Example model analysis of soil moisture data

In the figure below, I have taken the data from the Mokwakwaila office station. We are looking at the measured data from the most shallow sensor. In addition to this, I have created a model that takes the precipitation into account, as well as evaporation and run-off. The numbers are displayed in per cent.

The model looks something like

topModel(m) = topModel(m-1) + scaleRain*(rainfall(m) + rainfall(m-1)) - topModel(m-1)*topModel(m-1)*(evaporation + dillution)*(timeVector(m)-timeVector(m-1));

The current, modelled value of soil moisture is equal to the previous one plus rain times a scaling factor. In addition to this, moisture will disappear through air and ground, this is a time-dependent parameter and it will also depend on the soil moisture itself. I have assumed a square model. The more moist it is, the more will evaporate.

Evaporation, etc., is also a function of air and soil temperature, not included here, that would further refine the model. Evaporation and dillution, is approximately 2% per hour.