The Episodic Master Recession (EMR) method identifies and quantifies recharge episodes, along with their associated
infiltration-related inputs, by a consistent, systematic procedure. It is based on the water-table fluctuation (WTF) method of recharge estimation, adapted such that the necessary
system-characterizing parameter values, once established, are applied consistently through the entire data set. The EMR algorithm partitions a time series of water table elevations
E(t) into discrete recharge episodes and intervals of no episodic recharge. It correlates each recharge episode with a specific interval of rainfall, so that a precise amount of storm
input or infiltration, and its time-varying intensity, can be associated with the amount of recharge that results. When storms occur closely spaced in time, as commonly occurs in humid
climates, the algorithm evaluates the separability of events, so that those whose recharge cannot be associated with a single storm can be appropriately lumped together. The site-specific characteristics that must be established at the start are: The master recession curve parameters, typically specified as the intercept and slope of a line fitted to calculated values
of dE/dt vs. E, must be previously determined using the MRCfit program or other methods. Specific yield also must be estimated by other methods. The lag time and fluctuation tolerance
are typically determined by trial and error, running the program with the data set of interest. Though the determination of these parameter values requires hydrologic judgment, they can be established once for each given
site, and thus do not allow subjective influences to affect episode-to-episode comparisons. By centralizing the elements requiring judgment, this method keeps the most subjective elements
openly apparent, making it easy to maintain consistency. If applied to a data set with diverse recharge episodes, with broadly differing characteristics, the method serves in evaluating how storm
characteristics and antecedent conditions affect recharge, with application to climate change and other important issues. The MRC and EMR programs are written in the R programming language and run using R studio, an open-source platform
available at www.rstudio.com. The downloadable versions of these codes have been set up with filenames and parameter values for a sample data set, which must be changed for the user’s data. Primary publication describing the method: Nimmo, J.R., Horowitz, C., and Mitchell, L., 2015, Discrete-storm water-table fluctuation method to estimate episodic recharge: Groundwater, v.53, no. 2, doi: 10.1111/gwat.12177.
( PDF) EMR Program information ( PDF) Reference for the water table fluctuation method: Heppner, C.S., and Nimmo, J.R., 2005, A computer program for predicting recharge with a master recession curve: U.S. Geological Survey Scientific Investigations Report 2005-5172.
( PDF) Create an input file: this comma delimited (.csv) file created by the user contains 3 columns of data. It can be
created in excel and saved in comma-delimited format. The first column is time, referenced from t=0 at any starting time that is relevant to the data set as a whole
(usually at or before the earliest time in the data). Time must be specified on a continuous scale with consistent units such as h or d. Formats such as month/day/year must be
converted to a continuous, single-unit scale. The second column is elevation of the water table, given as height above sea level, or depth below land surface (in which case the
numbers will be negative), or any other convenient reference level. If it is known what elevation the recession asymptotically approaches as recession continues indefinitely without
episodic input, this elevation may be a convenient reference level. The third column is cumulative precipitation from a chosen reference time. Water level and precipitation can be
in any desired units. Column headings should be chosen with care as their text will appear in output labels. It is usually a convenience to parenthetically specify units. MRCfit.v2.0.r: This program estimates values of the adjustable parameters
needed to specify the fit to the master recession curve as required for the EMR program. Below is a screen shot of the MRCfit code on the R Studio interface.
Lines that require changes are 13, 14, 17, 19, 22, 25, 30, 34, 37, 40, 44, 48, and 51. The # symbol indicates a comment in the program. Many of these parameters will depend on site-specific data and will require some judgments based on water table
behavior in response to precipitation. It is also good to start with a best guess and adjust parameters based on examination of the output graphs. The program requires four time series: The three time series to be supplied by the user are the same as those needed for MRCfit, so identical input files can be used for the two programs. The user chooses the time units for use with T and the length units for use with E and P. The same chosen units are used throughout the calculations and output. There are 3 necessary files: a start file, the main program file, and the input file containing columns of T, E, and P. Start file: This file contains information that informs the main program such as the location of the main program file, the data file, and the adjustable parameter values.
Below is a screen shot of an EMRstart code on the R Studio interface. Lines that require changes are 2, 5, 6, 9, 10, 13, 14, 15, 16, 17, 18, and 20. The # symbol indicates a comment
in the program Main program file (EMR_main_v34.8 or later): this is the main code that takes the input data and determines periods of recharge based on parameters and tolerances set in the start file.. Recharge to precipitation ratio (RPR) can be calculated for each episode by dividing column E by column F. Note that unit conversion may be necessary if E and P
are specified using different units in the input file. Introduction
Downloadable Resources
Required form of input data
Using the MRC Program
Step by step instructions
Output files
Using the EMR Program
Step by Step Instructions
Output files