Weather Forecast Incorporation

Being able to assess the impact of predicted weather in a watershed is useful for some applications. For example, reservoir management can better time needed water releases if they know the impact of storms in the near future.

SWAT+ allows a forecast period to be defined in a simulation. The simulation is split into two parts. During the first portion of the simulation, climatic data is read in from input files or generated using the long-term averages input by the user in the weather generator (.wgn) file. When the simulation reaches the first day of the forecast period (defined by FCSTDAY and FCSTYR in file.cio) the model replaces the long-term weather generator averages with averages provided for the forecast period. All climatic data required by SWAT+ is generated during the forecast period.

Forecast data provided by the U.S. National Weather Service is summarized by region. SWAT+ allows the user to incorporate data for multiple regions within one simulation. The forecast region number assigned to a subbasin must correspond to a forecast region number given for a specific dataset in the forecast input file (.cst).

SWAT+ allows the user to define alternative temperature and precipitation averages for the forecast period to generate daily precipitation and temperature values. For temperature, the user specifies the average maximum and minimum air temperature and the standard deviation for these averages. For precipitation, the user specifies the average amount of precipitation falling by month along with the standard deviation and skew coefficient for that average. The user must also define the wet/dry day probabilities and the average number of days of precipitation expected.

The forecast period must be simulated a number of times to obtain a distribution of possible weather scenarios. The user defines the number of model runs made (FCSTCYCLES in file.cio). A minimum of 20 cycles is recommended. The only difference between forecast scenarios is the value of the random number seeds used to generate daily weather values.

Table 1:4-3: SWAT+ input variables that pertain to forecast incorporation.

Variable NameDefinitionFile Name

FCSTDAY

First day of forecast period (julian date).

file.cio

FCSTYR

Year that forecast period begins.

file.cio

FCSTCYCLES

Number of times forecast period is simulated.

file.cio

FCSTFILE

Name of input file containing forecast data.

file.cio

FCST_REG

Forecast region number

.sub,.cst

FCST_REGTOT

Total number of forecast regions used in watershed

.cst

FTMPMX(mon)

μmxmon\mu mx_{mon}: average maximum air temperature for month (°C)

.cst

FTMPMN(mon)

μmnmon\mu mn_{mon}: average minimum air temperature for month (°C)

.cst

FTMPSTDMX(mon)

σmxmon\sigma mx_{mon}: standard deviation for maximum air temperature in month (°C)

.cst

FTMPSTDMN(mon)

σmnmon\sigma mn_{mon}: standard deviation for minimum air temperature in month (°C)

.cst

FPCPMM(mon)

average amount of precipitation falling in month (mm H2_2O)

.cst

FPCPSTD(mon)

σmon\sigma _{mon}: standard deviation for daily precipitation in month (mm H2_2O)

.cst

FPCPSKW(mon)

gmong_{mon}: skew coefficient for daily precipitation in month

.cst

FPR_W(1,mon)

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

.cst

FPR_W(2,mon)

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

.cst

FPCPD(mon)

average number of days of precipitation in month

.cst

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