth processes. Plant residue is broken down into glucose which is then converted to energy:
The energy released by the conversion of glucose to carbon dioxide and water is used for various cell processes, including protein synthesis. Protein synthesis requires nitrogen. If the residue from which the glucose is obtained contains enough nitrogen, the bacteria will use nitrogen from the organic material to meet the demand for protein synthesis. If the nitrogen content of the residue is too low to meet the bacterial demand for nitrogen, the bacteria will use and from the soil solution to meet its needs. If the nitrogen content of the residue exceeds the bacterial demand for nitrogen, the bacterial will release the excess nitrogen into soil solution as . A general relationship between C:N ratio and mineralization/immobilization is:
The nitrogen mineralization algorithms in SWAT+ are net mineralization algorithms which incorporate immobilization into the equations. The algorithms were adapted from the PAPRAN mineralization model (Seligman and van Keulen, 1981). Two sources are considered for mineralization: the fresh organic N pool associated with crop residue and microbial biomass and the active organic N pool associated with soil humus. Mineralization and decomposition are allowed to occur only if the temperature of the soil layer is above 0°C.
Mineralization and decomposition are dependent on water availability and temperature. Two factors are used in the mineralization and decomposition equations to account for the impact of temperature and water on these processes.
The nutrient cycling temperature factor is calculated:
3:1.2.1
where is the nutrient cycling temperature factor for layer , and is the temperature of layer (°C). The nutrient cycling temperature factor is never allowed to fall below 0.1.
The nutrient cycling water factor is calculated:
3:1.2.2
where is the nutrient cycling water factor for layer , is the water content of layer on a given day (mm HO), and is the water content of layer at field capacity (mm HO). The nutrient cycling water factor is never allowed to fall below 0.05.
Dry deposition of nitrate and ammonia is input to the model for each subbasin. Average daily deposition is added to the appropriate surface soil pool.
Table 3:1-5: SWAT+ input variables that pertain to dry deposition.
| Variable Name | Definition | Input File |
|---|
As water evaporates from the soil surface, the water content at the surface drops, creating a gradient in the profile. Water from lower in the profile will move upward in response to the gradient, carrying dissolved nutrients with it. SWAT+ allows nitrate to be transported from the first soil layer defined in the .sol file to the surface top 10 mm of soil with the equation:
3:1.7.1
where is the amount of nitrate moving from the first soil layer to the soil surface zone (kg N/ha), is the nitrate content of the first soil layer (kg N/ha), is the amount of water removed from the first soil layer as a result of evaporation (mm HO), and is the soil water content of the first soil layer (mm HO).
Legumes are able to obtain a portion of their nitrogen demand through fixation of atmospheric performed by rhizobia living in association with the plant. In exchange for nitrogen, the plant supplies the bacteria with carbohydrates.
Atmospheric deposition occurs when airborne chemical compounds settle onto the land or water surface. Some of the most important chemical pollutants are those containing nitrogen or phosphorus. Nitrogen compounds can be deposited onto water and land surfaces through both wet and dry deposition mechanisms. Wet deposition occurs through the absorption of compounds by precipitation as it falls carrying mainly nitrate () and ammonium (). Dry deposition is the direct adsorption of compounds to water or land surfaces and involves complex interactions between airborne nitrogen compounds and plant, water, soil, rock, or building surfaces.
The relative contribution of atmospheric deposition to total nutrient loading is difficult to measure or indirectly assess and many deposition mechanisms are not fully understood. Most studies and relatively extended data sets are available on wet deposition of nitrogen, while dry deposition rates are not well defined. Phosphorus loadings due to atmospheric deposition have not been extensively studied and nation-wide extended data set were unavailable at the time of data preparation for the CEAP project. While research continues in these areas, data records generated by modeling approaches appear to be still under scrutiny.
A number of regional and local monitoring networks are operating in the U.S. mainly to address information regarding regional environmental issues. For example, the Integrated Atmospheric Deposition Network (IADN) (Galarneau et al., 2006) that estimates deposition of toxic organic substances to the Great Lakes. Over the CONUS (conterminous United States), the National Atmospheric Deposition Program (NADP) National Trends Network (NTN) (NADP/NTN, 1995; NADP/NTN, 2000; Lamb and Van Bowersox, 2000) measures and ammonium in one-week rain and snow samples at nearly 240 regionally representative sites in the CONUS and is considered the nation’s primary source for wet deposition data.
The U.S. EPA Clean Air Status and Trends Network (CASTNET), developed form the National Dry Deposition Network (NDDN), operates a total of 86 operational sites (as of December 2007) located in or near rural areas and sensitive ecosystems collecting data on ambient levels of pollutants where urban influences are minimal (CASTNET, 2007). As part of an interagency agreement, the National Park Service (NPS) sponsors 27 sites which are located in national parks and other Class-I areas designated as deserving special protection from air pollution.
The majority of plant-essential nutrients are cations which are attracted and sorbed to negatively-charged soil particles. As plants extract these cations from soil solution, the soil particles release bound cations into soil solution to bring the ratio of nutrients in solution and on soil particles back into equilibrium. In effect, the soil buffers the concentration of cations in solution.
In contrast, nitrate is an anion and is not attracted to or sorbed by soil particles. Because retention of nitrate by soils is minimal, nitrate is very susceptible to leaching. The algorithms used by SWAT+ to calculated nitrate leaching simultaneously solve for loss of nitrate in surface runoff and lateral flow also. These algorithms are reviewed in Chapter 4:2.
Decomposition and mineralization of the fresh organic nitrogen pool is allowed only in the first soil layer. Decomposition and mineralization are controlled by a decay rate constant that is updated daily. The decay rate constant is calculated as a function of the C:N ratio and C:P ratio of the residue, temperature and soil water content.
The C:N ratio of the residue is calculated:
3:1.2.5
where is the C:N ratio of the residue in the soil layer, is the residue in layer (kg/ha), 0.58 is the fraction of residue that is carbon, is the nitrogen in the fresh organic pool in layer (kg N/ha), and is the amount of nitrate in layer (kg N/ha).
The C:P ratio of the residue is calculated:
3:1.2.6
where is the C:P ratio of the residue in the soil layer, is the residue in layer (kg/ha), 0.58 is the fraction of residue that is carbon, is the phosphorus in the fresh organic pool in layer (kg P/ha), and is the amount of phosphorus in solution in layer (kg P/ha).
The decay rate constant defines the fraction of residue that is decomposed. The decay rate constant is calculated:
3:1.2.7
where is the residue decay rate constant, is the rate coefficient for mineralization of the residue fresh organic nutrients, is the nutrient cycling residue composition factor for layer , is the nutrient cycling temperature factor for layer , and is the nutrient cycling water factor for layer .
The nutrient cycling residue composition factor is calculated:
3:1.2.8
where is the nutrient cycling residue composition factor for layer , is the C:N ratio on the residue in the soil layer, and is the C:P ratio on the residue in the soil layer.
Mineralization from the residue fresh organic N pool is then calculated:
3:1.2.9
where is the nitrogen mineralized from the fresh organic N pool (kg N/ha), is the residue decay rate constant, and is the nitrogen in the fresh organic pool in layer (kg N/ha). Nitrogen mineralized from the fresh organic pool is added to the nitrate pool in the layer.
Decomposition from the residue fresh organic N pool is calculated:
3:1.2.9
where is the nitrogen decomposed from the fresh organic N pool (kg N/ha), is the residue decay rate constant, and is the nitrogen in the fresh organic pool in layer (kg N/ha). Nitrogen decomposed from the fresh organic pool is added to the humus active organic pool in the layer.
Table 3:1-2: SWAT+ input variables that pertain to mineralization.
drydep_no3 | Daily nitrate dry deposition rate (kg/ha) | .atm |
drydep_nh4 | Daily ammonia dry deposition rate (kg/ha) | .atm |
Denitrification is the bacterial reduction of nitrate, , to or gases under anaerobic (reduced) conditions. Denitrification is a function of water content, temperature, presence of a carbon source and nitrate.
In general, when the water-filled porosity is greater than 60% denitrification will be observed in a soil. As soil water content increases, anaerobic conditions develop due to the fact that oxygen diffuses through water 10,000 times slower than through air. Because the rate of oxygen diffusion through water slows as the water temperature increases, temperature will also influence denitrification.
Cropping systems where water is ponded, such as rice, can lose a large fraction of fertilizer by denitrification. For a regular cropping system, an estimated 10-20% of nitrogen fertilizer may be lost to denitrification. Under a rice cropping system, 50% of nitrogen fertilizer may be lost to denitrification. In a flooded cropping system, the depth of water plays an important role because it controls the amount of water oxygen has to diffuse through to reach the soil.
SWAT+ determines the amount of nitrate lost to denitrification with the equation:
if 3:1.4.1
if 3:1.4.2
where is the amount of nitrogen lost to denitrification (kg N/ha), is the amount of nitrate in layer (kg N/ha), is the rate coefficient for denitrification, is the nutrient cycling temperature factor for layer calculated with equation 3:1.2.1, is the nutrient cycling water factor for layer calculated with equation 3:1.2.2, is the amount of organic carbon in the layer (%), and is the threshold value of nutrient cycling water factor for denitrification to occur.
Table 3:1-3: SWAT+ input variables that pertain to denitrification.
| Variable Name | Definition | Input File |
|---|---|---|
Lightning discharge converts atmospheric to nitric acid which can then be transferred to the soil with precipitation. The chemical steps involved are:
step 1: (monoxide)
step 2: (dioxide)
step 3: (nitric acid and monoxide)
More nitrogen will be added to the soil with rainfall in areas with a high amount of lightning activity than in areas with little lightning.
The amount of nitrate added to the soil in rainfall is calculated:
3:1.5.1
where is nitrate added by rainfall (kg N/ha), is the concentration of nitrate in the rain (mg N/L), and is the amount of precipitation on a given day (mm HO). The nitrogen in rainfall is added to the nitrate pool in the top 10 mm of soil.
The amount of ammonia added to the soil in rainfall is calculated:
3:1.5.2
where is nitrate added by rainfall (kg N/ha), is the concentration of ammonia in the rain (mg N/L), and is the amount of precipitation on a given day (mm HO). The nitrogen in rainfall is added to the ammonia pool in the top 10 mm of soil.
Table 3:1-4: SWAT+ input variables that pertain to nitrogen in rainfall.
| Variable Name | Definition | Input File |
|---|---|---|
Users may define the amount of soluble P and organic phosphorus contained in humic substances for all soil layers at the beginning of the simulation. If the user does not specify initial phosphorus concentrations, SWAT+ will initialize levels of phosphorus in the different pools.
The concentration of solution phosphorus in all layers is initially set to 5 mg/kg soil. This concentration is representative of unmanaged land under native vegetation. A concentration of 25 mg/kg soil in the plow layer is considered representative of cropland (Cope et al., 1981).
The concentration of phosphorus in the active mineral pool is initialized to (Jones et al., 1984):
3:2.1.1
where is the amount of phosphorus in the active mineral pool (mg/kg), is the amount of phosphorus in solution (mg/kg), and is the phosphorus availability index.
The concentration of phosphorus in the stable mineral pool is initialized to (Jones et al., 1984):
3:2.1.2
where is the amount of phosphorus in the stable mineral pool (mg/kg), and is the amount of phosphorus in the active mineral pool (mg/kg).
Organic phosphorus levels are assigned assuming that the N:P ratio for humic materials is 8:1. The concentration of humic organic phosphorus in a soil layer is calculated:
3:2.1.3
where is the concentration of humic organic phosphorus in the layer (mg/kg) and is the concentration of humic organic nitrogen in the layer (mg/kg).
Phosphorus in the fresh organic pool is set to zero in all layers except the top 10mm of soil. In the top 10 mm, the fresh organic phosphorus pool is set to 0.03% of the initial amount of residue on the soil surface.
3:2.1.4
where is the phosphorus in the fresh organic pool in the top 10mm (kg P/ha), and is material in the residue pool for the top 10mm of soil (kg/ha).
While SWAT+ allows nutrient levels to be input as concentrations, it performs all calculations on a mass basis. To convert a concentration to a mass, the concentration is multiplied by the bulk density and depth of the layer and divided by 100:
3:2.1.5
where is the concentration of phosphorus in a layer (mg/kg or ppm), is the bulk density of the layer (Mg/m), and is the depth of the layer (mm).
Table 3:2-1: SWAT+ input variables that pertain to nitrogen pools.
Phosphorus in the humus fraction is partitioned between the active and stable organic pools using the ratio of humus active organic N to stable organic N. The amount of phosphorus in the active and stable organic pools is calculated:
3:2.2.3
3:2.2.4
where is the amount of phosphorus in the active organic pool (kg P/ha), is the amount of phosphorus in the stable organic pool (kg P/ha), is the concentration of humic organic phosphorus in the layer (kg P/ha), is the amount of nitrogen in the active organic pool (kg N/ha), and is the amount of nitrogen in the stable organic pool (kg N/ha).
Mineralization from the humus active organic P pool is calculated:
3:2.2.5
where is the phosphorus mineralized from the humus active organic pool (kg P/ha), is the rate coefficient for mineralization of the humus active organic nutrients, is the nutrient cycling temperature factor for layer , is the nutrient cycling water factor for layer , and is the amount of phosphorus in the active organic pool (kg P/ha).
Phosphorus mineralized from the humus active organic pool is added to the solution P pool in the layer.
The three major forms of phosphorus in mineral soils are organic phosphorus associated with humus, insoluble forms of mineral phosphorus, and plant-available phosphorus in soil solution. Phosphorus may be added to the soil by fertilizer, manure or residue application. Phosphorus is removed from the soil by plant uptake and erosion. Figure 3:2-1 shows the major components of the phosphorus cycle.
Unlike nitrogen which is highly mobile, phosphorus solubility is limited in most environments. Phosphorus combines with other ions to form a number of insoluble compounds that precipitate out of solution. These characteristics contribute to a build-up of phosphorus near the soil surface that is readily available for transport in surface runoff. Sharpley and Syers (1979) observed that surface runoff is the primary mechanism by which phosphorus is exported from most catchments.
SWAT+ monitors six different pools of phosphorus in the soil (Figure 3:2-2). Three pools are inorganic forms of phosphorus while the other three pools are organic forms of phosphorus. Fresh organic P is associated with crop residue and microbial biomass while the active and stable organic P pools are associated with the soil humus. The organic phosphorus associated with humus is partitioned into two pools to account for the variation in availability of humic substances to mineralization. Soil inorganic P is divided into solution, active, and stable pools. The solution pool is in rapid equilibrium (several days or weeks) with the active pool. The active pool is in slow equilibrium with the stable pool.
| Variable Name | Definition | File Name |
|---|---|---|
| Variable Name | Definition | Input File |
|---|
CMN
: Rate coefficient for mineralization of the humus active organic nutrients
.bsn
RSDCO
: Rate coefficient for mineralization of the residue fresh organic nutrients
.bsn
RSDCO_PL
: Rate coefficient for mineralization of the residue fresh organic nutrients
crop.dat
SOL_CBN
: Amount of organic carbon in the layer (%)
.sol
CDN
: Rate coefficient for denitrification
.bsn
SDNCO
: Threshold value of nutrient cycling water factor for denitrification to occur
.bsn
Decomposition is the breakdown of fresh organic residue into simpler organic components. Mineralization is the microbial conversion of organic, plant-unavailable phosphorus to inorganic, plant-available phosphorus. Immobilization is the microbial conversion of plant-available inorganic soil phosphorus to plant-unavailable organic phosphorus.
The phosphorus mineralization algorithms in SWAT+ are net mineralization algorithms which incorporate immobilization into the equations. The phosphorus mineralization algorithms developed by Jones et al. (1984) are similar in structure to the nitrogen mineralization algorithms. Two sources are considered for mineralization: the fresh organic P pool associated with crop residue and microbial biomass and the active organic P pool associated with soil humus. Mineralization and decomposition are allowed to occur only if the temperature of the soil layer is above 0°C.
Mineralization and decomposition are dependent on water availability and temperature. Two factors are used in the mineralization and decomposition equations to account for the impact of temperature and water on these processes.
The nutrient cycling temperature factor is calculated:
3:2.2.1
where is the nutrient cycling temperature factor for layer , and is the temperature of layer (°C). The nutrient cycling temperature factor is never allowed to fall below 0.1.
The nutrient cycling water factor is calculated:
3:2.2.2
where is the nutrient cycling water factor for layer , is the water content of layer on a given day (mm HO), and is the water content of layer at field capacity (mm HO). ). The nutrient cycling water factor is never allowed to fall below 0.05.
Although plant phosphorus demand is considerably less than nitrogen demand, phosphorus is required for many essential functions. The most important of these is its role in energy storage and transfer. Energy obtained from photosynthesis and metabolism of carbohydrates is stored in phosphorus compounds for later use in growth and reproductive processes.
Highly water-soluble pesticides can be transported with percolation deep into the soil profile and potentially pollute shallow groundwater systems. The algorithms used by SWAT+ to calculated pesticide leaching simultaneously solve for loss of pesticide in surface runoff and lateral flow also. These algorithms are reviewed in Chapter 4:3.
SOL_SOLP | .chm |
SOL_ORGP | .chm |
PSP | .bsn |
RSDIN | .hru |
SOL_BD | .sol |
Decomposition and mineralization of the fresh organic phosphorus pool is allowed only in the first soil layer. Decomposition and mineralization are controlled by a decay rate constant that is updated daily. The decay rate constant is calculated as a function of the C:N ratio and C:P ratio of the residue, temperature and soil water content.
The C:N ratio of the residue is calculated:
3:2.2.6
where is the C:N ratio of the residue in the soil layer, is the residue in layer (kg/ha), 0.58 is the fraction of residue that is carbon, is the nitrogen in the fresh organic pool in layer (kg N/ha), and is the amount of nitrate in layer (kg N/ha).
The C:P ratio of the residue is calculated:
3:2.2.7
where is the C:P ratio of the residue in the soil layer, is the residue in layer (kg/ha), 0.58 is the fraction of residue that is carbon, is the phosphorus in the fresh organic pool in layer (kg P/ha), and is the amount of phosphorus in solution in layer (kg P/ha).
The decay rate constant defines the fraction of residue that is decomposed. The decay rate constant is calculated:
3:2.2.8
where is the residue decay rate constant, is the rate coefficient for mineralization of the residue fresh organic nutrients, is the nutrient cycling residue composition factor for layer , is the nutrient cycling temperature factor for layer , and is the nutrient cycling water factor for layer .
The nutrient cycling residue composition factor is calculated:
3:2.2.9
where is the nutrient cycling residue composition factor for layer , is the C:N ratio on the residue in the soil layer, and is the C:P ratio on the residue in the soil layer.
Mineralization from the residue fresh organic P pool is then calculated:
3:2.2.10
where is the phosphorus mineralized from the fresh organic pool (kg P/ha), is the residue decay rate constant, and is the phosphorus in the fresh organic pool in layer (kg P/ha). Phosphorus mineralized from the fresh organic pool is added to the solution pool in the layer.
Decomposition from the residue fresh organic P pool is calculated:
3:2.2.11
where is the phosphorus decomposed from the fresh organic pool (kg P/ha), is the residue decay rate constant, and is the phosphorus in the fresh organic pool in layer (kg P/ha). Phosphorus decomposed from the fresh organic pool is added to the humus organic pool in the layer.
Table 3:2-2: SWAT+ input variables that pertain to mineralization.
Groundwater flow entering the main channel from the shallow aquifer can contain nitrate. With SWAT+ the nitrate pool in the shallow aquifer is modeled, allowing for fluctuations in nitrate loadings in the groundwater over time.
Nitrate enters the shallow aquifer in recharge from the soil profile. Water that moves past the lowest depth of the soil profile by percolation or bypass flow enters and flows through the vadose zone before becoming shallow and/or deep aquifer recharge. SWAT+ assumes there is no change in nitrate concentration of the recharge as it moves through the vadose zone.
An exponential decay weighting function proposed by Venetis (1969) and used by Sangrey et al. (1984) in a precipitation/groundwater response model is utilized in SWAT+ to account for the time delay in aquifer recharge once the water exits the soil profile. The delay function accommodates situations where the recharge from the soil zone to the aquifer is not instantaneous, i.e. 1 day or less. This same relationship is used to account for the delay in nitrate movement from the soil profile to the aquifers.
The nitrate in recharge to both aquifers on a given day is calculated:
3:1.9.1
where is the amount of nitrate in recharge entering the aquifers on day (kg N/ha), is the delay time or drainage time of the overlying geologic formations (days), is the total amount of nitrate exiting the bottom of the soil profile on day (kg N/ha), and is the amount of nitrate in recharge entering the aquifers on day (mm HO). The total amount of nitrate exiting the bottom of the soil profile on day is calculated using the percolation equation given in Chapter 4:2.
Nitrate in the shallow aquifer may be remain in the aquifer, move with recharge to the deep aquifer, move with groundwater flow into the main channel, or be transported out of the shallow aquifer with water moving into the soil zone in response to water deficiencies. The amount of nitrate in the shallow aquifer after all these processes are taken into account is:
3:1.9.2
while the amount of nitrate lost in groundwater flow is
3:1.9.3
the amount of nitrate lost in revap to the soil profile is
3:1.9.4
and the amount of nitrate transported to the deep aquifer is
3:1.9.5
where is the amount of nitrate in the shallow aquifer at the end of day (kg N/ha), is the amount of nitrate in the shallow aquifer at the end of day (kg N/ha), is the amount of nitrate in recharge entering the aquifers on day (kg N/ha), is the amount of nitrate in groundwater flow from the shallow aquifer on day (kg N/ha), is the amount of nitrate in revap to the soil profile from the shallow aquifer on day (kg N/ha), is the amount of nitrate in recharge entering the deep aquifer on day (kg N/ha), is the amount of water stored in the shallow aquifer at the end of day (mm HO), is the amount of recharge entering the aquifers on day (mm HO), is the groundwater flow, or base flow, into the main channel on day (mm HO), is the amount of water moving into the soil zone in response to water deficiencies on day (mm HO), and is the amount of recharge entering the deep aquifer on day (mm HO).
Because nitrogen is a very reactive element, nitrate in the shallow aquifer may be lost due to uptake by bacteria present in the aquifer, chemical transformations driven by a change in redox potential of the aquifer, and other processes. To account for losses of nitrate due to biological and chemical processes, a half-life for nitrate in the aquifer may be defined that specifies the number of days required for a given nitrate concentration to be reduced by one-half. The half-life entered for nitrate in the shallow aquifer is a lumped parameter that includes the net effect of all reactions occurring in the aquifer.
Nitrate removal in the shallow aquifer is governed by first-order kinetics:
3:1.9.6
where is the amount of nitrate in the shallow aquifer at time (kg N/ha), is the initial amount of nitrate in the shallow aquifer (kg N/ha), is the rate constant for removal of nitrate in the shallow aquifer (1/day), and is the time elapsed since the initial nitrate amount was determined (days). The rate constant is related to the half-life as follows:
3:1.9.6
where is the half-life of nitrate in the shallow aquifer (days).
Table 3:1-5: SWAT+ input variables that pertain to nitrogen in the shallow aquifer.
Many studies have shown that after an application of soluble P fertilizer, solution P concentration decreases rapidly with time due to reaction with the soil. This initial “fast” reaction is followed by a much slower decrease in solution P that may continue for several years (Barrow and Shaw, 1975; Munns and Fox, 1976; Rajan and Fox, 1972; Sharpley, 1982). In order to account for the initial rapid decrease in solution P, SWAT+ assumes a rapid equilibrium exists between solution P and an “active” mineral pool. The subsequent slow reaction is simulated by the slow equilibrium assumed to exist between the “active” and “stable” mineral pools. The algorithms governing movement of inorganic phosphorus between these three pools are taken from Jones et al. (1984).
Equilibration between the solution and active mineral pool is governed by the phosphorus availability index. This index specifies the fraction of fertilizer P which is in solution after an incubation period, i.e. after the rapid reaction period.
A number of methods have been developed to measure the phosphorus availability index. Jones et al. (1984) recommends a method outlined by Sharpley et al. (1984) in which various amounts of phosphorus are added in solution to the soil as KHPO. The soil is wetted to field capacity and then dried slowly at 25°C. When dry, the soil is rewetted with deionized water. The soil is exposed to several wetting and drying cycles over a 6-month incubation period. At the end of the incubation period, solution phosphorus is determined by extraction with anion exchange resin.
The availability index is then calculated:
3:2.3.1
where is the phosphorus availability index, is the amount of phosphorus in solution after fertilization and incubation, is the amount of phosphorus in solution before fertilization, and is the amount of soluble fertilizer added to the sample.
The movement of phosphorus between the solution and active mineral pools is governed by the equilibration equations:
if 3:2.3.2
if 3:2.3.3
where is the amount of phosphorus transferred between the soluble and active mineral pool (kg P/ha), is the amount of phosphorus in solution (kg P/ha), is the amount of phosphorus in the active mineral pool (kg P/ha), and is the phosphorus availability index. When is positive, phosphorus is being transferred from solution to the active mineral pool. When is negative, phosphorus is being transferred from the active mineral pool to solution. Note that the rate of flow from the active mineral pool to solution is 1/10th the rate of flow from solution to the active mineral pool.
SWAT+ simulates slow phosphorus sorption by assuming the active mineral phosphorus pool is in slow equilibrium with the stable mineral phosphorus pool. At equilibrium, the stable mineral pool is 4 times the size of the active mineral pool.
When not in equilibrium, the movement of phosphorus between the active and stable mineral pools is governed by the equations:
if 3:2.3.4
if 3:2.3.5
where is the amount of phosphorus transferred between the active and stable mineral pools (kg P/ha), is the slow equilibration rate constant (0.0006 d), is the amount of phosphorus in the active mineral pool (kg P/ha), and is the amount of phosphorus in the stable mineral pool (kg P/ha). When is positive, phosphorus is being transferred from the active mineral pool to the stable mineral pool. When is negative, phosphorus is being transferred from the stable mineral pool to the active mineral pool. Note that the rate of flow from the stable mineral pool to the active mineral pool is 1/10th the rate of flow from the active mineral pool to the stable mineral pool.
Table 3:2-3: SWAT+ input variables that pertain to inorganic P sorption processes.
RCN
: Concentration of nitrogen in the rain (mg/L)
.bsn
rammo_sub
Atmospheric deposition of ammonium (mg/L) values for entire watershed
.atm
Rcn_sub
Atmospheric deposition of nitrate (mg/L) for entire watershed
.atm
The primary mechanism of phosphorus movement in the soil is by diffusion. Diffusion is the migration of ions over small distances (1-2 mm) in the soil solution in response to a concentration gradient. The concentration gradient is created when plant roots remove soluble phosphorus from soil solution, depleting solution P in the root zone.
Due to the low mobility of phosphorus, SWAT+ allows soluble P to leach only from the top 10 mm of soil into the first soil layer. The amount of solution P moving from the top 10 mm into the first soil layer is:
3:2.4.1
where is the amount of phosphorus moving from the top 10 mm into the first soil layer (kg P/ha), is the amount of phosphorus in solution in the top 10 mm (kg P/ha), is the amount of water percolating to the first soil layer from the top 10 mm on a given day (mm HO), is the bulk density of the top 10 mm (Mg/m) (assumed to be equivalent to bulk density of first soil layer), is the depth of the “surface” layer (10 mm), and is the phosphorus percolation coefficient (m/Mg). The phosphorus percolation coefficient is the ratio of the phosphorus concentration in the surface 10 mm of soil to the concentration of phosphorus in percolate.
Table 3:2-4: SWAT+ input variables that pertain to phosphorus leaching.
| Variable Name | Definition | Input File |
|---|---|---|
Groundwater flow entering the main channel from the shallow aquifer can contain soluble phosphorus. With SWAT+ the soluble phosphorus pool in the shallow aquifer is not directly modeled. However, a concentration of soluble phosphorus in the shallow aquifer and groundwater flow can be specified to account for loadings of phosphorus with groundwater. This concentration remains constant throughout the simulation period.
Table 3:2-5: SWAT+ input variables that pertain to phosphorus in groundwater.
| Variable Name | Definition | Input File |
|---|
Degradation is the conversion of a compound into less complex forms. A compound in the soil may degrade upon exposure to light (photo degradation), reaction with chemicals present in the soil (chemical degradation) or through use as a substrate for organisms (biodegradation).
The majority of pesticides in use today are organic compounds. Because organic compounds contain carbon, which is used by microbes in biological reactions to produce energy, organic pesticides may be susceptible to microbial degradation. In contrast, pesticides that are inorganic are not susceptible to microbial degradation. Examples of pesticides that will not degrade are lead arsenate, a metallic salt commonly applied in orchards before DDT was invented, and arsenic acid, a compound formerly used to defoliate cotton.
Pesticides vary in their susceptibility to degradation. Compounds with chain structures are easier to break apart than compounds containing aromatic rings or other complex structures. The susceptibility of a pesticide to degradation is quantified by the pesticide’s half-life.
The half-life for a pesticide defines the number of days required for a given pesticide concentration to be reduced by one-half. The soil half-life entered for a pesticide is a lumped parameter that includes the net effect of volatilization, photolysis, hydrolysis, biological degradation and chemical reactions in the soil. Because pesticide on foliage degrades more rapidly than pesticide in the soil, SWAT+ allows a different half-life to be defined for foliar degradation.
Pesticide degradation or removal in all soil layers is governed by first-order kinetics:
3:3.2.1
where is the amount of pesticide in the soil layer at time (kg pst/ha), is the initial amount of pesticide in the soil layer (kg pst/ha), is the rate constant for degradation or removal of the pesticide in soil (1/day), and is the time elapsed since the initial pesticide amount was determined (days). The rate constant is related to the soil half-life as follows:
3:3.2.2
where is the half-life of the pesticide in the soil (days).
The equation governing pesticide degradation on foliage is:
3:3.2.3
where is the amount of pesticide on the foliage at time (kg pst/ha), is the initial amount of pesticide on the foliage (kg pst/ha), is the rate constant for degradation or removal of the pesticide on foliage (1/day), and is the time elapsed since the initial pesticide amount was determined (days). The rate constant is related to the foliar half-life as follows:
3:3.2.4
where is the half-life of the pesticide on foliage (days).
Table 3:3-2: SWAT+ input variables that pertain to pesticide degradation.
| Variable Name | Definition | Input File |
|---|
: Initial soluble P concentration in soil layer (mg/kg or ppm)
: Initial humic organic phosphorus in soil layer (mg/kg or ppm)
: Phosphorus availability index
: Material in the residue pool for the top 10mm of soil (kg ha)
: Bulk density of the layer (Mg/m3)
| Variable Name | Definition | Input File |
|---|---|---|
| Variable Name | Definition | Input File |
|---|---|---|
CMN
: Rate coefficient for mineralization of the humus active organic nutrients
.bsn
RSDCO
: Rate coefficient for mineralization of the residue fresh organic nutrients
.bsn
RSDCO_PL
: Rate coefficient for mineralization of the residue fresh organic nutrients
crop.dat
GW_DELAY
: Delay time for aquifer recharge (days)
.gw
SHALLST_N
: Amount of nitrate in the shallow aquifer (kg N/ha)
.gw
HLIFE_NGW
: Half-life of nitrate in the shallow aquifer (days)
.gw
SOL_BD
: Bulk density of the layer (Mg/m)
.sol
PPERCO
: Phosphorus percolation coefficient (m/Mg)
.bsn
PSP
: Phosphorus availability index
.bsn
GWSOLP | Soluble phosphorus concentration in groundwater flow (mg P/L) | .gw |
Contamination of drinking water by pathogenic organisms is a major environmental concern. Similar to water pollution by excess nutrients, water pollution by microbial pathogens can also be caused by point and nonpoint sources. Point source water contamination normally results from a direct entry of wastewater from municipal or water treatment systems into a drinking water supply. Nonpoint sources of bacterial pollution can be difficult to identify as they can originate from animal production units, land application of different manure types, and wildlife.
Although there are many potential sources of pathogenic loadings to streams, agronomic practices that utilize animal manures contaminated with pathogenic or parasitic organisms appear to be the major source of nonpoint contamination in watersheds. In recent years, a concentration of animal feeding operations has occurred in the cattle, swine and poultry production industries. These operations generate substantial amounts of animal manure that are normally applied raw to relatively limited land areas. Even though animal manure can be considered a beneficial fertilizer and soil amendment, high rates of land applied raw manure increase the risk of surface or groundwater contamination, both from excess nutrients and pathogenic organisms such as Cryptosporidium, Salmonella, or Escherichia coli 0157:H7.
Fecal coliforms (generic forms of bacteria) have customarily been used as indicators of potential pathogen contamination for both monitoring and modeling purposes (Baudart et al., 2000; Hunter et al., 2000; Pasquarell and Boyer, 1995; Walker et al., 1990; Stoddard et al., 1998; Moore et al., 1988). However, recent studies have documented waterborne disease outbreaks caused by Cryptosporidium, Norwalk and hepatitis A viruses, and salmonella despite acceptably low levels of indicator bacteria (Field et al, 1996).
SWAT+ considers fecal coliform an indicator of pathogenic organism contamination. However, to account for the presence of serious pathogens that may follow different growth/die-off patterns, SWAT+ allows two species or strains of pathogens with distinctly different die-off/re-growth rates to be defined. The two-population modeling approach is used to account for the long-term impacts of persistent bacteria applied to soils, whose population density when initially applied may be insignificant compared to that of less persistent bacteria.
One or two bacteria populations may be introduced into an HRU through one of the three types of fertilizer applications reviewed in Chapter 6:1. When bacteria in manure are applied to an HRU, some fraction is intercepted by plant foliage with the remainder reaching the soil. SWAT+ monitors the two bacteria populations on foliage and in the top 10 mm of soil that interacts with surface runoff. Bacteria in the surface soil layer may be in solution or associated with the solid phase. Bacteria incorporated deeper into the soil through tillage or transport with percolating water is assumed to die.
Land use changes and the intensification of agricultural production have dramatically altered the flow of nutrients resulting in unprecedented transcontinental inter-watershed and intra-watershed transfers of nitrogen (N), phosphorus (P), and other nutrients with fertilizer, harvest product, and pollutant flow (Galloway et al., 2008). Nutrient cycling in soils plays a major role in the control of these flows. Carbon (C), N, and P cycling are intimately linked through soil, plant and microbial processes. These processes affect the level of inorganic N and P and the C:N and C:P ratios of SOM. To realistically represent these C, N, and P transfers in river-basin scale models such as the Soil Water Assessment Tool (SWAT+, Arnold et al., 1998). a comprehensive integration of the cycling of these nutrients through soil organic matter (SOM) is required.
Most conceptual and quantitative SOM cycling models compartmentalize soil C and N in pools with different, yet stable, turnover rates and C:N ratios (Paul et al., 2006, McGill et al., 1981; Parton et al., 1988; Verberne et al., 1990). Incubation experiments also suggest the existence of pools with varying turnover rates (e.g. Collins et al, 2000); however, Six et al. (2002) indicated after an extensive literature review that the success at matching measurable and modelable SOM pools has been minimal. Furthermore, the division of SOM in pools has been criticized on mathematical grounds, as continuous turnover rates distributions can be artificially represented by discrete pools (Bruun and Luxhoi, 2006). These criticisms do not deny the existence of pools but rather emphasize the difficulty in establishing generalized methods to measure or predict their size and turnover rate. This unpredictability can limit the applicability of multi-pool SOM sub-models if the parameterization for different agricultural soils, pasturelands, forestlands and organic soils is uncertain or requires intensive calibration.
In this chapter, we describe the one-pool SOM sub-model implemented in SWAT+. This sub-model is conceptually based on the model described in Kemanian and Stockle (2010), and was adapted to the SWAT+ algorithms and integrated to the cycling of N and P.
The previous versions of SWAT+ have separate pools for soil organic N (two pools, active and stable) and organic P (one pool) and do not include explicitly , , or pools. Nitrogen and P decompose separately, excepting the common effect of soil moisture and temperature on the actual decomposition rate and the indirect control of decomposition through and . The higher the ratios the lower the decomposition rate, but no immobilization of mineral N or P occurs. Of the N and P decomposed from residues, 20% is allocated to the active soil organic N and the soil organic P pools, respectively, and 80% is allocated to the nitrate () and P in the soil solution. The 20% allocated to the N and P organic pools is roughly similar to the humification of C described in the new sub-model.
In the new sub-model, mineralization of N from organic pools feeds the pool instead of the pool. This will possibly increase volatilization of ammonium because in SWAT the latter is tightly linked to nitrification. Since mineralization and immobilization are explicitly calculated, the fluctuations in mineral , should be more realistically simulated, which has obvious implications for transport and other processes across the watershed. Tillage accelerates SOM turnover and mixes layers according to the tillage depth. In the previous version tillage had some effects on the surface properties (residue cover) and mixing only involved two layers. No effect of tillage on the organic N or P decomposition rate was previously simulated. The new sub-model also enhances the capacity of SWAT+ to simulate the impact of tillage on nutrient cycling.
The sub-model described here pertains to soil processes at the hydrologic unit response level. The new sub-model has one pool for soil organic C, N, and P ( respectively, kg m), and separate pools for residue and manure C, N, and P( and , respectively, kg m). The pools are not separated in active and stable pools. Microbial activity on SOM, manure, and residues decomposes simultaneously the organic C, N, and P. Decomposition of residues may add to (mineralization) or subtract from (immobilization) the inorganic N and P pools, depending on the C:N and C:P ratio of the decomposing pools (, and , respectively) and those of the SOM or destiny pool (), and on the humification rate (h). The humification rate represents the fraction of C in the decomposing residues that are effectively incorporated in the pool, the reminder being respired as . The balance equations for each soil layer for the organic residue, manure, and soil pools are as follows.
Residue and manure pools (represented as R and M) gain mass through additions ( and for residue and manure, respectively) and lose mass from decomposition following first order kinetics:
3:5.1.1a
3:5.1.1b
3:5.1.1c
where is the combined effect of the soil factors temperature (), moisture (), and aeration (), (0.67) is a power regulating the multiplicative effect of the three environmental factors, and (0.05 day) and (0.025 day) are the optimum decomposition rate (day) for residues and manure, respectively. The addition of residues (or manures) from different sources are bulked with the existing pool and not tracked separately, with rates shown above assumed to apply to all sources. If these decomposition rates are made residue- or manure-specific, every time there is an addition of residues or manure the effective decomposition rates would have to be calculated as weighted averages of the rate of the already decomposing pools and that attributed to the newly added materials, with a weighting function that should change over time, or each pool tracked separately, both rather impractical propositions.
For the soil pools, the differential equations are as follows:
3:5.1.2a
3:5.1.2b
where and are the residue and manure humification rates (kg kg) and is the apparent organic matter decomposition rate (day). The humification rates depend on the current and a reference ():
3:5.1.3a
3:5.1.3b
3:5.1.4
Clay is the soil layer clay fraction (kg clay kg dry soil), is the soil layer bulk density (kg m), and is the soil layer thickness (m). The constant (default ) modulates the response of the humification the current . The maximum attainable residue humification is approximately 0.18 kg kg. The same humification is used for below and aboveground residues. The humification of C from manure was assumed to be 60% higher than that of fresh residues (approximately 0.29 kg kg). The reference or depends linearly on the soil layer clay fraction (Eq. 3:5.1.4) as proposed by Hassink and Whitmore (1997). When then the humification is 0 and no accumulation of above can occur (Kemanian and Stockle, 2010). In addition, this approach assumes a dependence of humification on the clay fraction, a dependence represented in many different ways in other models (e.g. Jenkinson, 1990; Bradbury et al., 1993). The control of and in Eq. [3.5.1.3] with implies a non-linear response of and to . It is likely that a better formulation is needed for these functional equations to apply in organic horizons, tropical soils, or soils with a high proportion of volcanic ashes.
The C:N ratio of the newly formed organic matter or ranges from 8.5 to 14. The and determine how high can be when there is no mineral N available that can be an N source for the soil microbes. This estimate of is reduced depending on the mineral N availability, as follows:
3:5.1.5
where is the mineral N in the layer (mg N kg soil in this equation). The first term within brackets represents the control of the residues and the second term represents the control of mineral N on so that the higher the ratio of the higher the resulting , and the higher the amount of the lower , with ranging from 8.5 to 14 kg C kg N in SOM. For manures, substitutes for and 55 substitutes for the constant 110. The ratio is derived from by assuming that the newly formed SOM will conserve the N:P ratio of the decomposing residue and manure. Thus, the C:N and C:P ratios of SOM are not constant but fluctuates according to these equations during the simulation.
Residues and manure may not supply sufficient N and P to satisfy the (Eq. 3:5.1.2b) and (Eq. 3:5.1.2c), in which case N and P will be mined from the inorganic soluble pools. If the inorganic pools cannot supply N and P for decomposition to proceed, then the decomposition rate of residue and manure is reduced. Therefore, lack of mineral N and P in solution may slow down decomposition. The net mineralization is obtained from:
3:5.1.6a
3:5.1.6b
where and are the net mineralization rates (kg m day) from decomposing residues (Eq. 3:5.1.6a) and manure (Eq. 3:5.1.6b), respectively, with negative values indicating immobilization and positive values net mineralization. The same equation applies for P with appropriate C:P ratios. The SOM decomposition rate () is calculated from:
3:5.1.7
The apparent turnover rate () is scaled down from an optimum of 4.5% yr for undisturbed soils ( = 0.000123 day so that × 365 = 0.045) based on environmental conditions and . The power modulates (default = 0.5) so that when is low, the turnover rate slows sharply. Substituting Eq. 3:5.1.7 for in Eq. 3:5.1.2a with = 0.5 renders a kinetics of order 3/2 for decomposition, as opposed to the typical first order kinetics commonly use in SOM decomposition models (see Kemanian and Stockle, 2009). Tillage can enhance through the factor . This factor is calculated independently for each soil layer and depends on the tillage tool mixing factor (, range 0 to 1) and the soil texture. The mixing factor and the tillage depth determine the fraction of the soil layer that is mixed by a tillage operation. The basal value is 1 and it is enhanced immediately after a tillage event based on the estimated cumulative (or ):
3:5.1.8
The factor () is reduced on a daily basis based on soil moisture to simulate soil settling. If > 1 and a tillage operation is executed, the corresponding has to be added to the current . This requires solving for by inverting Eq 3:5.1.6 before recalculating . Since Eq 3:5.1.6 is non-linear on the solution has to be obtained iteratively. In the SWAT+ code the solution for has been approximated by a functional equation to prevent recurrent iterations that can be computationally expensive. The SOM decomposition always causes net mineralization to be positive because humification is assumed to be zero. In actuality, the humification is not zero but since no explicit microbial pool is considered, the decomposition rate is an decomposition rate that represents the net loss of C from the SC and underestimates the true turnover rate of organic C, N, and P (Jenkinson and Parry, 1989).
HLIFE_S | pest.dat |
HLIFE_F | pest.dat |
Chick’s Law first order decay equation is used to determine the quantity of bacteria removed from the system through die-off and added to the system by regrowth. The equation for die-off/re-growth was taken from Reddy et al. (1981) as modified by Crane and Moore (1986) and later by Moore et al. (1989). The equation was modified in SWAT+ to include a user-defined minimum daily loss. Die-off/re-growth is modeled for the two bacteria populations on foliage, in the surface soil solution and sorbed to surface soil particles. The equations used to calculate daily bacteria levels in the different pools are:
3:4.2.1
3:4.2.2
3:4.2.3
3:4.2.4
3:4.2.5
3:4.2.6
where is the amount of less persistent bacteria present on foliage on day (#cfu/m), is the amount of less persistent bacteria present on foliage on day (#cfu/m), is the overall rate constant for die-off/re-growth of less persistent bacteria on foliage (1/day), is the minimum daily loss of less persistent bacteria (#cfu/m), is the amount of persistent bacteria present on foliage on day (#cfu/m), is the amount of persistent bacteria present on foliage on day (#cfu/m), is the overall rate constant for die-off/re-growth of persistent bacteria on foliage (1/day), is the minimum daily loss of persistent bacteria (#cfu/m), is the amount of less persistent bacteria present in soil solution on day (#cfu/m), is the amount of less persistent bacteria present in soil solution on day (#cfu/m), is the overall rate constant for die-off/re-growth of less persistent bacteria in soil solution (1/day), is the amount of persistent bacteria present in soil solution on day (#cfu/m), is the amount of persistent bacteria present in soil solution on day (#cfu/m), is the overall rate constant for die-off/re-growth of persistent bacteria in soil solution (1/day), is the amount of less persistent bacteria sorbed to the soil on day (#cfu/m), is the amount of less persistent bacteria sorbed to the soil on day (#cfu/m), is the overall rate constant for die-off/re-growth of less persistent bacteria sorbed to the soil (1/day), is the amount of persistent bacteria sorbed to the soil on day (#cfu/m), is the amount of persistent bacteria sorbed to the soil on day (#cfu/m), and is the overall rate constant for die-off/re-growth of persistent bacteria sorbed to the soil (1/day).
The overall rate constants define the net change in bacterial population for the different pools modeled. The impact of temperature effects on bacteria die-off/re-growth were accounted for using equations proposed by Mancini (1978). The user defines the die-off and growth factors for the two bacterial populations in the different pools at 20°C. The overall rate constants at 20°C are then calculated:
3:4.2.7
3:4.2.8
3:4.2.9
3:4.2.10
3:4.2.11
3:4.2.12
where is the overall rate constant for die-off/re-growth of less persistent bacteria on foliage at 20°C (1/day), is the rate constant for die-off of less persistent bacteria on foliage at 20°C (1/day), is the rate constant for re-growth of less persistent bacteria on foliage at 20°C (1/day), is the overall rate constant for die-off/re-growth of persistent bacteria on foliage at 20°C (1/day), is the rate constant for die-off of persistent bacteria on foliage at 20°C (1/day), is the rate constant for re-growth of persistent bacteria on foliage at 20°C (1/day), is the overall rate constant for die-off/re-growth of less persistent bacteria in soil solution at 20°C (1/day), is the rate constant for die-off of less persistent bacteria in soil solution at 20°C (1/day), is the rate constant for re-growth of less persistent bacteria in soil solution at 20°C (1/day), is the overall rate constant for die-off/re-growth of persistent bacteria in soil solution at 20°C (1/day), is the rate constant for die-off of persistent bacteria in soil solution at 20°C (1/day), is the rate constant for re-growth of persistent bacteria in soil solution at 20°C (1/day), is the overall rate constant for die-off/re-growth of less persistent bacteria attached to soil particles at 20°C (1/day), is the rate constant for die-off of less persistent bacteria attached to soil particles at 20°C (1/day), is the rate constant for re-growth of less persistent bacteria attached to soil particles at 20°C (1/day), is the overall rate constant for die-off/re-growth of persistent bacteria attached to soil particles at 20°C (1/day), is the rate constant for die-off of persistent bacteria attached to soil particles at 20°C (1/day), and is the rate constant for re-growth of persistent bacteria attached to soil particles at 20°C (1/day).
The overall rate constants are adjusted for temperature using the equations:
3:4.2.13
3:4.2.14
3:4.2.15
3:4.2.16
3:4.2.17
3:4.2.18
where is the temperature adjustment factor for bacteria die-off/re-growth, is the mean daily air temperature, and all other terms are as previously defined.
Table 3:4-2: SWAT+ input variables that pertain to bacteria die-off/re-growth.
One of the primary purposes of tillage and harvesting practices in early farming systems was to remove as much plant residue from the field as possible so that pests had no food source to sustain them until the next growing season. As research linked erosion to lack of soil cover, farmers began to perform fewer tillage operations and altered harvesting methods to leave more residue. As mechanical methods of pest control were minimized or eliminated, chemical methods of pest control began to assume a key role in the management of unwanted organisms.
Pesticides are toxic by design, and there is a natural concern about the impact of their presence in the environment on human health and environmental quality. The fate and transport of a pesticide are governed by properties such as solubility in water, volatility and ease of degradation. The algorithms in SWAT+ used to model pesticide movement and fate are adapted from GLEAMS (Leonard et al., 1987).
Pesticide may be aerially applied to an HRU with some fraction intercepted by plant foliage and some fraction reaching the soil. Pesticide may also be incorporated into the soil through tillage. SWAT+ monitors pesticide amounts on foliage and in all soil layers. Figure 3:3-1 shows the potential pathways and processes simulated in SWAT+.
A portion of the pesticide on plant foliage may be washed off during rain events. The fraction washed off is a function of plant morphology, pesticide solubility, and the timing and intensity of the rainfall event. Wash-off will occur when the amount of precipitation on a given day exceeds 2.54 mm.
The amount of pesticide washing off plant foliage during a precipitation event on a given day is calculated:
3:3.1.1
where is the amount of pesticide on foliage that is washed off the plant and onto the soil surface on a given day (kg pst/ha), is the wash-off fraction for the pesticide, and is the amount of pesticide on the foliage (kg pst/ha). The wash-off fraction represents the portion of the pesticide on the foliage that is dislodgable.
Table 3:3-1: SWAT+ input variables that pertain to pesticide wash-off.
| Variable Name | Definition | Input File |
|---|---|---|
Bacteria can be transported with percolation into the soil profile. Only bacteria present in the soil solution is susceptible to leaching. Bacteria removed from the surface soil layer by leaching are assumed to die in the deeper soil layers.
The amount of bacteria transported from the top 10 mm into the first soil layer is:
3:4.3.1
3:4.3.2
where is the amount of less persistent bacteria transported from the top 10 mm into the first soil layer (#cfu/m), is the amount of less persistent bacteria present in soil solution (#cfu/m), is the amount of water percolating to the first soil layer from the top 10 mm on a given day (mm HO), is the bulk density of the top 10 mm (Mg/m) (assumed to be equivalent to bulk density of first soil layer), is the depth of the “surface” layer (10 mm), is the bacteria percolation coefficient (10 m/Mg), is the amount of persistent bacteria transported from the top 10 mm into the first soil layer (#cfu/m), and is the amount of persistent bacteria present in soil solution (#cfu/m).
Table 3:4-3: SWAT+ input variables that pertain to bacteria transport in percolate.
| Variable Name | Definition | Input File |
|---|---|---|
A portion of the bacteria on plant foliage may be washed off during rain events. The fraction washed off is a function of plant morphology, bacteria characteristics, and the timing and intensity of the rainfall event. Wash-off will occur when the amount of precipitation on a given day exceeds 2.54 mm.
The amount of bacteria washing off plant foliage during a precipitation event on a given day is calculated:
3:4.1.1
3:4.1.2
where is the amount of less persistent bacteria on foliage that is washed off the plant and onto the soil surface on a given day (# cfu/m), is the amount of persistent bacteria on foliage that is washed off the plant and onto the soil surface on a given day (# cfu/m), is the wash-off fraction for the less persistent bacteria, is the wash-off fraction for the persistent bacteria, is the amount of less persistent bacteria attached to the foliage (# cfu/m), and is the amount of persistent bacteria attached to the foliage (# cfu/m). The wash-off fraction represents the portion of the bacteria on the foliage that is dislodgable.
Bacteria that washes off the foliage is assumed to remain in solution in the soil surface layer.
Table 3:4-1: SWAT+ input variables that pertain to bacteria wash-off.
| Variable Name | Definition | Input File |
|---|---|---|
: Half-life of the pesticide in the soil (days)
: Half-life of the pesticide on foliage (days)
| Variable Name | Definition | Input File |
|---|---|---|
WOF
: Wash-off fraction for the pesticide
pest.dat
WDPQ
: Die-off factor for persistent bacteria in soil solution at 20°C (1/day)
.bsn
WGPQ
: Growth factor for persistent bacteria in soil solution at 20°C (1/day)
.bsn
WDLPQ
: Die-off factor for less persistent bacteria in soil solution at 20°C (1/day)
.bsn
WGLPQ
: Growth factor for less persistent bacteria in soil solution at 20°C (1/day)
.bsn
WDPS
: Die-off factor for persistent bacteria adsorbed to soil particles at 20°C (1/day)
.bsn
WGPS
: Growth factor for persistent bacteria adsorbed to soil particles at 20°C (1/day)
.bsn
WDLPS
: Die-off factor for less persistent bacteria adsorbed to soil particles at 20°C (1/day)
.bsn
WGLPS
: Growth factor for less persistent bacteria adsorbed to soil particles at 20°C (1/day)
.bsn
WDPF
: Die-off factor for persistent bacteria on foliage at 20°C (1/day)
.bsn
WGPF
: Growth factor for persistent bacteria on foliage at 20°C (1/day)
.bsn
WDLPF
: Die-off factor for less persistent bacteria on foliage at 20°C (1/day)
.bsn
WGLPF
: Growth factor for less persistent bacteria on foliage at 20°C (1/day)
.bsn
THBACT
: Temperature adjustment factor for bacteria die-off/growth
.bsn
BACTMINLP
: Minimum daily loss of less persistent bacteria (# cfu/m)
.bsn
BACTMINP
: Minimum daily loss of persistent bacteria (# cfu/m)
.bsn
SOL_BD
: Bulk density of the layer (Mg/m)
.sol
BACTMIX
: Bacteria percolation coefficient (10 m/Mg)
.bsn
WOF_P
: Wash-off fraction for persistent bacteria
.bsn
WOF_LP
: Wash-off fraction for less persistent bacteria
.bsn
The balanced equation for in a single layer (Eq. [3:5.1.2a]) can be combined with Eq. [3:5.1.3a] and Eq. [3:5.1.7] and with a few assumptions allow for an analytical solution to the differential equation. The soil clay content and the C input rate were assumed to be constant and the powers and set to 1, so that the balance equation can be solved explicitly for . The time step was considered to be a year and we assumed that residues and manure fully decompose in that time frame so that . Since the influence of residues and manure on the balance is similar we assumed that C inputs are only through residues. With these substitutions Eq. [3:5.1.2a] becomes:
3:5.3.1
The constant k substitutes for . This differential equation can be solved analytically, with integration rendering the following solution:
3:5.3.2
The integration constant depends on the initial . The steady state solution for Eq. 3:5.3.2 is:
3:5.3.3
The ratio is the equilibrium that would be obtained if neither nor had a dependence on . As increases, the value of the fraction will get smaller. Therefore, the squared root term in Eq. 3:5.3.3 can be approximated as by preserving just the first two terms of the binomial expansion, from which Eq. 3:5.3.4 can be re-written as:
3:5.3.4
Therefore, as increases approaches asymptotically (Figure 1). Taking as a reference a soil layer with = 25 Mg C ha, = 0.2, and , it can be seen in Figure 1 that doubling and have a similar effect but of opposite sign such that the equilibrium increases with increasing and decreases with increasing . In both cases the increase and the decrease in are less than proportional to the increase in these two parameters. The equilibrium , however, is very sensitive to changes in , which makes this variable critical for a correct representation of dynamics. This formulation is a mathematical representation of the concept of saturation (Hassink and Whitmore, 1997; Six et al., 2002), enhanced with a control of the decomposition rate by .
The transient trajectory of is controlled by the quotient of the two exponential terms in Eq. [3:5.3.5].
[3.5.3.5]
For a given and initial , increasing the inputs () changes the steady state with decreasing marginal increments as approaches , yet the steady state condition is approached faster with higher inputs (Figure 3:5-1). For a given , changing has a substantial impact on the rate of change of when the inputs are medium to high (Figure 3:5-1) but a minor effect if inputs are too low. This formulation strongly suggests that soils with higher carbon storage capacity (higher ) that are currently depleted of should be the primary targets for storing , or that soils with low may store carbon quickly for a few years but the rate of gains will decrease earlier than in soils with higher .
The conditions for which the can be modeled analytically as shown here are very restrictive. The numerical solution implemented in the model is more flexible as the constants and are allowed to differ from 1. The model can be expanded to accommodate saturation of different SOM pools, instead of just one uniform pool, as strongly suggested by the results and analysis of Stewart et al. (2008). Yet, this will require a level of parameterization for which we consider there is simply not sufficient information for a realistic implementation in numerical models.
Figure 3:5-1. Equilibrium soil organic carbon (SC, Mg C ha) for the steady state condition (Eq. [3:5.3.3]) with different values for humification (, kg kg), SOM apparent turnover rate (, yr), and saturation soil organic carbon (, Mg C ha). The line without a symbol in both panels was arbitrarily chosen as a reference. The linear, no asymptotic line in Panel A shows the equilibrium for the case in which and do not depend on so that at equilibrium = , where is the residue carbon input rate (Mg C ha yr). Panel A shows the equilibrium when is doubled and Panel B shows the equilibrium when or is doubled.
