MODFLOW Lab 19: Application of a Groundwater Flow Model to a Water Supply Problem An Introduction to MODFLOW and SURFER The problem posed in this lab was reported in Chapter 19 of "A Manual of Instructional Problems for the U.S.G.S. MODFLOW Model," by P.F. Andersen, EPA/600/R-93/010, February 1993. The details about the problem were exerpted from the chapter along with additional comments provided by J.S. Gierke. Purpose Utilize groundwater modeling software to forecast the pumping drawdown in a regional aquifer for public drinking water supply Groundwater flow models are often used in water resource evaluations to assess the long-term productivity of local or regional aquifers. This exercise presents an example of an application to a local system and involves calibration to an aquifer test and prediction using best estimates of aquifer properties. Of historical interest, this problem is adapted from one of the first applications of a digital model to a water resource problem (cf. Pinder, G.F., and G.D. Bredehoeft, "Application of the digital computer for aquifer evaluation," Water Resources Research, 4, 1069-1093, 1968). The specific objective was to assess whether a glaciofluvial aquifer could provide an adequate water supply for a village in Nova Scotia. Objectives 1) Become familiar with MODFLOW and its various input packages 2) Gain experience in model calibration 3) Become aquainted with model data presentation (e.g., Surfer contours) Background The aquifer is located adjacent to the Musquodoboit River, ¼-mile northwest of the village of Musquodoboit Harbour, Nova Scotia. It is a glaciofluvial deposit consisting of coarse sand, gravel, cobbles, and boulders deposited in a U-shaped glacial valley (Figures 19.1 and 19.2). The aquifer, which is up to 62 feet thick, is extensively overlain by recent alluvial deposits of sand, silt and clay, which act as confining beds. For the purposes of our analysis, it is assumed that the aquifer is fully confined with several zones of varied transmissivity (Figure 19.3). A pump test was conducted to evaluate the aquifer transmissivity and storage coefficient, and to estimate recharge from the river. The test was run for 36 hours using a well discharging at 0.963 cubic feet per second (432 gallons per minute, gpm) and three observation wells (Figure 19.4). The test was discontinued when the water level in the pumping well became stable. Initial estimates of aquifer parameters were calculated using the Theis curve and the early segment of the drawdown curves for the observation wells. The results were somewhat variable, ranging from 1.45 ft 2 /s to 0.3 ft 2 /s, due to influence of boundary conditions (the Musquidoboit River) on the pumping test. 1
Introduction to MODFLOW MODFLOW, developed by the U.S. Geological Survey, uses the finite difference method to obtain an approximate solution to the partial differential equations that describe the movement of groundwater of constant density through porous material. Hydrogeologic layers can be simulated as confined, unconfined, or a combination of confined and unconfined. External stresses such as wells, areal recharge, evapotranspiration, drains, and streams can also be simulated. Boundary conditions include specified head, specified flux, and head-dependent flux. Packages available in MODFLOW and their major function are: Table 1: Names and descriptions of MODFLOW input packages. Package Name (.extension) Problem Set up and Definition Basic (.bas) Block Centered Flow (.bcf) Boundary Condition Packages Well (.wel) Drain (.drn) Evapotranspiration (.et) River (.riv) General Head Boundary (.ghb) Recharge (.rch) Solution Technique Packages Strongly Implicit Procedure (.sip) Slice Successive Over Relaxation (.sor) Pre-conditioned Conjugate Gradient (.pcg) Output Control (.oc) Purpose Overall model setup and execution Sets up grid and material properties Specified constant flux condition Head-dependent flux condition limited to discharge Simulate areal withdrawal of water due to E/T. Head-dependent flux condition with a maximum Head-dependent flux condition, no maximum Specified areal flux input, e.g., infiltration Numerical solution technique Numerical solution technique Numerical solution technique Directs amount, type, and format of output Problem Scope For this first exercise, you are to gain experience in "using" MODFLOW and in manipulating input files manually. In future exercises, you will learn how to prepare input from scratch. So here, you will be using previously prepared input files and manipulating them just a little. This is just an introduction, you will by no means be an expert at the end of this. Obtaining and Organizing the Input Files To start, create a subdirectory: modflow and then off that one another modflow/lab19. All the files will be placed in the lab1 subdirectory. Remember, unix is case sensitive, so it is suggested that you work in lower case. Access the webpage: http://www.geo.mtu.edu/~jsgierke/classes/modflow/lab19/lab19.html 2
Hold the SHIFT key down while clicking on each file with the left mouse button (Sun mouse) or right mouse button (PC mouse). When a pop-up menu appears asking where to save the file, insert the subdirectory path you created above (modflow/lab19) between your root diretory and the filename. You should have received the following data files (type ls -l): lab19.bas lab19.bcf lab19.wel lab19.riv lab19.sip lab19.oc Running MODFLOW The format of MODFLOW input files is give in Appendix A. You will use this appendix frequently. The version of MODFLOW that you will use here is called "surfmod" and this is run by typing the following: surfmod The program will ask for file names according to input and output unit numbers as defined below: Unit = 66: this is the standard MODFLOW output; the name is user specified. CAREFULL: you can overwrite other files if you do not provide a unique filename. Call this lab19.out Unit=1: lab19.bas; this is always the basic package, which defines the unit numbers for the other packages. The ones listed below are unique to this problem. Unit=11: lab19.bcf Unit=12: lab19.wel Unit=14: lab19.riv Unit=19: lab19.sip Unit=22: lab19.oc Unit=80: 1lay19.dat, this is a file prepared for input into Surfer contouring software. Ignore this file for the time being and overwrite it with each simulation during the calibration phase below. Run the model with these given data sets (a summary of the input is given in Table 19.1). Plot the drawdowns (using either an Excel or Applix spreadsheet) the observation wells and compare to the field data listed in Table 19.2. Manipulate the value of the Transmissivity Multiplier and/or the Storativity (both can be found in lab1.bcf) until you are satisfied with the results. (Hint: It is pretty easy to edit lab1.bcf with the vi or pico editors, save it, and rerun surfmod. Use different names for the Unit=66 file for each run so that you can save them and zero in on the 3
best values of T & S.) Print out the graph with the "best" fit. You might as well know now that there is no combination of S and T that will yield an exact agreement. In fact, you will be able to match either the early time data (< 100 minutes) or the later time data (>100 minutes) but not both unless you use time-variable storage coefficient, which is beyond the scope of this lab. So fit the part you want realizing that you are calibrating to the pumptest data with the purpose of "forecasting" drawdowns for even longer times (see below). Once you have calibrated S and T, now run a simulation for 1000 days by altering the value of PERLEN in lab1.bas (the units are seconds) and NSTEPS (increase to 30, if not already set to 30). Using Surfer and 1lay19.dat, draw a drawdown contour for the aquifer region at 1000 days (the data for this is the last 2420 lines of data in the file 1lay19.dat). Examine the water budget calculations at the end of the best fit simulation (36-hrs) and the 1000- day simulation. Compare where the water is coming from between these two times. Introduction to Surfer The Surfer program is designed to generate contour plots of inputted data by three different methods (see Appendix B for a little more details): inverse distance, kriging, or minimum curvature. Inverse distance is an averaging method that weights data values such that the influence of a data point decreases with the distance from the grid value being generated. Kriging performs a moving average that defines trends in the data. High points in the same region of the map tend to be connected as ridges, or low points connected as troughs. Minimum curvature generates the smoothest surface of the three methods, however, data may not support the trends as shown. Surfer can also utilize MODFLOW output to generate drawdown contour maps. In this way, Surfer allows a visual representation of the effects of pumping on a hydrogeologic system. What to Hand in A spreadsheet plot of the model-simulated drawdowns compared to the observed drawdowns. Use good technical labelling practices. A contour plot for the 1000-day drawdown and use good technical labelling practices. A memo containing the following sections: (1) Background (simply reference the lab handout for the background information); (2) Objectives; (3) Approach (i.e., what did you use as a model, what parameters were calibrated and how); (4) Results and Discussion (Describe the calibration results and the contour plot, is the system at steady state at 1000 days, why or why not (use the water budget results)?, comment on weaknesses of and/or limitations to the calibration). 4
Table 19.1. Input date for the water supply problem Grid: 44 rows, 55 columns, 1 layer Grid Spacing: Uniform 100 ft Initial Head: 0.0 ft Transmissivity: Non-uniform spatially, 3 zones Storage Coefficient: Uniform spatially Closure Criterion: 0.001 Number of Time Steps: 10 Time Step Multiplier: 1.414 Length of Simulation: 36 hours Production Well Location: Row 29, column 32 Pumping Rate: 0.963 ft 3 /s (432 gpm) River Stage: 0.0 ft River Conductance: 0.02 ft 2 /s River Bottom Elevation: -10 ft Table 19.2. Observed drawdown data from aquifer test Drawdown (ft) Time (min) Well 1 Well 2 Well 3 1 0.17 0.04 0.00 4 0.26 0.12 0.01 10 0.33 0.16 0.02 40 0.48 0.22 0.08 100 0.57 0.29 0.14 400 0.79 0.51 0.30 1000 0.99 0.70 0.50 2000 1.19 0.86 0.68 3000 1.33 0.98 0.78 5
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