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Sorry for the late reply. When you say "full course materials", can you tell me more specifically what you are looking for? As for GMS, you can contact the staff at aquaveo.com about educational discounts, licenses, etc.

@@groundwatermodeling No worries, Sir. Thank for sharing the info. I'm learning groundwater modeling to apply on my MSc. thesis, which is to study the impacts of climate change on groundwater resources using a hydrogeological modeling approach.

That is an excellent question. Sorry for the slow reply. You are absolutely correct that the location of the screen does not change the observed head value. However, if you are working with a multi-layer model, the location of the screen can be used to help determine what model layer the observation should be associated with and the model-computed head values do indeed vary by layer.

1) It depends on your grid resolution, but I would imagine that 30m SRTM data should be adequate in most cases. 2) Yes, is you use an automated stream-delineation method, the location of your streams may or may not match your basemap if the resolution of the grid you use for the delineation is too coarse. But for use with GMS, you turn on your basemap in GMS and then manually digitize the streams in the map module by tracing the stream locations on the basemap. You could then use a DEM to interpolate the stream elevations or you could assign them manually to the nodes in the stream network. 3) A hand-held GPS should be plenty accurate. 4) I do not know of any practical way to accurately and cheaply measure riverbed thickness and hydraulic conductivity. The typical approach is to estimate the values. All that really matters in the end is the resulting conductance values. You can examine gains or losses from streams to back-calculate or calibrate your river conductance. Also, in my experience, the model results are generally not highly sensitive to conductance.

Thanks for the kind note. Yes, hydraulic conductivity has the same units as velocity (length per time). The reason is that hydraulic conductivity (K) is a scaling constant that is used to define flow velocity as a function of the hydraulic gradient (v = ki, or v = k*(dh/dl)) where i = dh/dl = hydraulic gradient. The hydraulic gradient is unitless because it is length/length. That doesn't mean that K is a velocity, it just means that it is used to convert a dimensionless term to velocity. Does that make sense?

@@groundwatermodeling Thanks for explaining! So, hydraulic conductivity acts as a scaling constant to convert a dimensionless term to velocity. That makes sense now. Appreciate the clarification!

Thank you!

Thank you.

Good question. There are multiple ways to define the observation weights. See the MODLOW PES documentation here: water.usgs.gov/nrp/gwsoftware/modflow2000/MFDOC/pes.html And scroll down to Data Set 10 and look at the STATP and STAT-FLAG variables. GMS uses the STAT-FLAG = 1 option where the weight = 1/variance and the variance = std dev^2. Therefore the weight = 1/(std dev)^2. This makes it possible to define and think about weights in terms of the interval and confidence, which is more intuitive than standard deviation.

Thank you for the kind feedback.

Thank you. I am glad you enjoy them.

Hey, that sounds like an interesting problem. Typically we use arcs to simulate rivers and the conductance per unit length value that you assign to the arc includes the width of the river as part of the conductance, but it is a single value for the entire arc (average width over the river reach). So even though the river object is assigned only to the cells overlapped by the arc, the full width would be implicitly represented. However, there could be exchange of water between the other cells overlapped by the river. Another option you could consider is to use the General Head package and represent the river as a polygon. This would ensure that all cells overlapped by the river are properly linked to the river. Keep in mind that with the general head package there is always a direct hydraulic connection between the river and aquifer and Q is proportional to the head difference. With the River package, the river becomes disconnected once the head is below the river bottom elevation and Q becomes limited. But if you have a large river, there is probably a strong hydraulic connection anyway. Also, another challenge with using a general head polygon is assigning the river stage is a spatially varying manner. With a river arc, the stage is linearly interpolated along the length of the river. With general head we often use a single value, but there is an option in the Attribute table dialog to assign the general head stage to a TIN or Raster of river stage elevations. By the way, as I typed this up, I just launched GMS and checked and it appears that you can associate the River package with polygons in the map module as well as general head. So it would work either way. Again, you would need to set up a TIN or raster to define your river stage and river bottom elevation, but that could certainly be done. Good luck!

Can you be more specific? The components of the conceptual model are things that translate directly to inputs in MODFLOW packages. Wells are a fundamental part of the conceptual model as they directly map to one of the well packages. Drill hole data (boreholes) can be used in GMS to build 3D solid models, but they aren't represented directly in conceptual models.

@@normjones thank you for your kind reply Professor John. I follow you lectures and this benefit a lot for a novice like me to understand more about groundwater subject . I have a work on a small area roughly around 1 km x 0.5 km. I have four wells, three of them are production (discharge) wells and one well designed for recharge well (all the wells had been installed), on my opinion it is a very small area comparing to 'the conceptual model' of large region of groundwater basin (168,000 hectares) . my questions are: 1. does regional model adaptable/reliable to local scale (in terms of regional data resolution)? 2. how to asses the performance of a recharge well? by considering of what parameters shall be taken into account in order to see the number of recharge well is adequate (sufficient enough) to the sustainability of the underlying aquifers? 3. what strategy shall be taken into account in terms of the depth of the recharge well design for deep seated layer of confined aquifer? (for example: hydrostatic pressure in confined aquifer seemingly greater than water column/head in recharge well). 4. regarding to my above first question before: I only have well data that consisting: a. monthly groundwater level, b. SP and resistivity log, c. the lithology of three discharge/production wells. and unfortunately no pumping test were performed. is there any suggestion and solution for this? I know it's kind of my 'silly' question 🤐 I try to follow many lectures and guidance to groundwater modeling (I struggle to follow this due to my background, but your lecture give me a rigorous approach to groundwater problem), is that safe to infer the 'hydrogeologic' parameters for the hydrostratigraphic unit by 'empirical' way? (estimating the typical value of K, S, Sy, etc solely based on lithological characteristics?) - I apologize for my too 'basic' trivial questions - I can't thank enough for your generosity to share free lectures about groundwater. Best regards,

@@ARMUTTAQIEN The conceptual model approach is especially useful for large regional models with complex boundaries, aquifer shapes, river networks, large well datasets, etc. However, you can certainly use the conceptual model approach for smaller local-scale models. For local-scale models, you need to be very careful with the boundary conditions. If you have not done so yet, I recommend you watch the sequence of videos on boundary condition analysis. Here is the first one: ruclips.net/video/QP47ONSvs7Q/видео.html. As described in the video, calibration can be tricky with local scale models due to the issue of non-uniqueness. You can address that problem by first building a regional model, calibrating the model, and then transferring the boundary conditions to the local scale model. Another (often simpler) approach is to build your local scale model and then perform your analysis/design using range of hydraulic conductivity, Sy, etc values based on your best guess of the parameter values in order to bracket the problem (this relates to question 4). As for your recharge well, I am not sure what your question is (number, sustainability, etc). Are you trying to determine what injection rate to use on the well? Or are you simply wanting to come up with a reasonable model that can be used to simulate various scenarios with the well?

@@normjones hello prof Jones, I've tried to make a model using multiple packages that correspond to my data requirements, I know this is absolutely a trivial question (since I'm not a hydrogeologist), How can we define the 'water table' in modflow GMS? which heads option shall be used? thank you in advance

@@ARMUTTAQIEN I am not sure I understand your question. Are you talking about starting heads? Some kind of head-based boundary condition? Or observed heads in monitoring wells for calibration?

I think it is in the right spot. It explain how to set up the MODFLOW layer elevation arrays.

@@normjones MODFLOW is a free software. With this video, the author is introducing a comercial software (GMS), and its own features, that are not available in MODFLOW or Model Muse. I don´t agree they should mix too softwares in the same playlist, called MODFLOW.

That is very kind of you. Happy to hear you find them helpful.

That is very kind of you.

I cover the general 3D case in the prior video. Here his the link: ruclips.net/video/zqMcbitcwYE/видео.html

Haha. You are welcome!

The interval is typically quite subjective. If you are doing a large regional model and/or don't have a lot of good data to build your model, you may want to go with a larger interval of 5-10 meters. If you are doing a more localized model and/or you have lots of high quality data, you can use 1-3 meters. In either case, you typically calibrate until you are unable to lower the residual error any further, so ultimately you may want to adjust the interval so that the calibration targets (red, green, yellow bars) are helpful in showing the spatial distribution of the errors. For example, if your interval is too big, all of the targets will be green. If your interval is too small, all of your targets will be red. I hope this helps.

@@normjones yes it definitely does help. Can we go the other way around by estimating the transient head std. Deviations of observations wells and at 95% confidence interval obtain the head interval?

@@ankitt25 Yes, you certainly can. But in my experience, that is rarely done. Remember that it is the standard deviation of the measurement error, not the standard deviation of measurement values.

You are welcome. Glad you enjoyed the video.

You are welcome.

You are welcome!

Can you give me more detail?

@@excelvbaprimer sir Do you have an email to send the error message Thanks for your attention

What new lecture?

Thank you!

Glad you liked it.