15EngDrainReport

Modeling Water-Table Elevations for
Engineered Drain Applications with On-
Site Wastewater Treatment Systems in
Ohio
Final Report Submitted to the Ohio Department of Health
Version-5/13/2015
Report prepared by
Vinayak Shedekar, Larry C. Brown, Yuhui Shang
Project Director
Dr. Larry C. Brown
Professor and Extension Agricultural Engineer
Project coordinator
Vinayak Shedekar
Graduate Research Associate
Modeling team
Yuhui Shang, Rogelio Toledo De Leon, Marwa Ghumrawi,
Lindsay Pease, Lamine Diop, Kpoti (Stephan) Gunn
Graduate Research Associates
Department of Food, Agricultural and Biological Engineering
The Ohio State University
590 Woody Hayes Drive
Columbus, OH 43210-1058

ODH - Curtain Drains Simulation| Page 2 of 43
5/13/2015
Table of Contents
1. Executive Summary...............................................................................................................................4
2. Introduction ..........................................................................................................................................5
3. Methodology.........................................................................................................................................7
3.1. Soil series selection.......................................................................................................................7
3.2. Soils data.......................................................................................................................................7
3.3. Weather data ..............................................................................................................................11
3.4. DRAINMOD – Inputs and set up..................................................................................................12
3.4. 1 Soil Inputs............................................................................................................................12
3.4. 2 Weather inputs ...................................................................................................................12
3.4. 3 Crop inputs..........................................................................................................................13
3.4. 4 Drainage Design (Conceptual On-Site System) ...................................................................13
3.4. 5 Other Parameters ...............................................................................................................13
3.5. Modeling framework and process ..............................................................................................13
3.5. 1 Setting up DRAINMOD Project files ....................................................................................13
3.5. 2 Setting up DRAINMOD batch files & Model runs................................................................14
3.5. 3 Model outputs of interest...................................................................................................14
3.6. Outputs processing for summaries and analysis ........................................................................14
3.6. 1 SAS Program for summarizing model outputs....................................................................14
3.6. 2 Annual average number of days the water table would remain within certain depth from
soil surface ..........................................................................................................................................14
3.6. 3 Annual variation of water table depths..............................................................................15
3.6. 4 Probabilities and Recurrence Intervals of daily water table depths...................................15
4. Results.................................................................................................................................................15
4.1 How to read and interpret results ..............................................................................................15
4.1.1 Overview of results .............................................................................................................15
4.1.2 Detailed yearly outputs for each soil ..................................................................................15
4.1.3 Annual summaries and long-term averages .......................................................................15
4.1.4 Probabilities and Recurrence intervals for WT criteria.......................................................18

4.2 Some odd results ........................................................................................................................21
5. Summary.............................................................................................................................................23
6. Future Work........................................................................................................................................24
7. Acknowledgements and Credits .........................................................................................................24
Acknowledgements.................................................................................................................................24
Research Team........................................................................................................................................24
8. Contact Information:...........................................................................................................................24
9. References ..........................................................................................................................................25
10. Appendices......................................................................................................................................33
Appendix A: Summary of DRAINMOD modeling work related to Engineered drains in Ohio................34
Appendix B: Preview of Files...................................................................................................................36
Appendix C: DRAINMOD inputs ..............................................................................................................38

1. Executive Summary
Engineered drains are frequently used Ohio’s small and rural communities to artificially lower the water
table in On-Site Wastewater Treatment Systems (OSWTS). While Engineered drains may help lower the
water table for some conditions, there is minimal if any information about how frequently on-site
systems may be inundated by the natural water table.
This report contains the results of modeling studies that evaluated the performance of subsurface drains
to remove excess soil water from the soil profile with application to OSWTS. Sixty six representative soil
series were analyzed using the agricultural water management computer model DRAINMOD N II. For
each soil series, DRAINMOD was used to simulate daily water table depths under different combinations
of drain depths and spacings for a period of 30+ years. For each soil, two spacings (15 ft. and 22 ft.) and
6 drain depths (1 ft., 1.5 ft., 2 ft., 2.5 ft., 3 ft., and maximum profile depth) were simulated using
hydrologic simulation model DRAINMOD N II. A “No Dainage” scenario was also simulated for each soil.
The daily water table depths simulated under each scenario were analyzed to count number of days
(NODs) in a year that the water table depths were less than or equal to 30, 45, 60, 75 and 90 cm (1, 1.5,
2, 2.5, and 3 ft.), respectively. The outputs were then summarized to obtain probabilities of exceedance
and recurrence intervals for the water table depths to be within certain depths from the soil surface.
The data were further summarized into annual summaries for each WT criterion. Demonstration videos
are available at https://www.youtube.com/playlist?list=PLaK4N1a0b7wBC9AHessGbcdlltoUhQPcN for detailed
description of available results and utilities. All result files including this report are available for
download at: https://goo.gl/LxJXId

2. Introduction
Most On-Site Wastewater Treatment Systems (OSWTS) in Ohio’s small and rural communities are
subsurface soil absorption systems. However, Ohio’s precipitation, soil and geologic characteristics limit
the proper operation of these systems on some sites because of saturated soil conditions during parts of
the year. Engineered drains are frequently used in these cases to artificially lower the water table (see
Figure 1), with the goal of eliminating saturation of any portion of the treatment trench by natural water
table conditions. However, there are only a few
Figure 1. Example trench and Engineered drain configuration
(Source: Brian Tornes, Burges and Niple, Inc.)
With on-site systems installed on poorly drained soils, the concern from a public health standpoint
primarily is the potential for partially or untreated wastewater to discharge to surface water bodies. The
goal of using Engineered drains near on-site systems should be to minimize, if not eliminate, any
interaction between untreated wastewater and the near-surface ground water, eliminate any discharge
of untreated wastewater to surface waters, and enhance the proper operation of the on-site system.
While Engineered drains may help lower the water table for some conditions, there is minimal if any
information about how frequently on-site systems may be inundated by the natural water table, and
even less published information on how Engineered drains affect near-surface ground water near on-
site systems. Furthermore, not all soil series are suitable for treating wastewater (See Figure 2). Thus, if
on-site systems are installed in soils that are less or not suitable for wastewater treatment, it becomes
even more critical to assess the risk of water table fluctuations due to Engineered drains. An option is to
use hydrologic models to estimate the effect of Engineered drains on water tables. With this type of
information, public health officials can better assess the risks of any potential interaction between
untreated, or partially treated, wastewater and ground water, the potential for on-site system failure,
and the potential for polluting surface waters with wastewater from on-site systems.

Figure 2. Percent of soils by county suited to traditional leach lines or mound systems in Ohio.
(Source: OSU Extension Bulletin 896)
This report contains the results of modeling studies that evaluated the performance of subsurface drains
to remove excess soil water from the soil profile with application to OSWTS. We evaluated water table
levels in selected soil series where Engineered drains may be installed near on-site wastewater
treatment trenches. Sixty six representative soil series were analyzed using the agricultural water
management computer model DRAINMOD 6 (Skaggs, Skaggs, 1977, 1978; and Youssef et al., 2005,
2006). This computer model was developed to use long-term climatic data and soil property information
to predict water table levels for various combinations of drain depth and drain spacings on cropland,
and has been validated on conditions in Ohio as well as several other states. For each soil series,
DRAINMOD was used to simulate daily water table depths under different combinations of drain depths
and spacings for a period of 30+ years. The outputs were then summarized to obtain probabilities of
exceedance and recurrence intervals for the water table depths to be within certain depths from the soil
surface. These results refer to average daily water table depths midway between two parallel drain
pipes on soils where Engineered drains (see Figure 3).

Figure 3. Schematic representation of water table depth simulation by DRAINMOD
(Source: Brown, 2008)
3. Methodology
3.1. Soil series selection
Among the approximate 475 recognized soil series in Ohio, 66 reference soil series (see Table 2) were
selected as a representative sample of Ohio soil series.
3.2. Soils data
The drainage related properties of each soil series were obtained from the NRCS Web Soil Survey. The
soil properties are available for different layers, representing different horizons in each soil series.
Several descriptions of the same soil series existed in the web soil survey. However, due to limited time
availability, properties for the most common description of each soil series were used for DRAINMOD
simulations. The soil properties were then summarized and used to create raw input files for Rosetta (a
pedo-transfer function program that creates soil inputs for DRAINMOD). The process was partially
automated using VBA Macros in MS-Access, in order to facilitate handling of huge soils database
downloaded from the web soil survey. For more detailed methodology, please continue reading this
section.
An excerpt from the 2008 Engineered-drains related project report explains methodology for obtaining
soils data:
“The USDA Soil Interpretation Record (SIR) database and the Map Unit Use File (MUUF)
(http://www.wcc.nrcs.usda.gov/wetdrain/wetdrain-tools.html) were used to obtain all soils information
and to develop the soils input format files. The soil data include soil-water retention data, drainage
volume, upward flux, Green-Ampt infiltration parameters, and lateral saturated hydraulic conductivity.
The methodologies and algorithms used in MUUF to derive soils parameter values for DRAINMOD are
described by Baumer (1989) and Baumer and Rice (1988).”
We used a different approach for obtaining soils data than the one suggested above. The following
section gives a brief summary of reasoning behind, and description of the new methodology.

Table 1: List of selected soil series and corresponding lengths of weather record used for simulation
Soil name Texture # of
Years
Soil name Texture # of
Years
1. Bennington Silt loam 28 34. Latham Silt loam 30
2. Blount Silt loam 43 35. Latty Silty clay 40
3. Bogart Loam 45 36. Lenawee Silty clay loam 36
4. Bono Silty clay loam 51 37. Licking Silt loam 30
5. Braceville Gravelly loam 20 38. Lowell Silt loam 51
6. Brady Sandy loam 40 39. Marengo Clay loam 36
7. Brookside Silty clay loam 37 40. Mcgary Silt loam 44
8. Brushcreek Silt loam 30 41. Mcgary Silty clay loam 41
9. Canadice Silty clay loam 20 42. Milford Silty clay loam 26
10. Caneadea Silt loam 20 43. Montgomery Silty clay loam 42
11. Cardington Silt loam 36 44. Morningsun Silt loam 45
12. Celina Silt loam 45 45. Painesville Fine sandy loam 22
13. Clarksburg Silt loam 37 46. Patton Silty clay loam 36
14. Claysville Silty clay loam 37 47. Pierpont Silt loam 31
15. Colwood Fine sandy loam 30 48. Platea Silt loam 30
16. Colwood Loam 30 49. Randolph Silty clay loam 26
17. Colwood Silt loam 30 50. Randolph Silt loam 26
18. Condit Silt loam 36 51. Rawson Loam 28
19. Conneaut Silt loam 49 52. Rimer Loamy sand 40
20. Corwin Silt loam 44 53. Seward Loamy fine sand 20
21. Darien Silt loam 20 54. Sheffield Silt loam 20
22. Digby Loam 41 55. Smothers Silt loam 47
23. Elliott Silt loam 35 56. St.Clair Clay loam 47
24. Fincastle Silt loam 45 57. Sugarvalley Silt loam 45
25. Fulton Silty clay loam 41 58. Taggart Silt loam 44
26. Glynwood Silt loam 41 59. Trumbull Silty clay loam 46
27. Granby Loamy sand 26 60. Tygart Silt loam 30
28. Guernsey Silt loam 31 61. Venango Silt loam 20
29. Homewood Silt loam 35 62. Weinbach Silt loam 37
30. Hoytville Clay loam 45 63. Westgate Silt loam 31
31. Hoytville Silty clay loam 45 64. Westland Silt loam 45
32. Jimtown Loam 47 65. Wyatt Silt loam 30
33. Kibbie Loam 40 66. Xenia Silt loam 45
We used a different approach for obtaining soils data than the one suggested above. The following
section gives a brief summary of reasoning behind, and description of the new methodology.
 We were unable to use and/or locate the old Soils-5 database and the MUUF program for
generating soil inputs for DRAINMOD. Therefore we decided to use web soil survey for obtaining
soils data.
 The SIN/SIR codes provided for each soil series in the original proposal could not be used for this
work, since the NRCS has discontinued the use of SIR for the publically available database (such

as web soil survey). We had several conversations with Larry Tornes and Jeff Glanville regarding
the link between the new soils database and the old SIR codes. A summary of our
communications is given below:
 SIN / SIR was first started @1976 as an identifier for map units, when soil survey was first
digitized and made available through online database. Before that, all soil surveys were hand
typed/printed. And none of them were available in a database format. SIN / SIR number is
obsolete now. The "central concept" of each soil series was directly tied with the SIR number in
the past. However, NRCS does not use the term "central concept" anymore. Therefore, they
haven't provided any such field in their latest databases. The latest soils databases available
through NRCS, all use "Map unit Key" as an identifier for soil series (referred to as map unit
and/or major component). The SIN/SIRs are not available in the public domain versions of web
soil survey. However, the internal NRCS soils database still has SIRs as an obsolete field that is
not being updated anymore. Thus, some of the newer soil series don’t have any SIRs assigned.
After several discussions within the research team and with Jeff Glanville and Larry Tornes, the following
approach was adapted for obtaining soils data:
 The web soil survey offers STATSGO as well as SSURGO data sets with relevant soil properties.
We selected SSURGO for the DRAINMOD work, since they are more detailed and are available at
a finer resolution.
 SSURGO database is available at county levels and consists of several different descriptions of
the same soils series. We first used the “NRCS Soil Series Extent Mapping Tool” (Figure 4a) to
find out county(ies) with largest area under the each soil series. We downloaded the soils data
for the entire county from web soil survey. The MS-Access file provided by the NRCS to import
and organize soils data for each county, was further modified using VBA and Macros to extract
the properties required for creating soil inputs for DRAINMOD. For some of the soil series, Jeff
Glanville designed a SQL query for the NRCS internal database; and extracted the same soil
properties for this project. We have ensured and verified that both approaches generated the
same results for any soil series.
 For all soil series, we used the properties of soils at 0 to 2% slope. In some cases, there were
more than one descriptions of the same soil series within a county. In such cases, we selected
the soil description that occupies the largest area within the county.
 For each soil series, we extracted the representative properties (%sand, silt, clay, bulk density,
Theta_0.33bar, Theta_15bar, Ksat).
Appendix A shows a comparison between the current study and the study conducted in 2008 by Brown
et al.

(source: http://websoilsurvey.sc.egov.usda.gov)
(a) Geographic extent of Westland soil series
(b) Locations of weather stations available for simulation
Figure 4: Example of selection process for soil properties and weather station (The example shows
extent of Westland soil)

The following properties were obtained from the web soil survey for each soil series:
Table 2: List of soil properties used from web soil survey
Soil Property
Acronym
Soil Property Unit of
Measure
Description
hzdept_r Top Depth of layer -
Representative Value
centimeters The distance from the top of the soil to the
upper boundary of the soil horizon.
hzdepb_r Bottom Depth of layer -
centimeters The distance from the top of the soil to the
base of the soil horizon.
sandtotal_r Total Sand -
percent Mineral particles 0.05mm to 2.0mm in
equivalent diameter as a weight percentage of
the less than 2 mm fraction.
silttotal_r Total Silt -
percent Mineral particles 0.002 to 0.05mm in
the less than 2.0mm fraction.
claytotal_r Total Clay -
percent Mineral particles less than 0.002mm in
the less than 2.0mm fraction.
dbovendry_r Bulk density - oven dry -
grams per
cubic
centimeter
The oven dry weight of the less than 2 mm soil
material per unit volume of soil exclusive of the
desication cracks, measured on a coated clod.
ksat_r Saturated hydraulic
conductivity - Ksat -
micrometers
per second
The amount of water that would move
vertically through a unit area of saturated soil
in unit time under unit hydraulic gradient.
wtenthbar_r 0.1 bar H2O -
percent The volumetric content of soil water retained
at a tension of 1/10 bar (10 kPa), expressed as
a percentage of the whole soil.
wthirdbar_r 0.33 bar H2O -
at a tension of 1/3 bar (33 kPa), expressed as a
percentage of the whole soil.
wfifteenbar_r 15 bar H2O -
at a tension of 15 bars (1500 kPa), expressed as
a percentage of the whole soil.
3.3. Weather data
Weather data required for DRAINMOD simulations were obtained from weather stations nearest to the
general spatial extent of the respective soil series within the state of Ohio. Counties with largest area
under the respective soil series were obtained from the “NRCS Soil Series Extent Mapping Tool” (Figure
4a). A map showing spatial location of weather stations with data available for DRAINMOD was created

in ArcGIS (Figure 4b). Both map layers (soil extent and weather stations) were overlayed in ArcGIS to
select the weather stations in the general vicinity of each soil series in the state.
3.4. DRAINMOD – Inputs and set up
3.4. 1 Soil Inputs
Soil properties extracted for each soil series were used in Rosetta model that uses pedotransfer
functions to create the detailed soil inputs for DRAINMOD. Figure 5 shows step-by-step procedure used
to create soil inputs for DRAINMOD.
Figure 5: Steps for creating Soil Inputs for DRAINMOD
The soil input files required for running DRAINMOD are *.SOI, *.MIS and *.WDV. Since, we are not
simulating Nitrogen fluxes, *.WDV file was not used for any simulations.
It was assumed that the vertical and lateral components of saturated hydraulic conductivity (Ksat) for a
soil are equal. The web soil survey reports only vertical components of the Ksat values. DRAINMOD, on
the other hand, requires horizontal component, i.e. lateral saturated hydraulic conductivity of soil.
3.4. 2 Weather inputs
The main inputs required for DRAINMOD are daily precipitation and daily minimum and maximum
temperatures. The weather inputs were generated using DRAINMOD weather input utility. The raw data
required for the weather utility were obtained from various weather stations across the state of Ohio.
For each soil series, weather station(s) closest to the general spatial extent of the series were selected
using ArcGIS (Figure 4). In some cases, precipitation and temperature data were missing and/or not
available from the same weather station. In such cases, data from another nearest weather station were
used. The heat index values used for Northern, Central and Southern regions of Ohio were 46, 50, and
57, respectively.
Soil (layer) Properties
from Websoil Survey
•Ksat, bulk density
•% sand, silt, clay,
•Theta_0.33bar
• Theta_15bar
Rosetta
•Output File:
• *.ROS file
DRAINMOD Soil Utility
•Input file: *.ROS
•Output Files:
• *.SOI, *.MIS, *.WDV
•Inputs for DRAINMOD

In general we used 30+ years of weather records ranging between 1950s and 1990s. This period was
chosen in order to maintain comparability between the current project and the project conducted in
2008.
Precipitation
Daily precipitation records for at least 30 years were used from each weather station. The daily rainfall
was divided equally over a period of 4 hours, starting at hour 17:00 (5 PM). The other option would be
to use hourly rainfall data for the weather stations. However, due to limited data availability and time
available for simulations, it was decided to use daily rainfall data.
Temperature
Daily temperature data (i.e. maximum and minimum temperatures) were used in the DRAINMOD utility
to create the actual temperature files for DRAINMOD.
3.4. 3 Crop inputs
It was assumed that uniform grass cover was maintained over the entire area between Engineered
drains. The crop inputs are summarized in Appendix C.
3.4. 4 Drainage Design (Conceptual On-Site System)
We considered two scenarios of a conceptual on-site system. In first scenario, we assumed a single
trench, 91.44 cm (3 ft) in width and 60.96 cm (2 ft) in depth, bounded on both sides with Engineered
drains. Although this may not often be the case in application, we consider it a best case. The
Engineered drains were assumed to be located approximately 2.1 m (~7 ft) from each side of the trench.
This General Case conceptualization is illustrated in Figure 3. In second scenario, we assumed two
trenches with same dimensions, bounded on both sides with Engineered drains. The spacing between
the Engineered drains in this case was assumed to be 22 ft. With these two spacings we considered six
different drain depths as explained in the following paragraph.
Drain depths of 1 ft.(30 cm), 1.5 ft (45 cm)., 2 ft. (60cm), 2.5 ft. (75 cm), 3 ft. (90 cm), and maximum soil
profile depth were used for analysis. Drain spacings of 15 ft (460 cm) and 22 ft (670 cm) were used. Six
depths and two spacings resulted in 12 unique depth-spacing combinations. A drain spacing of 1000 m
(~3281 ft) and drain depth of 1 cm was used to represent “no drainage” scenario. Thus, a total of 13
scenarios were evaluated for each soil series.
3.4. 5 Other Parameters
Several other parameters were needed to initialize the DRAIMOD simulations. All the parameters are
summarized in Appendix C.
3.5. Modeling framework and process
This section describes the overall modeling framework and procedure we used during the project.
3.5. 1 Setting up DRAINMOD Project files
In general, setting up a project file in DRAINMOD requires specifying all the input files (soils, weather,
crops etc.); and the specifying all the initial parameters (e.g. PET factors, drainage design, soil freeze and

thaw parameters etc.). For each soil series, one “master project” was set up, that consisted of all the
model parameters that would remain the same (e.g. input files, soil properties, crop parameters, heat
index etc.). This master project was then used to create multiple projects representing respective
parameter changes (e.g. drain depth, spacing etc.).
For each soil series, separate DRAINMOD projects were set up for 12 combinations of drain depths and
spacings. An additional project representing “No-Drainage” scenario was also set up. Thus a total of 13
project files were created for each soil series.
3.5. 2 Setting up DRAINMOD batch files & Model runs
DRAINMOD provides a utility that can run several project files in a “batch run” mode. This utility was
used to run all 13 project files for each soil series. The model was set to run for at least 30 years. The
simulation period remained the same for all 13 project files for each soil series. However, the simulation
periods varied by a year or two between different soil series.
3.5. 3 Model outputs of interest
DRAINMOD provides several output parameters representing the various components of the water
budget of the system at daily, monthly and annual scales. We used the daily outputs of water table
depths for further analyses. Thus, 13 output files representing 13 scenarios (drain depths and spacings)
were used for further analysis for each soil. Each output file consisted daily outputs for a period of 30+
years (approximately 11,000+ rows).
3.6. Outputs processing for summaries and analysis
3.6. 1 SAS Program for summarizing model outputs
All the output files were read and processed using a program written in SAS (a statistical analysis
software). The automated program reads all output files for all the soils with different drainage system
designs, extracts the daily water table data from the same, and then generates statistical summaries for
each soil series. The following summaries were derived for the model simulated daily water table depth
data for each soil series:
3.6. 2 Annual average number of days the water table would remain within certain depth
from soil surface
For each soil, the 30-year output file that consists of daily water table depths was summarized by the
SAS program. In first step, the program counts the number of days (NOD) in each year, that each of the
following water table criteria were met:
 Event30: NOD that the water table depth was less than or equal to ~1' (30 cm);
 Event45: NOD that the water table depth was less than or equal to ~1.5' (45 cm);
 Event60: NOD that the water table depth was less than or equal to ~2' (~60 cm); and
 Event75: NOD that the water table depth was less than or equal to ~2.5' (75 cm);
 Event90: NOD that the water table depth was less than or equal to ~3' (90 cm)

Thus, for each soil, the program generated a 30+ year list with 4 columns, representing the four water
table criteria. The average of each column was then calculated by the SAS program as the “average NOD
the WT criteria was met”.
3.6. 3 Annual variation of water table depths
For each soil with different drainage system design, the NODs for each WT criteria and the amount of
precipitation are plotted against time. These graphs give a general idea of how drainage design and
precipitation may affect the WT criteria over 30+ years of simulation period. Examples of the graphs are
shown in Figure 12 and Figure 14.
3.6. 4 Probabilities and Recurrence Intervals of daily water table depths
Statistical summaries were generated to estimate the frequency with which a criterion was equaled or
exceeded. We used a Cumulative Distribution Function analysis. A Cumulative Distribution Function
(CDF) of a random variable X (number of days, NOD) is defined as F(x) = P(X ≤ x) for x≥0 while the
Probability Proportional to Frequency (PPF) is defined as 1-CDF. The CDF was calculated using a SAS
program, the recurrence interval (RI) of the water table time distribution could also be predicted by
RI=1/PPF.
4. Results
4.1 How to read and interpret results
4.1.1 Overview of results
Table 3 summarizes all the results that are available for reference and interpretation. Several different
products have been made available considering the typical requirements for design of Engineered drains
for septic systems. Some of the results are in PDF format, and some are in the form of an interactive
utility. The following subsections will describe each of the products briefly. It is recommended that users
refer to the demonstration videos for more details.
4.1.2 Detailed yearly outputs for each soil
The drainmod outputs summarized using SAS program provide the number of days (NOD) each water
table criterion was met during each year. Thus, for each year, program counted NOD related to 5 WT
criteria. The list of these yearly NODs for the entire simulation period of each soil is given in the “Each
Soill.PDF” file. This file is not directly useful for design purpose. However, it shows all the “source data”
that were used for preparing additional products described in subsequent sections.
Using the data from “Each Soil.PDF”, the Graphs1.PDF and Graphs2.PDF files were prepared. The graphs
in these files are simply visual representation of the yearly tabular data for each soil. An example is given
in Figure 12. In general for any soil, the NODs with WT<=30cm is less than those with WT<=60cm.
Similarly, the WT<=90cm criteria results in highest number of days.
4.1.3 Annual summaries and long-term averages
The yearly values for each soil were averaged over the entire simulation period to derive the annual
summaries and averages. Two main files are available for use.

Summary of all soils with Utility.XLSX is a Macro-enabled Microsoft Excel (2010) file (Figure 6) that
allows users to select one soil at a time. A pre-formatted table shows summaries for the selected soil.
The first column lists the drain depths and NODs realted to each WT criteria are listed in the subsequent
columns for 15 ft. and 22 ft. drain spacings, respectively (Figure 7). The file also consists of graphs that
are automatically updated based on summary table for selected soil. The first two graphs show variation
of NODs for each WT criteria (Y-axis) with drain depth (X-axis) at given drain spacing. Thus, first graph
refers to 15-ft. drain spacing and second graph refers to 22-ft. drain spacing. Each line series on the
graph represents one out 5 WT criteria (Figure 8). The subsequent 5 graphs show the relationship
between NODs, drain depth and drain spacing for each of the WT criteria, respectively. Figure 10 shows
a sample graph for Hoytville clay loam.
Summary of all soils.PDF is a PDF file that consists of summary tables for all 66 soils as part of a single
document. This is a ready-to-print file that can be used as a printed source of reference for the same
data from the utility. This file consists of only tabular data. No graphs are available for visual
representation.
Figure 6: Screenshot of Summary of all soils with Utility.XLSX

Figure 7: Example of summary table for Hoytville clay loam soil
[First column (row labels) shows all drain depths in ft. The WT<=30cm column represents NODs the WT<=1ft.
crtieria was fulfilled with a drain spacing of 15ft., and 22 ft. respectively. Grey shading represents NODs > 30 days]
Figure 8: Example graph for Hoytville Clay loam
[X-axis represents drain depth. Chart title suggests, drain spacing of 15 ft. Similar graph is available for 22 ft.
spacing. Each colored line on graph represents one WT criterion. This shows, how the NODs under a WT criteria
change with increasing drain depth. Deeper the drains, less NODs fulfilling that WT criterion]
0
30
60
90
120
150
180
210
240
270
300
330
360
0 1 2 3 4 5 6 7
No.ofDays
Drain Depth, ft.
WT criteria at 15ft. Drain Spacing
WT<1ft. WT<1.5ft. WT<2ft. WT<2.5ft. WT<3ft.

Figure 9: Example graph for Hoytville Clay loam
[This graph compares two drain spacings for the same WT criteria. X-axis represents drain depth. Chart title
suggests, WT<=1.5 ft criteria. Similar graphs are available for WT<= 1ft, 2ft, 2.5ft, and 3 ft, respectively. Red line
represents 22 ft. and blue line represents 15 ft. drain spacing. This shows, how the NODs under a certain WT
criteria change with increasing drain depth for both drain spacings. Deeper the drains, less NODs fulfilling the WT
criterion. Wider the spacing, more NODs fulfilling the WT criterion.]
4.1.4 Probabilities and Recurrence intervals for WT criteria
The yearly-data were used to derive the probabilities and recurrence intervals for each WT criteria. The
recurrence interval is particularly useful for designing Engineered drains. Usually, the designed system is
required to meet the WT criteria for at least 9 out of 10 years. For example, for a selected soil, the NODs
the WT <= 1.5 ft. should be less than 30 days in a year. This criteria needs to be met 9 out of 10 years. In
other words, the recurrence interval for exceedance (or violation) of this criteria should be once in 10
years. This statistic can be read using one the recurrence interval graphs for the given soil. Such graphs
are provided in the macro-enabled excel file: Recurrence Interval Utility.XLSX (Figure 10). The user can
select the soil under consideration and get printable graphs that sho recurrence intervals for each WT
criteria. Figure 11 shows an illustration of how to use the recurrence interval graphs for design purpose.
Appendix B shows a preview of other important output files available.
0
50
100
150
200
No Drainage 1 ft. 1.5 ft. 2 ft. 2.5 ft. 3 ft. 6.6 ft.
No.ofDays
Drain Depth, cm
Water table within 1.5 ft. from surface
30-day criteria 15 ft. Spacing 22 ft. Spacing No Drainage

Figure 10: Screenshot of Recurrence Interval Utility.XLSX
Figure 11: Recurrence interval graphs for Bono soil, with drainage spacing = 22 ft., and drainage
depths from 1.5 ft. to 5.8 ft.
[Objective is to determine optimum drain depth at 22 ft. spacing, such that the WT criteria is met 9 out of 10 years.
The WT criteria in this case is: 30 or less number of days that the WT was less than 30 cm (1 ft.) in a year. This WT
criteria is to be met at least 9 out of 10 years. Note that the graph shows the recurrence interval of “exceedance”
(failure) of this WT criteria. Thus, point “A” on graph represents the drain depth such that: once in 10 years, the
30-day criteria is exceeded (violated). Thus, the green shaded region is the desirable region. Thus, drain depths of
5.8, 3 and 2.5 ft. fulfill the required WT criteria for required recurrence interval. On the other hand, the drain
depths of 2 ft. and 1.5 ft. do not meet the required criteria]
0
5
10
15
20
25
30
35
40
45
50
0 30 60 90 120
RecurranceInterval,YEARS
No. of Days WT criteria not met
22 ft. Spacing (WT<=30cm)
1.5 ft 2 ft 2.5 ft 3 ft 5.8 ft
A

Table 3: Summary of files (All files are available for download at: https://goo.gl/LxJXId )
File Name Summarized by Remarks
Each Soil.PDF Soil >> drain depth >> WT Criteria >>
drain spacing
Contains detailed summary of outputs for each soil. For each soil, 7 separate tables are
included. Each table represents the depth of Engineered drain used (no-drainage, 30, 45,
60, 75 90, and maximum profile depth or 200cm). For any given depth, the table shows,
number of days the water table was within a certain depth range during each simulation
year. Each row represents one year. Main columns are water table criteria (WT<=30cm,
WT<=45cm, WT<=60cm, WT<=75cm, and WT<=90cm). The WT criteria columns are
subdivided for 2 spacings, viz. 15 ft. (460 cm) and 22 ft. (670 cm).
Graphs1.PDF Soil >> drain spacing >> drain depth Contains graphical representation of tables give in “Each Soil.PDF”. Each graph shows
annual precipitation, and number of days the water table criteria was met in the
corresponding year. Each line series represents one of the five WT criteria (WT <= 30, 45,
60, 75, & 90 cm). Each graph represents a unique combination of soil name, drain
spacing and drain depth.
Graphs2.PDF Soil >> drain spacing >> drain depth Same as above
Summary of All Soils with
Utility.XLSX
Soil >> drain spacing >> This file contains a utility that can be used to access data for each soil. After selecting the
soil of interest, the utility displays the table that summarizes results for all 13 depth-
spacing combinations and all 5 water table criteria. The utility also provides graphs that
can aid in visualizing the summary tables. A demonstration of this utility is posted on
youtube at:
https://www.youtube.com/playlist?list=PLaK4N1a0b7wBC9AHessGbcdlltoUhQPcN
Summary of all soils.PDF Drain depth >> soil >> WT Criteria >>
drain spacing
This file lists average number of days each WT criteria was met for all soils. First page
shows number of simulation years for each soil. Each table representing a soil
summarizes data for all the drain depths and spacings of each soil for all WT criteria.
Long term annual average rainfall is also given in the last column.
RecurranceInterval
Utility.XLSX
Soil >> drain spacing This utility allows users to select a file and displays recurrence intervals associated with
the same. The file shows the recurrence interval (years) of the events when WT was <=
30, 45, 60, 75, and 90 cm for a certain (target) number of days. Each graph represents a
unique combination of soil name and drain spacing for one of the 5 water table criteria.
A demonstration of this utility is posted on youtube at:
https://www.youtube.com/playlist?list=PLaK4N1a0b7wBC9AHessGbcdlltoUhQPcN

4.2 Some odd results
Some results from the simulations may seem to be unrealistic and/or unreasonable. However, there are
good reasons for these types of results as explained below.
Case 1: Different NOD for the same depth-spacing combination with same annual precipitation
For most of the soil series, it is you can notice that years with similar annual precipitation resulted in
significantly different number of days for the water table criteria. For example, in Figure 12, simulations
summarized for Platea soil series show the number of days in a year, each water table criteria was
fulfilled and the respective annual precipitation.
Figure 12: Graph showing annual precipitation and number of days water table criteria were met each
year for Platea soil series (drain spacing = 460 cm; drain depth = 75 cm). Note the years marked with
black star ( ). The annual precipitation was similar during all these years, however the number of
days for WTD <= 60cm fluctuates considerably.
The years 1953, 1961, 1969 and 1976 (marked with a black start) all show approximately same annual
precipitation (~90 cm); however, the number of days for these years vary from as low as 40 to as high as
200 for WT <= 60cm criteria. Similar observations can be made for the WT <= 30 cm and WT <= 90 cm
criteria, respectively. A possible reasoning for such a behavior can be explained using the daily time
series of water table depths, and precipitation plotted for all four years (Figure 13). Although, the annual
totals of precipitation are the same for the four years, the distribution of daily rainfall is different for all
four years. Daily evapotranspiration, in combination with temperatures, also affects the water balance,
such that the water table remains at deeper depths due to excessive water loss to atmosphere
(especially during summer months).

200
days
with WT
<= 60cm
Annual
Precip =
89.3 cm
40 days
with WT
<= 60cm
Annual
Precip =
91.5 cm
50 days
with WT
<= 60cm
Annual
Precip =
91.8 cm
185
days
with WT
<= 60cm
Annual
Precip =
91.4 cm
Figure 13: Daily water table depth and precipitation for Platea soil at drain depth = 75 cm and drain
spacing = 460 cm. Four figures represent years 1953, 1961, 1969 and 1976, respectively. These four
years had similar annual total precipitation (~90cm).
Case 2: Results for “No Drainage” scenario
For most of the soil series, “no drainage” scenario resulted in fewer number of days that the water table
was within certain depth range compared to those calculated for “with drainage” scenarios (Figure 14).
Ideally, No Drainage should result in more number of days that the water table was closer to the
surface, compared to the case of having drainage in the same soil at any depth. A closer look at the
annual water budget provides a clarification for this anomaly. For the “No Drainage” scenario, we
observed that most of the water was lost from the system due to increased runoff. For “With Drainage”
scenarios, the average annual runoff ranged from 1 to 8 cm for most soils. However, for “No Drainage”
scenario, the average annual runoff was in the range of 25 to 40 cm. Thus, there was less water that

actually entered the soil profile in case of No Drainage scenario, resulting in lesser number of days that
the water table was closer to the surface. More realistic results can be obtained if DRAINMOD was run
such that the runoff did not change between different scenarios. The parameters related to surface
storage, surface roughness and soil infiltration capacity primarily affect the runoff estimation in
DRAINMOD. These parameters can be adjusted in order to achieve more realistic results for the “No
Drainage” scenario. Furthermore, we have specified the drain depth to be 1 cm for the no drainage
scenario with extremely wide spacing (1000 m). The depth of drain in “no drainage” scenario affects the
estimation of water budget, and hence the estimation of water table elevations to some extent. Further
work and analysis is required to come up with appropriate recommendations for “no drainage”
scenario.
Figure 14: Example showing annual precipitation and number of days water table criteria were met
each year for Platea soil series with No Drainage.
5. Summary
About 66 different soil descriptions were simulated using 30+ years of weather records for analyzing the
water table fluctuations under OSWTS with Engineered drains. For each soil, two spacings (15 ft. and 22
ft.) and 6 drain depths (1 ft., 1.5 ft., 2 ft., 2.5 ft., 3 ft., and maximum profile depth) were simulated using
hydrologic simulation model DRAINMOD N II. A “No Dainage” scenario was also simulated for each soil.
The daily water table depths simulated under each scenario were analyzed to count number of days
(NODs) in a year that the water table depths were less than or equal to 30, 45, 60, 75 and 90 cm (1, 1.5,
2, 2.5, and 3 ft.), respectively. The data were further summarized into annual summaries for each WT
criterion. Demonstration videos are available at https://goo.gl/4E1pVS for detailed description of
available results and utilities. All output files are available for download at: https://goo.gl/LxJXId

6. Future Work
The next phase of this work may involve reanalyzing the 50+ soils that were simulated by Brown et al. in
2008. With data from 100+ soils, there is a potential to create an interactive database utility that will
allow users to select a soil and display results.
7. Acknowledgements and Credits
Acknowledgements
This report was developed with partial funding from the Ohio Department of Health and the Overholt
Drainage Education and Research Program, and the Department of Food, Agricultural, and Biological
Engineering, College of Food, Agricultural and Environmental Sciences at the Ohio State University.
Larry Tornes, provided valuable guidance regarding soils-5 database and properties of soils under
consideration in this report. Jeff Glanville, Soil Scientiest and Soil Database Manager at the USDA-NRCS
(Columbus, OH) helped collect soils data from the NRCS database. Dr. Norman Fausey, USDA-ARS
(Columbus, OH) provided valuable guidance regarding the drainage-realted properties of soils under
consideration. We would also like to acknowledge the contributions of our research team as follows:
Research Team
Name Responsibilities
Larry Brown Project Investigator
Vinayak Shedekar Project coordinator, data collection, organization, report writing, DRAINMOD
simulations, Protocol design
Yuhui Shang Data analysis, DRAINMOD simulations
Kpoti (Stephan) Gunn DRAINMOD simulations; soil data collection and processing
Lindsay Kilpatrick-Pease DRAINMOD simulations; soil data collection and processing
Lamine Diope DRAINMOD simulations; soil data collection and processing
Rogelio Toledo De Leon DRAINMOD simulations; soil data collection and processing
Scott Schwieterman DRAINMOD simulations
Marwa Ghumrawi DRAINMOD simulations; soil data collection and processing
8. Contact Information:
Larry C Brown
Professor & Extension Agricultural Engineer
Department of Food, Agricultural and Biological
Engineering,
The Ohio State University,
590 Woody Hayes Drive, Columbus, OH 43210-1058
Phone: 614-292-3826 | Fax: 614-292-9448
Email: brown.59@osu.edu
Vinayak Shedekar
Graduate Research Associate,
Dept. of Food, Agricultural and Biological
Engineering,
The Ohio State University,
590 Woody Hayes Drive, Columbus, OH 43210
Phone: 203-321-5568 | Fax: 614-292-9448
Email: shedekar.1@osu.edu

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Schwab, G.O., N.R. Fausey and C.R. Weaver. 1975. Tile and surface drainage of clay soils: II. Hydrologic
performance with field crops (1962-72); III. Corn, oats, and soybean yields (1962-72). Research
Bulleting 1081. Wooster, Ohio: Ohio Agricultural Research and Development Center.
Schwab, G.O., N.R. Fausey, E.D. Desmond and J.R. Holman. 1985. Tile and surface drainage of clay soils:
IV. Hydrologic performance with field crops (1973-80); V. Corn, oats and soybean yields (1973-
80); VI. Water quality; VII. Cross moling over tile drains. Wooster, Ohio: The Ohio State
University, Ohio Agricultural Research and Development Center.
Schwab, G.O., T.J. Thiel, G.S. Taylor and J.L. Fouss. 1963. Tile and surface drainage of clay soils: I.
Hydrologic performance with grass cover. Research Bulletin 935. Wooster, Ohio: Ohio
Agricultural Experiment Station.
Seymore, R.M., R.W. Skaggs and R.O. Evans. Predicting corn yield response to planting date delay.
TRANS of the ASAE 35(3):865-869.
Shukla, M.B., S.O. Prasher, A. Madani and G.P. Gupta .1994. Field evaluation of DRAINMOD in Atlantic
Canada. Canadian Agricultural Engineering 36(4):205-213.
Skaggs, R. W. 1977. Evaluation of drainage-water table control systems using a water management
model. In Proc. 3rd Natl. Drainage Symposium, 61-68. ASAE Publication 1-77. St. Joseph, Mich.:
ASAE.
Skaggs, R. W. 1978. A water management model for shallow water table soils. Technical Report No. 134.
Raleigh, N.C.: North Carolina State University, Water Resources Research Institute.
Skaggs, R.W. .1980b. Combination surface-subsurface drainage systems for humid regions. J. of the
Irrigation and Drainage Division ASCE 106(IR4).
Skaggs, R.W. 1976. Determination of the hydraulic conductivity-drainable porosity ratio from water
table measurements. TRANS of the ASAE 19(1):73-80,84.
Skaggs, R.W. 1978. A water management model for shallow water table soils. Rpt. No. 134. Water
Resources Research Institute, Univ. of North Carolina. Raleigh, NC. 175 p.

Skaggs, R.W. 1980a. DRAINMOD Reference Report. Methods for design and evaluation of drainage-
water management systems for soils with high water tables. North Carolina State University,
Raleigh, NC. 177 p.
Skaggs, R.W. 1982. Field evaluation of a water management simulation model. TRANS of the ASAE
25(3):666-674.
Skaggs, R.W. 1987a. Principles of Drainage. In: Farm Drainage in the United States: History, Status, and
Prospects. Misc. Publication No. 1455. Washington, D.C.: U.S. Government Printing Office.
Skaggs, R.W. 1987b. Design and management of drainage systems. In Drainage Design and
Management: Proceedings of the Fifth National Drainage Symposium. December 14-15, 1987,
Hyatt Regency Chicago in Illinois Center. ASAE Publication 07-87. St. Joseph, Mich.: ASAE.
Skaggs, R.W. and A. Nassehzadeh-Tabrizi .1982c. Drainage systems for land treatment of wastewater. J.
of the Irrigation and Drainage Division, Proceedings of ASCE108 No.IR3:196-211.
Skaggs, R.W. and A. Nassehzadeh-Tabrizi. 1982b. Effect of drainage system design on surface and
subsurface runoff from artificially drained lands: Computer simulation model, DRAINMOD. In:
Applied Modeling in Catchment Hydrology, ed. V.P. Singh. Littleton, Colo.: Water Resources
Publications.
Skaggs, R.W. and A. Nassehzadeh-Tabrizi. 1983. Optimum Drainage for Corn Production. Technical
Bulletin 274. North Carolina Agricultural Research Service. Raleigh, NC.: North Carolina State
University.
Skaggs, R.W. and A. Nassehzadeh-Tabrizi. 1986. Design drainage rates for estimating drain spacings in
North Carolina. TRANS of the ASAE 29(6):1631-1640.
Skaggs, R.W., A. Nassehzadeh-Tabrizi, G.R. Foster .1982d. Subsurface drainage effects on erosion. J. of
Soil and Water Conservation, May-June, 167-172.
Skaggs, R.W., M.A. Breve, A.T. Mohammad, J.E. Parsons and J.W. Gilliam. 1995. Simulation of drainage
water quality with DRAINMOD. Irrigation and Drainage Systems 9(3):259-277.
Skaggs, R.W., N.R. Fausey and B.H. Nolte. 1981. Water management model evaluation for North Central
Ohio. TRANS of the ASAE 24(4):922-928.
Skaggs, R.W., S. Hardjoamidjojo, E.H. Wiser and E.A. Hiler .1982a. Simulation of crop response to surface
and subsurface drainage systems. TRANS of the ASAE: 1673-1678.
Skonard, C.J., D.W. DeBoer and H.D. Werner .1993. Water table management evaluation on glacial till
soils. ASAE Paper No.932124. St. Joseph, Mich.: ASAE.

Soil Survey Staff, Natural Resources Conservation Service, United States Department of Agriculture. Web
Soil Survey. Available online at http://websoilsurvey.nrcs.usda.gov/. Accessed Apr. 2014- Apr.
2015.
Tornes, L., B.C. Atherton, L.C. Brown, R.M. Gehring, B. Slater, J.R. Steiger, M. DeBrock, T.L. Zimmerman,
N.R. Fausey, and G.S. Hall. 1998. Soil property database for design, construction, operation and
management of agricultural water management systems for irrigation, constructed wetlands,
drainage, and environmental considerations. Presented at the July 1998 ASAE International
Meeting, Orlando, Florida.
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Extension Service, The Ohio State University and Ohio Department of Natural Resources,
Division of Lands and Soil. 1976. Ohio Drainage Guide. Hyattsville, MD.: USDA Soil Conservation
Service.
Workman, S. R., R.W. Skaggs, J.E. Parsons and J. Rice. 1990. DRAINMOD User's Manual. N.C. State
University. Raleigh. 95 p.
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drained plots. TRANS of the ASAE 28(5):1612-1616.
Workman, S.R. and R.W. Skaggs. 1989. Comparison of two drainage simulation models using field data.
TRANS of the ASAE 32(6):1933-1938.
Workman, S.R. and R.W. Skaggs. 1994. Sensitivity of water management models to approaches for
determining soil hydraulic properties. TRANS of the ASAE 37(1):95-102.
Workman, S.R., R.W. Skaggs, J.E. Parsons and J. Rice (Eds). 1986. DRAINMOD User’s Manual. Biological
and Agricultural Engineering Department, North Carolina State University, Raleigh, North
Carolina. 90 p.
Youssef, M. A., R. W. Skaggs, G. M. Chescheir, and J. W. Gilliam. 2005. The nitrogen simulation model,
DRAINMOD-N II. Trans ASAE 48(2): 611-626.
Youssef, M. A., R. W. Skaggs, J. W. Gilliam, and G. M. Chescheir. 2006. Field evaluation of a model for
predicting nitrogen losses from drained lands. J. Environ. Qual. 35(6): 2026-2042.
Zucker, L.A. and L.C. Brown. (Eds.). 1998. Agricultural Drainage: Water Quality Impacts and Subsurface
Drainage Studies in the Midwest. Ohio State University Extension, Bulletin 871. The Ohio State
University. 40 pp.

10.Appendices

Appendix A: Summary of DRAINMOD modeling work related to Engineered
drains in Ohio
2008
(Modeling Water-Table Elevations for Curtain-Drain Applications with On-Site Wastewater Treatment
Systems in Ohio)
 58 representative soil series were analyzed
 Drain spacings: 5 m (~16 ft), 10 m (~33 ft), and 15 m (~50 ft)
 Drain depth: a maximum drain depth of ~4.5' (140 cm)
o Except for Loudonvile and Millsdale, with maximum drain depths of 90 cm (~2.95') and
100 cm (~3.28'), respectively.
 Undrained condition: spacing of 1000 m (~3,281') for about one-half of these soils series.
 Water Table Scenarios:
o Water table depth less than or equal to ~1 ft (30 cm);
o water table depth less than or equal to ~2 ft (~60 cm); and
o water table depth less than or equal to ~3 ft (90 cm).
 The drainage coefficient was 1.27 cm/day (3/8 in/day)
 In addition to the original 51 soil series, 7 additional series were added to this group at the
request of representatives from the Ohio Department of Health:
o Haskins, Lewisburg, Mahoning, Rittman, Sebring, Switzerland and Tedrow.
o Drain spacings of 5 m (~16'), 10 m (~33'), and 15 m (~50'),.
o Maximum drain depth of 140 cm (~4.6') for the general case.
 For Loudonvile and Millsdale, with maximum drain depths of 90 cm (~2.95') and
100 cm (~3.28'), respectively.
o For all of the undrained cases analyzed, a drain spacing of 1000 m (~3,281') and a drain
depth of 60 cm (~2') cm were used.
 Additional Analysis for 4 soil series
o Blount, Crosby, Hoytville, and Mahoning were further modeled and analyzed for a set of
four Case Studies:
o The effect of daily wastewater application in addition to precipitation;
 Two different application depths: 1.25 cm/day (~0.5 in/day) and 0.33 cm/day
(0.13 in/day).
o The effect of land slope
 Land slopes of 3% and 6% were evaluated.
o The use of a shallower curtain drain depth; and
 Drain depths of 60 cm (~24 in) and 90 cm (~36 in).
o The use of a gravel envelope to increase the effective radius of the curtain drain
 Effective radius of 6 cm (2.36 in) was evaluated.
o For all of the results of these Case Studies, the results were compared and plotted
against the values obtained for the 140-cm (~55 in) drain depth cases.
 Seepage was not considered, land slope 0 to 2%,

 Used a Cumulative Distribution Function analysis. A Cumulative Distribution Function (CDF) of a
random variable X (number of days, NOD) is defined as F(x) = P(X ≤ x) for x≥0 while the
Probability Proportional to Frequency (PPF) is defined as 1-CDF. The CDF was calculated by using
MINITAB statistical software and as a result, the recurrence interval (RI) of the water table time
distribution could also be predicted by RI=1/PPF.
2014
 66 new soil series out of 475 recognized
 Drain depths: 1 ft.(30 cm), 1.5 ft (45 cm)., 2 ft. (60cm),2.5 ft. (75 cm),3 ft. (90 cm), and max
profile depth
 Drain spacings:
o 15 ft (4.6 m) and 22 ft (6.7 m)
o No Drainage (3000 ft or 1000 m)
 Water Table Scenarios:
o Water table depth less than or equal to ~1 ft (30 cm);
o Water table depth less than or equal to ~1.5 ft (45 cm);
o water table depth less than or equal to ~2 ft (~60 cm);
o Water table depth less than or equal to ~2.5 ft (75 cm); and
o water table depth less than or equal to ~3 ft (90 cm).
 Conduct an 8 hour workshop to provide training on soils analysis using DRAINMOD. Provide
related training materials and supplies.

Appendix B: Preview of Files
1. Each Soil.PDF

2. Graphs.PDF

Appendix C: DRAINMOD inputs

Table: List of Inputs and parameters used for DRAINMOD N II simulations
Input Description
DM code
variable
Selected Input Parameter Comments Source
Drainage Design
System Design
Depth to Drain (ft - cm) DDRAIN
1.0 - 30
1.5 - 45
2.0 - 60
2.5 - 75
3.0 - 90
Max soil profile up to 6.5 - 200
Distance Between Drains (ft - cm) SDRAIN
15 - 460
For selected high Ksat values add 60, 75, 90,
105 m22 - 670
No drainage - 100000
Effective Radius of Drains (cm) EFFRAD 0.51
Effective radius of the drain is the radius of a
completely open tube w/ the same
resistance to inflow as the real drain tube.
For standard 4-in corrugated drain tile w/
openings 38 cm2/m, EFFRAD=0.51 cm
p. 29 DRAINMOD manual
Actual Depth from Surface to Impermeable
Layer (cm)
ADEPTH
Profile depth (bottom depth of
the lowest soil layer)
Depth to impermeable layer should be taken
as the bottom of the profile given from the
soils information (most often=152 cm); have
used 180 cm as input. Model insensitive to
changes in depth to impermeable layer
(Kurien et al., 1995). Leave at 180 cm?
Kurien, V.M., R.A. Cooke,
M.C. Hirschi, J.K. Mitchell.
1995. Estimation of
Effective Drain Spacing for
Incomplete Drainage
Systems.
Equivalent Depth from Drain to Impermeable
Layer
HDRAIN recalc
Drainage Coefficient (cm/day - in/day) DC 1.27 - 0.5
From Schwab et al. (1982), for 20-cm
drawdown depth (most practical for most
field crops), DC=1.27 cm/day. 1/2-in/day
and 3/8-in/day commonly used for design in
Ohio. 1/2-in/day selected because less
limiting and suggested by Schwab et al.
Schwab, G.O., D.W.
Michener, D.E. Kopcak.
1982. Spacings for
Subsurface Drains in Heavy
Soils.
Kirkham's Coefficient G GEE recalc

Input Description
DM code
variable
Initial Depth to Water Table (cm) DTWT 50
DTWT has no effect on results of long term
simulations. If initial depth to the water
table is not known, a value of 1/2 the drain
depth is a good approximation.
p. 29 DRAINMOD manual
Maximum Surface Storage (cm) STMAX 2.5
STMAX represents the maximum surface
storage which must be filled before runoff
occurs. Good (0.2-0.5cm), Fair (1.0-1.5cm),
Poor (>2.0cm). STMAX=2.5cm selected
based on sensitivity analysis performed and
represents poor surface drainage conditions.
p. 30 DRAINMOD manual;
Skaggs, Hardjoamidjojo,
Wisser, Hiler. Simulation of
Crop Response to Surface
and Subsurface Drainage
Systems.
Kirkham's Depth for Flow to Drains (cm) STORRO 1.0
STORRO is the storage in local depressions
such that water is prevented from moving
freely to a position over drain. A level
surface w/ little ponding=0.5cm, sloping field
w/ small ponds=0.9cm, a field w/ a large
depression=3.4cm storage (Workman...)
Workman, S., N. Fausey.
Macro relief Surface
Storage on Naturally
Occuring and Surface
Drained Plots.
Weir settings
Bottom width of the ditch (cm) 200
Ditch side slope (%????) 0.5
Seepage
Downslope NONE
Vertical NONE
Lateral NONE
Soils Data
Layer characteristics
Bottom Depth of Layer
varies by soil - use bracketed
values on screen
Web soil survey
Lateral Hydraulic Saturated Conductivity
varies by soil - use bracketed
values on screen
DRAINMOD output is very sensitive to
variations in K of the drain tile layer, but
insensitive to changes in K above the tile
drain layer (Kurien et al., 1995).
Web soil survey
Soil-Water Characteristics
THETA,
HEAD
Use values that appear from
soil file
Web soil survey
Water Table Depth WTD
soil file
Web soil survey

Input Description
DM code
variable
Volume Drained XVOL
soil file
The last entry for XVOL must be 100.0 and
the last entry for WTD must be 1000 for the
volume drained relationship (p. 34
DRAINMOD manual)
Web soil survey
Upward Flux UPFLUX
soil file
The last value for depth to the water table
must be 1000 cm and 0 for upward flux (p.
35 DRAINMOD manual).
Web soil survey
Green-Ampt Equation Parameters DEPTH,A,B
soil file
Web soil survey
Soil temperature
ZA coefficient 2.5 reference from Minneapolis
ZB coefficient 1.21
TKA Coefficient 0.39
TKB Coefficient 1.33
Avg air temperature below which
precipitation is snow (deg C)
0
Avg air temperature above which snow starts
to melt
1
snow melt coefficient (mm/dd-deg C) 5
Critical ice content above which infiltration
stops (cm3/cm3)
0.2
initial conditions
(0,0)(299,9.11) snow depth=0,
snow density=100(kg/m3)
Phase lag for daily air temperature sine wave
(hour)
8
Soil temperature at bottom of the profile (deg
C)
9.11
Freezing Characteristics
(0, saturated water content for
the soil)
(-1.00, 0.10)
(-3.00, 0.01)
(-35.00, 0.00)

Input Description
DM code
variable
Weather data
station ID from weather file
latitude find from station location
heat index
46 - North
50 - Central
57 - South
PET factors
Monthly, use 1 for all the
months
Crop Data
Crop Inputs
Root Depth (cm) 15 (for grass all the year round) Mengle and Barber(1974)
lower limit of water content in root
zone(cm3/cm3)
0.08
Limiting Water Table Depth (cm) SEWX 30 Skaggs, 1981
Dates to Begin Counting ISEWMS… 4/15 (North)
Wet/Drought Stress IDRYMS… 4/12 (Central)
4/10 (South)
Date to End Counting Wet/Drought Stress ISEWME 9/30
Trafficability Inputs
Month Number to Begin Counting Work Days
(Period 1)
MOBW1 4 (April)
Day to Begin Counting Work Days (Period 1) IDABW1 4/10 (North)
Based on planting date information from
Ohio Agronomy Guide. Assume 5 days to
prepare seed bed, and subtract from desired
planting date for when to start counting
work days.
Ohio Agronomy Guide
4/7 (Central)
4/5 (South)
Month Number to End Counting Work Days
(Period 1)
MOEW1 6 (June)

Input Description
DM code
variable
Day to End Counting Work Days (Period 1) IDAEW1 15
Based on the model's need for a long Spring
trafficability window when considering yield
outputs.
Starting Hour of Work Day (Period 1) SWKHR1 8 Common farm practice
Ending Hour of Work Day (Period 1) EWKHR1 22 Common farm practice
Minimum Air Volume Required to Work Land
(Period 1) (cm)
AMIN1 2.0
Also Jane's sensitivity analysis suggested this
value
Nolte,et.al 1983
Skaggs(1980b)
Minimum Rain to Delay Work (Period 1) (cm) ROUTA1 0.5
ROUTA1 and ROUTT1, ROUTA2 and ROUTT2
were chosen based on what was used by
Nolte in his 1983 study
Nolte,et.al 1983
Delay After Rain to Recommence Work
(Period 1) (days)
ROUTT1 1 Nolte,et.al 1983
Month Number to Begin Counting Work Days
(Period 2)
MOBW2 10 (October)
Day to Begin Counting Work Days (Period 2) IDABW2 1
Month Number to End Counting Work Days
(Period 2)
MOEW2 12 (December)
Day to End Counting Work Days (Period 2) IDAEW2 31
Starting Hour of Work Day (Period 2) SWKHR2 8
Ending Hour of Work Day (Period 2) EWKHR2 20
Minimum Air Volume Required to Work Land
(Period 2) (cm)
AMIN2 2
Minimum Rain to Delay Work (Period 2) (cm) ROUTA2 0.5 Nolte,et.al 1983
Delay After Rain to Recommence Work
(Period 2) (day)
ROUTT2 1.0 Nolte,et.al 1983

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