Input Data¶
Precipitation¶
The surface runoff is generated under the impact of precipitation. The precipitation (rainfall) is specified in form of time series, i.e. as a sequence of measured or synthetic values for rainfalls with time and date labels.
Precipitation time series can be specified as intensity (a constant intensity since the previous entry) or as the rain depth (accumulated since the previous entry). The time series for rainfall should contain one of the following Item types:
- Rainfall (A or SA)
- Rainfall depth (A or SA)
- Rainfall intensity (I, BS or FS)
- Rainfall rate (I, BS or FS)
Different rain time series can be applied to the different catchments in the current model set-up, i.e. spatially distributed rain can be simulated. This can be achieved automatically by associating the rain gauge co-ordinates with the time series. The closest rainfall time series is geographically allocated to the specific catchments. Alternatively, individual explicit allocation of specific time series to specific catchments can be applied. There are several ways of adding a rainfall as boundary condition to the catchments:
- Individual: the rain time series is directly link to a specific catchment for a given period
- List: the rain time series is applicable to several for a given period
- Global: it is possible to add a rain time series as a “global”. This rain will applicable for all catchments that don’t have already a rain time series given as individual or as a list. It is also possible to add several “global” rain to the model if they are geo-located. Then the engine will apply the closest rain to each catchment that don’t have individual or list types of rain. It is not allowed to have more than one rain boundary not geo-located in the model
The rain time series can have irregular intervals between the subsequent values. The computational time step for runoff computations is not conditioned by the resolution of the rain time series.
The runoff models calculate the rain intensity for each particular time step, so that the rain volume applied by the model in the time interval covered by the current time step remains preserved, i.e. the applied volume is equal to the volume contained in the same interval of the input data.
Evaporation¶
For most of the models, it is not required to specify a time series for the evaporation, a default value will be applied (see the specific models for more details).
However if a time series is specified, it has to be of one of these types:
- Evaporation (accumulated)
- Evaporation rate (instantaneous)
- Evapo-transpiration (instantaneous)
Temperature¶
A temperature is required when using the snow module.
The only type that can be specified is:
- Temperature (I)
Catchment discharge and load¶
The only type that can be specified is:
- Discharge (I)
Time series data types¶
Instantaneous (I): The values are representative at one precise instance of time.
Backward Step (BS): The values are representative of the average value over one time step, from the previous time step to this time step. This is what is called Mean_Step_Accumulated in the DFS system
Forward Step (FS): The values are representative of the average value over one time step, from this time step to the next time step. This is what is called Reverse_Mean_Step_Accumulated in the DFS system
Accumulated (A): The values are representative of successive accumulation of values since the start of the time series. First values in the time series must be zero.
Step Accumulated (SA): The values are representative of accumulation over one time step. For example, rainfall can be measured in a step-accumulated fashion. We start measuring rainfall at 10:00:00 by setting up a recipient. At 11:00:00 the value of 10 is registered and the recipient is emptied. At 12:00:00 the same process but with a value of 15 and so on. In the time series we get the value 10 at time step 11:00:00 and the value 15 at time step 12:00:00 and so on.