The first point on the stomatal conductance curve is comprised of a vapor pressure deficit of 1 kPa and a fraction of maximum stomatal conductance equal to 1.00.

As with radiation-use efficiency, stomatal conductance is sensitive to vapor pressure deficit. Stockle et al. (1992) compiled a short list of stomatal conductance response to vapor pressure deficit for a few plant species. Due to the paucity of data, default values for the second point on the stomatal conductance vs. vapor pressure deficit curve are used for all plant species in the database.

References

Stockle et al. (1992)

This variable pertains to perennials and trees only. It is not used for other types of plants.

Please see the explanation given for parameter to obtain additional information about this parameter and methods used to measure it.

This variable pertains to trees only. It is not used for other types of plants. The maximum biomass for a mature forest stand generally falls in the range of 30-50 metric tons/ha.

The wash-off fraction is a function of the nature of the leaf surface, plant morphology, pesticide solubility, polarity of the pesticide molecule, formulation of the commercial product and timing and volume of the rainfall event.

The BOD for a conventional system is typically 170 mg/L. The value varies greatly for different types of septic systems (see Table A-1 of Siegrist et al. (2005)).

References

Siegrist et al. (2005)

The nitrogen fixation coefficient in the SWAT+ plant database is 0.5 for legumes and 0.0 for non-legumes.

Fall-planted land covers will go dormant when daylength is less than the threshold daylength.

The PHU program was incorporated directly into SWAT+. The heat units to maturity were changed to days to maturity (days_mat). The concept of heat units to maturity was developed for annual crops and we use heat units for the entire growing season for native perennials and native annuals. By inputting days to maturity, we can include different crop varieties as defined by length of growing season (e.g., 120-, 110-, 100- and 90-day varieties for corn). The heat units to maturity calculation in the model first computes base zero heat units for the entire year and assumes a planting date when heat units exceed 0.15 * base zero. Then, the model calculates heat units from planting date through the days to maturity using the crop's base temperature as specified by tmp_base. If the maximum days for a crop are input, e.g., 120 days for corn, and the growing season is less than 120 days, the model essentially sums heat units for the entire growing season which represents (and estimates) the maximum days to maturity.

The algorithm currently uses monthly weather generator parameters but could be modified to alternatively use daily temperature inputs. The model provides heat unit estimates in both the northern and southern hemispheres.

There are several advantages to incorporating the heat unit program into SWAT+ including:

1. It eliminates the need for running an external program when developing inputs,

2. allows input of a commonly understood variable (days) instead of a variable that is not commonly known at every location (heat units),

3. allows the model to calculate heat units for native perennials and annuals that are location dependent,

4. a database (plants.plt) can be maintained and supported that includes different crop varieties, and

5. by inputting the maximum growing season for a crop, the model will calculate appropriate heat units for that crop anywhere in the northern or southern hemisphere.

Please see the explanation given for parameter lai_pot to obtain additional information about this parameter and methods used to measure it.

The harvest index defines the fraction of the aboveground biomass that is removed in a harvest operation. This value defines the fraction of plant biomass that is “lost” from the system and unavailable for conversion to residue and subsequent decomposition. For crops where the harvested portion of the plant is aboveground, the harvest index is always a fraction less than 1. For crops where the harvested portion is belowground, the harvest index may be greater than 1. Two harvest indices are provided in the database, the harvest index for optimal growing conditions and the harvest index under highly stressed growing conditions (harv_idx_ws).

To determine the harvest index, the plant biomass removed during the harvest operation is dried at least 2 days at 65°C and weighed. The total aboveground plant biomass in the field should also be dried and weighed. The harvest index is then calculated by dividing the weight of the harvested portion of the plant biomass by the weight of the total aboveground plant biomass. Plants will need to be grown in two different plots where optimal climatic conditions and stressed conditions are produced to obtain values for both harvest indices.

There are several databases included in SWAT+:

• Plants/land cover: plants.plt

• Urban land use: urban.urb

• Tillage:

• Fertilizer and manure:

• Pesticides:

• Septic systems:

The name of the plant/landcover is a primary key referenced by plt_name in plant.ini. All names in the plants.plt database must be unique.

The names in the plant database are also used by QSWAT+ to link the grid codes in land use/land cover maps to SWAT+ land use types.

Please see the explanation given for parameter lai_pot to obtain additional information about this parameter and methods used to measure it.

Please see the explanation given for parameter lai_pot to obtain additional information about this parameter and methods used to measure it.

Please see the explanation given for parameter lai_pot to obtain additional information about this parameter and methods used to measure it.

Please see the explanation given for parameter lai_pot to obtain additional information about this parameter and methods used to measure it.

In addition to the amount of plant biomass removed in the yield, SWAT+ needs to know the amount of nitrogen and phosphorus removed in the yield. The harvested portion of the plant biomass is sent to a testing laboratory to determine the fraction of nitrogen and phosphorus in the biomass.

This value is estimated on a dry weight basis.

Maximum canopy height is a straightforward measurement. The canopy height of non-stressed plants should be recorded at intervals throughout the growing season. The maximum value recorded is used in the database.

To determine maximum rooting depth, plant samples need to be grown on soils without an impermeable layer. Once the plants have reached maturity, soil cores are taken for the entire depth of the soil. Each 0.25-meter increment is washed and the live plant material collected. Live roots can be differentiated from dead roots by the fact that live roots are whiter and more elastic and have an intact cortex. The deepest increment of the soil core in which live roots are found defines the maximum rooting depth.

In addition to the amount of plant biomass removed in the yield, SWAT+ needs to know the amount of nitrogen and phosphorus removed in the yield. The harvested portion of the plant biomass is sent to a testing laboratory to determine the fraction of nitrogen and phosphorus in the biomass.

This value is estimated on a dry weight basis.

The biomass-energy ration or radiation-use efficiency (RUE) is the amount of dry biomass produced per unit intercepted solar radiation. It is assumed to be independent of the plant’s growth stage. The variable bm_e represents the potential or unstressed growth rate (including roots) per unit of intercepted photosynthetically active radiation.

The following overview of the methodology used to measure RUE was summarized from Kiniry et al. (1998) and Kiniry et al. (1999).

To calculate RUE, the amount of photosynthetically active radiation (PAR) intercepted and the mass of aboveground biomass is measured several times throughout a plant’s growing season. The frequency of the measurements taken will vary, but in general 4 to 7 measurements per growing season are considered to be adequate. As with leaf area determinations, the measurements should be performed on non-stressed plants. Intercepted radiation is measured with a light meter. Whole spectrum and PAR sensors are available and calculations of RUE will be performed differently depending on the sensor used. A brief discussion of the difference between whole spectrum and PAR sensors and the difference in calculations is given in Kiniry (1999). The use of a PAR sensor in RUE studies is strongly encouraged.

When measuring radiation, three to five sets of measurements are taken rapidly for each plant plot. A set of measurements consists of 10 measurements above the leaf canopy, 10 below, and 10 more above. The light measurements should be taken between 10:00 am and 2:00 pm local time. The measurements above and below the leaf canopy are averaged and the fraction of intercepted PAR is calculated for the day from the two values. Daily estimates of the fraction of intercepted PAR are determined by linearly interpolating the measured values. The fraction of intercepted PAR is converted to an amount of intercepted PAR using daily values of incident total solar radiation measured with a standard weather station. To convert total incident radiation to total incident PAR, the daily solar radiation values are multiplied by the percent of total radiation that has a wavelength between 400 and 700 mm. This percent usually falls in the range 45 to 55% and is a function of cloud cover. 50% is considered to be a default value. Once daily intercepted PAR values are determined, the total amount of PAR intercepted by the plant is calculated for each date on which biomass was harvested. This is calculated by summing daily intercepted PAR values from the date of seedling emergence to the date of biomass harvest.

To determine biomass production, aboveground biomass is harvested from a known area of land within the plot. The plant material should be dried at least 2 days at 65°C and then weighed.

RUE is determined by fitting a linear regression for aboveground biomass as a function of intercepted PAR. The slope of the line is the RUE. The figure below shows the plots of aboveground biomass and summed intercepted photosynthetically active radiation for Eastern gamagrass. Note that the units for RUE values in the graph, as well as values typically reported in literature, are different from those used by SWAT+. To obtain the value used in SWAT+, multiply by 10.

References

Kiniry et al. (1998)

Kiniry (1999)

Kiniry et al. (1999)

The variable lai_pot is one of six parameters used to quantify leaf area development of a plant species during the growing season. The figure below illustrates the relationship of the database parameters to the leaf area development modeled by SWAT+.

The values for lai_pot in the plant growth database are based on average plant densities in dryland (rainfed) agriculture. The parameter may need to be adjusted for drought-prone regions where planting densities are much smaller or irrigated conditions where densities are much greater.

To identify the leaf area development parameters, record the leaf area index and number of accumulated heat units for the plant species throughout the growing season and then plot the results. For best results, several years worth of field data should be collected. At the very minimum, data for two years is recommended. It is important that the plants undergo no water or nutrient stress during the years in which data is collected.

The leaf area index incorporates information about the plant density, so field experiments should either be set up to reproduce actual plant densities or the maximum LAI value for the plant determined from field experiments should be adjusted to reflect plant densities desired in the simulation. Maximum LAI values in the default database correspond to plant densities associated with rainfed agriculture.

The leaf area index is calculated by dividing the green leaf area by the land area. Because the entire plant must be harvested to determine the leaf area, the field experiment needs to be designed to include enough plants to accommodate all leaf area measurements made during the year.

Although measuring leaf area can be laborious for large samples, there is no intrinsic difficulty in the process. The most common method is to obtain an electronic scanner and feed the harvested green leaves and stems into the scanner. Older methods for estimating leaf area include tracing of the leaves (or weighed subsamples) onto paper, the use of planimeters, the punch disk method of Watson (1958) and the linear dimension method of Duncan and Hesketh (1968).

Chapter 5:1 in the Theoretical Documentation reviews the methodology used to calculate accumulated heat units for a plant at different times of the year as well as determination of the fraction of total, or potential, heat units that is required for the plant database.

References

Watson (1958)

Duncan and Hesketh (1968)

SWAT+ uses the base temperature to calculate the number of heat units accrued every day. The minimum or base temperature for plant growth varies with growth stage of the plant. However, this variation is ignored by the model - SWAT+ uses the same base temperature throughout the growing season.

Base temperature is measured by growing plants in growth chambers at several different temperatures. The rate of leaf tip appearance as a function of temperature is plotted. Extrapolating the line to the leaf tip appearance rate of 0.0 leaves/day gives the base or minimum temperature for plant growth. The figure below plots data for corn. Note that the line intersects the x-axis at 8°C.

The minimum C factor can be estimated from a known average annual C factor using the following equation (Arnold and Williams, 1995):

$C_{USLE,mn} = 1.463 * ln⁡[C_{USLE,aa}] + 0.1034$

where $C_{USLE,mn}$ is the minimum C factor for the land cover and $C_{USLE,aa}$ is the average annual C factor for the land cover.

References

Arnold and Williams (1995)

The value between 0.0 and harv_idx that represents the lowest harvest index expected due to water stress.

The harvest index defines the fraction of the aboveground biomass that is removed in a harvest operation. This value defines the fraction of plant biomass that is “lost” from the system and unavailable for conversion to residue and subsequent decomposition. For crops where the harvested portion of the plant is aboveground, the harvest index is always a fraction less than 1. For crops where the harvested portion is belowground, the harvest index may be greater than 1. Two harvest indices are provided in the database, the harvest index for optimal growing conditions (harv_idx) and the harvest index under highly stressed growing conditions.

To determine the harvest index, the plant biomass removed during the harvest operation is dried at least 2 days at 65°C and weighed. The total aboveground plant biomass in the field should also be dried and weighed. The harvest index is then calculated by dividing the weight of the harvested portion of the plant biomass by the weight of the total aboveground plant biomass. Plants will need to be grown in two different plots where optimal climatic conditions and stressed conditions are produced to obtain values for both harvest indices.

In order to calculate the plant nutrient demand throughout a plant’s growing cycle, SWAT+ needs to know the fraction of nutrient in the total plant biomass (on a dry weight basis) at different stages of crop growth. Six variables in the plant database provide this information: frac_n_em, frac_n_50, frac_n_mat, frac_p_em, frac_p_50, and frac_p_mat. Plant samples are analyzed for nitrogen and phosphorus content at three times during the growing season: shortly after emergence, near the middle of the season, and at maturity. Ideally, the plant samples tested for nutrient content should include the roots as well as the aboveground biomass. Differences in partitioning of nutrients to roots and shoots can cause erroneous conclusions when comparing productivity among species if only the aboveground biomass is measured.

In order to calculate the plant nutrient demand throughout a plant’s growing cycle, SWAT+ needs to know the fraction of nutrient in the total plant biomass (on a dry weight basis) at different stages of crop growth. Six variables in the plant database provide this information: frac_n_em, frac_n_50, frac_n_mat, frac_p_em, frac_p_50, and frac_p_mat. Plant samples are analyzed for nitrogen and phosphorus content at three times during the growing season: shortly after emergence, near the middle of the season, and at maturity. Ideally, the plant samples tested for nutrient content should include the roots as well as the aboveground biomass. Differences in partitioning of nutrients to roots and shoots can cause erroneous conclusions when comparing productivity among species if only the aboveground biomass is measured.

In order to calculate the plant nutrient demand throughout a plant’s growing cycle, SWAT+ needs to know the fraction of nutrient in the total plant biomass (on a dry weight basis) at different stages of crop growth. Six variables in the plant database provide this information: frac_n_em, frac_n_50, frac_n_mat, frac_p_em, frac_p_50, and frac_p_mat. Plant samples are analyzed for nitrogen and phosphorus content at three times during the growing season: shortly after emergence, near the middle of the season, and at maturity. Ideally, the plant samples tested for nutrient content should include the roots as well as the aboveground biomass. Differences in partitioning of nutrients to roots and shoots can cause erroneous conclusions when comparing productivity among species if only the aboveground biomass is measured.

In order to calculate the plant nutrient demand throughout a plant’s growing cycle, SWAT+ needs to know the fraction of nutrient in the total plant biomass (on a dry weight basis) at different stages of crop growth. Six variables in the plant database provide this information: frac_n_em, frac_n_50, frac_n_mat, frac_p_em, frac_p_50, and frac_p_mat. Plant samples are analyzed for nitrogen and phosphorus content at three times during the growing season: shortly after emergence, near the middle of the season, and at maturity. Ideally, the plant samples tested for nutrient content should include the roots as well as the aboveground biomass. Differences in partitioning of nutrients to roots and shoots can cause erroneous conclusions when comparing productivity among species if only the aboveground biomass is measured.

Both optimal and base temperatures are very stable for cultivars within a species.

Optimal temperature for plant growth is difficult to measure directly. Looking at the figure below, one might be tempted to select the temperature corresponding to the peak of the plot as the optimal temperature. This would not be correct. The peak of the plot defines the optimal temperature for leaf development—not for plant growth.

If an optimal temperature cannot be obtained through a review of literature, use the optimal temperature listed for a plant already in the database with similar growth habits.

Review of temperatures for many different plants have provided generic values for base and optimal temperatures as a function of growing season. In situations, where temperature information is unavailable, these values may be used. For warm season plants, the generic base temperature is ~8ºC and the generic optimal temperature is ~25ºC. For cool season plants, the generic base temperature is ~0ºC and the generic optimal temperature is ~13ºC.

The 1st point on the radiation use efficiency curve is comprised of the ambient CO2 concentration, 330 μL CO2/L air, and the biomass-energy ratio reported for bm_e.

In order to assess the impact of climate change on agricultural productivity, SWAT+ incorporates equations that adjust RUE for elevated atmospheric CO2 concentrations. Values must be entered for co2_hi and bm_e_hi in the plant database whether or not the user plans to simulate climate change.

To obtain radiation-use efficiency values at elevated CO2 levels for plant species not currently in the database, plants should be established in growth chambers set up in the field or laboratory where CO2 levels can be controlled. RUE values are determined using the same methodology described in the explanation of .

In order to calculate the plant nutrient demand throughout a plant’s growing cycle, SWAT+ needs to know the fraction of nutrient in the total plant biomass (on a dry weight basis) at different stages of crop growth. Six variables in the plant database provide this information: , , , frac_p_em, , and . Plant samples are analyzed for nitrogen and phosphorus content at three times during the growing season: shortly after emergence, near the middle of the season, and at maturity. Ideally, the plant samples tested for nutrient content should include the roots as well as the aboveground biomass. Differences in partitioning of nutrients to roots and shoots can cause erroneous conclusions when comparing productivity among species if only the aboveground biomass is measured.

In order to calculate the plant nutrient demand throughout a plant’s growing cycle, SWAT+ needs to know the fraction of nutrient in the total plant biomass (on a dry weight basis) at different stages of crop growth. Six variables in the plant database provide this information: , , , , frac_p_50, and . Plant samples are analyzed for nitrogen and phosphorus content at three times during the growing season: shortly after emergence, near the middle of the season, and at maturity. Ideally, the plant samples tested for nutrient content should include the roots as well as the aboveground biomass. Differences in partitioning of nutrients to roots and shoots can cause erroneous conclusions when comparing productivity among species if only the aboveground biomass is measured.

This variable pertains to trees only. It is not used for other types of plants. It governs the amount of biomass that falls off the tree and is converted to residue when the plant goes dormant in the winter.

This variable pertains to trees only. It is not used for other types of plants.

Stockle and Kiniry (1990) first noticed a relationship between RUE and vapor pressure deficit and were able to explain a large portion of within-species variability in RUE values for sorghum and corn by plotting RUE values as a function of average daily vapor pressure deficit values. Since this first article, a number of other studies have been conducted that support the dependence of RUE on vapor pressure deficit. However, there is still some debate in the scientific community on the validity of this relationship. If the user does not wish to simulate a change in RUE with vapor pressure deficit, the variable ru_vpd can be set to 0.0 for the plant.

To define the impact of vapor pressure deficit on RUE, vapor pressure deficit values must be recorded during the growing seasons that RUE determinations are being made. It is important that the plants are exposed to no other stress than vapor pressure deficit, i.e. plant growth should not be limited by lack of soil water and nutrients.

Vapor pressure deficits can be calculated from relative humidity (see Chapter 1:2 in Theoretical Documentation) or from daily maximum and minimum temperatures using the technique of Diaz and Campbell (1988) as described by Stockle and Kiniry (1990). The change in RUE with vapor pressure deficit is determined by fitting a linear regression for RUE as a function of vapor pressure deficit. The figure below shows a plot of RUE as a function of vapor pressure deficit for grain sorghum.

From the figure, the rate of decline in radiation-use efficiency per unit increase in vapor pressure deficit, Δruedcl, for sorghum is 8.4x10-1 g*MJ-1*kPa-1. When RUE is adjusted for vapor pressure deficit, the model assumes the RUE value reported for is the radiation-use efficiency at a vapor pressure deficit of 1 kPa.

References

Campbell (1988)

Stockle & Kiniry (1990)

This coefficient is used to calculate the amount of intercepted photosynthetically active radiation.

Differences in canopy structure for a species are described by the number of leaves present (leaf area index) and the leaf orientation. Leaf orientation has a significant impact on light interception and consequently on radiation-use efficiency. More erect leaf types spread the incoming light over a greater leaf area, decreasing the average light intensity intercepted by individual leaves (see figure below). A reduction in light intensity interception by an individual leaf favors a more complete conversion of total canopy-intercepted light energy into biomass.

Using the light extinction coefficient value (kℓ) in the Beer-Lambert formula to quantify efficiency of light interception per unit leaf area index, more erect leaf types have a smaller kℓ.

To calculate the light extinction coefficient, the amount of photosynthetically active radiation (PAR) intercepted and the mass of aboveground biomass (LAI) is measured several times throughout a plant’s growing season using the methodology described in the previous sections. The light extinction coefficient is then calculated using the Beer-Lambert equation:

The first point on the stomatal conductance curve is comprised of a vapor pressure deficit of 1 kPa and a fraction of maximum stomatal conductance equal to 1.00.

As with radiation-use efficiency, stomatal conductance is sensitive to vapor pressure deficit. Stockle et al. (1992) compiled a short list of stomatal conductance response to vapor pressure deficit for a few plant species. Due to the paucity of data, default values for the second point on the stomatal conductance vs. vapor pressure deficit curve are used for all plant species in the database.

The plant residue decomposition coefficient is the fraction of residue that will decompose in a day assuming optimal moisture, temperature, C:N ratio, and C:P ratio.

The 1st point on the radiation use efficiency curve is comprised of the ambient CO2 concentration, 330 μL CO2/L air, and the biomass-energy ratio reported for bm_e.

Please read the explanation for parameters co2_hi and bm_e to obtain additional information about this parameter and methods used to measure it.

Stomatal conductance of water vapor is used in the Penman-Monteith calculations of maximum plant evapotranspiration. The plant database contains three variables pertaining to stomatal conductance that are required only if the Penman-Monteith equation is used to model evapotranspiration: maximum stomatal conductance and two variables that define the impact of vapor pressure deficit on stomatal conductance (frac_stcon, vpd).

Körner et al. (1979) defines maximum leaf diffusive conductance as the largest value of conductance observed in fully developed leaves of well-watered plants under optimal climatic conditions, natural outdoor CO2 concentrations and sufficient nutrient supply. Leaf diffusive conductance of water vapor cannot be measured directly but can be calculated from measurements of transpiration under known climatic conditions. Various different methods are used to determine diffusive conductance: transpiration measurements in photosynthesis cuvettes, energy balance measurements or weighing experiments, ventilated diffusion porometers, and non-ventilated porometers. Körner (1977) measured diffusive conductance using a ventilated diffusion porometer.

To obtain maximum leaf conductance values, leaf conductance is determined between sunrise and late morning until a clear decline or no further increase is observed. Depending on phenology, measurements are taken on at least three bright days in late spring and summer, preferably just after a rainy period. The means of maximum leaf conductance of 5 to 10 samples each day are averaged, yielding the maximum diffusive conductance for the species. Due to the variation of the location of stomata on plant leaves for different plant species, conductance values should be calculated for the total leaf surface area.

References

Körner (1977)

Körner et al. (1979)

The name of the urban land type is a primary key referenced by in . All names in the urban.urb database must be unique.

The names in the urban database are also used by QSWAT+ to link the grid codes in land use/land cover maps to SWAT+ urban land types.

Impervious areas can be differentiated into two groups, the area that is hydraulically connected to the drainage system and the area that is not directly connected. As an example, assume there is a house surrounded by a yard where runoff from the roof flows into the yard where it infiltrates into the soil. The rooftop is impervious, but it is not hydraulically connected to the drainage system. In contrast, a parking lot whose runoff enters a storm water drain is hydraulically connected.

When modeling urban areas, the connectedness of the drainage system must be quantified. The best methods for determining the fraction total and directly connected impervious areas is to conduct a field survey or analyze aerial photographs.

Urban areas differ from rural areas in the fraction of total area that is impervious. Construction of buildings, parking lots and paved roads increases the impervious cover in a watershed and reduces infiltration. With development, the spatial flow pattern of water is altered and the hydraulic efficiency of flow is increased through artificial channels, curbing, and storm drainage and collection systems.

This fraction includes directly and indirectly connected impervious areas.

Curb length may be measured directly by scaling the total length of streets off of maps and multiplying by two. To calculate the density, the curb length is divided by the area represented by the map.

Number of days for amount of solids on impervious areas to build up from 0 kg/curb km to half the maximum amount of solids allowed (i.e. 0.5*).

Wash off is the process of erosion or solution of constituents from an impervious surface during a runoff event. The original default value for urb_wash was calculated as 0.18 mm-1 by assuming that 13 mm of total runoff in one hour would wash off 90% of the initial surface load (Huber and Heaney, 1982). Using sediment transport theory, Sonnen (1980) estimated values for the wash-off coefficient ranging from 0.002-0.26 mm-1. Huber and Dickinson (1988) noted that values between 0.039 and 0.390 mm-1 for the wash-off coefficient give sediment concentrations in the range of most observed values. This variable is used to calibrate the model to observed data.

References

Huber and Dickinson (1988)

Huber and Heaney (1982)

Sonnen (1980)

The name of the fertilizer or manure record is a primary key referenced when fertilizer or manure applications are scheduled in management.sch or lum.dtl. All names in the fertilizer.frt database must be unique.

The concentration of NH4-N for a conventional system is typically 60 mg N/L (ranging between 17 and 78 mg N/L). The value varies greatly for different types of septic systems (see Table A-1 of Siegrist et al. (2005)).

References

Siegrist et al. (2005)

McCray et al. (2005) proposed 0.227 m3/capita/day as the median value for the United States based on the data collected from various sources.

References

McCray et al. (2005)

The half-life for a pesticide defines the number of days required for a given pesticide concentration to be reduced by one-half. The half-life entered for a pesticide is a lumped parameter that includes the net effect of volatilization, photolysis, hydrolysis, biological degradation and chemical reactions.

For most pesticides, the foliar half-life is much less than the soil half-life due to enhanced volatilization and photodecomposition. If the foliar half-life is available for the pesticide this value should be used. If the foliar half-life is not available, the foliar half-life can be estimated using the following rules:

1. Foliar half-life is assumed to be less than the soil half-life by a factor of 0.5 to 0.25, depending on vapor pressure and sensitivity to photodegradation.

2. Foliar half-life is adjusted downward for pesticides with vapor pressures less than 10-5 mm Hg.

3. The maximum foliar half-life assigned is 30 days.

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.

The mixing efficiency specifies the fraction of materials (residue, nutrients, and pesticides) on the soil surface that are mixed uniformly throughout the soil depth specified by mix_dp. The remaining fraction of residue and nutrients is left in the original location (soil surface or layer).

The name of the urban land type is a primary key referenced when pesticide applications are scheduled in management.sch or lum.dtl. All names in the pesticide.pes database must be unique.

The name of the tillage record is a primary key referenced when tillage operations are scheduled in management.sch or lum.dtl. All names in the tillage.til database must be unique.

Information of water quality or effluent characteristics required to simulate different types of Onsite Wastewater Systems (OWSs) is stored in the septic water quality database. The information contained in the septic water quality database includes the septic tank effluent flow rate for per capita and the effluent characteristics of various septic systems. The database file distributed with SWAT+ includes water quality data for most conventional, advanced, and failing septic systems. It was developed based on the field data summarized by Siegrist et al. (2005), McCray et al. (2005), and OWTS 201 (2005).

References

Siegrist et al. (2005)

McCray et al. (2005)

OWTS 201 (2005)

Pesticides in the soil environment can be transported in solution or attached to sediment. The partitioning of a pesticide between the solution and soil phases is defined by the soil adsorption coefficient for the pesticide. The soil adsorption coefficient is the ratio of the pesticide concentration in the soil or solid phase to the pesticide concentration in the solution or liquid phase:

$K_p=\frac{C_{solidphase}}{C_{solution}}$

where $K_p$ is the soil adsorption coefficient ((mg/kg)/(mg/L) or m3/ton), $C_{solidphase}$ is the concentration of the pesticide sorbed to the solid phase (mg chemical/kg solid material or g/ton), and $C_{solution}$ is the concentration of the pesticide in solution (mg chemical/L solution or g/ton). The definition of the soil adsorption coefficient in this equation assumes that the pesticide sorption process is linear with concentration and instantaneously reversible. Because the partitioning of pesticide is dependent upon the amount of organic material in the soil, the soil adsorption coefficient input to the model is normalized for soil organic carbon content. The relationship between the soil adsorption coefficient and the soil adsorption coefficient normalized for soil organic carbon content is:

where is the soil adsorption coefficient ((mg/kg)/(mg/L)), is the soil adsorption coefficient normalized for soil organic carbon content ((mg/kg)/(mg/L) or m3/ton), and is the percent organic carbon present in the soil.

The water solubility value defines the highest concentration of pesticide that can be reached in the runoff and soil pore water. While this is an important characteristic, researchers have found that the soil adsorption coefficient, , tends to limit the amount of pesticide entering solution so that the maximum possible concentration of pesticide in solution is seldom reached. Reported solubility values are determined under laboratory conditions at a constant temperature, typically between 20°C and 30°C.