From 0d292ac4e62812451ba5d4f363a5c63d7a4da5ad Mon Sep 17 00:00:00 2001 From: FransRoelofsen Date: Wed, 24 Jan 2024 11:06:28 +0000 Subject: [PATCH] deploy: 30de9cce920ad7c3d5851b9689013684b3d52be6 --- index.html | 2 +- search.json | 14 +++++++------- tutorial.html | 4 ++-- tutorial_Rijsenhout.html | 23 ++++++++++++----------- tutorial_TheHague.html | 29 ++++++++++++++--------------- 5 files changed, 36 insertions(+), 36 deletions(-) diff --git a/index.html b/index.html index 1ee76ea..b384027 100644 --- a/index.html +++ b/index.html @@ -181,7 +181,7 @@

QGIS-Tim

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diff --git a/search.json b/search.json index 16b1c40..7747fc5 100644 --- a/search.json +++ b/search.json @@ -88,7 +88,7 @@ "href": "tutorial_TheHague.html#getting-started", "title": "Building Pit The Hague", "section": "Getting Started", - "text": "Getting Started\n\nLaunch QGIS from your START menu, from your desktop or click on …\\QGIS3.28.0\\bin\\qgis-bin.exe.\n\n\nIntermezzo: QGIS language settings\nPerhaps your QGIS was installed in another language than English. Because the Tutorial refers to the English version, let’s change to English.\n\nFrom the main menu click on Settings and select Options (e.g. in Dutch Extra and Opties).\nIn the new window go to the General section (Dutch: Algemeen) on the left.\nCheck the box to allow Override System Locale (Dutch: Landinstellingen negeren) and expand this sub menu.\nFrom the drop-down menu “User interface translation” (Dutch: Vertaling gebruikers-interface) select American English and click OK.\nClose QGIS and open it again to activate your language change.\n\n\nWe start with the creation of a new QGIS project.\n\nFrom the main menu click on Project and select New.\n\nThe case in this tutorial is located in The Netherlands, so next we select the appropriate projection.\n\nFrom the main menu click on Project and select Properties.\nIn the Properties window select the category CRS, search for “EPSG:28992” and you find “Amersfoort / RD New”. Select this option and click the Apply button, followed by the OK button to close the window.\n\n\nIn case your work is mostly in The Netherlands and in the “Amersfoort / RD New” projection, consider making this your default projection.\n\nFrom the main menu click on Settings and select Options….\nIn the section CRS and Transforms select CRS (handling), pick the radio button Use a default CRS and select “EPSG:28992 -Amersfoort / RD New”.\nClick OK.\nClose this window.\n\n\n\nInstall plugins\nThis is the moment to import four plugins needed for this tutorial:\n\nthe QGIS-Tim plugin (developed by Deltares).\nthe iMOD plugin (developed by Deltares).\nthe Value Tool. A plugin to display in table or plot values from raster layers (or mesh layers) at the current mouse position.\nthe PDOK plugin. This plugin gives access to a large database from which we will load the topographic maps and use the navigation option.\n\nTo install the plugins from QGIS you need an internet connection!\n\nNo internet connection? Follow the next steps to import the two Deltares’ plugins from a ZIP file provided in the Tutorial Dataset.\n\nGo to Plugins from the main menu and select Manage and Install Plugins… to open the plugin window.\nOn the left section select Install from ZIP.\nClick the Browse button () and select the ZIP file “QGIS-Tim_Tutorial\\QGIS-iMOD-plugin.zip”.\nClick Install Plugin.\nIn the same way, install the QGIS-Tim plugin using the ZIP file “QGIS-Tim_Tutorial\\QGIS-Tim-plugin.zip”.\n\n\nIf you have an internet connection, all four plugins can be downloaded within QGIS.\n\nAt the top, find the Plugins menu (~sixth object in the menubar).\nFind \"Manage and Install plugins\" (~first object in drop-down).\nFind \"All\" (~first in left section).\nSearch for \"Qgis-Tim\".\nClick \"Install Plugin\".\nSearch for “iMOD” and install it.\nSearch for “Value Tool” and install it.\nSearch for “PDOK services plugin” and install it.\nMake sure that under Plugins > Manage and Install Plugins > Installed now the 4 added plugins are checked.\nClose the Plugins window.\n\nSee in the toolbar section of QGIS that the plugins are installed:\n\niMOD Toolbar \nQGIS-Tim \nValue Tool \nPDOK Services Plugin \n\nFurther in this Tutorial we will use some default toolbars that might be hidden at the moment. Let’s check that and unhide if necessary.\n\nSelect View from the main menu and choose Panels and be sure these two toolbars are checked: - Layers; - Browser.\nSelect View from the main menu and choose Toolbars and be sure these three toolbars are checked: - Advanced Digitizing Toolbar; - Snapping Toolbar; - Attributes Toolbar.\n\n\n\nPrepare your project\nFor navigation purposes, let’s load a topographic map for The Netherlands from the online PDOK database.\n\nNo internet connection? Follow the next steps to import a simple PNG file as a background.\n\nGo to Layer in the main menu, go to Add layer and select Add Raster layer.\nUse the Browse button () and from the tutorial material select “…\\QGIS-Tim_Tutorial-TheHague\\TopographicMapTheHague.png”.\nClick on Add and Close the window.\nIf you do not see the map, select the layer “TopographicMapTheHague”, click your right mouse button and select “Zoom to Layer(s)”.\nContinue after step 23.\n\n\n\nIf you do have an internet connection click on the PDOK plugin button () to open the “PDOK Services Plugin” window.\nFrom the tab PDOK Services search for “pastel” and you will find a WMTS type layer called “BRT Achtergrondkaart WMTS”.\nSelect the layer.\nIn the section “laag toevoegen” click the button Onder.\nClose the PDOK window.\n\nOur project area is in the centre of the city of The Hague so let’s navigate to that city using the PDOK plugin.\n\nType “Parkstraat” in the PDOK search field, near the PDOK button ()\nOne of the locations PDOK will find is “Parkstraat, ’s-Gravenhage”. Click on it and QGIS will fly you to the project location.\n\nLet’s now open a shape file containing the circumference of the building location.\n\nGo to Layer in the main menu, go to Add layer and select Add Vector layer.\nUse the Browse button () and from the tutorial material select “…\\QGIS-Tim_Tutorial-TheHague\\building_pit.shp”.\nClick on Add and Close the window.\n\n Tip: a fast alternative for adding layers: from the menu View > Toolbar add the Manage Layers Toolbar and use the button .\n\nIn the Layers panel on the left, select the layer “building_pit”.\nClick your right mouse button and from the menu select Properties.\nIn the new window go to the section Symbology on the left and try to pick a polygon style with only a contour color.\nClick on OK a to save and close the window.\n\nLet’s save this project to be able to return to it later or in case of a crash of QGIS.\n\nGo to Project in the main menu, select Save As and select a folder and a file name for your project, e.g. “…\\QGIS-Tim_Tutorial-TheHague\\TheHague.qgz”\n\n\n\nOpen the QGIS-Tim panel\nNow we are ready to activate the QGIS-Tim plugin.\n\nClick on the QGIS-Tim plugin button () and the QGIS-Tim panel appears.\nGo to the tab GeoPackage. Here we will create an empty database (geopackage) to store all elements and parameters for the model.\nClick the New button to create the GeoPackage and save it for instance in the folder with your tutorial data, e.g. “..\\QGIS-Tim_Tutorial-TheHague\\case-TheHague.gpkg”.\n\nYour window looks like in Figure 4.\n\n\n\nFigure 4: QGIS-Tim panel\n\n\n\nCheck in the Layers panel on the left that your new geopackage is added as a group. A sub group timml for the steady state model input, the sub group ttim for the transient model input and a series of output formats (vector/mesh/raster).\n\nIf you had no introduction to the Tim plugin, read the Intermezzo below for a general explanation of the components.\n\nIntermezzo: introduction Tabs on the Tim panel\n\nGeoPackage: an overview of the elements in your geopackage. In case you switch to transient modelling, an extra column with ttim elements is added.\nElements: a list of 14 Tim elements from which you can build your model.\nCompute: here you can define your domain and cell size, decide if your model is transient or not and change the output name.\nExtract: open an existing 3d geohydrological model (NC file) and extract the data for your project area.\n\n\nLet’s save this project to be able to return to it later or in case of a crash of QGIS.\n\nGo to Project in the main menu, select Save As and select a folder and a file name for your project, e.g. “…\\QGIS-Tim_Tutorial-TheHague\\TheHague.qgz”" + "text": "Getting Started\n\nLaunch QGIS from your START menu, from your desktop or click on …\\QGIS3.28.0\\bin\\qgis-bin.exe.\n\n\nIntermezzo: QGIS language settings\nPerhaps your QGIS was installed in another language than English. Because the Tutorial refers to the English version, let’s change to English.\n\nFrom the main menu click on Settings and select Options (e.g. in Dutch Extra and Opties).\nIn the new window go to the General section (Dutch: Algemeen) on the left.\nCheck the box to allow Override System Locale (Dutch: Landinstellingen negeren) and expand this sub menu.\nFrom the drop-down menu “User interface translation” (Dutch: Vertaling gebruikers-interface) select American English and click OK.\nClose QGIS and open it again to activate your language change.\n\n\nWe start with the creation of a new QGIS project.\n\nFrom the main menu click on Project and select New.\n\nThe case in this tutorial is located in The Netherlands, so next we select the appropriate projection.\n\nFrom the main menu click on Project and select Properties.\nIn the Properties window select the category CRS, search for “EPSG:28992” and you find “Amersfoort / RD New”. Select this option and click the Apply button, followed by the OK button to close the window.\n\n\nIn case your work is mostly in The Netherlands and in the “Amersfoort / RD New” projection, consider making this your default projection.\n\nFrom the main menu click on Settings and select Options….\nIn the section CRS and Transforms select CRS (handling), pick the radio button Use a default CRS and select “EPSG:28992 -Amersfoort / RD New”.\nClick OK.\nClose this window.\n\n\n\nInstall plugins\nThis is the moment to import four plugins needed for this tutorial:\n\nthe QGIS-Tim plugin (developed by Deltares).\nthe iMOD plugin (developed by Deltares).\nthe Value Tool. A plugin to display in table or plot values from raster layers (or mesh layers) at the current mouse position.\nthe PDOK plugin. This plugin gives access to a large database from which we will load the topographic maps and use the navigation option.\n\nTo install the plugins from QGIS you need an internet connection!\n\nNo internet connection? Follow the next steps to import the two Deltares’ plugins from a ZIP file provided in the Tutorial Dataset.\n\nGo to Plugins from the main menu and select Manage and Install Plugins… to open the plugin window.\nOn the left section select Install from ZIP.\nClick the Browse button () and select the ZIP file “QGIS-Tim_Tutorial\\QGIS-iMOD-plugin.zip”.\nClick Install Plugin.\nIn the same way, install the QGIS-Tim plugin using the ZIP file “QGIS-Tim_Tutorial\\QGIS-Tim-plugin.zip”.\n\n\nIf you have an internet connection, all four plugins can be downloaded within QGIS.\n\nAt the top, find the Plugins menu (~sixth object in the menubar).\nFind \"Manage and Install plugins\" (~first object in drop-down).\nFind \"All\" (~first in left section).\nSearch for \"Qgis-Tim\".\nClick \"Install Plugin\".\nSearch for “iMOD” and install it.\nSearch for “Value Tool” and install it.\nSearch for “PDOK services plugin” and install it.\nMake sure that under Plugins > Manage and Install Plugins > Installed now the 4 added plugins are checked.\nClose the Plugins window.\n\nSee in the toolbar section of QGIS that the plugins are installed:\n\niMOD Toolbar \nQGIS-Tim \nValue Tool \nPDOK Services Plugin \n\nFurther in this Tutorial we will use some default toolbars that might be hidden at the moment. Let’s check that and unhide if necessary.\n\nSelect View from the main menu and choose Panels and be sure these two toolbars are checked: - Layers; - Browser.\nSelect View from the main menu and choose Toolbars and be sure these three toolbars are checked: - Advanced Digitizing Toolbar; - Snapping Toolbar; - Attributes Toolbar.\n\n\n\nPrepare your project\nFor navigation purposes, let’s load a topographic map for The Netherlands from the online PDOK database.\n\nNo internet connection? Follow the next steps to import a simple PNG file as a background.\n\nGo to Layer in the main menu, go to Add layer and select Add Raster layer.\nUse the Browse button () and from the tutorial material select “…\\QGIS-Tim_Tutorial-TheHague\\TopographicMapTheHague.png”.\nClick on Add and Close the window.\nIf you do not see the map, select the layer “TopographicMapTheHague”, click your right mouse button and select “Zoom to Layer(s)”.\nContinue after step 23.\n\n\n\nIf you do have an internet connection click on the PDOK plugin button () to open the “PDOK Services Plugin” window.\nFrom the tab PDOK Services search for “pastel” and you will find a WMTS type layer called “BRT Achtergrondkaart WMTS”.\nSelect the layer.\nIn the section “laag toevoegen” click the button Onder.\nClose the PDOK window.\n\nOur project area is in the centre of the city of The Hague so let’s navigate to that city using the PDOK plugin.\n\nType “Parkstraat” in the PDOK search field, near the PDOK button ()\nOne of the locations PDOK will find is “Parkstraat, ’s-Gravenhage”. Click on it and QGIS will fly you to the project location.\n\nLet’s now open a shape file containing the circumference of the building location.\n\nGo to Layer in the main menu, go to Add layer and select Add Vector layer.\nUse the Browse button () and from the tutorial material select “…\\QGIS-Tim_Tutorial-TheHague\\building_pit.shp”.\nClick on Add and Close the window.\n\n Tip: a fast alternative for adding layers: from the menu View > Toolbar add the Manage Layers Toolbar and use the button .\n\nIn the Layers panel on the left, select the layer “building_pit”.\nClick your right mouse button and from the menu select Properties.\nIn the new window go to the section Symbology on the left and try to pick a polygon style with only a contour color.\nClick on OK a to save and close the window.\n\nLet’s save this project to be able to return to it later or in case of a crash of QGIS.\n\nGo to Project in the main menu, select Save As and select a folder and a file name for your project, e.g. “…\\QGIS-Tim_Tutorial-TheHague\\TheHague.qgz”\n\n\n\nOpen the QGIS-Tim panel\nNow we are ready to activate the QGIS-Tim plugin.\n\nClick on the QGIS-Tim plugin button () and the QGIS-Tim panel appears.\nGo to the tab Model Manager. Here we will create an empty database (geopackage) to store all elements and parameters for the model.\nClick the New button to create the GeoPackage and save it for instance in the folder with your tutorial data, e.g. “..\\QGIS-Tim_Tutorial-TheHague\\case-TheHague.gpkg”.\n\nYour window looks like in Figure 4.\n\n\n\nFigure 4: QGIS-Tim panel\n\n\n\nCheck in the Layers panel on the left that your new geopackage is added as a group. A sub group timml for the steady state model input, the sub group ttim for the transient model input and a series of output formats (vector/mesh/raster).\n\nIf you had no introduction to the Tim plugin, read the Intermezzo below for a general explanation of the components.\n\nIntermezzo: introduction Tabs on the Tim panel\n\nModel Manager: an overview of the elements in your geopackage. In case you switch to transient modelling, an extra column with ttim elements is added.\nElements: a list of at least 16 Tim elements from which you can build your model.\nResults: here you can define your domain and cell size, decide if your model is transient or not and manage the output files.\n\n\nLet’s save this project to be able to return to it later or in case of a crash of QGIS.\n\nGo to Project in the main menu, select Save As and select a folder and a file name for your project, e.g. “…\\QGIS-Tim_Tutorial-TheHague\\TheHague.qgz”" }, { "objectID": "tutorial_TheHague.html#start-your-tim-model", @@ -102,7 +102,7 @@ "href": "tutorial_TheHague.html#computing-the-groundwater-head-drawdown", "title": "Building Pit The Hague", "section": "Computing the groundwater head drawdown", - "text": "Computing the groundwater head drawdown\n\nZoom in or out to desired domain for which you want to see the model results.\nIn the QGIS-Tim panel select the tab Compute.\nSelect the button Set to current extent to define the Domain.\nGrid spacing will follow automatically but for now make the results mesh more dense by changing “Grid spacing” to 3.00 m.\nIn the “Output” section give the name of the file where you want to store the results.\nFor contouring, select the check box “Auto-generate contours”.\nSet the increment for contouring to a proper value: 0.5, 0.25 or 0.1 as applicable for your study.\nPress the Compute button to have the program perform the calculations.\n\nA black Python.exe window pops up indicating that the TIM calculation started on the background. You can ignore this window but keep it open. Of course you van minimize it. If the calculation was completed successful, you will see this echo in QGIS. ." + "text": "Computing the groundwater head drawdown\n\nZoom in or out to desired domain for which you want to see the model results.\nIn the QGIS-Tim panel select the tab Results.\nSelect the button Set to current extent to define the Domain.\nGrid spacing will follow automatically but for now make the results mesh more dense by changing “Grid spacing” to 3.00 m.\nIn the “Output” section give the name of the file where you want to store the results.\nFor contouring, select the check box “Auto-generate contours”.\nSet the increment for contouring to a proper value: 0.5, 0.25 or 0.1 as applicable for your study.\nPress the Compute button to have the program perform the calculations.\n\nA black Python.exe window pops up indicating that the TIM calculation started on the background. You can ignore this window but keep it open. Of course you van minimize it. If the calculation was completed successful, you will see this echo in QGIS. ." }, { "objectID": "tutorial_TheHague.html#studying-output-results", @@ -116,14 +116,14 @@ "href": "tutorial_TheHague.html#making-calculations-with-parameter-variations-or-checking-bandwidth", "title": "Building Pit The Hague", "section": "Making calculations with parameter variations or checking bandwidth", - "text": "Making calculations with parameter variations or checking bandwidth\nThe authorities demand a drawdown effect of dewatering at a maximum of 0.10 m at surrounding buildings. This means that improvements for leakage control are needed but first we need to discover what parameter to focus on.\nTo check whether the wall resistance or the bottom resistance of the layer 1 (below the building pit) is more important we can make 2 variations; one with C-clay=200 d and one with R-wall=500 d.  Of course you can change your model input, rerun the model and overwrite your model results. The next steps show you how to change the model input and save the results in separate .gpkg and .nc files.\n\nIn the input group select layer timml Aquifer:…\nOpen the Attrribute Table (F6) and change the value for “aquitard_c” in layer 1 into 200 d.\nIn the QGIS-Tim panel go to the tab Compute and change the name of the output, e.g. case-TheHague_v1.\nClick Compute to run variant 1.\n\nCheck in the Layers panel and see that the results are not overwritten but added to the groups, e.g. layer case-TheHague_v1-timml Observation:observations is added to the group Vector.\n\nFill in your calculated heads at the observation locations in Table 4 or use Excel.\n\n\n\nTable 3: Table: calculated heads [m] in observation points for 2 variants compared to the initial situations. Your values will differ.\n\n\n\n\n\n\n\n\n\n\n\nObservation location\nDefault:Cc=40dRw=100d*\n your value:\nVariant 1:Cc=200dRw=100d*\nyour value:\nVariant 2:Cc=40dRw=500d*\nyour value:\n\n\n\n\nPb1 centre pit\n-3.95\n…\n-10.44\n…\n-4.00\n…\n\n\nPb2 south corner\n-0.43\n…\n-0.54\n…\n-0.35\n…\n\n\nPb3 street corner\n-0.35\n…\n-0.43\n…\n-0.31\n…\n\n\nPb4 south point\n-0.29\n…\n-0.32\n…\n-0.25\n…\n\n\nPb5 east wall\n-0.51\n…\n-0.70\n…\n-0.41\n…\n\n\n\n\n* Known issue in TimML: you have to multiply Rw by layer permeability (Rw*10).\nLet’s now run Variant 2.\n\nIn layer timml Aquifer:… reset the value for “aquitard_c” in layer 1 to the default of 40 d.\nIn layer timml Leaky Line Doublet:… change the value for “resistance” into 5000 d (500x10).\nIn the QGIS-Tim panel go to the tab Compute and change the name of the output, e.g. case-TheHague_v2.\nClick Compute to run variant 2.\nFill in your calculated heads at the observation locations in the table above.\n\nTo get the same lowering in the building pit, in the second variation the well flow might be reduced to 33% (10m3/d per well). For the sheet pile wall, increasing the wall quality or decreasing interlock leakage doesn’t make a big difference. We can conclude that the best investment during the phase of design would be to perform extra hydrogeological research, e.g. by making more cpt’s, borings or performing a pumping test." + "text": "Making calculations with parameter variations or checking bandwidth\nThe authorities demand a drawdown effect of dewatering at a maximum of 0.10 m at surrounding buildings. This means that improvements for leakage control are needed but first we need to discover what parameter to focus on.\nTo check whether the wall resistance or the bottom resistance of the layer 1 (below the building pit) is more important we can make 2 variations; one with C-clay=200 d and one with R-wall=500 d.  Of course you can change your model input, rerun the model and overwrite your model results. The next steps show you how to change the model input and save the results in separate .gpkg and .nc files.\n\nIn the input group select layer timml Aquifer:…\nOpen the Attrribute Table (F6) and change the value for “aquitard_c” in layer 1 into 200 d.\nIn the QGIS-Tim panel go to the tab Results and change the name of the output, e.g. case-TheHague_v1.\nClick Compute to run variant 1.\n\nCheck in the Layers panel and see that the results are not overwritten but added to the groups, e.g. layer case-TheHague_v1-timml Observation:observations is added to the group Vector.\n\nFill in your calculated heads at the observation locations in Table 4 or use Excel.\n\n\n\nTable 3: Table: calculated heads [m] in observation points for 2 variants compared to the initial situations. Your values will differ.\n\n\n\n\n\n\n\n\n\n\n\nObservation location\nDefault:Cc=40dRw=100d*\n your value:\nVariant 1:Cc=200dRw=100d*\nyour value:\nVariant 2:Cc=40dRw=500d*\nyour value:\n\n\n\n\nPb1 centre pit\n-3.95\n…\n-10.44\n…\n-4.00\n…\n\n\nPb2 south corner\n-0.43\n…\n-0.54\n…\n-0.35\n…\n\n\nPb3 street corner\n-0.35\n…\n-0.43\n…\n-0.31\n…\n\n\nPb4 south point\n-0.29\n…\n-0.32\n…\n-0.25\n…\n\n\nPb5 east wall\n-0.51\n…\n-0.70\n…\n-0.41\n…\n\n\n\n\n* Known issue in TimML: you have to multiply Rw by layer permeability (Rw*10).\nLet’s now run Variant 2.\n\nIn layer timml Aquifer:… reset the value for “aquitard_c” in layer 1 to the default of 40 d.\nIn layer timml Leaky Line Doublet:… change the value for “resistance” into 5000 d (500x10).\nIn the QGIS-Tim panel go to the tab Results and change the name of the output, e.g. case-TheHague_v2.\nClick Compute to run variant 2.\nFill in your calculated heads at the observation locations in the table above.\n\nTo get the same lowering in the building pit, in the second variation the well flow might be reduced to 33% (10m3/d per well). For the sheet pile wall, increasing the wall quality or decreasing interlock leakage doesn’t make a big difference. We can conclude that the best investment during the phase of design would be to perform extra hydrogeological research, e.g. by making more cpt’s, borings or performing a pumping test." }, { "objectID": "tutorial_TheHague.html#sheet-piles-with-extra-depth", "href": "tutorial_TheHague.html#sheet-piles-with-extra-depth", "title": "Building Pit The Hague", "section": "Sheet piles with extra depth", - "text": "Sheet piles with extra depth\nSuppose the best guess value of the clay layer resistance was right, then a mitigation measure for the effect of dewatering in the construction phase could be the installation of the wall to a deeper level where additional hydraulic resistance of 100d can be found at a depth of -13 m to -15 m NAP.\nIf we want to create extra depth of the sheet pile we will have to introduce it in a deeper layer. There are 2 options to implement it in your model:\n\nAdd a copy of the geometry of the sheet pile wall to the existing Leaky Line Doublet shape and assign it to layer 1.\nWe recommend to create an extra Leaky Line Doublet element. In this case it is more easy to switch on/off this additional element in your sensitivity analysis.\n\nHow to copy the sheet pile wall to an extra Leaky Line Doublet element?\n\nIn the QGIS-Tim panel go to the tab Elements and add a second Leaky Line Doublet and give it a name, e.g. “sheet_pile_L1”\nGo to the tab GeoPackage and see that the element separately is added to the list. Here is can switch this element on / off for a calculation.\nIn the Layers panel select the new layer timml Leaky Line Doublet:sheet_pile_l1.\nOpen its Attribute Table (F6) and start the editing mode. The table is empty.\nAlso open the Attribute Table of the first Leaky Line Doublet and select the existing element.\nClick on the Copy button () in the source table to copy the selected row to the clipboard.\n\n\n\nIn the target table, paste it with the Paste button () as a new layer.\nAssign this new sheet pile to layer=1.\nStop editing and save the new element.\nClick Compute to start the computation again.\n\nThe results are directly visible in the contours and cross-section again. We can conclude that the drawdown in the building pit increases with a factor of almost 2 (-7.48 m at the centre of the building pit). Therefore, we adjust the well flow to 3.95/7.48*30=15.54 m3/d per well.\n\nImplement this change in the timm Well element and recalculate the model.\n\n\n\n\nFigure 13: Cross section of groundwater heads per layer, sheet pile wall R=500d in layers 0 and 1 and 8 wells at 15.25 m3/d each in layer0\n\n\nWe conclude that the drawdown of groundwater level around the building pit with deep sheet piles decreased significantly.\nNext also alternatives with a shallow concrete cut-off wall will be calculated for a shallow and a deep wall. In that case we have R=1000 d, but note that the input in the attribute than becomes k*R=10000 due to the error in Tim.\n\nAfter changing the value in attribute tables of wall elements, we can compute again, switching off and on the element for the deep wall section (tab Geopackage on the QGIS-Tim panel).\n\nAgain extra calculation is needed to adjust well extractions for drawdown in the building pit. Results of calculations are gathered in the following table, showing extractions and head outside the wall at South East monitoring position.\n\n\nTable 4: Effect of 4 Wall alternatives on extraction rate and drawdown South East.\n\n\n\n\n\n\n\n\nWall alternative at c1=40 d\nWall resistance [d]\nGroundwater extraction [m3/d]\nHead SE monitoring [dh in m]\n\n\n\n\nShallow sheet pile wall\n100\n240\n-0.39\n\n\nDeep sheet pile wall\n100\n122\n-0.16\n\n\nShallow cut-off wall\n1000\n208\n-0.30\n\n\nDeep cut-off wall\n1000\n80\n-0.04\n\n\n\n\nInstallation of 15 m deep sheet pile wall or cut-off wall can be elaborated in a geotechnical design. Still, probably some decrease of interlock leakage is needed when sheet piles are chosen. Interlock sealing or maybe irrigation of water in a shallow drain pipe around the building pit could lead to approval by authorities." + "text": "Sheet piles with extra depth\nSuppose the best guess value of the clay layer resistance was right, then a mitigation measure for the effect of dewatering in the construction phase could be the installation of the wall to a deeper level where additional hydraulic resistance of 100d can be found at a depth of -13 m to -15 m NAP.\nIf we want to create extra depth of the sheet pile we will have to introduce it in a deeper layer. There are 2 options to implement it in your model:\n\nAdd a copy of the geometry of the sheet pile wall to the existing Leaky Line Doublet shape and assign it to layer 1.\nWe recommend to create an extra Leaky Line Doublet element. In this case it is more easy to switch on/off this additional element in your sensitivity analysis.\n\nHow to copy the sheet pile wall to an extra Leaky Line Doublet element?\n\nIn the QGIS-Tim panel go to the tab Elements and add a second Leaky Line Doublet and give it a name, e.g. “sheet_pile_L1”\nGo to the tab Model Manager and see that the element separately is added to the list. Here is can switch this element on / off for a calculation.\nIn the Layers panel select the new layer timml Leaky Line Doublet:sheet_pile_l1.\nOpen its Attribute Table (F6) and start the editing mode. The table is empty.\nAlso open the Attribute Table of the first Leaky Line Doublet and select the existing element.\nClick on the Copy button () in the source table to copy the selected row to the clipboard.\n\n\n\nIn the target table, paste it with the Paste button () as a new layer.\nAssign this new sheet pile to layer=1.\nStop editing and save the new element.\nClick Compute to start the computation again.\n\nThe results are directly visible in the contours and cross-section again. We can conclude that the drawdown in the building pit increases with a factor of almost 2 (-7.48 m at the centre of the building pit). Therefore, we adjust the well flow to 3.95/7.48*30=15.54 m3/d per well.\n\nImplement this change in the timm Well element and recalculate the model.\n\n\n\n\nFigure 13: Cross section of groundwater heads per layer, sheet pile wall R=500d in layers 0 and 1 and 8 wells at 15.25 m3/d each in layer0\n\n\nWe conclude that the drawdown of groundwater level around the building pit with deep sheet piles decreased significantly.\nNext also alternatives with a shallow concrete cut-off wall will be calculated for a shallow and a deep wall. In that case we have R=1000 d, but note that the input in the attribute than becomes k*R=10000 due to the error in Tim.\n\nAfter changing the value in attribute tables of wall elements, we can compute again, switching off and on the element for the deep wall section (tab “Model Manager” on the QGIS-Tim panel).\n\nAgain extra calculation is needed to adjust well extractions for drawdown in the building pit. Results of calculations are gathered in the following table, showing extractions and head outside the wall at South East monitoring position.\n\n\nTable 4: Effect of 4 Wall alternatives on extraction rate and drawdown South East.\n\n\n\n\n\n\n\n\nWall alternative at c1=40 d\nWall resistance [d]\nGroundwater extraction [m3/d]\nHead SE monitoring [dh in m]\n\n\n\n\nShallow sheet pile wall\n100\n240\n-0.39\n\n\nDeep sheet pile wall\n100\n122\n-0.16\n\n\nShallow cut-off wall\n1000\n208\n-0.30\n\n\nDeep cut-off wall\n1000\n80\n-0.04\n\n\n\n\nInstallation of 15 m deep sheet pile wall or cut-off wall can be elaborated in a geotechnical design. Still, probably some decrease of interlock leakage is needed when sheet piles are chosen. Interlock sealing or maybe irrigation of water in a shallow drain pipe around the building pit could lead to approval by authorities." }, { "objectID": "tutorial_TheHague.html#effect-of-a-not-closed-wall-about-20-cm", @@ -137,14 +137,14 @@ "href": "tutorial_TheHague.html#using-python-for-sensitivity-analyses-with-a-qgis-tim-model", "title": "Building Pit The Hague", "section": "Using Python for sensitivity analyses with a QGIS-Tim model", - "text": "Using Python for sensitivity analyses with a QGIS-Tim model\nQGIS-Tim offers the opportunity to export the geopackage of the created model to a Python script. This makes it possible to use the script for other ways of calculation, e.g.: - Calculation of model results in other Python environments, like Anaconda or Spyder or in a notebook. - Use in other Python oriented programs, like the Probabilistic Toolkit.\n\nIf input of all elements is ready and the model has proved to run properly, go to the QGIS-Tim panel and the tab Geopackage.\nAt the bottom press the button Convert GeoPackage to Python script.\nAfter a short period for translation in Python the explorer panel appears where you can enter the name you want to give for the python file, e.g. “case-TheHague.py” and store it in a directory you choose to save your work. The file looks like:\n\n\n\n\nFigure 15: Python script\n\n\nAs can be seen the converted Python file start with calls (e.g. import timml) to main necessary Python packages. After that, for each timm element in the model, all data coordinates and parameter values follow. At the end of the Python file the “model.solve” command is stated after which all head values in the domain with the desired mesh density are determined and also at demanded observation points.\nAs can be seen the Python script for TimML is written in a very dedicated and condensed manner.\nTo get the Python file running in a platform like Anaconda or Spyder, extra lines should be added at wish, to get the output that the user needs.\nNext this file can be used for geostatistical and scenario-analysis. There are several ways of handling this kind of study, like writing an additional Python program to perform repeated calculations and statistical analysis on results. But an easy way is to use the Probabilistic Toolkit (PTK), a platform for statistical analysis to be used together with geotechnical design programs, developed by Deltares. The PTK can be used for study of model sensitivity for variation of parameter values or reliability analysis.\nThe PTK can be downloaded free of charge at Probabilistic Toolkit - download.\n\nOpen the Probabilistic Toolkit from your desktop () or Windows menu (Deltares folder).\n\nThe Toolkit opens at the first of 5 tabs: Model.\n\nIn the section Model Type check if the dropdown menu Type is set to Internal.\nIn the section Model Type check if the dropdown menu Language is set to Python and a the field Version appears.\nSelect the tree points (‘…’) in the field Version and give the path where PTK can find the Python interpreter, e.g. Spyder at “C:\\roelofs_fs\\_software\\deltaforge\\pythonw.exe”.\nThan you copy the content of the Python file we converted from QGIS-Tim into the window “Model code”.\n\nWe handle the process in this way because we want to change some lines in the source code to get the program running in PTK.\nNext the specific parameters must be selected that are expected to be probably most relevant to variations in results. In the source code used in the PTK, those parameters will not have input on a value but need to be mentioned with a name that the PTK can use for input selection in the calculations. The parameters that seem to be important are:\n\nThe hydraulic resistance of the sheet pile wall Rwall.\nThe resistance c1 of the first clay layer.\nThe permeability of the sand layer k01.\nThe resistance c2 of the second clay layer at -14 m NAP.\n\n\n\n\nFigure 16: Declaration of Variables to control the analysis and first guess for values.\n\n\nIn PTK we have to set these parameters:\n\nIn the PTK panel Input click 4 times on the Add button (), to add 4 variables and name them Rshp, czba, khol and cbasis (see Figure 16)\nIn the tab Variables give these 4 variables the values 10000, 40, 10 and 100.\nReturn to the tab Model and assign these variable values to the parameters in the source code by copying this code block to the top of the Python source code (see Figure 17). Rwall = Rshp c0 = czba k0 = khol c2 = cbasis\nFinaly, replace the fixed value (NB! 2 times “Rwall”, for each sheet pile definition) in the Python code for the parameter name (see red elements in Figure 17).\n\n\n\n\nFigure 17: Replace parameters in the Python code.\n\n\n\nAt the end of the source code, eliminate the following lines from the converted file:\n\nhead = model.headgrid(xg=np.arange(80940.0, 81166.0, 4), yg=np.arange(455554.0, 455360.0, -4) )\n\nAlso eliminate the lines:\n\nobservation_peilbuis_2 = model.head(x=80970.16497991727, y=455495.54316352855) observation_peilbuis_3 = model.head(x=81004.86605597858, y=455389.68291883526) observation_peilbuis_4 = model.head(x=81049.06450220713, y=455485.0645022071)\n\nBecause we only are interested in 2 points, use the first two observation points and add these lines at the end of the Python script:\n\npb0 = observation_observations_0[0] pb1 = observation_observations_1[0]\n\nIn the panel Output of the PTK use the Add button () the new defined variables “pb0” and “pb1”.\nCheck if the program works properly. Field Analysis must contain “Run model”, field Results must contain “Single run”\nPress the RUN button () to calculate the model.\n\nIn the tab Run model we find the results of our calculation.\n\nCheck if it complies with your earlier calculations in QGIS-Tim.\n\n\n\n\nFigure 18: Result of test run in PTK to check model outcome.\n\n\nIf results are as expected, we can step to a sensitivity analyses.\n\nIn the tab Field, set the Analysis option to “Sensitivity*.\nGo to the tab Variables.\n\nFor each selected parameter a distribution is defined with certain limits or characteristic values. Distribution formulas can be chosen based on knowhow of the user. Best guess of the parameter value distributions is given in the next example window.\n\nChange the distributon types for each Variable in the column “Distrubution” and fill in the other values.\n\n\n\n\nFigure 19: Best guess of the parameter value distributions\n\n\n\nSelect the row with sheetpile resistance (Rshp) and in the panel below the distribution is shown (see Figure 20).\n\nParameter value distributions of silt layer resistance (czba), basic peat layer resistance (cbasis) and permeability of Holocene sand (khol) are shown in graphs below.\n\n\n\nFigure 20: Parameter value distributions of sheetpile resistance Rshp\n\n\n\n\n\nFigure 21: Parameter value distributions of silt layer resistance czba\n\n\n\n\n\nFigure 22: Parameter value distributions of basic peat layer resistance cbasis\n\n\n\n\n\nFigure 23: Parameter value distributions of permeability of Holocene sand khol\n\n\nLow and high value of resistivity are set in the tab Calculation to 10% and 90%.\n\nPress RUN () to recalculate the model in the Sensitivity mode.\nAfter the run is finished, a new tab Sensitivity is visible. Go to the tab.\n\nHere we can find what extent parameter variations contribute to model results. In Figure 24 it is shown what parameter variation means for drawdown in the building pit. We conclude that for a situation with a sheet pile wall in only the first sand layer the variation of the resistance of the loamy layer (czba) determines the drawdown, and with that this factor determines the amount of extraction in that situation for the largest part. Translated to practical considerations, it is worthwhile to spend extra budget on determining the homogeneity of that layer and the vertical permeability of the loamy layer in more detail.\n\n\n\nFigure 24: Sensitivity of drawdown in building pit to parameter value distributions of sheetpile resistance (Rshp), silt layer resistance (czba), basic peat layer resistance (cbasis) and permeability of Holocene sand (khol).\n\n\nHowever, with this model we get a varying outcome for the level in the building pit and this is not realistic for a practical situation. In real projects, the dewatering contractor would like to know what the effect on dewatering demand and interaction with environment would be if the aim is to reach the designed groundwater head in the building pit while adjusting the rate of extraction in the wells. \nWe can do this quite simply with the aid of the Python file. To perform this analysis we follow the assumption that the relation between drawdown and well extraction is linear.\n\nGo to the tab Model and in the panel Model code remove from the end of the script the lines for pb0 and the line for pb1.\nOn the top of the script, below the line k01 = khol add a value for the fixed total extraction flux and the fixed head within the building pit: Qws = 100 pb0d = -3.5\nNow add the following lines to the code. NB! Use the same observation variable name as is used in your script! pb0 = observation_observations_0[0] fact = pb0d/pb0 Qtot = 8*Qws*fact pb1 = observation_observations_1[0]*fact\nWithin the section of each of the 8 wells, go to the line defining the pumping rate (Qw) and make it variable: Qw=Qws\nRecalculate the sensitivity.\nAfter the calculation is finisched, go to the tab Sensitivity and in the top left field select “Qtot” and or “pb1”.\n\nAgain, we see that the parameter value for the hydraulic resistance of the loamy clay layer (czba) is most relevant to the variation of the outcome, not only for the drawdown effect in the area surrounding the building pit (pb1, see Figure 25) but also for the total flow to the extraction wells (Qtot, see Figure 26).\n\n\n\nFigure 25: Sensitivity of Pb1 (drawdown outside building pit) due to parameter value distributions of sheetpile resistance Rshp, silt layer resistance czba, basic peat layer resistance cbasis and permeability of Holocene sand khol with constant lowering inside the building pit.\n\n\n\n\n\nFigure 26: Sensitivity of Qtot (groundwater extraction from the building pit) due to parameter value distributions of sheetpile resistance Rshp, silt layer resistance czba, basic peat layer resistance cbasis and permeability of Holocene sand khol, with constant lowering inside the building pit.\n\n\nBased on the same statistic distributions for the parameter values we now are also able to calculate the uncertainty in output for this case, using a sheet pile wall in the first aquifer. The distribution of the results for drawdown just outside the building pit is given in Figure 27, which in the lower part shows the distribution for total flow rate from the dewatering in the building pit.\n\n\n\nFigure 27: Uncertainty in drawdown outside building pit due to parameter value distributions of sheetpile resistance Rshp, silt layer resistance czba, basic peat layer resistance cbasis and permeability of Holocene sand khol with constant lowering inside the building pit\n\n\n\n\n\nFigure 28: Uncertainty in groundwater extraction from the building pit due to parameter value distributions of sheetpile resistance Rshp, silt layer resistance czba, basic peat layer resistance cbasis and permeability of Holocene sand khol with constant lowering inside the building pit\n\n\nThe probabilistic model gives a 50% probability on a flow of 297 m3/d, even with a 10% chance of an overrun to 659 m3/d. The groundwater drawdown at the standpipe outside the building pit amounts -0.44 m with 50% probability but with 10% value of -1.10 m. \nMoreover, it is possible to perform a calculation of reliability with the PTK.\n\nGo to the tab Analysis and select the option Reliability.\nThen we check the variable distributions again.\nNext, we open the tab Calculation.\n\nThis gives the possibility to introduce a failure criterium for certain variable, like in our case pb1. We choose a less strict criterium because with a shallow sheetpile wall it is not possible to meet the requirements anyhow.\n\nChoose a comparison with undershooting a critical value of REF -0.5 m for the groundwater head in pb1 (see Figure 29).\n\nAt the right hand side in the settings window a calculation method needs to be selected. Many statistical methods are available, like Monte Carlo method etc. They are described in the help of the PTK in the main menu. We chose FORM (First Order Reliability Method) as a fast method because it is an automated intelligent iteration process to find a design point for reliability by using first calculated realisations (p.97 in the Help manual, see PTK menu).\n\n\n\nFigure 29: Setting up a reliability calculation by choosing a failure criterium and selecting a calculation method.\n\n\n\nRecalculate the model and go to the tab Reliability.\n\nFrom the result (see Figure 30) we conclude that the FORM method is able to find a solution in just a few iterations.\n\n\n\nFigure 30: Result of the reliability analysis for the selected failure criterium.\n\n\nIt follows that the probability of failure for even a not very discriminating criterium as a drawdown outside the building pit of REF -0.5 m is 42%. The calculation method also returns the contributions of all relevant parameters to the outcome. It is obvious that the loamy layer at shallow depth below the building pit does not deliver enough hydraulic resistance to isolate the building activities from surrounding monuments. \nAs is clear, the studied layout of the building pit plus dewatering will not meet the demands of the local authorities regarding the limitations on drawdown. By waterlocking the sheet pile wall we can hardly expect a satisfactory decrease of drawdown effects around the building site, therefore, the best solution is to install the sheet pile wall to a deeper level. \nRepeating the calculations with sheetpile wall in 2 layers the results will prove the possibility to meet the demands on groundwater effects with that building pit design.\nThis description of the possibilities like exporting a Python script from Qgis-Tim and using this in statistical analysis is just a short peek into all the options. To find more information we must refer to the manual of the Probabilistic toolkit PTK." + "text": "Using Python for sensitivity analyses with a QGIS-Tim model\nQGIS-Tim offers the opportunity to export the geopackage of the created model to a Python script. This makes it possible to use the script for other ways of calculation, e.g.: - Calculation of model results in other Python environments, like Anaconda or Spyder or in a notebook. - Use in other Python oriented programs, like the Probabilistic Toolkit.\n\nIf input of all elements is ready and the model has proved to run properly, go to the QGIS-Tim panel and the tab Model Manager.\nAt the bottom press the button Convert GeoPackage to Python script.\nAfter a short period for translation in Python the explorer panel appears where you can enter the name you want to give for the python file, e.g. “case-TheHague.py” and store it in a directory you choose to save your work. The file looks like:\n\n\n\n\nFigure 15: Python script\n\n\nAs can be seen the converted Python file start with calls (e.g. import timml) to main necessary Python packages. After that, for each timm element in the model, all data coordinates and parameter values follow. At the end of the Python file the “model.solve” command is stated after which all head values in the domain with the desired mesh density are determined and also at demanded observation points.\nAs can be seen the Python script for TimML is written in a very dedicated and condensed manner.\nTo get the Python file running in a platform like Anaconda or Spyder, extra lines should be added at wish, to get the output that the user needs.\nNext this file can be used for geostatistical and scenario-analysis. There are several ways of handling this kind of study, like writing an additional Python program to perform repeated calculations and statistical analysis on results. But an easy way is to use the Probabilistic Toolkit (PTK), a platform for statistical analysis to be used together with geotechnical design programs, developed by Deltares. The PTK can be used for study of model sensitivity for variation of parameter values or reliability analysis.\nThe PTK can be downloaded free of charge at Probabilistic Toolkit - download.\n\nOpen the Probabilistic Toolkit from your desktop () or Windows menu (Deltares folder).\n\nThe Toolkit opens at the first of 5 tabs: Model.\n\nIn the section Model Type check if the dropdown menu Type is set to Internal.\nIn the section Model Type check if the dropdown menu Language is set to Python and a the field Version appears.\nSelect the tree points (‘…’) in the field Version and give the path where PTK can find the Python interpreter, e.g. Spyder at “C:\\roelofs_fs\\_software\\deltaforge\\pythonw.exe”.\nThan you copy the content of the Python file we converted from QGIS-Tim into the window “Model code”.\n\nWe handle the process in this way because we want to change some lines in the source code to get the program running in PTK.\nNext the specific parameters must be selected that are expected to be probably most relevant to variations in results. In the source code used in the PTK, those parameters will not have input on a value but need to be mentioned with a name that the PTK can use for input selection in the calculations. The parameters that seem to be important are:\n\nThe hydraulic resistance of the sheet pile wall Rwall.\nThe resistance c1 of the first clay layer.\nThe permeability of the sand layer k01.\nThe resistance c2 of the second clay layer at -14 m NAP.\n\n\n\n\nFigure 16: Declaration of Variables to control the analysis and first guess for values.\n\n\nIn PTK we have to set these parameters:\n\nIn the PTK panel Input click 4 times on the Add button (), to add 4 variables and name them Rshp, czba, khol and cbasis (see Figure 16)\nIn the tab Variables give these 4 variables the values 10000, 40, 10 and 100.\nReturn to the tab Model and assign these variable values to the parameters in the source code by copying this code block to the top of the Python source code (see Figure 17). Rwall = Rshp c0 = czba k0 = khol c2 = cbasis\nFinaly, replace the fixed value (NB! 2 times “Rwall”, for each sheet pile definition) in the Python code for the parameter name (see red elements in Figure 17).\n\n\n\n\nFigure 17: Replace parameters in the Python code.\n\n\n\nAt the end of the source code, eliminate the following lines from the converted file:\n\nhead = model.headgrid(xg=np.arange(80940.0, 81166.0, 4), yg=np.arange(455554.0, 455360.0, -4) )\n\nAlso eliminate the lines:\n\nobservation_peilbuis_2 = model.head(x=80970.16497991727, y=455495.54316352855) observation_peilbuis_3 = model.head(x=81004.86605597858, y=455389.68291883526) observation_peilbuis_4 = model.head(x=81049.06450220713, y=455485.0645022071)\n\nBecause we only are interested in 2 points, use the first two observation points and add these lines at the end of the Python script:\n\npb0 = observation_observations_0[0] pb1 = observation_observations_1[0]\n\nIn the panel Output of the PTK use the Add button () the new defined variables “pb0” and “pb1”.\nCheck if the program works properly. Field Analysis must contain “Run model”, field Results must contain “Single run”\nPress the RUN button () to calculate the model.\n\nIn the tab Run model we find the results of our calculation.\n\nCheck if it complies with your earlier calculations in QGIS-Tim.\n\n\n\n\nFigure 18: Result of test run in PTK to check model outcome.\n\n\nIf results are as expected, we can step to a sensitivity analyses.\n\nIn the tab Field, set the Analysis option to “Sensitivity*.\nGo to the tab Variables.\n\nFor each selected parameter a distribution is defined with certain limits or characteristic values. Distribution formulas can be chosen based on knowhow of the user. Best guess of the parameter value distributions is given in the next example window.\n\nChange the distributon types for each Variable in the column “Distrubution” and fill in the other values.\n\n\n\n\nFigure 19: Best guess of the parameter value distributions\n\n\n\nSelect the row with sheetpile resistance (Rshp) and in the panel below the distribution is shown (see Figure 20).\n\nParameter value distributions of silt layer resistance (czba), basic peat layer resistance (cbasis) and permeability of Holocene sand (khol) are shown in graphs below.\n\n\n\nFigure 20: Parameter value distributions of sheetpile resistance Rshp\n\n\n\n\n\nFigure 21: Parameter value distributions of silt layer resistance czba\n\n\n\n\n\nFigure 22: Parameter value distributions of basic peat layer resistance cbasis\n\n\n\n\n\nFigure 23: Parameter value distributions of permeability of Holocene sand khol\n\n\nLow and high value of resistivity are set in the tab Calculation to 10% and 90%.\n\nPress RUN () to recalculate the model in the Sensitivity mode.\nAfter the run is finished, a new tab Sensitivity is visible. Go to the tab.\n\nHere we can find what extent parameter variations contribute to model results. In Figure 24 it is shown what parameter variation means for drawdown in the building pit. We conclude that for a situation with a sheet pile wall in only the first sand layer the variation of the resistance of the loamy layer (czba) determines the drawdown, and with that this factor determines the amount of extraction in that situation for the largest part. Translated to practical considerations, it is worthwhile to spend extra budget on determining the homogeneity of that layer and the vertical permeability of the loamy layer in more detail.\n\n\n\nFigure 24: Sensitivity of drawdown in building pit to parameter value distributions of sheetpile resistance (Rshp), silt layer resistance (czba), basic peat layer resistance (cbasis) and permeability of Holocene sand (khol).\n\n\nHowever, with this model we get a varying outcome for the level in the building pit and this is not realistic for a practical situation. In real projects, the dewatering contractor would like to know what the effect on dewatering demand and interaction with environment would be if the aim is to reach the designed groundwater head in the building pit while adjusting the rate of extraction in the wells. \nWe can do this quite simply with the aid of the Python file. To perform this analysis we follow the assumption that the relation between drawdown and well extraction is linear.\n\nGo to the tab Model and in the panel Model code remove from the end of the script the lines for pb0 and the line for pb1.\nOn the top of the script, below the line k01 = khol add a value for the fixed total extraction flux and the fixed head within the building pit: Qws = 100 pb0d = -3.5\nNow add the following lines to the code. NB! Use the same observation variable name as is used in your script! pb0 = observation_observations_0[0] fact = pb0d/pb0 Qtot = 8*Qws*fact pb1 = observation_observations_1[0]*fact\nWithin the section of each of the 8 wells, go to the line defining the pumping rate (Qw) and make it variable: Qw=Qws\nRecalculate the sensitivity.\nAfter the calculation is finisched, go to the tab Sensitivity and in the top left field select “Qtot” and or “pb1”.\n\nAgain, we see that the parameter value for the hydraulic resistance of the loamy clay layer (czba) is most relevant to the variation of the outcome, not only for the drawdown effect in the area surrounding the building pit (pb1, see Figure 25) but also for the total flow to the extraction wells (Qtot, see Figure 26).\n\n\n\nFigure 25: Sensitivity of Pb1 (drawdown outside building pit) due to parameter value distributions of sheetpile resistance Rshp, silt layer resistance czba, basic peat layer resistance cbasis and permeability of Holocene sand khol with constant lowering inside the building pit.\n\n\n\n\n\nFigure 26: Sensitivity of Qtot (groundwater extraction from the building pit) due to parameter value distributions of sheetpile resistance Rshp, silt layer resistance czba, basic peat layer resistance cbasis and permeability of Holocene sand khol, with constant lowering inside the building pit.\n\n\nBased on the same statistic distributions for the parameter values we now are also able to calculate the uncertainty in output for this case, using a sheet pile wall in the first aquifer. The distribution of the results for drawdown just outside the building pit is given in Figure 27, which in the lower part shows the distribution for total flow rate from the dewatering in the building pit.\n\n\n\nFigure 27: Uncertainty in drawdown outside building pit due to parameter value distributions of sheetpile resistance Rshp, silt layer resistance czba, basic peat layer resistance cbasis and permeability of Holocene sand khol with constant lowering inside the building pit\n\n\n\n\n\nFigure 28: Uncertainty in groundwater extraction from the building pit due to parameter value distributions of sheetpile resistance Rshp, silt layer resistance czba, basic peat layer resistance cbasis and permeability of Holocene sand khol with constant lowering inside the building pit\n\n\nThe probabilistic model gives a 50% probability on a flow of 297 m3/d, even with a 10% chance of an overrun to 659 m3/d. The groundwater drawdown at the standpipe outside the building pit amounts -0.44 m with 50% probability but with 10% value of -1.10 m. \nMoreover, it is possible to perform a calculation of reliability with the PTK.\n\nGo to the tab Analysis and select the option Reliability.\nThen we check the variable distributions again.\nNext, we open the tab Calculation.\n\nThis gives the possibility to introduce a failure criterium for certain variable, like in our case pb1. We choose a less strict criterium because with a shallow sheetpile wall it is not possible to meet the requirements anyhow.\n\nChoose a comparison with undershooting a critical value of REF -0.5 m for the groundwater head in pb1 (see Figure 29).\n\nAt the right hand side in the settings window a calculation method needs to be selected. Many statistical methods are available, like Monte Carlo method etc. They are described in the help of the PTK in the main menu. We chose FORM (First Order Reliability Method) as a fast method because it is an automated intelligent iteration process to find a design point for reliability by using first calculated realisations (p.97 in the Help manual, see PTK menu).\n\n\n\nFigure 29: Setting up a reliability calculation by choosing a failure criterium and selecting a calculation method.\n\n\n\nRecalculate the model and go to the tab Reliability.\n\nFrom the result (see Figure 30) we conclude that the FORM method is able to find a solution in just a few iterations.\n\n\n\nFigure 30: Result of the reliability analysis for the selected failure criterium.\n\n\nIt follows that the probability of failure for even a not very discriminating criterium as a drawdown outside the building pit of REF -0.5 m is 42%. The calculation method also returns the contributions of all relevant parameters to the outcome. It is obvious that the loamy layer at shallow depth below the building pit does not deliver enough hydraulic resistance to isolate the building activities from surrounding monuments. \nAs is clear, the studied layout of the building pit plus dewatering will not meet the demands of the local authorities regarding the limitations on drawdown. By waterlocking the sheet pile wall we can hardly expect a satisfactory decrease of drawdown effects around the building site, therefore, the best solution is to install the sheet pile wall to a deeper level. \nRepeating the calculations with sheetpile wall in 2 layers the results will prove the possibility to meet the demands on groundwater effects with that building pit design.\nThis description of the possibilities like exporting a Python script from Qgis-Tim and using this in statistical analysis is just a short peek into all the options. To find more information we must refer to the manual of the Probabilistic toolkit PTK." }, { "objectID": "tutorial_TheHague.html#creating-a-transient-model", "href": "tutorial_TheHague.html#creating-a-transient-model", "title": "Building Pit The Hague", "section": "Creating a transient model", - "text": "Creating a transient model\nAt this moment, it is not possible to create a transient (time dependent) model with correct answers to case studies with sheetpile walls. The TTim solution needs to be updated. Nevertheless in this section we want to guide you on setting up a basic transient model. \n\nReturn to QGIS and in the QGIS-Tim panel go to the tab Compute.\nIn the section Output turn on the option “Transient”.\nIn the panel Layers select timml Aquifer:Aquifer.\n\nAs can be seen in Figure 31, the matrix of properties is extended in the transient mode with cells for transient parameters, like specific storage coefficients (aquitard_s, and aquifer_s) and porosities (aquitard_npor and aquifer_npor). Take care that specific storage coefficient is a storage per meter layer thickness. In older MWell course material a speadsheet is presented for estimation of coefficient values but there we calculated storage coefficients per whole layer. Those values should be divided by layer thickness.\n\n\n\nFigure 31: Attribute Table for Aquifer in transient condition.\n\n\n\nFill in the Table with the corresponding values.\nIn the TTim section in the Layers panel go to the list of elements for transient calculations.\nSelect ttim Temporal Settings:Aquifer and open its Attribute Table (F6). Here the length of the time series is specified.\nSet the starting time to 0.\n\nBut calculations take place for the range of time steps between “time_min” and “time_max”. The time unit is according to central settings in the project, mostly time in days. “Time_min” should not be zero but given a slight offset. Here we also find a “Stehfest_M” number, related to the number of terms in the calculation method performing transformation of formulas in solving differential equations. A reference date can be set to relate the calculation to real time data.\n\nFill in the table according to Figure 32.\n\n\n\n\nFigure 32: Table for ttim Temporal Settings:Aquifer\n\n\nNB!: In QGIS it is an obligation to use a “reference_date” to get the model running and present outcomes!\n\nSelect ttim Computation Times:Domain and set the time values for time steps where we want to get calculations of spatially distributed heads in mesh or raster points and contours.\n\n\n\n\nFigure 33: Table for ttim Computation Times:Domain\n\n\nFor this case we will leave this table blank, because calculating several head distributions at different time steps is rather time consuming during this course.\n\nSelect ttim Observation:observations and here we can set the time steps for a time series at certain points we want to monitor the calculation results. We set points at intervals that follow a (approximately) logarithmic increase in time intervals. Proposed values are shown in the next table.\n\n\n\n\nFigure 34: Table for ttim Observation:observations\n\n\nDon’t choose exactly the same time as when changing the flow. So if 60 is an end value, choose 59.9.\nIn the Attribute Table of layer ttim Well:pumping_wells we can set the discharge amount. The value might change during time when excavation is considered or construction is performed in phases. For each change we have to add a line of input. In case there are a lot of switch on/off moments, this is a lot of work. We just leave this option without any change because there is an other option in case each well has only a singel start and end time.\n\nTherefor go to the layer timml Well:pumping_wells layer. This layer contains simple elements to make it behave as a simple Timm element.\nIn the Attribute Table make start_time=5, end_time=30 and discharge_transient=15.\nBut fill in a value of 0 m3/d in column “Discharge” because this variable is part of TimML well element. We use the “discharge_transient” variable to define flow in TTim. Remember: Solution of TTim is superposed on solution of TimML." + "text": "Creating a transient model\nAt this moment, it is not possible to create a transient (time dependent) model with correct answers to case studies with sheetpile walls. The TTim solution needs to be updated. Nevertheless in this section we want to guide you on setting up a basic transient model. \n\nReturn to QGIS and in the QGIS-Tim panel go to the tab Model Manager.\nIn the section Model Setup turn on the option “Transient”.\nIn the panel Layers select timml Aquifer:Aquifer.\n\nAs can be seen in Figure 31, the matrix of properties is extended in the transient mode with cells for transient parameters, like specific storage coefficients (aquitard_s, and aquifer_s) and porosities (aquitard_npor and aquifer_npor). Take care that specific storage coefficient is a storage per meter layer thickness. In older MWell course material a speadsheet is presented for estimation of coefficient values but there we calculated storage coefficients per whole layer. Those values should be divided by layer thickness.\n\n\n\nFigure 31: Attribute Table for Aquifer in transient condition.\n\n\n\nFill in the Table with the corresponding values.\nIn the TTim section in the Layers panel go to the list of elements for transient calculations.\nSelect ttim Temporal Settings:Aquifer and open its Attribute Table (F6). Here the length of the time series is specified.\nSet the starting time to 0.\n\nBut calculations take place for the range of time steps between “time_min” and “time_max”. The time unit is according to central settings in the project, mostly time in days. “Time_min” should not be zero but given a slight offset. Here we also find a “Stehfest_M” number, related to the number of terms in the calculation method performing transformation of formulas in solving differential equations. A reference date can be set to relate the calculation to real time data.\n\nFill in the table according to Figure 32.\n\n\n\n\nFigure 32: Table for ttim Temporal Settings:Aquifer\n\n\nNB!: In QGIS it is an obligation to use a “reference_date” to get the model running and present outcomes!\n\nSelect ttim Computation Times:Domain and set the time values for time steps where we want to get calculations of spatially distributed heads in mesh or raster points and contours.\n\n\n\n\nFigure 33: Table for ttim Computation Times:Domain\n\n\nFor this case we will leave this table blank, because calculating several head distributions at different time steps is rather time consuming during this course.\n\nSelect ttim Observation:observations and here we can set the time steps for a time series at certain points we want to monitor the calculation results. We set points at intervals that follow a (approximately) logarithmic increase in time intervals. Proposed values are shown in the next table.\n\n\n\n\nFigure 34: Table for ttim Observation:observations\n\n\nDon’t choose exactly the same time as when changing the flow. So if 60 is an end value, choose 59.9.\nIn the Attribute Table of layer ttim Well:pumping_wells we can set the discharge amount. The value might change during time when excavation is considered or construction is performed in phases. For each change we have to add a line of input. In case there are a lot of switch on/off moments, this is a lot of work. We just leave this option without any change because there is an other option in case each well has only a singel start and end time.\n\nTherefor go to the layer timml Well:pumping_wells layer. This layer contains simple elements to make it behave as a simple Timm element.\nIn the Attribute Table make start_time=5, end_time=30 and discharge_transient=15.\nBut fill in a value of 0 m3/d in column “Discharge” because this variable is part of TimML well element. We use the “discharge_transient” variable to define flow in TTim. Remember: Solution of TTim is superposed on solution of TimML." }, { "objectID": "deltaforge_install.html", @@ -291,7 +291,7 @@ "href": "tutorial_Rijsenhout.html#model-8-abstraction-effect-over-time", "title": "Building Pit Rijsenhout", "section": "Model 8: abstraction effect over time", - "text": "Model 8: abstraction effect over time\nNow you are ready for the last step: make your model transient. We keep it simple: we run the model for 30 days and see the increasing effect of the well.\n\nIn Results within the output section change “steady state” into “transient”.\nGo to Model Manager and see that only 5 elements have a transient component.\n\nBy selecting the “transient” option, columns containing extra parameters necessary for a transient model have been unhidden now. First of all we see it in the layer “timml Aquifer:Aquifer” where columns “storage” and “porosity are visible now.\n\nIn your geopackage select the layer “timml Aquifer:Aquifer”.\nOpen its table, start the editing mode and for every layer set both acquifer_s and acquitard_s to 0.001. Acquitard_s (layer 0) = 0.25. You can use copy and paste to do it quickly.\n\nNB! In transient mode, Tim can not handle aquitard with zero thickness so let’s set the aquitard thickness to 0.1 m\n\nChange the values in the column “aquifer_top” to -17.0, -22.1, -27.1 and -47.1 m.\nIn your geopackage select the layer “ttim Temporal Settings:Aquifer” to define the temporal properties of the model.\nOpen its table, start the editing mode and add a new feature.\nMake sure that tmin=0.01, tmax=30, tstart=0, reference_date=2023-03-23 00:00:00.\nIn your geopackage select the layer “ttim Computation Times:Domain” in order to define the moments in time for which raster output is saved.\nOpen its table, start the editing mode and add 7 features / periods (click 7 times “Add feature”).\nIn the column “time” add the moments 1,2,5,10, 15, 20 and 30.\nSave and Close the table.\n\nFor the observations we can define a different set of output moments.\n\nIn your geopackage select the layer “ttim Head Observation:Piezometers”.\nOpen its table, start the editing mode and add 10 features / periods (click 10 times “Add feature”).\nIn the column “time” add the moments 1,2,3,4,5,10,15,20,25 and 30.\nSave and Close the table.\n\nSpecial attention for the Well package while it has 2 options to make it transient:\n\nSimple: a well can be switched on and off only once. Parameters are set in the stationary part of the model, so in “timml Well:DewateringWell”.\nDetailed: a well can be switched on and off multiple times within the modelled period. Parameters are set in the transient part of the model, so in “ttim Well:DewateringWell”.\n\nIn this tutorial we show you the simple version.\n\nIn your geopackage select the layer “timml Well:DewateringWell”.\nOpen its table, start the editing mode and see that columns with time dependent parameters are visible now.\nSwitch off the Steady State abstraction, make discharge = 0.\nSwitch on the Transient abstraction: time_start = 2, time_end = 30, discharge_transient = 2000, caisson_radius = 1.\nSave your changes.\nCompute your transient model in the tab Results.\n\nIn case of a successful calculation a new layer is added to your Vector output: case-Rijsenhout-ttim Head Observation:Piezometers. This layer contains transient data which is indicated with the clock icon right from the layer name. There are 2 ways to visualize these calculated heads in the observations point a) animation over time and b) timeseries at location.\n\nFor the animation over time, activate the Temporal Control Panel with the button on the Map Navigation Toolbar.\nFor timeseries at location activate the Timeseries panel with the Timeseries button () on the iMOD Toolbar.\nBe sure that “case-Rijsenhout-ttim Head Observation:Piezometers” is checked and “case-Rijsenhout-timml Head Observation:Piezometers” is unchecked.\nIn the Temporal Controller panel click the green play button (). Navigation buttons appear.\nIncrease the Step to 16 hours and start the animation with a click on the Play button ().\n\nOnly the first few days you see most prominent drawdown. Let’s now display the timeseries at the point of your mouse with data from the mesh.\n\nGo to the iMOD Time Series panel.\nBe sure the layer “case-Rijsenhout-head_layer_0” is selected.\nFor “variable:” select head and for “layers:” select 0.\nClick the button Select Points, your mouse changes into a . Be sure Update on Selection is checked and hover over the mesh. The graph shows the timeseries at the location of your mouse.\nDeselect the checkbox Update on Selection.\nClick the button Select Points (your mouse becomes a and with the left mouse button select 3 points ad random.\nFinally click the Plot button and the 3 timeseries are added to the chart.\n\nIn the same way you can display the time series from the Observations.\n\nIn the iMOD time series panel select the layer “case-Rijsenhout-ttim Head Observation:Piezometers”.\nFor “ID column:” select label and for “Variable:” select head_layer0. Don’t forget to deselect fid.\nClick the button Select Points and draw a box with your mouse to select one or more observation points.\nClick the Plot button and the selected timeseries are added to the chart.\n\n\n\n\nFigure 11: Calculated time series at observations locations\n\n\nBefore closing the display we change the line properties and save the graph as a PNG file.\n\nSelect the single time series for the observation point closest to your dewatering well. The color of the line is now visible in the field next to the button Line Color.\nChange the color to red.\nSelect the timeseries with the most shallow timeseries and change the color to green.\nCheck the box Draw markers.\nMove your mouse to the display and click your right mouse button. Explore the different options.\nFrom this menu (or from the display) select the function Export….\nSet the export format to PNG and export the file and don’t forget to close the Export window." + "text": "Model 8: abstraction effect over time\nNow you are ready for the last step: make your model transient. We keep it simple: we run the model for 30 days and see the increasing effect of the well.\n\nIn the QGIS-Tim panel go to the tab Model Manager.\nIn the section Model Setup turn on the option “Transient”.\nSee below that only 5 elements have a transient component.\n\nBy selecting the “transient” option, columns containing extra parameters necessary for a transient model have been unhidden now. First of all we see it in the layer “timml Aquifer:Aquifer” where columns “storage” and “porosity are visible now.\n\nIn your geopackage select the layer “timml Aquifer:Aquifer”.\nOpen its table, start the editing mode and for every layer set both acquifer_s and acquitard_s to 0.001. Acquitard_s (layer 0) = 0.25. You can use copy and paste to do it quickly.\n\nNB! In transient mode, Tim can not handle aquitard with zero thickness so let’s set the aquitard thickness to 0.1 m\n\nChange the values in the column “aquifer_top” to -17.0, -22.1, -27.1 and -47.1 m.\nIn your geopackage select the layer “ttim Temporal Settings:Aquifer” to define the temporal properties of the model.\nOpen its table, start the editing mode and add a new feature.\nMake sure that tmin=0.01, tmax=30, tstart=0, reference_date=2023-03-23 00:00:00.\nIn your geopackage select the layer “ttim Computation Times:Domain” in order to define the moments in time for which raster output is saved.\nOpen its table, start the editing mode and add 7 features / periods (click 7 times “Add feature”).\nIn the column “time” add the moments 1,2,5,10, 15, 20 and 30.\nSave and Close the table.\n\nFor the observations we can define a different set of output moments.\n\nIn your geopackage select the layer “ttim Head Observation:Piezometers”.\nOpen its table, start the editing mode and add 10 features / periods (click 10 times “Add feature”).\nIn the column “time” add the moments 1,2,3,4,5,10,15,20,25 and 30.\nSave and Close the table.\n\nSpecial attention for the Well package while it has 2 options to make it transient:\n\nSimple: a well can be switched on and off only once. Parameters are set in the stationary part of the model, so in “timml Well:DewateringWell”.\nDetailed: a well can be switched on and off multiple times within the modelled period. Parameters are set in the transient part of the model, so in “ttim Well:DewateringWell”.\n\nIn this tutorial we show you the simple version.\n\nIn your geopackage select the layer “timml Well:DewateringWell”.\nOpen its table, start the editing mode and see that columns with time dependent parameters are visible now.\nSwitch off the Steady State abstraction, make discharge = 0.\nSwitch on the Transient abstraction: time_start = 2, time_end = 30, discharge_transient = 2000, caisson_radius = 1.\nSave your changes.\nCompute your transient model in the tab Results.\n\nIn case of a successful calculation a new layer is added to your Vector output: case-Rijsenhout-ttim Head Observation:Piezometers. This layer contains transient data which is indicated with the clock icon right from the layer name. There are 2 ways to visualize these calculated heads in the observations point a) animation over time and b) timeseries at location.\n\nFor the animation over time, activate the Temporal Control Panel with the button on the Map Navigation Toolbar.\nFor timeseries at location activate the Timeseries panel with the Timeseries button () on the iMOD Toolbar.\nBe sure that “case-Rijsenhout-ttim Head Observation:Piezometers” is checked and “case-Rijsenhout-timml Head Observation:Piezometers” is unchecked.\nIn the Temporal Controller panel click the green play button (). Navigation buttons appear.\nIncrease the Step to 16 hours and start the animation with a click on the Play button ().\n\nOnly the first few days you see most prominent drawdown. Let’s now display the timeseries at the point of your mouse with data from the mesh.\n\nGo to the iMOD Time Series panel.\nBe sure the layer “case-Rijsenhout-head_layer_0” is selected.\nFor “variable:” select head and for “layers:” select 0.\nClick the button Select Points, your mouse changes into a . Be sure Update on Selection is checked and hover over the mesh. The graph shows the timeseries at the location of your mouse.\nDeselect the checkbox Update on Selection.\nClick the button Select Points (your mouse becomes a and with the left mouse button select 3 points ad random.\nFinally click the Plot button and the 3 timeseries are added to the chart.\n\nIn the same way you can display the time series from the Observations.\n\nIn the iMOD time series panel select the layer “case-Rijsenhout-ttim Head Observation:Piezometers”.\nFor “ID column:” select label and for “Variable:” select head_layer0. Don’t forget to deselect fid.\nClick the button Select Points and draw a box with your mouse to select one or more observation points.\nClick the Plot button and the selected timeseries are added to the chart.\n\n\n\n\nFigure 11: Calculated time series at observations locations\n\n\nBefore closing the display we change the line properties and save the graph as a PNG file.\n\nSelect the single time series for the observation point closest to your dewatering well. The color of the line is now visible in the field next to the button Line Color.\nChange the color to red.\nSelect the timeseries with the most shallow timeseries and change the color to green.\nCheck the box Draw markers.\nMove your mouse to the display and click your right mouse button. Explore the different options.\nFrom this menu (or from the display) select the function Export….\nSet the export format to PNG and export the file and don’t forget to close the Export window." }, { "objectID": "tutorial_Rijsenhout.html#export-your-tim-model-to-python", diff --git a/tutorial.html b/tutorial.html index 9b9b690..1a778cd 100644 --- a/tutorial.html +++ b/tutorial.html @@ -222,7 +222,7 @@

Tutorials
-
+

@@ -242,7 +242,7 @@
-
+

diff --git a/tutorial_Rijsenhout.html b/tutorial_Rijsenhout.html index e53e5de..c73c6d0 100644 --- a/tutorial_Rijsenhout.html +++ b/tutorial_Rijsenhout.html @@ -830,16 +830,17 @@

Model 8: abstraction effect over time

Now you are ready for the last step: make your model transient. We keep it simple: we run the model for 30 days and see the increasing effect of the well.

    -
  1. In Results within the output section change “steady state” into “transient”.
    2. -
  2. Go to Model Manager and see that only 5 elements have a transient component.
    3. +
  3. In the QGIS-Tim panel go to the tab Model Manager.
    4. +
  4. In the section Model Setup turn on the option “Transient”.
    5. +
  5. See below that only 5 elements have a transient component.

By selecting the “transient” option, columns containing extra parameters necessary for a transient model have been unhidden now. First of all we see it in the layer “timml Aquifer:Aquifer” where columns “storage” and “porosity are visible now.

-
    +
    1. In your geopackage select the layer “timml Aquifer:Aquifer”.
    2. Open its table, start the editing mode and for every layer set both acquifer_s and acquitard_s to 0.001. Acquitard_s (layer 0) = 0.25. You can use copy and paste to do it quickly.

    NB! In transient mode, Tim can not handle aquitard with zero thickness so let’s set the aquitard thickness to 0.1 m

    -
      +
      1. Change the values in the column “aquifer_top” to -17.0, -22.1, -27.1 and -47.1 m.
      2. In your geopackage select the layer “ttim Temporal Settings:Aquifer” to define the temporal properties of the model.
      3. Open its table, start the editing mode and add a new feature.
        4. @@ -850,7 +851,7 @@

        Model
      4. Save and Close the table.

      For the observations we can define a different set of output moments.

      -
        +
        1. In your geopackage select the layer “ttim Head Observation:Piezometers”.
        2. Open its table, start the editing mode and add 10 features / periods (click 10 times “Add feature”).
        3. In the column “time” add the moments 1,2,3,4,5,10,15,20,25 and 30.
          4. @@ -862,7 +863,7 @@

          Model
        4. Detailed: a well can be switched on and off multiple times within the modelled period. Parameters are set in the transient part of the model, so in “ttim Well:DewateringWell”.

          5. In this tutorial we show you the simple version.

          -
            +
            1. In your geopackage select the layer “timml Well:DewateringWell”.
            2. Open its table, start the editing mode and see that columns with time dependent parameters are visible now.
            3. Switch off the Steady State abstraction, make discharge = 0.
              4. @@ -871,7 +872,7 @@

              Model
            4. Compute your transient model in the tab Results.

            In case of a successful calculation a new layer is added to your Vector output: case-Rijsenhout-ttim Head Observation:Piezometers. This layer contains transient data which is indicated with the clock icon right from the layer name. There are 2 ways to visualize these calculated heads in the observations point a) animation over time and b) timeseries at location.

            -
              +
              1. For the animation over time, activate the Temporal Control Panel with the button on the Map Navigation Toolbar.
              2. For timeseries at location activate the Timeseries panel with the Timeseries button () on the iMOD Toolbar.
              3. Be sure that “case-Rijsenhout-ttim Head Observation:Piezometers” is checked and “case-Rijsenhout-timml Head Observation:Piezometers” is unchecked.
                4. @@ -879,7 +880,7 @@

                Model
              4. Increase the Step to 16 hours and start the animation with a click on the Play button ().

              Only the first few days you see most prominent drawdown. Let’s now display the timeseries at the point of your mouse with data from the mesh.

              -
                +
                1. Go to the iMOD Time Series panel.
                2. Be sure the layer “case-Rijsenhout-head_layer_0” is selected.
                3. For “variable:” select head and for “layers:” select 0.
                  4. @@ -889,7 +890,7 @@

                  Model
                4. Finally click the Plot button and the 3 timeseries are added to the chart.

                In the same way you can display the time series from the Observations.

                -
                  +
                  1. In the iMOD time series panel select the layer “case-Rijsenhout-ttim Head Observation:Piezometers”.
                  2. For “ID column:” select label and for “Variable:” select head_layer0. Don’t forget to deselect fid.
                  3. Click the button Select Points and draw a box with your mouse to select one or more observation points.
                    4. @@ -902,7 +903,7 @@

                    Model

Before closing the display we change the line properties and save the graph as a PNG file.

-
    +
    1. Select the single time series for the observation point closest to your dewatering well. The color of the line is now visible in the field next to the button Line Color.
    2. Change the color to red.
    3. Select the timeseries with the most shallow timeseries and change the color to green.
      4. @@ -915,7 +916,7 @@

      Model

      Export your Tim model to Python

      For scenario calculation or sensitivity analysis you probably want to switch from QGIS to Python for efficiency reasons. In this tutorial we only show you the first step: export your model to a Python file (*.py). Your Tim model is just a set of elements (points, lines, polygons) and its parameters so the Python file is not very large.

      -
        +
        1. In QGIS-Tim go to the tab Model Manager.
        2. Click the button Convert GeoPackage to Python script and you can save the *.py file wherever you like.
        3. Check the content of the file with you text editor (e.g. Notepad).
          4. diff --git a/tutorial_TheHague.html b/tutorial_TheHague.html index 80abba1..aee8b2f 100644 --- a/tutorial_TheHague.html +++ b/tutorial_TheHague.html @@ -522,7 +522,7 @@

          Open the QGIS-Tim

          Now we are ready to activate the QGIS-Tim plugin.

          1. Click on the QGIS-Tim plugin button () and the QGIS-Tim panel appears.
            2. -
          2. Go to the tab GeoPackage.
            Here we will create an empty database (geopackage) to store all elements and parameters for the model.
            3. +
          3. Go to the tab Model Manager.
            Here we will create an empty database (geopackage) to store all elements and parameters for the model.
          4. Click the New button to create the GeoPackage and save it for instance in the folder with your tutorial data, e.g. “..\QGIS-Tim_Tutorial-TheHague\case-TheHague.gpkg”.

          Your window looks like in Figure 4.

          @@ -538,12 +538,11 @@

          Open the QGIS-Tim

          If you had no introduction to the Tim plugin, read the Intermezzo below for a general explanation of the components.

          Intermezzo: introduction Tabs on the Tim panel

          -
            -
          1. GeoPackage: an overview of the elements in your geopackage. In case you switch to transient modelling, an extra column with ttim elements is added.
            2. -
          2. Elements: a list of 14 Tim elements from which you can build your model.
            3. -
          3. Compute: here you can define your domain and cell size, decide if your model is transient or not and change the output name.
            4. -
          4. Extract: open an existing 3d geohydrological model (NC file) and extract the data for your project area.
            5. -
          +
            +
          • Model Manager: an overview of the elements in your geopackage. In case you switch to transient modelling, an extra column with ttim elements is added.
            • +
          • Elements: a list of at least 16 Tim elements from which you can build your model.
            • +
          • Results: here you can define your domain and cell size, decide if your model is transient or not and manage the output files.
            • +

          Let’s save this project to be able to return to it later or in case of a crash of QGIS.

            @@ -821,7 +820,7 @@

            Adding a Well

            Computing the groundwater head drawdown

            1. Zoom in or out to desired domain for which you want to see the model results.
              2. -
            2. In the QGIS-Tim panel select the tab Compute.
              3. +
            3. In the QGIS-Tim panel select the tab Results.
            4. Select the button Set to current extent to define the Domain.
            5. Grid spacing will follow automatically but for now make the results mesh more dense by changing “Grid spacing” to 3.00 m.
            6. In the “Output” section give the name of the file where you want to store the results.
              7. @@ -893,7 +892,7 @@

            7. In the input group select layer timml Aquifer:…
            8. Open the Attrribute Table (F6) and change the value for “aquitard_c” in layer 1 into 200 d.
              9. -
            9. In the QGIS-Tim panel go to the tab Compute and change the name of the output, e.g. case-TheHague_v1.
              10. +
            10. In the QGIS-Tim panel go to the tab Results and change the name of the output, e.g. case-TheHague_v1.
            11. Click Compute to run variant 1.

            Check in the Layers panel and see that the results are not overwritten but added to the groups, e.g. layer case-TheHague_v1-timml Observation:observations is added to the group Vector.

            @@ -977,7 +976,7 @@

          1. In layer timml Aquifer:… reset the value for “aquitard_c” in layer 1 to the default of 40 d.
          2. In layer timml Leaky Line Doublet:… change the value for “resistance” into 5000 d (500x10).
            3. -
          3. In the QGIS-Tim panel go to the tab Compute and change the name of the output, e.g. case-TheHague_v2.
            4. +
          4. In the QGIS-Tim panel go to the tab Results and change the name of the output, e.g. case-TheHague_v2.
          5. Click Compute to run variant 2.
          6. Fill in your calculated heads at the observation locations in the table above.

          @@ -994,7 +993,7 @@

          Sheet piles w

          How to copy the sheet pile wall to an extra Leaky Line Doublet element?

          1. In the QGIS-Tim panel go to the tab Elements and add a second Leaky Line Doublet and give it a name, e.g. “sheet_pile_L1”
            2. -
          2. Go to the tab GeoPackage and see that the element separately is added to the list. Here is can switch this element on / off for a calculation.
            3. +
          3. Go to the tab Model Manager and see that the element separately is added to the list. Here is can switch this element on / off for a calculation.
          4. In the Layers panel select the new layer timml Leaky Line Doublet:sheet_pile_l1.
          5. Open its Attribute Table (F6) and start the editing mode. The table is empty.
          6. Also open the Attribute Table of the first Leaky Line Doublet and select the existing element.
            7. @@ -1020,7 +1019,7 @@

            Sheet piles w

            We conclude that the drawdown of groundwater level around the building pit with deep sheet piles decreased significantly.

            Next also alternatives with a shallow concrete cut-off wall will be calculated for a shallow and a deep wall. In that case we have R=1000 d, but note that the input in the attribute than becomes k*R=10000 due to the error in Tim.

              -
            1. After changing the value in attribute tables of wall elements, we can compute again, switching off and on the element for the deep wall section (tab Geopackage on the QGIS-Tim panel).
              2. +
            2. After changing the value in attribute tables of wall elements, we can compute again, switching off and on the element for the deep wall section (tab “Model Manager” on the QGIS-Tim panel).

            Again extra calculation is needed to adjust well extractions for drawdown in the building pit.
            Results of calculations are gathered in the following table, showing extractions and head outside the wall at South East monitoring position.

            @@ -1092,7 +1091,7 @@

            Ef

            Using Python for sensitivity analyses with a QGIS-Tim model

            QGIS-Tim offers the opportunity to export the geopackage of the created model to a Python script. This makes it possible to use the script for other ways of calculation, e.g.: - Calculation of model results in other Python environments, like Anaconda or Spyder or in a notebook. - Use in other Python oriented programs, like the Probabilistic Toolkit.

              -
            1. If input of all elements is ready and the model has proved to run properly, go to the QGIS-Tim panel and the tab Geopackage.
              2. +
            2. If input of all elements is ready and the model has proved to run properly, go to the QGIS-Tim panel and the tab Model Manager.
            3. At the bottom press the button Convert GeoPackage to Python script.
            4. After a short period for translation in Python the explorer panel appears where you can enter the name you want to give for the python file, e.g. “case-TheHague.py” and store it in a directory you choose to save your work. The file looks like:
            @@ -1299,8 +1298,8 @@

            Creating a transient model

            At this moment, it is not possible to create a transient (time dependent) model with correct answers to case studies with sheetpile walls. The TTim solution needs to be updated.
            Nevertheless in this section we want to guide you on setting up a basic transient model.

              -
            1. Return to QGIS and in the QGIS-Tim panel go to the tab Compute.
              2. -
            2. In the section Output turn on the option “Transient”.
              3. +
            3. Return to QGIS and in the QGIS-Tim panel go to the tab Model Manager.
              4. +
            4. In the section Model Setup turn on the option “Transient”.
            5. In the panel Layers select timml Aquifer:Aquifer.

            As can be seen in Figure 31, the matrix of properties is extended in the transient mode with cells for transient parameters, like specific storage coefficients (aquitard_s, and aquifer_s) and porosities (aquitard_npor and aquifer_npor). Take care that specific storage coefficient is a storage per meter layer thickness. In older MWell course material a speadsheet is presented for estimation of coefficient values but there we calculated storage coefficients per whole layer. Those values should be divided by layer thickness.