The climatic inputs to the model are reviewed first because it is these inputs that provide the moisture and energy that drive all other processes simulated in the watershed. The climatic processes modeled in SWAT+ consist of precipitation, air temperature, soil temperature, and solar radiation. Depending on the method used to calculate potential evapotranspiration, wind speed and relative humidity may also be modeled.

Once water is introduced to the system as precipitation, the available energy, specifically solar radiation, exerts a major control on the movement of water in the land phase of the hydrologic cycle. Processes that are greatly affected by temperature and solar radiation include snow fall, snow melt and evaporation. Since evaporation is the primary water removal mechanism in the watershed, the energy inputs become very important in reproducing or simulating an accurate water balance.

The solar declination is the earth's latitude at which incoming solar rays are normal to the earth's surface. The solar declination is zero at the spring and fall equinoxes, approximately +23½° at the summer solstice, and approximately -23½° at the winter solstice. A simple formula to calculate solar declination from Perrin de Brichambaut (1975) is:

$\delta = sin^{-1} \{0.4sin [ 2 \pi /365] (d_n - 82)\}$ 1:1.1.2

where $\delta$ is the solar declination reported in radians and $d_n$ is the day number of the year.

The mean distance between the earth and the sun is $1.496 X 10^8$ km and is called one astronomical unit (AU). The earth revolves around the sun in an elliptical orbit and the distance from the earth to the sun on a given day will vary from a maximum of 1.017 AU to a minimum of 0.983 AU. An accurate value of the earth-sun distance is important because the solar radiation reaching the earth is inversely proportional to the square of its distance from the sun. The distance is traditionally expressed in mathematical form as a Fourier series type of expansion with a number of coefficients. For most engineering applications a simple expression used by Duffie and Beckman (1980) is adequate for calculating the reciprocal of the square of the radius vector of the earth, also called the eccentricity correction factor, $E_0$, of the earth's orbit:

$E_0 = (r_0/r)^2 = 1+ 0.033 cos [(2\pi d_n /365)]$ 1:1.1.1

where $r_0$is the mean earth-sun distance (1 AU), r is the earth-sun distance for any given day of the year (AU), and $d_n$ is the day number of the year, ranging from 1 on January 1 to 365 on December 31. February is always assumed to have 28 days, making the accuracy of the equation vary due to the leap year cycle.

A number of basic concepts related to the earth's orbit around the sun are required by the model to make solar radiation calculations. This section summarizes these concepts. Iqbal (1983) provides a detailed discussion of these and other topics related to solar radiation for users who require more information.

The angle between the line from an observer on the earth to the sun and a vertical line extending upward from the observer is called the zenith angle, $\theta_z$ (Figure 1:1-1). Solar noon occurs when this angle is at its minimum value for the day.

For a given geographical position, the relationship between the sun and a horizontal surface on the earth's surface is:

$\cos\theta_z = \sin\delta\sin\phi + \cos\delta \cos\phi\cos\omega t$ 1:1.1.3

where $\delta$ is the solar declination in radians, $\phi$ is the geographic latitude in radians, $\omega$ is the angular velocity of the earth's rotation (0.2618 rad $h^{-1}$ or 15˚ $h^{-1}$ ), and t is the solar hour. t equals zero at solar noon, is a positive value in the morning, and is a negative value in the evening. The combined term $\omega t$ is referred to as the hour angle.

Sunrise, $T_{SR}$, and sunset, $T_{SS}$, occur at equal times before and after solar noon. These times can be determined by rearranging the above equation as:

$T_{SR} = +(\cos^{-1}[-\tan\delta \tan\phi]/\omega)$ 1:1.1.4

and

$T_{SS} = - (\cos^{-1}[-tan \delta tan\phi]/\omega)$ 1:1.1.5

Total daylength, $T_{DL}$ is calculated:

$T_{DL} = (2 \cos^ {-1}[-1\tan \delta \tan \phi]/\omega)$ 1:1.1.6

At latitudes above $66.5\degree$or below $-66.5\degree$, the absolute value of [ $\tan\delta \tan\phi$ ] can exceed 1 and the above equation cannot be used. When this happens, there is either no sunrise (winter) or no sunset (summer) and $T_{DL}$ must be assigned a value of 0 or 24 hours, respectively.

To determine the minimum daylength that will occur during the year, equation 1:1.1.6 is solved with the solar declination set to $-23.5\degree$ (-0.4102 radians) for the northern hemisphere or $+23.5\degree$ (0.4102 radians) for the southern hemisphere.

The only SWAT+ input variable used in the calculations reviewed in Section 1:1.1 is given in Table 1:1-1.

Table 1:1-1: SWAT+ input variables that are used in earth-sun relationship calculations.

The radiant energy from the sun is practically the only source of energy that impacts climatic processes on earth. The solar constant, $I_{SC}$, is the rate of total solar energy at all wavelengths incident on a unit area exposed normally to rays of the sun at a distance of 1 AU from the sun. Quantifying this value has been the object of numerous studies through the years. The value officially adopted by the Commission for Instruments and Methods of Observation in October 1981 is

$I_{SC} = 1367 W m^{-2} = 4.921 MJm^{-2} h^{-1}$

On any given day, the extraterrestrial irradiance (rate of energy) on a surface normal to the rays of the sun, $I_{0n}$, is:

$I_{0n} = I_{SC}E_0$ 1:1.2.1

where $E_0$ is the eccentricity correction factor of the earth's orbit, and $I_{0n}$ has the same units as the solar constant,$I_{SC}$.

To calculate the irradiance on a horizontal surface,$I_0$,

$I_0 = I_{0n} \cos\theta_z = I_{SC}E_0\cos\theta_z$ 1:1.2.2

where $cos\theta_z$, is defined in equation 1:1.1.3.

The amount of energy falling on a horizontal surface during a day is given by

$H_0 = \int_{SR}^{SS} I_0dt = 2 \int_0^{SS} I_0dt$ 1:1.2.3

where $H_0$ is the extraterrestrial daily irradiation $(MJ m^{-2} d^{-1})$, SR is sunrise, and SS is sunset. Assuming that $E_0$ remains constant during the one day time step and converting the time $dt$ to the hour angle, the equation can be written

$H_0 = \frac{24}{\pi} I_{SC}E_0\int_0^{\omega*T_{SR} }(\sin\delta \sin\phi+\cos\delta\cos\phi\cos\omega*t)d\omega*T_{SR}$ 1:1.2.4

or

$H_0 = \frac{24}{\pi} I_{SC}E_0[{\omega*T_{SR} }(\sin\delta \sin\phi+\cos\delta\cos\phi\sin(\omega*T_{SR}))]$ 1:1.2.5

where $I_{SC}$ is the solar constant (4.921 $MJ m^{-2} h^{-1}$), E$_0$is the eccentricity correction factor of the earth's orbit, is the angular velocity of the earth's rotation ($0.2618 rad h^{-1}$), the hour of sunrise, $T_{SR}$, is defined by equation 1:1.1.4, δ is the solar declination in radians, and is the geographic latitude in radians. Multiplying all the constants together gives

$H_0 = 37.59E_0[{\omega*T_{SR} }\sin\delta \sin\phi+\cos\delta\cos\phi\sin(\omega*T_{SR})]$ 1:1.2.6

see description of .tmp file in the User’s Manual for input and format requirements if measured temperature data is being used.

When solar radiation enters the earth's atmosphere, a portion of the energy is removed by scattering and adsorption. The amount of energy lost is a function of the transmittance of the atmosphere, the composition and concentration of the constituents of air at the location, the path length the radiation travels through the air column, and the radiation wavelength.

Due to the complexity of the process and the detail of the information required to accurately predict the amount of radiant energy lost while passing through the atmosphere, SWAT+ makes a broad assumption that roughly 20% of the extraterrestrial radiation is lost while passing through the atmosphere under cloudless skies. Using this assumption, the maximum possible solar radiation, $H_{MX}$, at a particular location on the earth's surface is calculated as:

$H_{MX} = 30.0E_0[{\omega*T_{SR} }\sin\delta \sin\phi+\cos\delta\cos\phi\sin(\omega*T_{SR})]$ 1:1.2.7

where the maximum possible solar radiation, $H_{MX}$, is the amount of radiation reaching the earth's surface under a clear sky ($MJ m^{-2} d^{-1}$).

The radiant energy from the sun is practically the only source of energy that impacts climatic processes on earth. The solar constant, ISC, is the rate of total solar energy at all wavelengths incident on a unit area exposed normally to rays of the sun at a distance of 1 AU from the sun. Quantifying this value has been the object of numerous studies through the years. The value officially adopted by the Commission for Instruments and Methods of Observation in October 1981 is

$I_{SC} = 1367 W m^{-2} = 4.921 MJm^{-2} h^{-1}$

On any given day, the extraterrestrial irradiance (rate of energy) on a surface normal to the rays of the sun, $I_{0n}$, is:

$I_{0n} = I_{SC}E_0$ 1:1.2.1

where $E_0$ is the eccentricity correction factor of the earth's orbit, and $I_{0n}$ has the same units as the solar constant, $I_{SC}$. To calculate the irradiance on a horizontal surface, $I_{SC}$,

To calculate the irradiance on a horizontal surface,$I_0$,

$I_0 = I_{0n} \cos\theta_z = I_{SC}E_0\cos\theta_z$ 1:1.2.2

where $cos\theta_z$, is defined in equation 1:1.1.3.

The amount of energy falling on a horizontal surface during a day is given by

$H_0 = \int_{SR}^{SS} I_0dt = 2 \int_0^{SS} I_0dt$ 1:1.2.3

where $H_0$ is the extraterrestrial daily irradiation$(MJ m^{-2} d^{-1})$, SR is sunrise, and SS is sunset. Assuming that $E_0$remains constant during the one day time step and converting the time $dt$ to the hour angle, the equation can be written

$H_0 = \frac{24}{\pi} I_{SC}E_0\int_0^{\omega.T_{SR} }(\sin\delta \sin\phi+\cos\delta\cos\phi\cos\omega.t)d\omega.t$ 1:1.2.4

or

$H_0 = \frac{24}{\pi} I_{SC}E_0[{\omega.T_{SR} }(\sin\delta \sin\phi+\cos\delta\cos\phi\sin(\omega.T_{SR}))]$ 1:1.2.5

where $I_{SC}$ is the solar constant (4.921 $MJ m^{-2} h^{-1}$), E$_0$is the eccentricity correction factor of the earth's orbit, is the angular velocity of the earth's rotation ($0.2618 rad h^{-1}$), the hour of sunrise, $T_{SR}$, is defined by equation 1:1.1.4, δ is the solar declination in radians, and is the geographic latitude in radians. Multiplying all the constants together gives

$H_0 = 37.59E_0[{\omega.T_{SR} }\sin\delta \sin\phi+\cos\delta\cos\phi\sin(\omega.T_{SR})]$ 1:1.2.6

The extraterrestrial radiation falling on a horizontal surface during one hour is given by the equation:

$I_0=I_{SC}E_0(\sin\delta\sin\phi+\cos\delta\cos\phi\cos\omega*t)$ 1:1.2.8

where $I_0$ is the extraterrestrial radiation for 1 hour centered around the hour angle $t$.

An accurate calculation of the radiation for each hour of the day requires a knowledge of the difference between standard time and solar time for the location. SWAT+ simplifies the hourly solar radiation calculation by assuming that solar noon occurs at 12:00pm local standard time.

When the values of $I_0$ calculated for every hour between sunrise and sunset are summed, they will equal the value of $H_0$. Because of the relationship between $I_0$ and $H_0$, it is possible to calculate the hourly radiation values by multiplying $H_0$ by the fraction of radiation that falls within the different hours of the day. The benefit of this alternative method is that assumptions used to estimate the difference between maximum and actual solar radiation reaching the earth’s surface can be automatically incorporated in calculations of hourly solar radiation at the earth’s surface.

SWAT+ calculates hourly solar radiation at the earth’s surface with the equation:

$I_{hr}=I_{frac}*H_{day}$ 1:1.2.9

where$I_{hr}$ is the solar radiation reaching the earth’s surface during a specific hour of the day ($MJ m^{-2}hr^{-1}$), $I_{frac}$ is the fraction of total daily radiation falling during that hour, and $H_{day}$ is the total solar radiation reaching the earth’s surface on that day.

The fraction of total daily radiation falling during an hour is calculated

$I_{frac}=$\frac{(\sin\delta\sin\phi+\cos\delta\cos\phi\cos\omega*t_i)}{$\displaystyle{\sum_{t=SR}^{SS}}(\sin\delta\sin\phi+\cos\delta\cos\phi\ cos\omega*t)}

1:1.2.10

where $t_i$ is the solar time at the midpoint of hour i.

Net radiation requires the determination of both incoming and reflected short-wave radiation and net long-wave or thermal radiation. Expressing net radiation in terms of the net short-wave and long-wave components gives:

$H_{net}=H_{day}\downarrow-\alpha*H_{day}\uparrow+H_L\downarrow-H_L\uparrow$ 1:1.2.11

or

$H_{net} = (1-\alpha)*H_{day} + H_b$ 1:1.2.12

where $H_{net}$ is the net radiation ($MJ m^{-2} d^{-1}$), $H_{day}$ is the short-wave solar radiation reaching the ground ($MJ m^{-2} d^{-1}$), is the short-wave reflectance or albedo, $H_L$ is the long-wave radiation ($MJ m^{-2} d^{-1}$), $H_b$is the net incoming long-wave radiation ($MJ m^{-2} d^{-1}$) and the arrows indicate the direction of the radiation flux.

Net Short-Wave Radiation

Net short-wave radiation is defined as $(1-\alpha)*H_{day}$ . SWAT+ calculates a daily value for albedo as a function of the soil type, plant cover, and snow cover. When the snow water equivalent is greater than 0.5 mm,

$\alpha=0.8$ 1:1.2.13

When the snow water equivalent is less than 0.5 mm and no plants are growing in the HRU,

$\alpha=\alpha_{soil}$ 1:1.2.14

where $_{soil}$ is the soil albedo. When plants are growing and the snow water equivalent is less than 0.5 mm,

$\alpha=\alpha_{plant}*(1-cov_{sol})+\alpha_{soil}*cov_{sol}$ 1:1.2.15

where $_{plant}$ is the plant albedo (set at 0.23), and $cov_{sol}$ is the soil cover index. The soil cover index is calculated

$cov_{sol}=exp(-5.0X10^{-5}*CV)$ 1:1.2.16

where $CV$ is the aboveground biomass and residue ($kg ha^{-1}$).

Net Long-Wave Radiation

Long-wave radiation is emitted from an object according to the radiation law:

$H_R=\varepsilon*\sigma*T_K^{4}$ 1:1.2.17

where $H_R$ is the radiant energy ($MJ m^{-2} d^{-1})$, is the emissivity, is the Stefan-Boltzmann constant ($4.903 10^{-9} MJ m^{-2} K^{-4} d^{-1})$, and $T_K$ is the mean air temperature in Kelvin (273.15 + C). Net long-wave radiation is calculated using a modified form of equation 1:1.2.17 (Jensen et al., 1990):

$H_b=f_{cld}*(\varepsilon_a -\varepsilon_{vs})*\sigma*T_K^{4}$ 1:1.2.18

where $H_b$ is the net long-wave radiation ($MJ m^{-2} d^{-1}$), $f_{cld}$ is a factor to adjust for cloud cover, a is the atmospheric emittance, and vs is the vegetative or soil emittance.

Wright and Jensen (1972) developed the following expression for the cloud cover adjustment factor, $f_{cld}$:

$f_{cld}=a*\frac{H_{day}}{H_{MX}}-b$ 1:1.2.19

where $a$ and $b$ are constants, $H_{day}$ is the solar radiation reaching the ground surface on a given day ($MJ m^{-2}d^{-1}$), and $H_{MX}$ is the maximum possible solar radiation to reach the ground surface on a given day ($MJ m^{-2}d^{-1}$). The two emittances in equation 1:1.2.18 may be combined into a single term, the net emittance . The net emittance is calculated using an equation developed by Brunt (1932):

$\varepsilon'=\varepsilon_a-\varepsilon_{vs}=-(a_1+b_1*\sqrt(e))$ 1:1.2.20

where $a_1$ and $b_1$ are constants and $e$ is the vapor pressure on a given day (kPa). The calculation of e is given in Chapter 1:2. Combining equations 1:1.2.18, 1:1.2.19, and 1:1.2.20 results in a general equation for net long-wave radiation:

$H_b=-[a*\frac{H_{day}}{H_{MX}}-b]*[a_1+b_1*\sqrt(e)]*\sigma*T_k^4$ 1:1.2.21

Experimental values for the coefficients $a,b,a_1$and $b_1$ are presented in Table 1:1.3. The default equation in SWAT+ uses coefficient values proposed by Doorenbos and Pruitt (1977):

$H_b=-[0.9*\frac{H_{day}}{H_{MX}}+0.1]*[0.34-0.139\sqrt(e)]*\sigma*T_k^4$ 1:1.2.22

Table 1:1-3: Experimental coefficients for net long-wave radiation equations (from Jensen et al., 1990).

Table 1:1-4: SWAT+ input variables used in net radiation calculations.

The solar radiation reaching the earth's surface on a given day, $H_{day}$, may be less than $H_{mx}$ due to the presence of cloud cover. The daily solar radiation data required by SWAT+ may be read from an input file or generated by the model.

The variable SLRSIM in the master watershed (file.cio) file identifies the method used to obtain solar radiation data. To read in daily solar radiation data, the variable is set to 1 and the name of the solar radiation data file and the number of solar radiation records stored in the file are set. To generate daily solar radiation values, SLRSIM is set to 2. The equations used to generate solar radiation data in SWAT+ are reviewed in Chapter 1:3. SWAT+ input variables that pertain to solar radiation are summarized in Table 1:1-2.

Table 1:1-2: SWAT+ input variables used in solar radiation calculations.

see description of .slr file in the User’s Manual for input and format requirements if measured daily solar radiation data is being used.

Temperature influences a number of physical, chemical and biological processes. Plant production is strongly temperature dependent, as are organic matter decomposition and mineralization. Daily air temperature may be input to the model or generated from average monthly values. Soil and water temperatures are derived from air temperature.

Water temperature is required to model in-stream biological and water quality processes. SWAT+ uses an equation developed by Stefan and Preud’homme (1993) to calculate average daily water temperature for a well-mixed stream:

1:1.3.13

where is the water temperature for the day (C), and is the average air temperature on the day (C).

Due to thermal inertia of the water, the response of water temperature to a change in air temperature is dampened and delayed. When water and air temperature are plotted for a stream or river, the peaks in the water temperature plots usually lag 3-7 hours behind the peaks in air temperature. As the depth of the river increases, the lag time can increase beyond this typical interval. For very large rivers, the lag time can extend up to a week. Equation 1:1.3.13 assumes that the lag time between air and water temperatures is less than 1 day.

In addition to air temperature, water temperature is influenced by solar radiation, relative humidity, wind speed, water depth, ground water inflow, artificial heat inputs, thermal conductivity of the sediments and the presence of impoundments along the stream network. SWAT+ assumes that the impact of these other variables on water temperature is not significant.

Table 1:1-8: SWAT+ input variables that pertain to water temperature.

Air temperature data are usually provided in the form of daily maximum and minimum temperature. A reasonable approximation for converting these to hourly temperatures is to assume a sinusoidal interpolation function between the minimum and maximum daily temperatures. The maximum daily temperature is assumed to occur at 1500 hours and the minimum daily temperature at 300 hours (Campbell, 1985). The temperature for the hour is then calculated with the equation:

1:1.3.1

where is the air temperature during hour of the day (C), is the average temperature on the day (C), is the daily maximum temperature (C), and is the daily minimum temperature (C).

Table 1:1-6: SWAT+ input variables that pertain to hourly air temperature.

Daily Air Temperature SWAT+ requires daily maximum and minimum air temperature. This data may be read from an input file or generated by the model. The user is strongly recommended to obtain measured daily temperature records from gages in or near the watershed if at all possible. The accuracy of model results is significantly improved by the use of measured temperature data.

The variable TMPSIM in the master watershed (file.cio) file identifies the method used to obtain air temperature data. To read in daily maximum and minimum air temperature data, the variable is set to 1 and the name of the temperature data file(s) and the number of temperature records stored in the file are set. To generate daily air temperature values, TMPSIM is set to 2. The equations used to generate air temperature data in SWAT+ are reviewed in Chapter 1:3. SWAT+ input variables that pertain to air temperature are summarized in Table 1:1-5.

Table 1:1-5: SWAT+ input variables that pertain to daily air temperature.

See description of .tmp file in the User’s Manual for input and format requirements if measured temperature data is being used.

Wind speed is required by SWAT+ if the Penman-Monteith equation is used to estimate potential evapotranspiration and transpiration. SWAT+ assumes wind speed information is collected from gages positioned 1.7 meters above the ground surface.

When using the Penman-Monteith equation to estimate transpiration, the wind measurement used in the equation must be above the canopy. In SWAT+, a minimum difference of 1 meter is specified for canopy height and wind speed measurements. When the canopy height exceeds 1 meter, the original wind measurements is adjusted to:

1:1.4.1

where is the height of the wind speed measurement (cm), and is the canopy height (cm).

The variation of wind speed with elevation near the ground surface is estimated with the equation (Haltiner and Martin, 1957):

1:1.4.2

where is the wind speed (m s) at height (cm), is the wind speed (m s) at height (cm), and is an exponent between 0 and 1 that varies with atmospheric stability and surface roughness. Jensen (1974) recommended a value of 0.2 for and this is the value used in SWAT+.

The daily wind speed data required by SWAT+ may be read from an input file or generated by the model. The variable WNDSIM in the master watershed (file.cio) file identifies the method used to obtain wind speed data. To read in daily wind speed data, the variable is set to 1 and the name of the wind speed data file and the number of different records stored in the file are set. To generate daily wind speed values, WNDSIM is set to 2. The equations used to generate wind speed data in SWAT+ are reviewed in Chapter 1:3.

Table 1:1-9: SWAT+ input variables used in wind speed calculations.

See description of .wnd file in the User’s Manual for input and format requirements if measured daily wind speed data is being used.

Soil temperature will fluctuate due to seasonal and diurnal variations in temperature at the surface. Figure 1:1-2 plots air temperature and soil temperature at 5 cm and 300 cm below bare soil at College Station, Texas. Figure 1:1-2: Four-year average air and soil temperature at College Station, Texas.

This figure illustrates several important attributes of temperature variation in the soil. First, the annual variation in soil temperature follows a sinusoidal function. Second, the fluctuation in temperature during the year (the amplitude of the sine wave) decreases with depth until, at some depth in the soil, the temperature remains constant throughout the year. Finally, the timing of maximum and minimum temperatures varies with depth. Note in the above graph that there is a three month difference between the recording of the minimum temperature at the surface (January) and the minimum temperature at 300 cm (March).

Carslaw and Jaeger (1959) developed an equation to quantify the seasonal variation in temperature:

In order to calculate values for some of the variables in this equation, the heat capacity and thermal conductivity of the soil must be known. These are properties not commonly measured in soils and attempts at estimating values from other soil properties have not proven very effective. Consequently, an equation has been adopted in SWAT+ that calculates the temperature in the soil as a function of the previous day’s soil temperature, the average annual air temperature, the current day’s soil surface temperature, and the depth in the profile.

The equation used to calculate daily average soil temperature at the center of each layer is:

The depth factor is calculated using the equation:

The equation used to calculate the soil surface temperature is:

SWAT+ input variables that directly impact soil temperature calculations are listed in Table 1:1-7. There are several other variables that initialize residue and snow cover in the subbasins or HRUs (SNO_SUB and SNOEB in .sub; RSDIN in .hru). The influence of these variables will be limited to the first few months of simulation. Finally, the timing of management operations in the .mgt file will affect ground cover and consequently soil temperature.

Table 1:1-7: SWAT+ input variables that pertain to soil temperature.

Snow melt is controlled by the air and snow pack temperature, the melting rate, and the areal coverage of snow. Snow melt is included with rainfall in the calculations of runoff and percolation. When SWAT+ calculates erosion, the rainfall energy of the snow melt fraction of the water is set to zero. The water released from snow melt is assumed to be evenly distributed over the 24 hours of the day.

Precipitation is the mechanism by which water enters the land phase of the hydrologic cycle. Because precipitation controls the water balance, it is critical that the amount and distribution of precipitation in space and time is accurately simulated by the model.

The maximum half-hour rainfall is required by SWAT+ to calculate the peak runoff rate. The maximum half-hour rainfall is reported as a fraction of the total daily rainfall, 0.5. If sub-daily precipitation data is used in the model, SWAT+ will calculate the maximum half-hour rainfall fraction directly from the precipitation data. If daily precipitation data is used, SWAT+ generates a value for 0.5 using the equations summarized in Chapter 1:3.

Relative humidity is required by SWAT+ if the Penman-Monteith or Priestley-Taylor equation is used to estimate potential evapotranspiration. It is also used to calculate the vapor pressure deficit on plant growth. The Penman-Monteith equation includes terms that quantify the effect of the amount of water vapor in the air near the evaporative surface on evaporation. Both Penman-Monteith and Priestley-Taylor require the actual vapor pressure, which is calculated from the relative humidity.

Relative humidity is the ratio of an air volume’s actual vapor pressure to its saturation vapor pressure:

$R_h=\frac{e}{e^o}$ 1:2.3.1

where $R_h$ is the relative humidity on a given day, $e^o$ is the actual vapor pressure on a given day (kPa), and is the saturation vapor pressure on a given day (kPa).

The saturation vapor pressure is the maximum vapor pressure that is thermodynamically stable and is a function of the air temperature. SWAT+ calculates saturation vapor pressure using an equation presented by Tetens (1930) and Murray (1967):

$e^o=exp[\frac{16.78*\overline T_{av}-116.9}{\overline T_{av}+237.3}]$ 1:2.3.2

where $e^o$ is the saturation vapor pressure on a given day (kPa) and $\overline T_{av}$is the mean daily air temperature (C). When relative humidity is known, the actual vapor pressure can be calculated by rearranging equation 1:2.3.1:

$e=R_h*e^o$ 1:2.3.3

The saturation vapor pressure curve is obtained by plotting equation 1:2.3.2. The slope of the saturation vapor pressure curve can be calculated by differentiating equation 1:2.3.2:

$\Delta=\frac{4098*e^o}{(\overline T_{av}+237.3)^2}$ 1:2.3.4

where is the slope of the saturation vapor pressure curve (kPa C$^{-1}$), $e^o$is the saturation vapor pressure on a given day (kPa) and $\overline T_{av}$is the mean daily air temperature (C).

The rate of evaporation is proportional to the difference between the vapor pressure of the surface layer and the vapor pressure of the overlying air. This difference is termed the vapor pressure deficit:

$vpd=e^o-e$ 1:2.3.5

where $vpd$ is the vapor pressure deficit (kPa),$e^o$ is the saturation vapor pressure on a given day (kPa), and $e$ is the actual vapor pressure on a given day (kPa). The greater the value of $vpd$ the higher the rate of evaporation.

The latent heat of vaporization, , is the quantity of heat energy that must be absorbed to break the hydrogen bonds between water molecules in the liquid state to convert them to gas. The latent heat of vaporization is a function of temperature and can be calculated with the equation (Harrison, 1963):

$\lambda=2.501-2.361*10^{-3}*\overline T_{av}$ 1:2.3.6

where is the latent heat of vaporization (MJ kg$^{-1}$) and $\overline T_{av}$is the mean daily air temperature (C).

Evaporation involves the exchange of both latent heat and sensible heat between the evaporating body and the air. The psychrometric constant, $\gamma$ , represents a balance between the sensible heat gained from air flowing past a wet bulb thermometer and the sensible heat converted to latent heat (Brunt, 1952) and is calculated:

$\gamma=\frac{c_p*P}{0.622*\lambda}$ 1:2.3.7

where is the psychrometric constant (kPa C$^{-1}$), $c_p$ is the specific heat of moist air at constant pressure (1.013 10$^{-3}$ MJ kg$^{-1}$ C$^{-1}$), P is the atmospheric pressure (kPa),and is the latent heat of vaporization (MJ kg$^{-1}$).

Calculation of the psychrometric constant requires a value for atmospheric pressure. SWAT+ estimates atmospheric pressure using an equation developed by Doorenbos and Pruitt (1977) from mean barometric pressure data at a number of East African sites:

$P=101.3-0.01152*EL+0.544*10^{-6}*EL^2$ 1:2.3.8

where $P$ is the atmospheric pressure (kPa) and $EL$ is the elevation (m).

The daily relative humidity data required by SWAT+ may be read from an input file or generated by the model. The variable RHSIM in the master watershed (file.cio) file identifies the method used to obtain relative humidity data. To read in daily relative humidity data, the variable is set to 1 and the name of the relative humidity data file and the number of different records stored in the file are set. To generate daily relative humidity values, RHSIM is set to 2. The equations used to generate relative humidity data in SWAT+ are reviewed in Chapter 1:3.

Table 1:2-2: SWAT+ input variables used in relative humidity calculations.

See description of .hmd file in the User’s Manual for input and format requirements if measured relative humidity data is being used.

The precipitation reaching the earth's surface on a given day, $R_{day}$, may be read from an input file or generated by the model. Users are strongly recommended to incorporate measured precipitation into their simulations any time the data is available. The ability of SWAT+ to reproduce observed stream hydrographs is greatly improved by the use of measured precipitation data.

Unfortunately, even with the use of measured precipitation the model user can expect some error due to inaccuracy in precipitation data. Measurement of precipitation at individual gages is subject to error from a number of causes and additional error is introduced when regional precipitation is estimated from point values. Typically, total or average areal precipitation estimates for periods of a year or longer have relative uncertainties of 10% (Winter, 1981).

Point measurements of precipitation generally capture only a fraction of the true precipitation. The inability of a gage to capture a true reading is primarily caused by wind eddies created by the gage. These wind eddies reduce the catch of the smaller raindrops and snowflakes. Larson and Peck (1974) found that deficiencies of 10% for rain and 30% for snow are common for gages projecting above the ground surface that are not designed to shield wind effects. Even when the gage is designed to shield for wind effects, this source of error will not be eliminated. For an in-depth discussion of this and other sources of error as well as methods for dealing with the error, please refer to Dingman (1994).

The variable PCPSIM in the master watershed file (file.cio) identifies the method used to obtain precipitation data. To read in precipitation data, the variable is set to 1 and the names of the precipitation data files and the number of precipitation records stored in the files are defined. To generate precipitation values, PCPSIM is set to 2. The equations used to generate precipitation data in SWAT+ are reviewed in Chapter 1:3.SWAT+ input variables that pertain to precipitation are summarized in Table 1:2-1.

Table 1:2-1: SWAT+ input variables used in precipitation calculations.

See description of .pcp file in the User’s Manual for input and format requirements if measured daily precipitation data is being used.

SWAT+ classifies precipitation as rain or freezing rain/snow by the mean daily air temperature. The boundary temperature, $T_{s-r}$, used to categorize precipitation as rain or snow is defined by the user. If the mean daily air temperature is less than the boundary temperature, then the precipitation within the HRU is classified as snow and the water equivalent of the snow precipitation is added to the snow pack.

Snowfall is stored at the ground surface in the form of a snow pack. The amount of water stored in the snow pack is reported as a snow water equivalent. The snow pack will increase with additional snowfall or decrease with snow melt or sublimation. The mass balance for the snow pack is:

$SNO=SNO+R_{day}-E_{sub}-SNO_{mlt}$ 1:2.4.1

where $SNO$ is the water content of the snow pack on a given day (mm H$_2$O), $R_{day}$is the amount of precipitation on a given day (added only if ) (mm H$_2$O), $E_{sub}$ is the amount of sublimation on a given day (mm H$_2$O), and $SNO_{mlt}$ is the amount of snow melt on a given day (mm H$_2$O). The amount of snow is expressed as depth over the total HRU area.

Due to variables such as drifting, shading and topography, the snow pack in a subbasin will rarely be uniformly distributed over the total area. This results in a fraction of the subbasin area that is bare of snow. This fraction must be quantified to accurately compute snow melt in the subbasin.

The factors that contribute to variable snow coverage are usually similar from year to year, making it possible to correlate the areal coverage of snow with the amount of snow present in the subbasin at a given time. This correlation is expressed as an areal depletion curve, which is used to describe the seasonal growth and recession of the snow pack as a function of the amount of snow present in the subbasin (Anderson, 1976). The areal depletion curve requires a threshold depth of snow, $SNO_{100}$, to be defined above which there will always be 100% cover. The threshold depth will depend on factors such as vegetation distribution, wind loading of snow, wind scouring of snow, interception and aspect, and will be unique to the watershed of interest. The areal depletion curve is based on a natural logarithm. The areal depletion curve equation is:

$sno_{cov}=\frac{SNO}{SNO_{100}}*[\frac{SNO}{SNO_{100}}+exp[cov_1-cov_2*\frac{SNO}{SNO_{100}}]]^{-1}$ 1:2.4.2

where $sno_{cov}$ is the fraction of the HRU area covered by snow, $SNO$ is the water content of the snow pack on a given day (mm H$_2$O), $SNO_{100}$ is the threshold depth of snow at 100% coverage (mm H$_2$O), $cov_1$ and $cov_2$ are coefficients that define the shape of the curve. The values used for $cov_1$ and $cov_2$ are determined by solving equation 1:2.4.2 using two known points: 95% coverage at 95% $SNO_{100}$; and 50% coverage at a user specified fraction of $SNO_{100}$. Example areal depletion curves for various fractions of $SNO_{100}$ at 50% coverage are shown in the following figures.

Figure 1:2-1:10% $SNO_{100}$ = 50% coverage

Figure 1:2-2: 30% $SNO_{100}$ = 50% coverage

Figure 1:2-3: 50% $SNO_{100}$ = 50% coverage

Figure 1:2-4: 70% $SNO_{100}$ = 50% coverage

Figure 1:2-5: 90% $SNO_{100}$ = 50% coverage

It is important to remember that once the volume of water held in the snow pack exceeds $SNO_{100}$ the depth of snow over the HRU is assumed to be uniform, i.e. $sno_{cov}$ = 1.0. The areal depletion curve affects snow melt only when the snow pack water content is between 0.0 and $SNO_{100}$. Consequently if $SNO_{100}$ is set to a very small value, the impact of the areal depletion curve on snow melt will be minimal. As the value for $SNO_{100}$ increases, the influence of the areal depletion curve will assume more importance in snow melt processes.

Table 1:2-3: SWAT+ input variables used in snow cover calculations.

SWAT+ requires daily values of precipitation, maximum and minimum temperature, solar radiation, relative humidity and wind speed. The user may choose to read these inputs from a file or generate the values using monthly average data summarized over a number of years.

SWAT+ includes the WXGEN weather generator model (Sharpley and Williams, 1990) to generate climatic data or to fill in gaps in measured records. This weather generator was developed for the contiguous U.S. If the user prefers a different weather generator, daily input values for the different weather parameters may be generated with an alternative model and formatted for input to SWAT+.

The occurrence of rain on a given day has a major impact on relative humidity, temperature and solar radiation for the day. The weather generator first independently generates precipitation for the day. Once the total amount of rainfall for the day is generated, the distribution of rainfall within the day is computed if the Green & Ampt method is used for infiltration. Maximum temperature, minimum temperature, solar radiation and relative humidity are then generated based on the presence or absence of rain for the day. Finally, wind speed is generated independently.

The daily precipitation generator is a Markov chain-skewed (Nicks, 1974) or Markov chain-exponential model (Williams, 1995). A first-order Markov chain is used to define the day as wet or dry. When a wet day is generated, a skewed distribution or exponential distribution is used to generate the precipitation amount. Table 1:3-1 lists SWAT+ input variables that are used in the precipitation generator.

The snow pack temperature is a function of the mean daily temperature during the preceding days and varies as a dampened function of air temperature (Anderson, 1976). The influence of the previous day’s snow pack temperature on the current day’s snow pack temperature is controlled by a lagging factor,$\lambda_{sno}$ . The lagging factor inherently accounts for snow pack density, snow pack depth, exposure and other factors affecting snow pack temperature. The equation used to calculate the snow pack temperature is:

$T_{snow(d_n)}=T_{snow(d_n-1)}*(1-\lambda_{sno})+\overline T_{av}*\lambda_{sno}$ 1:2.5.1

where $T_{snow(d_n)}$is the snow pack temperature on a given day (C), $T_{snow(d_n-1)}$ is the snow pack temperature on the previous day (C), $\lambda_{sno}$ is the snow temperature lag factor, and $\overline T_{av}$is the mean air temperature on the current day (C). As $\lambda_{sno}$ approaches 1.0, the mean air temperature on the current day exerts an increasingly greater influence on the snow pack temperature and the snow pack temperature from the previous day exerts less and less influence.

The snow pack will not melt until the snow pack temperature exceeds a threshold value, $T_{mlt}$. This threshold value is specified by the user.

With the first-order Markov-chain model, the probability of rain on a given day is conditioned on the wet or dry status of the previous day. A wet day is defined as a day with 0.1 mm of rain or more.

The user is required to input the probability of a wet day on day $i$ given a wet day on day $i-1,Pi-1(W/W)$, and the probability of a wet day on day $i$ given a dry day on day $i-1,P_i(W/D)$, for each month of the year. From these inputs the remaining transition probabilities can be derived:

$P_i(D/W)=1-P_i(W/W)$ 1:3.1.1

$P_i(W/W)=1-P_i(W/D)$ 1:3.1.2

where $P_i(D/W)$ is the probability of a dry day on day $i$ given a wet day on day $i-1$ and $P_i(D/D)$ is the probability of a dry day on day $i$ given a dry day on day $i-1$.

To define a day as wet or dry, SWAT+ generates a random number between 0.0 and 1.0. This random number is compared to the appropriate wet-dry probability, $P_i(W/W)$ or $P_i(W/D)$. If the random number is equal to or less than the wet-dry probability, the day is defined as wet. If the random number is greater than the wet-dry probability, the day is defined as dry.

The snow melt in SWAT+ is calculated as a linear function of the difference between the average snow pack-maximum air temperature and the base or threshold temperature for snow melt:

$SNO_{mlt}=b_{mlt}*sno_{cov}*[\frac{T_{snow}+T_{mx}}{2}-T_{mlt}]$ 1:2.5.2

where $SNO_{mlt}$ is the amount of snow melt on a given day (mm H$_2$O), $b_{mlt}$ is the melt factor for the day (mm H$_2$O/day-C), $sno_{cov}$ is the fraction of the HRU area covered by snow,$T_{snow}$ is the snow pack temperature on a given day (C), $T_{mx}$ is the maximum air temperature on a given day (C), and $T_{mlt}$ is the base temperature above which snow melt is allowed (C).

The melt factor is allowed a seasonal variation with maximum and minimum values occurring on summer and winter solstices:

$b_{mlt}=\frac{(b_{mlt6}+b_{mlt12})}{2}+\frac{(b_{mlt6}-b_{mlt12})}{2}*sin(\frac{2\pi}{365}*(d_n-81))$ 1:2.5.3

where $b_{mlt}$ is the melt factor for the day (mm H$_2$O/day-C), $b_{mlt6}$ is the melt factor for June 21 (mm H2O/day-C), $b_{mlt12}$ is the melt factor for December 21 (mm H$_2$O/day-C), and $d_n$ is the day number of the year.