National Academies Press: OpenBook

Relationship Between Erodibility and Properties of Soils (2019)

Chapter: Chapter 5. Organization and Interpretation of the Data

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Suggested Citation:"Chapter 5. Organization and Interpretation of the Data." National Academies of Sciences, Engineering, and Medicine. 2019. Relationship Between Erodibility and Properties of Soils. Washington, DC: The National Academies Press. doi: 10.17226/25470.
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Suggested Citation:"Chapter 5. Organization and Interpretation of the Data." National Academies of Sciences, Engineering, and Medicine. 2019. Relationship Between Erodibility and Properties of Soils. Washington, DC: The National Academies Press. doi: 10.17226/25470.
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Suggested Citation:"Chapter 5. Organization and Interpretation of the Data." National Academies of Sciences, Engineering, and Medicine. 2019. Relationship Between Erodibility and Properties of Soils. Washington, DC: The National Academies Press. doi: 10.17226/25470.
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Suggested Citation:"Chapter 5. Organization and Interpretation of the Data." National Academies of Sciences, Engineering, and Medicine. 2019. Relationship Between Erodibility and Properties of Soils. Washington, DC: The National Academies Press. doi: 10.17226/25470.
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Suggested Citation:"Chapter 5. Organization and Interpretation of the Data." National Academies of Sciences, Engineering, and Medicine. 2019. Relationship Between Erodibility and Properties of Soils. Washington, DC: The National Academies Press. doi: 10.17226/25470.
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Suggested Citation:"Chapter 5. Organization and Interpretation of the Data." National Academies of Sciences, Engineering, and Medicine. 2019. Relationship Between Erodibility and Properties of Soils. Washington, DC: The National Academies Press. doi: 10.17226/25470.
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Suggested Citation:"Chapter 5. Organization and Interpretation of the Data." National Academies of Sciences, Engineering, and Medicine. 2019. Relationship Between Erodibility and Properties of Soils. Washington, DC: The National Academies Press. doi: 10.17226/25470.
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Suggested Citation:"Chapter 5. Organization and Interpretation of the Data." National Academies of Sciences, Engineering, and Medicine. 2019. Relationship Between Erodibility and Properties of Soils. Washington, DC: The National Academies Press. doi: 10.17226/25470.
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Suggested Citation:"Chapter 5. Organization and Interpretation of the Data." National Academies of Sciences, Engineering, and Medicine. 2019. Relationship Between Erodibility and Properties of Soils. Washington, DC: The National Academies Press. doi: 10.17226/25470.
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Suggested Citation:"Chapter 5. Organization and Interpretation of the Data." National Academies of Sciences, Engineering, and Medicine. 2019. Relationship Between Erodibility and Properties of Soils. Washington, DC: The National Academies Press. doi: 10.17226/25470.
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Suggested Citation:"Chapter 5. Organization and Interpretation of the Data." National Academies of Sciences, Engineering, and Medicine. 2019. Relationship Between Erodibility and Properties of Soils. Washington, DC: The National Academies Press. doi: 10.17226/25470.
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Suggested Citation:"Chapter 5. Organization and Interpretation of the Data." National Academies of Sciences, Engineering, and Medicine. 2019. Relationship Between Erodibility and Properties of Soils. Washington, DC: The National Academies Press. doi: 10.17226/25470.
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Suggested Citation:"Chapter 5. Organization and Interpretation of the Data." National Academies of Sciences, Engineering, and Medicine. 2019. Relationship Between Erodibility and Properties of Soils. Washington, DC: The National Academies Press. doi: 10.17226/25470.
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Suggested Citation:"Chapter 5. Organization and Interpretation of the Data." National Academies of Sciences, Engineering, and Medicine. 2019. Relationship Between Erodibility and Properties of Soils. Washington, DC: The National Academies Press. doi: 10.17226/25470.
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Suggested Citation:"Chapter 5. Organization and Interpretation of the Data." National Academies of Sciences, Engineering, and Medicine. 2019. Relationship Between Erodibility and Properties of Soils. Washington, DC: The National Academies Press. doi: 10.17226/25470.
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123 CHAPTER 5 5. ORGANIZATION AND INTERPRETATION OF THE DATA One of the major problems with analyzing erodibility parameters is that these parameters are derived from different test types, and are not consistent with one another. While bringing some uniformity between tests results is important as later discussed in Chapter 6, it is equally important to collect existing erodibility data obtained from each test. The first step in collecting such data was to come up with an acceptable and consistent fashion to organize the erosion data collected. To achieve this goal, a global erosion spread sheet called TAMU-Erosion Spread Sheet was developed. The entire TAMU-Erosion Spreadsheet in .xlsm format is available on the NCHRP website. Section 5.1 presents how TAMU-Erosion was organized and developed. Section 5.2 introduces the entries of each column in TAMU-Erosion. Section 5.3 provides the reader with a manual on how to probe and use TAMU-Erosion. 5.1. Development and Organization of the TAMU-Erosion During the first phase of this project, near 750 erosion tests were collected from the literature review as well as by contacting researchers and organizations working on erosion around the world. Table 26 shows the 34 organizations and people contacted in the first phase of this project. Erosion data were extracted from technical reports, lab test results, field test results, and well- known journal/conference papers. In parallel with the erosion tests, the geotechnical properties of each tested sample, alongside with any information on the latitude and longitude location or origin of them were compiled. The data collected includes the results of commercially used erosion tests such as the Erosion Function Apparatus test (EFA), the Jet Erosion Test (JET), the Hole Erosion Test (HET), the Slot Erosion Test (SET), the Ex-situ Scour Test Device (ESTD), the Borehole Erosion Test (BET), the Rotating Erosion Testing Apparatus (RETA), the Sediment Erosion Rate Flume (SERF), the In Situ Scour Profile (ISEEP), and some large-scale flume tests. In addition to the aforementioned erosion tests, according to Chapter 4, around 250 erosion tests were performed during this project. These tests include the EFA, the JET, the HET, the PET, and the BET. Alongside with the erosion testing, all major geotechnical properties tests were conducted on each sample that was tested in any erosion device (Section 4.4 and Appendix 2), and soil properties spreadsheets were generated for each sample. Collected erosion tests, and performed tests during this project formed a global spreadsheet that consists of 975 erosion tests. This spreadsheet is called the TAMU-Erosion Spreadsheet. Table 27 shows a summary of the number of test results obtained to date for each erosion device. Figure 79 shows a summary chart of data compilation for TAMU-Erosion since the start of the project.

124 Table 26. A selected list of contact people and organizations around the world Contact Person Organization Contact Person Organization 1 Stephane Bonelli IRSTEA, France 18 J Beard NCDOT, USA 2 Sherry Hunt USDA, USA 19 M Haeri NCDOT, USA 3 Johannes Wibowo USACE, USA 20 Kaye Brubaker U. of Maryland, USA 4 Axel Montalvo USACE, USA 21 Timothy Straub USGS, USA 5 Anna Shidlovskaya U. of Mines, Russia 22 Tom Over USGS, USA 6 Tony Wahl USBR, USA 23 Derrick Dasenbrock MnDOT, USA 7 Morvant, Maurice FCL Fugro, USA 24 Abdelkrim ESTP, France 8 John Delphia TxDOT, USA 25 Marie-Jo GOEDERT ESTP, France 9 Jeff Locke Fugro, USA 26 Heibaum, Michael BAW, Germany 10 M. A. Gabr NCSU, USA 27 Chenzuyu (Tsinghua) Beijing, China 11 Beatrice Hunt AECOM, USA 28 Gijs Hoffmans Deltares, Netherlands 12 Richard Whitehouse HRWallingFord, UK 29 Stephen Benedict USGS, USA 13 Kiseok Kwak KICT, Korea 30 Christophe Chevalier IFSTTAR, France 14 Brian Anderson Auburn, USA 31 Garey Fox NCSU, USA 15 Robbin Fell UNSW, Australia 32 Peter Allen Baylor University, USA 16 Kornel Kerenyi FHWA, USA 33 Lin Wang China Institute of Water Resources 17 D Henderson NCDOT, USA 34 Mike C. Lin & Scott Shewbridge USACE, USA

125 Table 27. A summary of the erosion test data in TAMU-Erosion Erosion test type Number of collected test result data EFA 346 HET 233 SET 84 ESTD 17 ISEEP 6 SERF 13 JET 147 BET 17 RETA 14 PET 95 Large-scaled widening test 3 TOTAL 975 Figure 79. Summary chart of data compilation for TAMU-Erosion since the start of the project The important characteristic of TAMU-Erosion is its ability to bring a wide range of erodibility parameters together and compare them in a consistent fashion as proposed by Briaud (2008). The erodibility parameters which were selected to represent the erosion characteristics of a soil are the critical shear stress , the critical velocity ,the initial slope of the versus curve, and the initial slope of the versus curve. In addition, the erosion function category (EC) in the Briaud erosion chart (2013) is considered as an additional parameter to describe erosion characteristics of a soil and is added as a parameter for the erosion correlations study. Figure 3 shows the erosion categories based on both velocity and shear stress, respectively. In TAMU-Erosion, all the erosion data are analyzed according to the procedures described below for the five erodibility parameters: , , , , and EC.

126 1) Critical velocity, : all the data points of the velocity erosion curve are plotted on the erosion chart (Figure 3). This plot is on log scale for both the x and the y axes. The “zero” on the y axis (log scale) is set at an arbitrarily low erosion rate of 0.1 mm/hour. The reasons to choose an arbitrary low erosion rate of 0.1 mm/hr is that 1) a log-log scale plot cannot take “zero” value, 2) 0.1 mm/hr is practically the same as 0 mm/hr. If the erosion curve intercepts the horizontal axis at any point, that point is the critical velocity. If there is no data point on that axis, the line between the first two points of the erosion curve, is extrapolated linearly and the point at which this extrapolated line crosses the horizontal axis is selected as the critical velocity value. 2) Critical shear stress, : all the data points of the shear stress erosion curve are plotted on the erosion chart (Figure 3). This plot is on log scale for both the x and the y axes. The “zero” on the y axis (log scale) is set at an arbitrarily low erosion rate of 0.1 mm/hour. If the erosion curve intercepts the horizontal axis at any point, that point is the critical shear stress. If there is no data point on that axis, the line between the first two points of the erosion curve, is extrapolated linearly and the point at which this extrapolated line crosses the horizontal axis is selected as the critical shear stress value. Figure 80 shows an example of how the critical shear stress is calculated for a case where the line has to be extended to cross the horizontal axis. 3) The initial slope of the versus plot is obtained by fitting a straight line through the initial points of the curve. 4) The initial slope of the versus plot is obtained by fitting a straight line through the initial points of the curve. 5) For the erosion function category (EC), the median point in the erosion curve is considered as the representative point for EC. Therefore, EC depends on the location of the median point on the erosion curve. The number of points on the erosion function can therefore impact the choice of EC; it is recommended that many points be obtained to define the erosion function category. As mentioned earlier, the erosion function is not a single number but a curve. EC translates this curve into one single number that gives useful information about the range of erosion rate for a sample at a given water velocity or the hydraulic shear stress. Figure 81 shows an example of how EC is determined. EC for this particular example is obtained as 2.25. Note that the dash lines on Figure 81 represent the EC values corresponding to 1.25, 1.75, 2.25, 2.75, and so on.

127 Figure 80. An example showing how critical shear stress is obtained when erosion curve itself does not cross the horizontal axis Figure 81. An example showing how EC is obtained for a sample erosion curve – EC for this example is 2.25

128 5.2. Column Contents in TAMU-Erosion As discussed in the previous section, TAMU-Erosion includes 975 erosion tests, or in other words 975 rows. Each row in TAMU-Erosion consists of 49 columns. The entries for the columns are listed in Table 28 from left to right. All test results are presented in the same format of erosion rate versus velocity and/or versus shear stress. Furthermore, they are all plotted on the erosion categories proposed by Briaud (2013). In several cases, the data collected had to be digitized. Now, all plots of erosion functions in the erosion function column have embedded spread sheets of their own. That way the user can click on the plot and obtain the point by point data. A manual on how to use the TAMU-Erosion is presented in the Section 5.3. A comments column for each erosion test as gives pertinent details about any special treatment or condition during the erosion test, or in interpretation of the results. Also, a column for general comments about the sample provide related special information about the sample, if applicable. Figure 82 shows a general view of TAMU-Erosion, including the three parts: Part 1) Record Information, Part 2) Erosion Information, and Part 3) Soil Properties Information which itself is divided into two sections. Section 1 refers to the most common geotechnical soil properties while Section 2 refers to less common properties. The entries of each aforementioned part are described in the following sections. It is very important to note that obviously many cells in TAMU-Erosion are empty, due to the lack of information for each sample. Part 1 – Record Information This part of TAMU-Erosion presents the general record information of the soil sample. Figure 83 shows a zoomed-in picture of the “Part 1 – Record Information” of one sample from TAMU- Erosion as an illustration. The column “Record Number” shows the row number associated with the sample in TAMU-Erosion. Second column “Contact/Credit” provides information about the person or entity that owns the data associated with this sample. The third column “Date conducted/ Sampled” shows when the test was conducted or sometimes as in the case of natural samples, when the sample is obtained from the field. The fourth column “Project Title/ Sponsor” presents the title of the project or the sponsor, when applicable, that led to the measurement of this sample’s test results. The fifth column “Sample Name” shows the name associated with the sample. The sixth column “Sample Depth” provides the depth of the sample in the case of natural samples. The unit of depth is either meter or feet, depending on the original data. The sample is classified according to the USCS and AASHTO classification methods in the eighth and ninth columns, respectively. Finally, the last column in Part 1 identifies whether the sample is remolded (man-made) or natural (intact).

129 Figure 82. General view of TAMU-Erosion Table 28. List of entries in TAMU-Erosion Part 1 1. Record numbers Part 3 Sec. 1 26. Tensile strength (kPa) 2. Contact / Credit 27. UCS (kPa) 3. Data Conducted / Sampled 28. Vane shear strength, Su (kPa) 4. Project Title / Sponsor 29. Percent fines (%) 5. Sample Name 30. SPT N-value 6. Sample Depth 31. D50 (mm) 7. Soil Type 32. D10 (mm) 8. USCS Classification 33. D30 (mm) 9. AASHTO Classifiaction 34. D60 (mm) 10. Natural / Man-made 35. Cc Part 2 11. Erosion Test Type 36. Cu 12. Erosion Function Curve Part 3 Sec. 2 37. Void ratio, e (%) 13. Erosion Category 38. Degree of saturation, Sr (%) 14. Slope of velocity curve (Ev) 39. Percent compaction (%) 15. Slope of shear stress curve (E ) 40. Specific Gravity (Gs) 16. Critical Velocity (Vc) 41. Dispersion ratio (%) 17. Critical Shear Stress ( c) 42. pH 18. Remarks on erosion test 43. Electrical Conductivity (micro-siemens) Part 3 Sec. 1 19. General comments 44. Fluid Temperature (C) 20. Liquid limit, LL (%) 45. Salinity (ppm) 21. Plastic limit, PL (%) 46. Percent Clay (%) 22. Plasticity index, PI (%) 47. Percent Silt (%) 23. Wet unit weight, (kN/m3) 48. Organic Content (%) 24. Water content (%) 49. Soil Activity 25. Pocket penetrometer strength (kPa)

130 Figure 83. Record information (Part 1) of TAMU-Erosion Part 2 – Erosion Information This part of TAMU-Erosion presents the erosion test results of the sample. Figure 84 shows a zoomed-in picture of the “Part 2 – Erosion Information” of the same sample that was described in the previous section, as an illustration. The first column “Erosion Test Type” identifies the type of the erosion test that was conducted on the sample. In this example, the sample was tested in the EFA. Each erosion test type is designated with a specific color in TAMU-Erosion. A list of the colors used to designate each erosion test in TAMU-Erosion is shown in Table 29. These colors help the user identify each test more easily in a big-picture view of the spreadsheet. Table 29. List of colors used to designate each erosion test in TAMU-Erosion Erosion Test Type Associated Color EFA Pink JET Light Blue HET Gray PET Orange SET Lavender SERF Yellow ESTD Green ISEEP Dark Blue BET Dark Orange RETA Red Large-scaled Flume White The second column “Erosion Function” plots the erosion test results on the erosion category chart which was proposed by Briaud (2008). As mentioned earlier, all plots of erosion functions Record  Numer Contact /  Credit Date  Conducted /  Sampled Project  Title /  Sponser Sample Name Sample  Depth Soil Type USCS  Classifica tion AASHTO  Classification Natural /  Manmade 786 Jean Louis  Briaud /  TAMU, US 1/17/2017 NCHRP  24‐43 B‐12‐16 (18'‐20.5') @18.95' 18.95' Clay CL A‐7‐6 (23.6) Natural

131 in the erosion function column have embedded spread sheets of their own. That way the user can click on the plot and obtain the point by point data. A manual on how to use TAMU-Erosion is presented later in Section 5.3. The next five columns (i.e. “Erosion Category”, “ ”, “ ”, “ ”, and “ ”) present the five erodibility parameters obtained after each erosion test. It should be noted that not all erosion tests can produce all five erodibility parameters. For instance, the JET and the HET can only report three out of five of these erodibility parameters (i.e. Erosion Category, , and ), while the EFA can generate all five parameters. Finally, the last column on Figure 84, “Remarks on Erosion Test”, presents any special treatment or necessary comment regarding the erosion test. Figure 84. Erosion information (Part 2) of TAMU-Erosion Part 3 – Soil Properties Information Section 1 – More typically obtained geotechnical properties This part of TAMU-Erosion presents the geotechnical index properties of the sample that are more typically obtained by the engineers. Figure 85 shows a zoomed-in picture of the Section 1 of the “Part 3 – Soil Properties Information” for the same sample that was described in the previous section, as an illustration. The first column provides some general information about the location of the sample, longitude/latitude coordinates, color, and any special treatment of the sample, where applicable. The other columns as shown in Figure 85 include mostly the more typically obtained geotechnical properties. Erosion  Test Type Erosion Function Erosion  Category Ev (mm/hr‐ m/s) Eτ (mm/hr‐ pa) Vc (m/s)  c (Pa) Remarks on  Erosion Test EFA 2.5 4.66 1.22 0.57 0.92 E R O S I O N     P A R A M E T E R S 0.1 1 10 100 1000 10000 100000 0.1 1 10 100 Er os io n  Ra te (m m /h r) Velocity (m/s) Very High Erodibility I High Erodibility II Medium Erodibility III Low Erodibility IV Very Low Erodibility V Non-Erosiv e VI 0.1 1 10 100 1000 10000 100000 0.1 1 10 100 1000 10000 100000 Er os io n  Ra te (m m /h r) Shear Stress (Pa) Very High Erodibility I High Erodibility II Medium Erodibility III Low Erodibility IV Very Low Erodibility V Non-Erosiv e VI

132 Figure 85. Geotechnical Properties (Part 3-Section 1) of TAMU-Erosion Section 2 – Less typically obtained geotechnical properties This part of TAMU-Erosion presents the geotechnical index properties of the sample that are less typically obtained by the engineers. Figure 86 shows a zoomed-in picture of the Section 2 of the “Part 3 – Soil Properties Information” for the same sample that was described in the previous section, as an illustration. The columns that represent the less typically obtained geotechnical properties are shown in Figure 86. Figure 86. Geotechnical Properties (Part 3-Section 2) of TAMU-Erosion General  Comments LL PL PI ϒ  (kN/m3) Water  Content  (%) Pocket  Penet.  (kPa) Tensile  Strengt h (KPa) UCS  (KPa) VST Su  (KPa) Percent  Fines  (%) SPT N‐value D50  (mm) D10  (mm) D30  (mm) D60  (mm) Cu Cc 1‐ Alcona Dam 2‐ Cemented 3‐Light Brown 4‐ Undrained  shear strength is  predicted from  Pocket  Penetrometer  (=0.3*Compressi on Strength) 42.1 18.6 23.5 18.2 20.51 354 106.2 95.5 0.0028 0.0040 G E O T E C H N I C A L     P R O P E R T I E S  Void  Ratio Degree of  Saturation Percent  Compaction  (%) Gs Dispersion  Ratio pH Electrical  Conductivity  (micro siemens) Fluid  Temp. (oC) Salinity  (ppm) Percent  Clay (%) Percent  Silt (%) Organic  Content  (%) Soil  Activity 2.7017 47.66 47.84 0.492 G E O T E C H N I C A L     P R O P E R T I E S 

133 5.3. TAMU-Erosion Manual One of the most important features of TAMU-Erosion is its ability to be filtered with regard to any column-entry. In other words, TAMU-Erosion is a relational spreadsheet which allows the user to perform multi-conditional inquiries. Table 28 shows a list of all 49 entries for one test record in TAMU-Erosion. In the following, the description of the embedded sheets in TAMU- Erosion is provided. Also, the manual for sample inquiry operation in the Windows version of the Microsoft Excel (2016) is presented. Description of Embedded Sheets in TAMU-Erosion The first sheet in TAMU-Erosion is called “About”. This sheet provides all the information about the spreadsheet including: what it is called, when it is developed, who the authors are, what organization has performed the research, and for whom organization the spreadsheet is developed. This sheet also includes the responses to the three basic questions: 1) what is TAMU-Erosion?, 2) what does TAMU-Erosion incorporate?, and 3) what does TAMU-Erosion do?. Figure 87 shows the picture of the first sheet named as “About” in TAMU-Erosion. The second sheet, named as “Inquiry Operation Manual” provides the instruction on how to filter and search within TAMU-Erosion. The instructions presented within this sheet are according to the Microsoft Excel (2016) for Windows. The macOS version of the Microsoft Excel might be slightly different in appearance, however, it is similar to the Windows version in terms of the procedure. The instructions provided in the “Inquiry Operation Manual” are also presented in following Section 5.3.2. The third sheet embodies the entire TAMU-Erosion spreadsheet, which is explained in the previous sections 5.1 and 5.2. The fourth sheet to the end incorporate the original test data used to plot the erosion functions for each erosion test. In fact, each sheet is named in the format of a three- word title: “abbreviated or summarized project name-contact organization-erosion test type”. For instance, the embedded sheet named as “ALDOT-Auburn-EFA Data” provides the EFA test data corresponding to an Alabama Department of Transportation project, and the contact organization is the Auburn University. It should be noted that the detailed information on the title of the project and person to contact are stated in the corresponding row in TAMU-Erosion. It should be also noted that the names of some embedded sheets are in the format of a two-word title: “contact organization-erosion test type”. Figure 88 shows the image of a small part of TAMU-Erosion, focusing on the embedded sheets.

134 Figure 87. An image of the first sheet named as “About” in TAMU-Erosion

135 Figure 88.The image of a small part of TAMU-Erosion focusing on the embedded sheets Inquiry Operation Manual The operation manual in this section is presented using an example inquiry within TAMU- Erosion. The procedure explained below can be used in any other application regardless of the number of the filters that the user desires to incorporate to search into the spreadsheet. The list of the choices that the user can opt from to filter each column-entry are also described within this example inquiry. As shown in Figure 89, the bottom-left corner of each column’s header shows a small arrow which can be expanded by clicking them. After clicking on the arrow, the list of choices that the user can select from is shown. Depending on the column entry, the list can include the names of the contact people, project titles, sample names, soil type, USCS, etc. For example, Figure 89 shows the list of the contact people/organizations that have contributed to TAMU-Erosion. The user has the option to filter the TAMU-Erosion data to the data associated with only one, two, or a few of the contact people by only checking the box near the desired contact person/organization and unchecking all other choices. In this example inquiry, the entire data are filtered down to only show the erosion test data from “Jean-Louis Briaud / TAMU, USA”. As shown in Figure 89, the user also has the option to write down any name in the small search box instead of scrolling down within all the choices to find the desired person. In this example inquiry, the next goal is to filter down the Briaud data to show only the data for “clay” samples. Figure 90 shows the list of choices to select from in the “soil type” column. Similarly, all the boxes should must be unchecked except for the box near the clay choice. As shown in Figure 90, user has the options: cemented sand, clay, gatarock, gravel, limestone, sand,

136 silt, and silt-clay to select from. Also, some data do not have any entries in the “soil type” column; they are shown with a dash, -, in the choices. Figure 89. Filtering the data with regard to the contact person/organization – In this example inquiry: Steps 1 and 2 show how to filter data to show only the data from Jean-Louis Briaud Figure 90. Filtering the data with regard to the soil type

137 In this example inquiry, the next goal is to further filter the clay data into only low plastic clays (CL) soils. Figure 91 shows the list of USCS that the user can select from. Similar top previous columns, the entries might be missing for some columns; they are shown with a dash, -. The user has the option to select from either “USCS classification” or “AASHTO classification” or even both columns. It is very important to mention that Figure 91 shows all possible choices for the USCS entry, while if the user selects only “clay”, as in the example inquiry, the USCS choices are limited to only the clay symbols (See Figure 92). As shown in Figure 92, after filtering the data into only clay soils, the USCS options are also narrowed down to a list of CH, CH with sand, CL, CL / CH, CL with sand, CL with sand / SC, and OH. It should be noted that at each step, the user can clear the filter by selecting the “Data” from the Tabs toolbar in Microsoft Excel, and then clicking on the “clear” Command on the Command Toolbar. (i.e. Select: Data → Clear). Figure 93 shows this process. Figure 91. Filtering the data with regard to the USCS

138 Figure 92. Filtering the data with regard to the USCS – In this example inquiry: Steps 1 and 2 show how to filter data to show only the low plastic clay (CL) soils out of all clay data Figure 93. Clearing the filters The next step in this example inquiry is to filter the selected data further into only the EFA test data. Figure 94 shows the process of checking the box near the EFA, and unchecking all other choices. As shown in Figure 94, the choices adjust themselves and update, as the prior filters are applied to the search. In this example, the choices are narrowed down to the list of BET, EFA, ESTD, HET, JET, widening test, PET, and SET.

139 Figure 94. Filtering the data with regard to the erosion test type - In this example inquiry: Steps 1 and 2 show how to filter data to show only the EFA data The next step in this example inquiry is to filter the data further into the data that have liquid limit (LL) between 5% and 30%. Figure 95 shows how the selected data can be filtered with regard to the LL. Please note that more filters on each column entry can be applied and added to the search criteria. In this example inquiry, only the filter process with regard to LL is shown. The same procedure can be applied to all other column entries. As shown in Figure 95, Microsoft Excel itself has some pre-defined boundaries such as “Greater Than …” or “Between”, etc. which can be selected. However, the custom filter allows the user to choose any arbitrary boundary for filtering the data. After selecting “Custom Filter …” as shown in Figure 95, the custom AutoFilter window pops up (Figure 96). This window allows the user to select within a wide range of choices to define a custom boundary to filter the data. As described earlier, the example inquiry in this section narrows the data to those that have a liquid limit between 5% and 30%. Figure 96 shows how this range is define in the custom AutoFilter window in the Microsoft Excel (2016).

140 Figure 95. Filtering data with regard to the liquid limit Figure 96. Custom AutoFilter window in the Microsoft Excel - In this example inquiry: The data is filtered to show only the liquid limit between 5% and 30%

Next: Chapter 6. Comparison of Selected Soil Erosion Tests by Numerical Simulations »
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TRB’s National Cooperative Highway Research Program (NCHRP) has released the pre-publication version of NCHRP Research Report 915: Relationship Between Erodibility and Properties of Soils, which provides reliable and simple equations quantifying the erodibility of soils based on soil properties.

The report a detailed analysis of the issue. In addition, the project that developed the report also produced a searchable spreadsheet that uses statistical techniques to relate geotechnical properties to soil erodibility. The spreadsheet, NCHRP Erosion, includes a searchable database that includes compiled erosion data from the literature review and a plethora of erosion tests. It contains equations which may be used to estimate the erosion resistance of soil and determine whether erosion tests are needed.

The following appendices to NCHRP Report 915 were published online in a single Appendices Report.

Appendix 1 – Erosion Test Results Spreadsheets

Appendix 2 – Geotechnical Properties Spreadsheets

Appendix 3 – First and Second Order Statically Analysis Results

Appendix 4 – Deterministic Frequentists’ Regression Analysis

Appendix 5 – Probabilistic Calibration Results

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