For each month, users provide the maximum half-hour rain observed over the entire period of record. These extreme values are used to calculate representative monthly maximum half-hour rainfall fractions.

Prior to calculating the representative maximum half-hour rainfall fraction for each month, the extreme half-hour rainfall values are smoothed by calculating three month average values:

$R_{0.5sm(mon)}=\frac{R_{0.5x(mon-1)}+R_{0.5x(mon)}+R_{0.5x(mon+1)}}{3}$ 1:3.2.1

where $R_{0.5sm(mon)}$ is the smoothed maximum half-hour rainfall for a given month (mm H$_2$O) and $R_{0.5x}$ is the extreme maximum half-hour rainfall for the specified month (mm H$_2$O). Once the smoothed maximum half-hour rainfall is known, the representative half-hour rainfall fraction is calculated using the equation:

1:3.2.2

where is the average half-hour rainfall fraction for the month, is an adjustment factor, is the smoothed half-hour rainfall amount for the month (mm HO), is the mean daily rainfall (mm HO) for the month, is the number of years of rainfall data used to obtain values for monthly extreme half-hour rainfalls, and are the number of wet days in the month. The adjustment factor is included to allow users to modify estimations of half-hour rainfall fractions and peak flow rates for runoff.

For simulations where the timing of rainfall within the day is required, the daily rainfall value must be partitioned into shorter time increments. The method used in SWAT+ to disaggregate storm data was taken from CLIGEN (Nicks et al., 1995).

A double exponential function is used to represent the intensity patterns within a storm. With the double exponential distribution, rainfall intensity exponentially increases with time to a maximum, or peak, intensity. Once the peak intensity is reached, the rainfall intensity exponentially decreases with time until the end of the storm.

The exponential equations governing rainfall intensity during a storm event are:

1:3.3.1

,

The user has the option of using the monthly maximum half-hour rainfall for all days in the month or generating a daily value. The variable ISED_DET in the basin input file (.bsn) defines which option the user prefers. The randomness of the triangular distribution used to generated daily values can cause the maximum half-hour rainfall value to jump around. For small plots or microwatersheds in particular, the variability of the triangular distribution is unrealistic.

The triangular distribution used to generate the maximum half-hour rainfall fraction requires four inputs: average monthly half-hour rainfall fraction, maximum value for half-hour rainfall fraction allowed in month, minimum value for half-hour rainfall fraction allowed in month, and a random number between 0.0 and 1.0.

The maximum half-hour rainfall fraction, or upper limit of the triangular distribution, is calculated from the daily amount of rainfall with the equation:

1:3.2.3

The procedure used to generate daily values for maximum temperature, minimum temperature and solar radiation (Richardson, 1981; Richardson and Wright, 1984) is based on the weakly stationary generating process presented by Matalas (1967).

The rainfall intensity distribution given in equation 1:3.3.1 can be normalized to eliminate units. To do this, all time values are divided, or normalized, by the storm duration and all intensity values are normalized by the average storm intensity. For example,

$\hat i =\frac{i}{i_{ave}}$ 1:3.3.2

$\hat t=\frac{T}{T_{dur}}$ 1:3.3.3

where $\hat i$ the normalized rainfall intensity at time $\hat t$, $i$ is the rainfall intensity at time T (mm/hr), $i_{ave}$ is the average storm rainfall intensity (mm/hr),$\hat t$ is the time during the storm expressed as a fraction of the total storm duration (0.0-1.0), $T$ is the time since the beginning of the storm (hr), and $T_{dur}$ is the duration of the storm (hr).

The normalized storm intensity distribution is:

1:3.3.4

,

where the normalized rainfall intensity at time , is the normalized maximum or peak rainfall intensity during the storm, is the time during the storm expressed as a fraction of the total storm duration (0.0-1.0), is the time from the beginning of the storm till the peak intensity expressed as a fraction of the total storm duration (0.0-1.0), and are equation coefficients.

The relationship between the original equation coefficients and the normalized equation coefficients is:

1:3.3.5

1:3.3.6

where is the equation coefficient for rainfall intensity before peak intensity is reached (hr), is the normalized equation coefficient for rainfall intensity before peak intensity is reached, is the equation coefficient for rainfall intensity after peak intensity is reached (hr), is the normalized equation coefficient for rainfall intensity after peak intensity is reached, and is the storm duration (hr).

Values for the equation coefficients, and , can be determined by isolating the coefficients in equation 1:3.3.4. At = 0.0 and at = 1.0,

1:3.3.7

1:3.3.8

where is the normalized equation coefficient for rainfall intensity before peak intensity is reached, is the normalized equation coefficient for rainfall intensity after peak intensity is reached, is the time during the storm expressed as a fraction of the total storm duration (0.0-1.0), is the time from the beginning of the storm till the peak intensity expressed as a fraction of the total storm duration (0.0-1.0), is the normalized rainfall intensity at time , and is the normalized maximum or peak rainfall intensity during the storm.

Residuals for maximum temperature, minimum temperature and solar radiation are required for calculation of daily values. The residuals must be serially correlated and cross-correlated with the correlations being constant at all locations. The equation used to calculate residuals is:

$\chi_i(j)=A{\chi_{i-1}}(j)+B{\varepsilon_i}(j)$ 1:3.4.1

where $\chi_i(j)$ is a 3 × 1 matrix for day $i$ whose elements are residuals of maximum temperature ($j=1$), minimum temperature ($j=2$) and solar radiation ($j=3$), $\chi_{i-1}(j)$) is a 3 × 1 matrix of the previous day’s residuals, $\varepsilon_i$ is a 3 × 1 matrix of independent random components, and $A$ and $B$ are 3 × 3 matrices whose elements are defined such that the new sequences have the desired serial-correlation and cross-correlation coefficients. The $A$ and $B$ matrices are given by

1:3.4.2

1:3.4.3

where the superscript denotes the inverse of the matrix and the superscript T denotes the transpose of the matrix. and are defined as

1:3.4.4

1:3.4.5

is the correlation coefficient between variables and on the same day where and may be set to 1 (maximum temperature), 2 (minimum temperature) or 3 (solar radiation) and is the correlation coefficient between variable and with variable lagged one day with respect to variable . Correlation coefficients were determined for 31 locations in the United States using 20 years of temperature and solar radiation data (Richardson, 1982). Using the average values of these coefficients, the and matrices become

1:3.4.6

1:3.4.7

Using equations 1:3.4.2 and 1:3.4.3, the A and B matrices become

1:3.4.8

1:3.4.9

The A and B matrices defined in equations 1:3.4.8 and 1:3.4.9 are used in conjunction with equation 1:3.4.1 to generate daily sequences of residuals of maximum temperature, minimum temperature and solar radiation.

The daily generated values are determined by multiplying the residual elements generated with equation 1:3.4.1 by the monthly standard deviation and adding the monthly average value.

1:3.4.10

1:3.4.11

1:3.4.12

where is the maximum temperature for the day (°C), is the average daily maximum temperature for the month (°C), is the residual for maximum temperature on the given day, is the standard deviation for daily maximum temperature during the month (°C), is the minimum temperature for the day (°C),

The continuity equation relates average daily solar radiation adjusted for wet or dry conditions to the average daily solar radiation for the month:

1:3.4.19

where is the average daily solar radiation for the month (MJ m), are the total number of days in the month, is the average daily solar radiation of the month on wet days (MJ m), are the number of wet days in the month, is the average daily solar radiation of the month on dry days (MJ m), and are the number of dry days in the month.

The wet day average solar radiation is assumed to be less than the dry day average solar radiation by some fraction:

The triangular distribution used to generate daily relative humidity values requires four inputs: mean monthly relative humidity, maximum relative humidity value allowed in month, minimum relative humidity value allowed in month, and a random number between 0.0 and 1.0.

The maximum relative humidity value, or upper limit of the triangular distribution, is calculated from the mean monthly relative humidity with the equation:

1:3.5.4

where is the largest relative humidity value that can be generated on a given day in the month, and is the average relative humidity for the month.

The minimum relative humidity value, or lower limit of the triangular distribution, is calculated from the mean monthly relative humidity with the equation:

Maximum temperature and solar radiation will be lower on overcast days than on clear days. To incorporate the influence of wet/dry days on generated values of maximum temperature and solar radiation, the average daily maximum temperature, , and average daily solar radiation, , in equations 1:3.4.10 and 1:3.4.12 are adjusted for wet or dry conditions.

The continuity equation relates average daily maximum temperature adjusted for wet or dry conditions to the average daily maximum temperature for the month:

1:3.4.14

where is the average daily maximum temperature for the month (°C), are the total number of days in the month,

Relative humidity is defined as the ratio of the actual vapor pressure to the saturation vapor pressure at a given temperature:

1:3.5.1

where is the average relative humidity for the month, is the actual vapor pressure at the mean monthly temperature (kPa), and is the saturation vapor pressure at the mean monthly temperature (kPa). The saturation vapor pressure, , is related to the mean monthly air temperature with the equation:

1:3.5.2

where is the saturation vapor pressure at the mean monthly temperature (kPa), and

Wind speed is required by SWAT+ when the Penman-Monteith equation is used to calculate potential evapotranspiration. Mean daily wind speed is generated in SWAT+ using a modified exponential equation:

1.3.6.1

where is the mean wind speed for the day (m s), is the average wind speed for the month (m s), and is a random number between 0.0 and 1.0.

Table 1:3-6: SWAT+ input variables that pertain to generation of wind speed.

To incorporate the effect of clear and overcast weather on generated values of relative humidity, monthly average relative humidity values can be adjusted for wet or dry conditions.

The continuity equation relates average relative humidity adjusted for wet or dry conditions to the average relative humidity for the month:

$R_{hmon}*days_{tot}=R_{hWmon}*days_{wet}+R_{hDmon}*days_{dry}$ 1:3.5.8

where $R_{hmon}$ is the average relative humidity for the month, $days_{tot}$ are the total number of days in the month, $R_{hWmon}$ is the average relative humidity for the month on wet days, $days_{wet}$ are the number of wet days in the month, $R_{hDmon}$ is the average relative humidity of the month on dry days, and $days_{dry}$ are the number of dry days in the month.

The wet day average relative humidity is assumed to be greater than the dry day average relative humidity by some fraction:

1:3.5.9

where is the average relative humidity of the month on wet days, is the average relative humidity of the month on dry days, and is a scaling factor that controls the degree of deviation in relative humidity caused by the presence or absence of precipitation. The scaling factor, , is set to 0.9 in SWAT+.

To calculate the dry day relative humidity, equations 1:3.5.8 and 1:3.5.9 are combined and solved for :

1:3.5.10

To reflect the impact of wet or dry conditions, SWAT+ will replace with on wet days or on dry days in equations 1:3.5.4 through 1:3.5.7.

Table 1:3-5: SWAT+ input variables that pertain to generation of relative humidity.

Relative humidity is required by SWAT+ when the Penman-Monteith equation is used to calculate potential evapotranspiration. It is also used to calculate the vapor pressure deficit on plant growth. Daily average relative humidity values are calculated from a triangular distribution using average monthly relative humidity. This method was developed by J.R. Williams for the EPIC model (Sharpley and Williams, 1990).

Maximum half-hour rainfall is required by SWAT+ to calculate the peak flow rate for runoff. When daily precipitation data are used by the model, the maximum half-hour rainfall may be calculated from a triangular distribution using monthly maximum half-hour rainfall data or the user may choose to use the monthly maximum half-hour rainfall for all days in the month. The maximum half-hour rainfall is calculated only on days where surface runoff has been generated.

The normalized time to peak intensity is calculated by SWAT+ using a triangular distribution. The triangular distribution used to generate the normalized time to peak intensity requires four inputs: average time to peak intensity expressed as a fraction of total storm duration $(\hat t_{peakM})$, maximum time to peak intensity expressed as a fraction of total storm duration $(\hat t_{peakU})$, minimum time to peak intensity expressed as a fraction of total storm duration $(\hat t_{peakL})$and a random number between 0.0 and 1.0.

The maximum time to peak intensity, or upper limit of the triangular distribution, is set at 0.95. The minimum time to peak intensity, or lower limit of the triangular distribution is set at 0.05. The mean time to peak intensity is set at 0.25.

The triangular distribution uses one of two sets of equations to generate a normalized peak intensity for the day. If $rnd_1\le[\frac{\hat t_{peakM} - \hat t_{peakL}}{\hat t_{peakU} - \hat t_{peakL}}]$ then

$\hat t_{peak}=\hat t_{peakM} * \frac{\hat t_{peakL}+[rnd_1*(\hat t_{peakU}-\hat t_{peakL})*(\hat t_{peakM}-\hat t_{peakL})]^{0.5}}{\hat t_{peak,mean}}$ 1:3.3.9

If then

1:3.3.10

where is the time from the beginning of the storm till the peak intensity expressed as a fraction of the total storm duration (0.0-1.0),is the average time to peak intensity expressed as a fraction of storm duration, is a random number generated by the model each day, is the minimum time to peak intensity that can be generated,is the maximum time to peak intensity that can be generated, and is the mean of and .

The volume of rain is related to rainfall intensity by:

1:3.3.11

where is the amount of rain that has fallen at time (mm HO) and is the rainfall intensity at time (mm/hr).

Using the definition for rainfall intensity given in equation 1:3.3.1, equation 1:3.3.11 can be integrated to get: