Orographic precipitation is a significant phenomenon in certain areas of the world. To account for orographic effects on both precipitation and temperature, SWAT+ allows up to 10 elevation bands to be defined in each subbasin. Precipitation and maximum and minimum temperatures are calculated for each band as a function of the respective lapse rate and the difference between the gage elevation and the average elevation specified for the band. For precipitation,

$R_{band}=R_{day}+(EL_{band}-EL_{gage})*\frac{plaps}{days_{pcp,yr}*1000}$ when $R_{day}>0.01$

1:4.1.1

where $R_{band}$ is the precipitation falling in the elevation band (mm H$_2$O), $R_{day}$ is the precipitation recorded at the gage or generated from gage data (mm H$_2$O), $EL_{band}$ is the mean elevation in the elevation band (m), $EL_{gage}$ is the elevation at the recording gage (m), $plaps$ is the precipitation lapse rate (mm H$_2$O/km), $days_{pcp,yr}$ is the average number of days of precipitation in the subbasin in a year, and 1000 is a factor needed to convert meters to kilometers. For temperature,

$T_{mx,band}=T_{mx}+(EL_{band}-EL_{gage})*\frac{tlaps}{1000}$ 1:4.1.2

$T_{mn,band}=T_{mn}+(EL_{band}-EL_{gage})*\frac{tlaps}{1000}$ 1:4.1.3

$\overline T_{av,band} =\overline T_{av} +(EL_{band}-EL_{gage})*\frac{tlaps}{1000}$ 1:4.1.4

where $T_{mx,band}$ is the maximum daily temperature in the elevation band (°C), $T_{mn,band}$ is the minimum daily temperature in the elevation band (°C), is the mean daily temperature in the elevation band (°C), $T_{mx}$ is the maximum daily temperature recorded at the gage or generated from gage data (°C), $T_{mn}$ is the minimum daily temperature recorded at the gage or generated from gage data (°C), is the mean daily temperature recorded at the gage or generated from gage data (°C), $EL_{band}$ is the mean elevation in the elevation band (m), $EL_{gage}$ is the elevation at the recording gage (m), tlaps is the temperature lapse rate (°C/km), and 1000 is a factor needed to convert meters to kilometers.

Once the precipitation and temperature values have been calculated for each elevation band in the subbasin, new average subbasin precipitation and temperature values are calculated:

$R_{day}= \sum_{bnd=1}^{b}R_{band}*fr_{bnd}$ 1:4.1.5

$T_{mx}=\sum_{bnd=1}^b T_{mx,band}*fr_{bnd}$ 1:4.1.6

$T_{mn}=\sum_{bnd=1}^b T_{mn,band} *fr_{bnd}$ 1:4.1.7

$\overline T_{av}=\sum_{bnd=1}^b \overline T_{av,band}*fr_{bnd}$ 1:4.1.8

where $R_{day}$ is the daily average precipitation adjusted for orographic effects (mm H$_2$O), $T_{mx}$ is the daily maximum temperature adjusted for orographic effects (°C), $T_{mn}$ is the daily minimum temperature adjusted for orographic effects (°C), is the daily mean temperature adjusted for orographic effects (°C), $R_{band}$ is the precipitation falling in elevation band $bnd$ (mm H2O), $T_{mx,band}$ is the maximum daily temperature in elevation band $bnd$ (°C), $T_{mn,band}$ is the minimum daily temperature in elevation band $bnd$ (°C), is the mean daily temperature in elevation band $bnd$ (°C), $fr_{bnd}$ is the fraction of subbasin area within the elevation band, and $b$ is the total number of elevation bands in the subbasin.

The only processes modeled separately for each individual elevation band are the accumulation, sublimation and melting of snow. As with the initial precipitation and temperature data, after amounts of sublimation and snow melt are determined for each elevation band, subbasin average values are calculated. These average values are the values that are used in the remainder of the simulation and reported in the output files.

Table 1:4-1: SWAT+ input variables that pertain to orographic effects.

SWAT+ is capable of simulating a number of climate customization options. Orographic impacts on temperature and precipitation for watersheds in mountainous regions can be simulated. The model will also modify climate inputs for simulations that are looking at the impact of climatic change in a given watershed. Finally, SWAT+ allows a weather forecast period to be incorporated into a simulation to study the effects of predicted weather in a watershed.

The impact of global climate change on water supply is a major area of research. Climate change can be simulated with SWAT+ by manipulating the climatic input that is read into the model (precipitation, temperature, solar radiation, relative humidity, wind speed, potential evapotranspiration and weather generator parameters). A less time-consuming method is to set adjustment factors for the various climatic inputs.

SWAT+ will allow users to adjust precipitation, temperature, solar radiation, relative humidity, and carbon dioxide levels in each subbasin. The alteration of precipitation, temperature, solar radiation and relative humidity are straightforward:

$R_{day}=R_{day}*(1+\frac{adj_{pcp}}{100})$ 1:4.2.1

where $R_{day}$ is the precipitation falling in the subbasin on a given day (mm H$_2$O), and $adj_{pcp}$ is the % change in rainfall.

$T_{mx}=T_{mx}+adj_{tmp}$ 1:4.2.2

where $T_{mx}$ is the daily maximum temperature (°C), and $adj_{tmp}$ is the change in temperature (°C).

$T_{mn}=T_{mn}+adj_{tmp}$ 1:4.2.3

where $T_{mn}$ is the daily minimum temperature (°C), and $adj_{tmp}$ is the change in temperature (°C).

$\overline T_{av} =\overline T_{av} +adj_{tmp}$ 1:4.2.4

where $\overline T_{av}$ is the daily mean temperature (°C), and $adj_{tmp}$ is the change in temperature (°C).

$H_{day}= H_{day}+ adj_{rad}$ 1:4.2.5

where $H_{day}$ is the daily solar radiation reaching the earth’s surface ($MJ m^{-2}$), and $adj_{rad}$ is the change in radiation ($MJ m^{-2} d^{-1}$).

$R_h=R_h +adj_{hmd}$ 1:4.2.6

where $R_h$ is the relative humidity for the day expressed as a fraction, and $adj_{hmd}$ is the change in relative humidity expressed as a fraction.

SWAT+ allows the adjustment terms to vary from month to month so that the user is able to simulate seasonal changes in climatic conditions.

Changes in carbon dioxide levels impact plant growth. As carbon dioxide levels increase, plant productivity increases and plant water requirements go down. The equations used to account for the impact of carbon dioxide levels on plant water requirements are reviewed in Chapters 2:2 and 5:2. When carbon dioxide climate change effects are being simulated, the Penman-Monteith equation must be used to calculate potential evapotranspiration. This method has been modified to account for CO2 impacts on potential evapotranspiration levels.

Table 1:4-2: SWAT+ input variables that pertain to climate change.

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.