Pfeffer Park is Falling Down: How Erosion Patterns and its effects modify the cliff

This topic submitted by Austin Bunch, Brittany Converse, Sarah Sobel, Shannon Wilhelm at 1:49 PM on 12/5/02. Additions were last made on Wednesday, May 7, 2014. Section: Negron-Ortiz

Natural Systems 1 Fall, 2002 -Western Program-Miami University

Sarah Sobel

Brittany Converse

Austin Bunch

Shannon Wilhelm

"Pfeffer Park is Falling Down: How Erosion Patterns and its Effects Modify the Cliff"

I. Introduction

For our group project, we decided to test the erosion patterns on the cliff above the bluff at Pfeffer Park. On our nature hike earlier in the semester, the teaching assistants mentioned that over the years, the cliff had slowly eroded away, thus leaving tree roots visible from the cliff's edge. We were intrigued by the erosive history of the cliff. After the hike, we sat down to brainstorm ideas for our student-generated lab. After much deliberation, we came to the conclusion that further research would predict the future conditions of the cliff at Pfeffer Park. We believe that our study will be useful in aiding the conservation of the park based on drastic erosional changes within recent years. Our goal for our project is to collect data weekly that illustrates the impact of rain on the landscape of the cliff. Our hypothesis is that over the course of our experiment, our data will reflect patterns of deterioration due to the natural forces of rainfall and the resultant soil moisture on the cliff.

The cliff at Pfeffer Park is an example of the progressing stages of erosion. These stages include first, sheet erosion, the uniform removal of soil from the surface. Second is rill erosion which is considered the intermediate stage between sheet and gully erosion. In the rill erosion stage, channels are created by sediment runoff. Third is gully erosion, which produces deeply incised channels, as seen at the cliff in Pfeffer Park. We will be examining the type of soil to determine how it correlates with the amount of erosion. In examining the soil contents we will be comparing soil surveys taken from each of the ten stakes in the10 by 5 plotted areas near the edge of the cliff (Toy et. al, 2002). The other erosion factor we will be examining is precipitation runoff as the cliff has been subject to rill, sheet and gully erosion. Our main objective is to observe just how fast it erodes, and how the precipitation and soil type contribute to the rate of erosion.

For rainfall as an rosive agent, our goal is to understand the cause and effect of how the forces of precipitation must overcome the soil's particular bonding forces and how these bonding forces cause particle detachment, thus leading to erosion.

II. Relevance

In proceeding to find more information about erosion patterns due to rainfall and soil types we discovered many pieces of literature where others had delved into this topic. Researchers have developed the theory that the "landscape develops by the upslope encroachment, upon each slope element, of the one below it of lower gradient and greater degree of reduction" (Gerrad 1981). This idea might help us in understanding the reason why the bluff has so many layers, and why these layers have been formed. Other researchers have found that erosion rates vary with groundwater, climate relief, rock and soil type, and location of the stream system. Lanbein et. al. (1949), shows that the mean annual run-off decreases with increasing temperatures. Calculations have revealed the fact that erosion decreases exponentially with increased vegetation cover under the same conditions. This information will help our group to further understand why some areas are more prone to erosion, the areas with less vegetation (Daniels, 1992). Our research is going to yield very interesting results, as we test one researchers findings that, "rainfall impact is negligible when the flow depth is larger than three times the raindrop diameter" (Julien, 1995).

We hope to discover a general pattern of degradation in the cliff area, and apply that further to the park as a whole. By finding these new patterns, we can hopefully propose mechanisms and practices which can slow the destructive forces of erosion. Furthermore, we may find that in the course of our experiment, the soil of the site is either especially susceptible or resistant to erosive agents such as rainfall, and this knowledge can be used not only in methods to slow erosion in the park, but in broader environments, such as the Miami Valley.

III. Materials and Methods

A. Materials

10 Wooden Stakes

Plastic Bags

Measuring Tape




Soil Moisture Meter

Munsell's Soil Color Chart

B. Methods

We began our project by assigning a 10m x 5m area that served as our experimental context. We then placed our stakes at one meter intervals with the last stake being placed 2 meters from the edge of the cliff. After the stakes were placed, we marked the ground level on each stake, so as to indicate where the ground level was at the beginning of the project, and then compared it to successive levels altered by runoff.

Each week, we visited the site twice, each time recording not only the distance of the final stake from the edge of the cliff, but also the ground level at each stake. These tests ensured an accurate measurement of any erosion that occurred. We recorded the cumulative rainfall totals each time since the last data collection. To supplement these totals, we collected soil moisture data to understand the precise impact of precipitation on the site. We combined the data we collect from the soil moisture meter with the composition of the soil based on the Butler County Soil Survey.

Additionally, we had students take soil samples at each stake and placed them in plastic bags at the beginning of the project, and then we compared that to soil samples taken at its conclusion. We conducted soil profiles initially as well as at the project's conclusion, and mapped and measured soil horizons, such as A and B layers. Each distinct was collected and identified using Munsell's Soil Color Chart. This data will provide information how susceptible the soil is to erosion as well as if there have been any changes in the soil due to erosive agents. We will compare the soil to Munsell's Soil Color Chart in order to figure out the soil's composition.

We will also be taking pictures of the site once every week, to provide others with a visual representation of the changes over time. As much as we can control the actions and attitudes of the students, we are hoping that by demonstrating our design through an outline, pictures, and any needed individual explanation, the students will be able to perform the tasks that we require of them.

Our project is as statistically sound as it can be, because without more time and resources, we cannot accurately study all of the forces which have an impact on the cliff area. We will be taking only a few statistical data tests because of the limited amount of time. We will tabulate weekly averages for the amount of precipitation. Also, we will compare the weekly means of precipitation and the soil moisture. Based on the data collected from the means, we plan to calculate the total mean precipitation and soil moisture over the span of the five week data collection. We will only be able to study rainfall, because it is the only force that will be likely to provide us with statistically significant data and meaningful results within the time frame. However, we do plan to graphically analyze our data, and extrapolate information that will indicate to us how possible future patterns of erosion. Our data will be unbiased within the framework of our project because we have established a superficial experimental context which will become a rather standard setting for empirical data collection.

Project Timeline

We will do our data collections Tuesdays and Fridays at 4:30 in the afternoon.

Week 1:

October 22nd - Student participation- soil sampling & digging

Week 3:

November 5th - collect data at site

November 8th - collect data at site

Week 4:

November 12th - collect data at site

November 15th - collect data at site

Week 5:

November 23rd - collect data at site

Analyze data, type up results, write discussion, and finish lab write

up in general.

** Thanksgiving break**

Pictures of us taking measurements:

IV. Results

Our results can be found within our data sheet below. In addition to our numeric data, we also took observations of the cliff testing area each collection. On November 5th, we observed that the soil was very muddy and moist with puddles due to heavy rainfall that day. However, the rainfall is not included in our data because it was our initial collection or reference point. On November 8th, the soil was very dry, cakey, and firm. For our observation on November 12th, the ground was damp but not muddy, well-packed, soft, and smooth. On November 15th, we observed that the soil was very loose, wet, and muddy. For our final collection on November 23rd, we observed that the soil was damp but firm.

Below you will find our data for each collection.

Data Sheet/Results, Data Graphs, and Statistical Tests can be found here:

V. Discussion

Based on our background research discussed in the introduction and relevance sections, we witnessed sheet erosion in action. Sheet erosion is the uniform removal of soil from the surface. Over the course of our experiment, rain and precipitation caused the soil to erode away and thus caused the soil to wash away. The decline of ground level demonstrates the effects of sheet erosion because the soil has been removed from the surface.

We calculated t-tests for both the ground level and the distance from edge. In figure 1, the average ground level, the p-value was 0.6675. Because it was greater than 0.05, the value is significant and we fail to reject the null hypothesis. Figure 3 supports these findings as all but one p-value was greater than 0.05. In figure 2, the average distance from edge, the p-value was <.0001. Because the p-value was less than 0.05, the value is insignificant and we reject the null hypothesis. Figure 4 supports these findings as all p-values are less than 0.05. This proves that upon further testing, our ground level results would be similar 95% of the time. Yet, because the distance from edge values were insignificant, this information is irrelevant.

In figure 5, the average weekly ground level, the mean ground level for each collection decreased. This proves that our hypothesis was correct in that

the ground level decreased and erosion occurred. In figure 6, the average distance from edge, the mean distance from edge for each collection decreased. This proves that our hypothesis was correct in that the distance from edge decreased and erosion occurred.

Following identification of the soil samples using Munsell's Soil Color Chart, we observed a distinct change in soil color due to precipitation. It is therefore possible that the mineral composition was changed by said precipitation thus causing the modification of the soil. For example, at stake 2, our initial soil sample was brown, but over the course of our experimental period, it changed to olive-brown. Additionally, at Stake 10 our initial sample at A layer was brown, but upon conclusion of our experiment, it had shifted to yellowish-brown. This shows a 15-spectral unit shift on the Munsell's Soil Color Chart.

Research in this field is limited due to the lack of geographic significance of Pfeffer Park, and thus our research is pioneering in spirit. The research is confined to a few studies done by Miami's Geology Department, with little attention given to sedimentology or soil geomorphology. Further research questions include investigation into the effects of other natural forces, such as wind and other forms of precipitation (.i.e. snow), and the cohesive and formative function of root systems.

Our results could have been affected greatly by several factors. Primarily, our stakes were all removed prior to initial collection, thus truncating our experimental period. Additionally, on November 15th, we discovered three stakes (1,3,4) were removed, and any further ground level data collection could not be completed for those stakes. Stake 9 was cracked, and titled, corrupting our ground level measurements further. The height at which the measuring tape was placed also altered our distance measurements.


Agassi, M., & Bradford, J. (1999, January 18). Methodologies for interrill soil erosion studies. Soil & Tillage Research, 277-287.

Chulsang, Y., Valdes, J. & North, G. (1998, August 15). Evaluation of the impact of rainfall on soil moisture variability. Advances in Water Resources, 375-384.

Daniels, R.B., and Hammer, R.D. (1992) Soil and Geomorphology (John Wiley and Sons, Inc.)

Fox, D., & Bryan, R. (2000, January). The relationship of soil loss by interrill erosion to slope gradient. Catena, 211-222.

Gerrard, A.J. (1981) Soil and Landforms (George Allen and Unwin)

Julien, P.Y. (1995) Erosion and Sedimentation (Cambridge University Press)

Lee, E., Hall J., & Meadowcroft I. (2001, October). Coastal cliff recession: the use of probabilistic prediction methods. Geomorphology, 253-269.

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Sidorchuk, A. (1999, October). Dynamic and static models of gully erosion. Catena, 401-414.

Toy, T.J., Foster, G.R., Renard, K.G. (2002) Soil Erosion: Processes, Prediction, Measurement, and Control (John Wiley and Sons, Inc.)

United States. Department of Agriculture. Soil Conservation Service. Butler County Soil Survey Lerch, Norbert K. Issued 1980

Weather Underground. World Wide Website:

Zachar, P. (1982) Soil Erosion: Developments in Soil Science 10 (VEDA: Publishing House of the Slovak Academy of Science)

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