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1:3.1.2 Amount of Precipitation

Numerous probability distribution functions have been used to describe the distribution of rainfall amounts. SWAT+ provides the user with two options: a skewed distribution and an exponential distribution.

The skewed distribution was proposed by Nicks (1974) and is based on a skewed distribution used by Fiering (1967) to generate representative streamflow. The equation used to calculate the amount of precipitation on a wet day is:

Rday=μmon+2∗σmon∗([(SNDday−gmon6)∗gmon6+1]3−1gmon)R_{day}=\mu_{mon}+2*\sigma_{mon}*(\frac{[(SND_{day}-\frac{g_{mon}}{{6}})*\frac{g_{mon}}{{6}}+1]^3-1}{g_{mon}})Rday​=μmon​+2∗σmon​∗(gmon​[(SNDday​−6gmon​​)∗6gmon​​+1]3−1​) 1:3.1.3

where RdayR_{day}Rday​ is the amount of rainfall on a given day (mm H2Omm\space H_2Omm H2​O), μmon\mu_{mon}μmon​ is the mean daily rainfall (mm H2Omm\space H_2Omm H2​O) for the month, σmon\sigma_{mon}σmon​ is the standard deviation of daily rainfall (mm H2Omm\space H_2Omm H2​O) for the month, SNDdaySND_{day}SNDday​ is the standard normal deviate calculated for the day, and gmong_{mon}gmon​ is the skew coefficient for daily precipitation in the month.

The standard normal deviate for the day is calculated:

1:3.1.4

where and are random numbers between 0.0 and 1.0.

The exponential distribution is provided as an alternative to the skewed distribution. This distribution requires fewer inputs and is most commonly used in areas where limited data on precipitation events is available. Daily precipitation is calculated with the exponential distribution using the equation:

1:3.1.5

where is the amount of rainfall on a given day (), is the mean daily rainfall () for the month, is a random number between 0.0 and 1.0, and is an exponent that should be set between 1.0 and 2.0. As the value of is increased, the number of extreme rainfall events during the year will increase. Testing of this equation at locations across the U.S. have shown that a value of 1.3 gives satisfactory results.

Table 1:3-1: SWAT+ input variables that pertain to generation of precipitation.

Definition
Source Name
Input Name
Input File

wet_wet

Rainfall distribution code: 0-skewed, 1-exponential

IDIST

file.cio

: value of exponent (required if IDIST = 1)

REXP

file.cio

average amount of precipitation falling in month ()

pcpmm

pcp_ave

average number of days of precipitation in month(= PCPMM / PCPD)

pcpd

pcp_days

: standard deviation for daily precipitation in month ()

pcpstd

pcp_sd

: skew coefficient for daily precipitation in month

pcpskw

pcp_skew

SNDday=cos(6.283∗rnd2)∗−2ln(rnd1)SND_{day}=cos(6.283*rnd_2)*\sqrt{-2ln(rnd_1)}SNDday​=cos(6.283∗rnd2​)∗−2ln(rnd1​)​
rnd1rnd_1rnd1​
rnd2rnd_2rnd2​
Rday=μmon∗(−ln(rnd1))rexpR_{day}=\mu_{mon}*(-ln(rnd_1))^{rexp}Rday​=μmon​∗(−ln(rnd1​))rexp
RdayR_{day}Rday​
mm H2Omm\space H_2Omm H2​O
μmon\mu_{mon}μmon​
mm H2Omm\space H_2Omm H2​O
rnd1rnd_1rnd1​
rexprexprexp
rexprexprexp

Precipitation input: 'sim' for simulated or gage name

pgage

pcp

weather-sta.cli

Pi(W/D)P_i(W/D)Pi​(W/D): probability of a wet day following a dry day in month

pr_wd

wet_dry

weather-wgn.cli

Pi(W/W)P_i(W/W)Pi​(W/W): probability of a wet day following a wet day in month

pr_ww

rexprexprexp
mm H2Omm\space H_2Omm H2​O
μmon\mu_{mon}μmon​
σmon\sigma_{mon}σmon​
mm H2Omm\space H_2Omm H2​O
gmong_{mon}gmon​
weather-wgn.cli
weather-wgn.cli
weather-wgn.cli
weather-wgn.cli
weather-wgn.cli