Hello,
Thank you Blair for the clarification. After applying the recharge as a material property, the rate budget does indeed resemble more the water balance from the previous model.
However, my model still fails to converge. (I set the convergence criterion at 1e-5 as for the original model)
One thing that I haven’t specified in my previous post is that I set the top layer of my model as phreatic (the following layers as dependant). Because I do not want my mesh to deform.
Also, I have chosen to treat the “storage change in phreatic top layer where the water table exceeds surface” as confined.
In the original watflow model, “groundwater fow in the elements above the water table is impeded through an ad-hoc exponential relationship between the pressure head p and some artificial "saturation" S:
S(p) = Sr + (1 ¡ Sr)e[sup]?p[/sup] for p < 0
Where Sr is a residual “saturation” and ? is a parameter controlling the exponential drop-off from full to residual “saturation”. Partial “saturation” of the elements results in a lower hydraulic conductivity, impeding groundwater flow. This is accomplished by scaling the relative permeability of an element according to its “saturation”: kr = S(p). The conductivity K is now replaced by krK.
Similar to the deforming mesh algorithm, the flow equation is solved with hydraulic head as the state variable. Convergence criteria are imposed for hydraulic head and the "saturation" updates.”
So in the original model I input a residual saturation (0.1 (unitless)) and a fitting parameter (0.2 (unitless)). From my understanding theses parameters would somehow relate to the scaling of sources/sinks by pseudosaturation which is defined through the “residual water depth for unconfined layers” in meters.
As suggested by other posts on the forum, I have tried increasing the value of this parameter.
What I have noticed is that higher the residual water depth value, the less oscillations I have in my errors from one iteration to the other, the error reaches a plateau at a lower value and my head distribution is more realistic. It’s good! (Although the minimum error seems to reach a minimum 0.0003 with a residual water depth of 1 (10 and 100 give similar results to 1). But I remain unclear as to what this “residual water depth for unconfined layers” does exactly, how it affects the rest of my model. Is there a maximum value? How does it relate to the residual saturation?
Thank you again for your help.