The Groundwater Modeling Tool for GRASS; a tutorial

Jaime J. Carrera-Hernandez

Description

The Groundwater Modeling Tool for GRASS;
a tutorial
Jaime J. Carrera Hernandez
January 2005 DRAFT version
McGill University
Department of Civil Engineering and Applied Mechanics
[e-mail]
Abstract
This tutorial shows how to develop groundwater flow models using GRASS
and MODFLOW. This is done through the “Groundwater Modeling Tool for
GRASS” (GMTG) or r.gmtg module which works under GRASS. This mod
ule can be used to run stady state and transient simulations on multilayer
aquifers. The current MODFLOW packages supported by r.gmtg are those
used to simulate wells (extraction and injection), rivers, recharge and drains.
1 Introduction
This is a brief tutorial on how to develop groundwater flow models using GRASS’
module r.gmtg. The user should be familiar with different modules of GRASS
such as r.reclass, r.mapcalc. For further reference on GRASS you can read the on
line tutorials or the GRASS book by Neteler and Mitasova (2004). The problems
developed in this tutorial are taken from Chiang (2001), who developed the Pro
cessing MODFLOW for Windows (PMWIN) software. These examples are used
to compare the results obtained using a well known MODFLOW processor with
those obtained using GMTG. This module is an improved version of the one de
scribed by Carrera Hernandez´ and Gaskin (2004) and current work is being done
to use other MODFLOW packages.
11.1 Description of tutorial
The examples developed in this tutorial will help you to gain a general knowl ...

Sujets

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• Aquifère
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Informations

• Publié par: Fewyug
• Nombre de lectures: 95
• Langue: English

Extrait

The Groundwater Modeling Tool for GRASS; a tutorial

Jaime J. Carrera-Hernandez January 2005 DRAFT version

McGill University Department of Civil Engineering and Applied Mechanics [e-mail] Abstract This tutorial shows how to develop groundwater ow models using GRASS and MODFLOW. This is done through the “Groundwater Modeling Tool for GRASS” (GMTG) or r.gmtg module which works under GRASS. This mod- ule can be used to run stady state and transient simulations on multilayer aquifers. The current MODFLOW packages supported by r.gmtg are those used to simulate wells (extraction and injection), rivers, recharge and drains.

1 Introduction This is a brief tutorial on how to develop groundwater ow models using GRASS’ module r.gmtg. The user should be familiar with different modules of GRASS such as r.reclass, r.mapcalc. For further reference on GRASS you can read the on- line tutorials or the GRASS book by Neteler and Mitasova ( 2004 ). The problems developed in this tutorial are taken from Chiang ( 2001 ), who developed the Pro- cessing MODFLOW for Windows (PMWIN) software. These examples are used to compare the results obtained using a well known MODFLOW processor with those obtained using GMTG. This module is an improved version of the one de- scribed by Carrera-Hern´ dez  and Gaskin ( 2004 ) and current work is being done an to use other MODFLOW packages.

1

1.1 Description of tutorial The examples developed in this tutorial will help you to gain a general knowl- edge on how to use GRASS and GMT to develop groundwater ow models. The tutorial will explain how to: 1. Create a GRASS region. 2. Import ASCII les (e.g. Digital Elevation Models and sites les) using the module r.in.ascii 3. Reclassify existing categories from raster maps using r.reclass 4. Use map algebra with r.mapcalc

2 Module description The r.gmt module uses GRASS as a preprocessor and postprocessor for MOD- FLOW. It uses raster maps as input for MODFLOW simulations and then imports the results to different raster maps with a prex specied by the user which are explained in table 1 . r.gmt simulation=value units=value layers=value aqtype=value[,value,. . . ] stress=value length=value[,value,...] steps=value[,value,...] [tsmult=name[,name,. . . ]] region=name[,name,. . . ] heads=name[,name,...] [Sy=name[,name,. . . ]] [T=name[,name,. . . ]] [K=name[,name,. . . ]] [bottom=name[,name,. . . ]] [vcond=name[,name,. . . ]] [top=name[,name,. . . ]] [Syb=name[,name,. . . ]] [recharge=name[,name,. . . ]] [wells=name[,name,. . . ]] [river _ heads=name] [river _ cond=name] [river _ elev=name] [drain=name[,name,. . . ]] drawdownin=name headsin=name

3 Requirements If you are running GRASS under Linux you should not have any problems when attempting to use GMT; as GMT links GRASS with MODFLOW you need to have MODFLOW installed on your system. You need to download the source code available from GRASS’ TWIKI site http://grass.gdf-hannover.de/twiki/ bin/view/GRASS/JaimeCarrera . From this site you will also need to download the programs rddown and rheads ; these les are required to import MODFLOW’s output into GRASS. All data related to this tutorial is available from the same site.

2

ing rivercondName eufsroercaehssrtaprmthwiagstalevdaehmaNsrfoeetsa ng ri stri levNvere seofavul hcser r ae ongcininceanctduretsarfoatnocpam d g arniaN eu s s rtniation val -bedelevrgnirevinocpniatstramaereoamheft mrpasaetoerfNnmaownirawd ing d astrtadniardgniniatncos)p(matesiofme irts ot gn maNpafoexineinstasgrrmte saetmrpaiwhteVtricalconduc- tance tsixenafetsargnithwiaprmarndcoSe htoTpaiwuqfiopafringerst ameoSybN ngtistraanofisexcerhgrahamretiwp Values styStorage raegaNem irgn erhc ELgWinintaon)c(s revir gnirtsatadL g wel trinuesseval selisetemfoslan ARDWofDrmiluWOsNnvalatiotrinuess nisdaeh g arfoemaNpfmaerstsiADHEorumalitnoavulsetsring 3

Number of layers in the model Type of aquifer

layers aqtype

inbertnum nCo0= nc=U d 1 ne ts1=Seconds 2=min atet nutiTsmiuein =y s 5rsea setu oh=3 4 sru yad= yTepitnoumal eu is nValptioscrierDe sydaetS=1 tneisnaTr0=ontilamusiof endedeotaremetsrable1:PaT raP g tema rgnitmg.tilausonnarumusi eilpitluhcaerofrpessrestatoodrire er unbm aNemignosterofraithamapw spetbmuNforeemitepstorsfchearestssepirdonintmuebr tsmultTimestepm siodripessrestof eLhtgnel rebmuntn resschstofeangtheb s rntmudoniepir riValeab non 2= ed tnat V=3 T htiw snoc ith varia ariablew ssuNbmre lbTe tser st TT ngri amKNs)e( refitiwsNOChNATS BLEcon- nmentaqu aDuqfireosVrRAAIfoEDIRQUNEFIONrC issimsna-ER.ytivmap(sterthTrs)wifoxeaNemgnarsiit rts s T gni vtneeula - e co cif toysgerahtrpmiraam(p)siwngrasterofexistiemaNyS gnirtssdaelhiaitinthwiaprmsaetoerfNsmaehda ringlsstecelctiv lb T e tsirgn cvnoNdameofanexistingr denvdnaairaaelbifquswerhvitiaar fireahuqmoR.obtt ired e- qunconforu emaNmottsixenafostrangtiitpwmaer erswithVentaquif tsirgn ob RAAILBTE ifqusaerFIONDaNE ocELmnnAV dn BAIR ivitduct Con-ntal UrCNdeofuqri.yeR erstrangtiisexofoziroHhtiw)s(pam

4 Developing groundwater ow models This section shows how to use GRASS and GMT to develop groundwater ow models. However, it is important to stress that this tool is better when using real world data and to develop groundwater ow models with a conceptual approach. This tutorial only explains how to use GMT and GRASS to develop groundwa- ter ow models and the examples are quite simple. The book by Anderson and Woessner ( 1992 ) is a very good reference for groundwater modeling; to learn more about MODFLOW it is strongly suggested to read its documentation ( Mc- Donald and Harbaugh , 1988 ).

4.1 Example 1 The rst tutorial has two parts: 1. A steady state simulation without pumping is used to determine the spatial distribution of heads in the model domain. 2. A transient model is used to simulate the effect of pumping in a wet season while at the dry season there is no pumping at all. The heads obtained in the steady state simulation are used as the initial heads for the transient simulation.

4.1.1 Steady state simulation This rst example shows how to develop a groundwater ow model using the r.gmtg module. An unconned aquifer has a hydraulic conductivity of 160 m/day and a recharge of 7.5 × 10 − 4 m/day. The elevations of the aquifer top and bottom are 25 m and 0 m respectively. Additionaly, a total of nine wells are pumping water from the aquifer at a rate of 3888 m 3 /day, as shown in gure 1 .

Creating the region to model: The rst step consists in creating the region; if you already know how to set up regions with GRASS you can skip this section. First create a directory on which you will have all data and then change to it, then copy or download the data les into this directory. [jaime@civpc-08 jaime] mkdir tutorial [jaime@civpc-08 jaime] cd tutorial [jaime@civpc-08 tutorial]

4

Figure

1:

Model

domain

5

for

problem

1

Figure 2: GRASS’ initial window

Figure 3: Available regions in current di- rectory

Figure 4: Required data to set-up a region in GRASS

This step is recommended because all MODFLOW les will be created on this directory; to avoid overwriting of les from different models, r.gmt should be invoked from the project’s directory. Start GRASS by typing grass5 in the command line and create the region tutorial1 as shown in gure 2 and presss CTRL-ENTER. The next screen will show the existing regions in the current database as gure 3 shows. Type y and ENTER as you want to create a new region for which you need to know four items as illustrated in gure 4 . After this you need to type in y and the region’s settings as exemplied in gure 5 . After the region has been created, the next step consists in importing the data that will be used in this example. The data is available as and ASCII le named

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(a) Coordinate system for new region

(c) Extents of new region

(b) Description of new region

(d) Created region

Figure 5: Creating a region in GRASS

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Figure 6: Raster map imported with r.in.ascii

basemap.map . To import it use the r.in.ascii module and name the resultant map basemap . If this map is displayed, it should be similar to Figure 6 . GRASS:˜tutorial > r.in.ascii input=basemap.dat output=basemap GRASS:˜tutorial > d.start x0 GRASS:˜tutorial > d.rast basemap We do not know the values of the map that was just imported. To nd out the number of categories in a raster map as well as some extra information on it, the r.info command can be used: GRASS:˜/MVB/MODFLOW > r.info basemap The module r.info shows basic information about a raster map: The lim- its,resolution and projection; in addition the data range is also displayed. For this map the minimum value is -1 while the maximum is 2. To nd out which areas correspond to each category you need to diplay the raster map and then use the module r.what . We need to assign a value of 0 to those cells that are inactive; in order to do this, the category values of basemap are reclassied into a new raster le which will be called boundaries . To create the new map, reclassify the category value 2 into 0 and keep the values of the other two categories.

8

GRASS:˜> r.reclass input=basemap output=boundaries Enter the rule or ’help’ for the format description: > -1 = -1 > 1 = 1 > 2 = 0 > end GRASS:˜> We will also create a map with an uniform value of 1; this map will be used to create the remainder maps for the groundwater model, as the following maps are still needed: • Initial Heads • Hydraulic Conductivity • Recharge values • Aquifer bottom The basemap raster map is reclassied to map area with only one category (value 1): GRASS:˜> r.reclass input=basemap output=area Enter the rule or ’help’ for the format description: > * = 1 > end GRASS:˜> The other raster maps are now created using r.mapcalc as follows: GRASS:˜ > r.mapcalc H.conductivity=area*160 100% GRASS:˜ > r.mapcalc recharge=area*.00025 100% GRASS:˜ > r.mapcalc initial.heads=area*15 100% GRASS:˜ > r.mapcalc bottom=area*0 100% GRASS:˜ >

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The southern boundary is a specied ux boundary of 0.0672 m 3 /day/m.In order to account for this ux a well will be used at each cell with a ow of 0.0672 × 200 m which equals 13.4 m 3 /day. To create a well le an ASCII le is imported into GRASS using s.in.ascii. Open a text editor such as emacs and type in the values of table 2 without the header and leaving a space between each value or use the data available on the web site. Save this le as a plain text with emacs and now import it using r.in.ascii : GRASS:˜ > s.in.ascii sites=cst.flux input=cst.flux d=3 GRASS:˜ > Now all required data to run the groundwater ow model have been set up. Before running the simulation we need to check if all required data is available: GRASS:˜ > r.gmt simulation=1 units=4 layers=1 aqtype=1 stress=1 length=1 steps=1 tsmult=1 region=boundaries heads=initial.heads K=H.conductivity bottom=bottom recharge=recharge wells=cst.flux drawdownin=dd headsin=hd The simulated head has been saved on le hd.lay1.stp1.tst1 where hd is the name entered for the option headsin of GMT. The remainder parts of the le name are generated automatically to facilitate the task of reading the results of each simulation: hd.lay1.stp1.tst1 means that this map shows the head at layer 1, for stress period (stp) 1 at the rst time step (tst). Now we can create a vector map to show drawdown values at increments of 0.5 m. To create this map the module r.contour is used as follows: GRASS:˜/tutorial > r.contour input=hd.lay1.stp1.tst1 output=ss.heads step=0.5 minlevel=15 maxlevel=20 Reading data. Percent complete: 100% FPRange of data: min = 15.000000 max = 19.270000 Minimum level will be 15.000000 Maximum level will be 19.000000 Continue?(y/n) [y] y Now the head values for the simulation as well as the contours at every 0.5 m can be displayed simultaneously to get a more representative map: GRASS: /tutorial > d.mon x0 ˜ using default visual which is TrueColor ncolors: 16777216

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Table 2: Coordinates of wells for specied ux boundary

East 100 300 500 700 900 1100 1300 1500 1700 1900 2100 2300 2500 2700 2900 3100 3300 3500 3700 3900 4100 4300 4500 4700 4900

North 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100

Layer 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

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Flow 13.4 13.4 13.4 13.4 13.4 13.4 13.4 13.4 13.4 13.4 13.4 13.4 13.4 13.4 13.4 13.4 13.4 13.4 13.4 13.4 13.4 13.4 13.4 13.4 13.4

Description ”Cux ”Cux” ”Cux” ”Cux” ”Cux” ”Cux” ”Cux” ”Cux” ”Cux” ”Cux” ”Cux” ”Cux” ”Cux” ”Cux” ”Cux” ”Cux” ”Cux” ”Cux” ”Cux” ”Cux” ”Cux” ”Cux” ”Cux” ”Cux” ”Cux”