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.

1:4.2.2

where is the daily maximum temperature (°C), and is the change in temperature (°C).

1:4.2.3

where is the daily minimum temperature (°C), and is the change in temperature (°C).

1:4.2.4

where is the daily mean temperature (°C), and is the change in temperature (°C).

1:4.2.5

where is the daily solar radiation reaching the earth’s surface (), and is the change in radiation ().

1:4.2.6

where is the relative humidity for the day expressed as a fraction, and 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 impacts on potential evapotranspiration levels.

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

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.

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,

1:4.1.2

1:4.1.3

1:4.1.4

where is the maximum daily temperature in the elevation band (°C), is the minimum daily temperature in the elevation band (°C), is the mean daily temperature in the elevation band (°C), is the maximum daily temperature recorded at the gage or generated from gage data (°C), 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), is the mean elevation in the elevation band (m), is the elevation at the recording gage (m), 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:

1:4.1.5

1:4.1.6

1:4.1.7

1:4.1.8

where is the daily average precipitation adjusted for orographic effects (mm HO), is the daily maximum temperature adjusted for orographic effects (°C), is the daily minimum temperature adjusted for orographic effects (°C), is the daily mean temperature adjusted for orographic effects (°C), is the precipitation falling in elevation band (mm H2O), is the maximum daily temperature in elevation band (°C), is the minimum daily temperature in elevation band (°C), is the mean daily temperature in elevation band (°C), is the fraction of subbasin area within the elevation band, and 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.