Next Article in Journal
Landslides in the Himalayas: The Role of Conditioning Factors and Their Resolution in Susceptibility Mapping
Next Article in Special Issue
Review and Inventory of Pedological and Stratigraphical Knowledge for Investigating Shallow Landslides: A Case Study of the Cervinara Area (Central Campanian Apennines, Southern Italy)
Previous Article in Journal
Quantitative Biofacies Analysis of Upper Oligocene Reef-Coral Neritic Carbonates (Southern Pakistan)
Previous Article in Special Issue
Tools for Predicting Long Runout Landslides
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Geosciences
Volume 15
Issue 4
10.3390/geosciences15040130
geosciences-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Landslide at the River’s Edge: Alum Bluff, Apalachicola River, Florida

by
Joann Mossa
1,* and
Yin-Hsuen Chen
2
1
Spatial and Temporal Analysis of Rivers (STAR) Laboratory, Department of Geography, University of Florida, Gainesville, FL 32611, USA
2
Center for Geospatial Science, Education, and Analytics, Old Dominion University, Norfolk, VA 23529, USA
*
Author to whom correspondence should be addressed.
Geosciences 2025, 15(4), 130; https://doi.org/10.3390/geosciences15040130
Submission received: 31 January 2025 / Revised: 14 March 2025 / Accepted: 21 March 2025 / Published: 1 April 2025
(This article belongs to the Special Issue Landslides Runout: Recent Perspectives and Advances)
Browse Figures
Versions Notes

Abstract

:
When rivers impinge on the steep bluffs of valley walls, dynamic changes stem from a combination of fluvial and mass wasting processes. This study identifies the geomorphic changes, drivers, and timing of a landslide adjacent to the Apalachicola River at Alum Bluff, the tallest natural geological exposure in Florida at ~40 m, comprising horizontal sediments of mixed lithology. We used hydrographic surveys from 1960 and 2010, two sets of LiDAR from 2007 and 2018, historical aerial, drone, and ground photography, and satellite imagery to interpret changes at this bluff and river bottom. Evidence of slope failure includes a recessed upper section with concave scarps and debris fans in the lower section with subaqueous features including two occlusions and a small island exposed from the channel bottom at lower water levels. Aerial photos and satellite images indicate that the failure occurred in at least two phases in early 2013 and 2015. The loss in volume in the 11-year interval, dominantly from the upper portion of the bluff, was ~72,750 m3 and was offset by gains of ~14,760 m3 at the lower portion of the bluff, suggesting that nearly 80% of the material traveled into the river, causing changes in riverbed morphology from the runout. Despite being along a cutbank and next to the scour pool of a large meandering river, this failure was not driven by floods and the associated lateral erosion, but instead by rainfall in noncohesive sediments at the upper portion of the bluff. This medium-magnitude landslide is now the second documented landslide in Florida.

1. Introduction

Large rivers with high bluffs of sedimentary material are highly prone to failure and subsequent river erosion. Whether driven by slope processes or lateral erosion, these bluffs can be important sources of sediment [1,2] and in some cases dominate watershed sediment budgets [1] and influence sediment connectivity [3]. Prominent examples of landslides and erosion along rivers with moderately high bluffs (>10 m) include the Danube in Hungary [4], the Mississippi River at Port Hudson, Louisiana [2,5], the Greater Blue Earth River, Minnesota [1], the Colville River, North Slope Alaska [6], the Oso landslide across the Stillguamish River, Washington [7], and the Fox Creek tributary to Peace River basin, NW Alberta, Canada [8].
Historical, field, and bathymetric data can be useful in determining the subaqueous condition and drivers of long-term change in bluffs along rivers; however, bathymetric data have rarely been used for this purpose. In three tributaries of the Greater Blue Earth River, Minnesota, daily time-lapse photographs, trail cameras, and repeated topographic surveys using Structure-from-Motion Photogrammetry revealed that floods drove most of the change at bluff sites ranging from 3 to 70 m high, although geomorphic change occurred throughout the year [1]. At a site along Fox Creek, with massive (47 Mm3 of displaced materials) sliding blocks of clayey glaciolacustrine sediments forming a 19 m high landslide dam in May 2007. Aerial photo interpretation, meteorological data, and detailed field mapping aided to determine the contributing factors [8]. Working together, record precipitation and snow melt raised pore water pressures, creek bed incision led to a loss of toe support, and a weak layer within the glaciolacustrine sediments created this landslide and dam in the Peace River basin in Alberta, Canada [8]. Only one prior study on the Mississippi River at Port Hudson, where the bluff height ranged from 14 to 27 m, included some bathymetric data in their analysis. Failure was driven by subaqueous undercutting of the river, associated with the scour pool in its thalweg, and fluctuating river stages that increased weight and pore water pressure, contributing to slope failure following a lowering of river stage [2].
Unlike other sites which have been the subject of intensive repeated study, such as the Castle Hill site on the Danube in Hungary [4] or the Port Hudson Bluff next to the Mississippi River in Louisiana [2,5], minimal prior work has been conducted on landslides in Florida. The only landslide described in the literature occurred ~75 years ago in April of 1948 near Greensboro, located roughly 25 km from the study area and 10 km from the Apalachicola River mainstem [9]. Excess rainfall triggered this failure, with 406 mm of precipitation in the prior 30 days, resulting in 112,000 m3 of sediment moving downslope and a 13.7 m high horseshoe-shaped scar. The scar is now forested and lies next to a water body labeled Pitt’s Landslide Pond (Location: 30.6167° N, 84.7939° W, Figure 1A). This landslide is also denoted as a “landslide of special interest” on an overview map of landslides in the conterminous United States [10]. The Global Landslide Catalog (URL https://svs.gsfc.nasa.gov/4710, accessed on 30 January 2025), compiled by NASA’s Scientific Visualization Studio, shows the location of 11,033 reported landslides triggered by rainfall for the period 2007–2019. The accompanying map and spreadsheet identify a landslide classified as occurring in “Williston” “Florida” on 21 July 2011; however, the other columns suggest that the landslide occurred at Grotto Spring near Eureka Springs, Arkansas. It is important to investigate unreported landslides not in this database to better understand the reasons and locations of omissions to improve further compilations.
Higher than 40 m above the Apalachicola River, Alum Bluff (Location: 30.4691° N, 84.9860° W) in the Florida panhandle, located approximately 3 km north of Bristol, is the tallest natural geological exposure in Florida as well as an important Miocene to Pliocene fossil site (Figure 1). Alum Bluff is a dynamic area at the river’s edge, subject to river erosion at the base and the wetting of permeable sediments and slope runoff at the top. Early photographs of this bluff in 1909 show both highly vegetated and bare areas, suggesting a history of slope activity. We focus on a failure that initiated sometime between February and April in 2013 involving bluff retreat and basal debris that affected the morphology of the bluff face and channel boundary. Using Light Detection and Ranging (LiDAR) data acquired in 2007 and 2018, combined with hydrographic surveys in 1960 and 2010, as well as aerial photographs and a satellite image, we examine spatial and temporal variations along this bluff, landslide, and the associated deposits in the river. This study provides some insights into bluff landslides intermittently contributing sediment to coastal plain rivers, as well as the role of the river in modifying and reworking mass wasting deposits. The following questions are relevant to this study: (1) How active has Alum Bluff been historically in terms of landslides? (2) Is the bluff change due primarily to slope processes or fluvial undercutting? (3) Where is sediment lost and accumulated along the profile? (4) How have landslides affected the channel morphology? (5) Have floods since the landslide occurred reworked and mobilized landslide-derived deposits at the base?

2. Study Area

Alum Bluff is located on the upper Apalachicola River in Florida at ~River Mile 84.2 (Figure 1). It is situated more than 29 km downstream of the Jim Woodruff dam at Chattahoochee. The Apalachicola River drainage is part of the ACF or Apalachicola–Chattahoochee–Flint River, and the area of basin is ~51,000 km2 with headwaters in Georgia and Alabama (Figure 1B). This bluff is one of several exposures along the upper Apalachicola River, all of which are on the east or left bank of the river. Alum Bluff and other exposures formed because of the river impinging on the valley wall, here on a cutbank of a meander bend. The top of the bluff is at about 60 m in elevation, and the base is around 15 m depending on water levels, resulting in ~45 m of vertical exposure, making Alum Bluff the tallest natural exposure in Florida [11]. The enhanced LiDAR/Sonar image from 2018 and 2010 shows Alum Bluff on the east bank of the Apalachicola River with the river impinging on the bluff (Figure 1C).
According to [11], the section exposed at Alum Bluff is probably one of the most extensively studied, widely known, and described outcrops in the southeastern United States [12]. Five lithologic units are exposed at Alum Bluff, including the Miocene Chipola Formation and Alum Bluff Group, undifferentiated, Pliocene Jackson Bluff Formation, Plio–Pleistocene Citronelle Formation, and a section of undifferentiated surficial clastic sediments (Figure 2). These coastal plain unconsolidated sediments are nearly flat, dipping less than one degree toward the Gulf of Mexico [13]; thus, the geological structure does not promote or influence the occurrence and nature of failures; however, lithological discontinuity is potentially an aspect of the failure. Fluctuating water levels expose as much as 3 m of the Chipola Formation at low river stages and cover parts of the Preston Sand during major flooding stages. This lithology, with the harder, more cohesive, and more resistant sediment rocks at the base and noncohesive sediments higher in the profile, contrasts with most riverbanks which tend to fine upwards [14,15].
The upland adjacent to the bluff is part of the Apalachicola Bluffs and Ravines Preserve and is managed by the Nature Conservancy. The thick sequence of undifferentiated sands and Citronelle Formation sand-dominated sediments overlying the clayey Jackson Bluff Formation, an effective aquiclude, is the ideal geologic situation for the formation of steephead ravines whose bed is at this contact [11]. The dimensions of these small, incised streams that flow westward toward Alum Bluff are typically 20 to 40 m deep and about 100 m wide [16,17]. Researchers attribute steephead occurrence to sapping, a process associated with groundwater seepage through porous, poorly consolidated sediment; groundwater detaches sediment grains and transports them further downstream [17,18,19]. This process causes the sediment above the seepage face to collapse, causing headward erosion of the valley head and creating a ravine, at the bottom of which flows a stream fed by the surrounding unconfined surficial aquifer [16,20]. The seepage face collapse corresponds to the spatial position of the April 1948 landslide reported by [9] at the valley head of a steephead. This same sequence of relatively thick, unconsolidated sandy sediment overlying resistant clays also represents an important contact for the recent landslides (Figure 2).
Geosciences 15 00130 g002
Figure 2. Geologic cross section of Alum Bluff (modified from [12,21]) with annotated water levels calculated from linear interpolation of upstream and downstream gage stations. More of the base of the bluff is now exposed because of ongoing degradation associated with an upstream dam, as well as dredging and rock removal as part of a navigation project.
Figure 2. Geologic cross section of Alum Bluff (modified from [12,21]) with annotated water levels calculated from linear interpolation of upstream and downstream gage stations. More of the base of the bluff is now exposed because of ongoing degradation associated with an upstream dam, as well as dredging and rock removal as part of a navigation project.
Geosciences 15 00130 g002

3. Methods

We compiled various primary and secondary data including aerial and drone photography, satellite image, LiDAR, and hydrographic surveys (Table 1). LiDAR has been used as a tool in landslide investigations [22]. Four types of analyses were conducted to assess changes before and after the Alum Bluff landslide: aerial photo and satellite image interpretation, elevation change computation, profile change analysis, and bluff surface texture extraction (Figure 3). Aerial photos and satellite images were first retrieved from various sources (Table 1). Since the exact date of the landslide event is unknown, we initially examined high-resolution aerial photos and then expanded our search to lower-resolution satellite images, allowing us to further narrow down the event’s timeframe. Using the series of aerial photos, we also investigated other landslide-related features, such as scars from previous mass movements and vegetation recovery. Additionally, we retrieved rainfall data from the U.S. Geological Survey (USGS) station in Chattahoochee (02358000, ~29 km from the study site) to help identify a possible triggering event for the landslide. Most of the data processing and analyses were conducted using ESRI® ArcMap 10.8.X and ArcGIS Pro 3.X.
To analyze elevation changes and landslide features, 2007 and 2018 LiDAR and 2010 multi-beam sonar survey data were obtained in LAS and .xyz formats. The LiDAR point cloud was converted to a point layer using the LAS To Multipoint tool, and the multi-beam survey points were imported as a point layer based on the X and Y coordinates in the .xyz file. For the 1960 river profile survey, we geo-referenced the scanned hydrographic survey sheets utilizing the coordinate grid lines and digitized the survey points. These survey points were manually digitized into a point layer at a fixed mapping scale of 1:2000. Some cross sections from the 1960 hydrographic survey extend up the bluff, enabling comparison of long-term bluff erosion with the more recent landslide.
Using LiDAR data from 2007 and 2018, we first created triangulated irregular network (TIN)-based elevation models by creating a terrain model. Using the TIN to Raster tool, we then converted the TIN model into 5-by-5 m grid-based digitation elevation models (DEMs). Since LiDAR data do not capture underwater areas, we digitized the edge of the LiDAR point cloud as the waterline, created polygons to represent the channel area, which we used to mask out these regions from the DEMs. The channel area was assigned a value of zero, as our analyses aimed to examine the elevation differences at Alum Bluff without accounting for water surface elevation. Following the same approach as with the LiDAR data, we created a TIN-based model from the 2010 multi-beam sonar survey and converted it into a DEM for elevation extraction.
To investigate the change in elevation of Alum Bluff, we calculated the DEM of difference (DoD) by subtracting the 2018 DEM from 2007 DEM. This process was conducted using the Raster Calculator tool, which created a DoD surface with values indicating positive or negative changes between two DEMs. Additionally, we quantified volume change within the landslide area by digitizing it as a polygon and using it to define the computation extent. We utilized the Cut Fill tool to compute volume changes, which generated a table indicating the net gain and loss between two surfaces.
Based on two hydrographic and two LiDAR surveys, we chose eight cross sections to compare the profile changes of Alum Bluff and channel bottom. The location of profiles matches the 1960 cross sections, with cross sections B and C corresponding to the recent landslide (Figure 4). Following the orientation and location of the 1960 river survey, we extended the cross sections as straight lines with 350 m lengths across the bluff, split each cross section into 1 m intervals, and converted each 1 m segment into points. Using these points, we extracted the elevation values from the DEMs of 2007 LiDAR, 2010 multi-beam survey, and 2018 LiDAR, and plotted the values to examine their changes.
The textures on the bluff surface provide details of landform structure [24]. To identify features and interpret development of the landslide at Alum Bluff, we applied the Curvature function in ArcMap to compute the profile curvature for the 2007 and 2018 DEMs. Profile curvature specifically shows the curvature parallel to the slope, representing the direction of maximum slope. Negative values indicate convex shapes, while positive values indicate concave shapes [25]. Concave landforms are typically associated with headwalls, channels, or gullies, while convex features correspond to debris fans or talus deposits—both indicative of progressive landscape mass wasting [26]. With the profile curvature maps, we digitized the continuous structure line and investigated their changes.

4. Results

The earliest photographs of the Alum Bluff taken in 1909 [27] show that most of the bluff is densely vegetated, but part of it is bare, reflecting that slope failures have occurred here historically. A sequence of images between 1979 and 2021 (Figure 5A–H) depicts bare and vegetated areas of Alum Bluff, showing intermittent mass wasting activities along the slope during the 1970s to 1990s as seen in the 1979 and 1999 infrared images and recovery up through February 2013. The photograph from 9 February 2013 shows a largely intact slope, and based on a review of low-resolution RapidEye images in April 2013, we bracket the initial failure in between February and April 2013. The higher-resolution October 2013 NAIP image shows a bare slope with one occlusion into the river. By October 2015, the month of the next set of aerials, more of the slope failed, adding to the size of the bare area and changing the shape of the upstream occlusion and adding a second downstream occlusion (Figure 5F). While the accurate date of landslide event remains unknown, the daily and cumulative precipitation data from October 2012 to December 2015 reveal a possible explanation for the Alum Bluff landslide. Several intensive rainfall events occurred during the spring months of 2013, 2014, and 2015 (Figure 5I), which might have triggered more mass failure. Ground and drone photos give more insight. A ground photo in January 2015 shows the appearance of the slope after the initial failure and before reactivation (Figure 6A), contrasted with more recent images from 2018 (Figure 6B,C), which provide an aerial perspective showing fans of varied sizes with their apices in rills or notches in the sandy clay. Most of the material is from the top and north end of the slope and traveled southwestward over the clay layer until it broke through a section. The clay bar or island in the lower left foreground at a distance from the fan shows that much (~80%, depending on water level) of the material traveled into the river (Figure 6C). The field photo from 2019 shows some toppled trees, indicating the continuous shifting of debris, and a clay bar or island surrounded by water and separated from the bluff and landslide fans (Figure 6D). Thus, combining the aerial and field photos, the second phase of the landslide occurred between January and October 2015. This two-stage event, or possibly more, is bracketed by the two sets of LiDAR data collected in 2007 and 2018. Digital elevation models (DEMs) demonstrated a mass movement from the top of the bluff surface and deposition on the downhill side (Figure 1C).
The Apalachicola River was the site of a U.S. Army Corps Navigation Project, which included the Jim Woodruff Dam ~30 km upstream that was constructed in 1954. To support navigation, the upper river also had blasting and removal of rock shoals and ledges, as well as the emplacement of several dikes [28,29]. Dredging, disposal of dredge material, and snag removal occurred throughout the river [28,30]. Anthropogenic changes in the upper Apalachicola River and the resulting pronounced degradation were primarily associated with the dam [28,31,32] and secondarily dikes [33]. Dam-associated channel incision and enlargement have affected stage levels, which in turn affect the length and frequency of inundation such that more of the base of the bluff has been exposed over time (Figure 2). Near the bluff, the position of the river has migrated eastward as it erodes into the bluff.
The DEM from 2007 shows two steephead ravines on the upper scarp, with most of the remaining slope having parallel contours (Figure 7A). After the landslide occurred, a new concave area at the bluff top was formed, and the elevation changed at the former waterline at the toe of the bluff comparing the 2007 and 2018 DEM (Figure 7A,B). The drone photo taken in August 2018 shows the area of the landslide (Figure 7C), with the area surrounded by a red dashed line representing the extent for volume change calculations. Computations within this area from the DoD show a loss of 72,749 m3, mostly at the top of the scarp, and a gain of 14,756 m3 at the base; much of the remainder of the failed material is likely subaqueous (Figure 7D). Based on the scarp morphology, the zone from which most of the material was removed is largely to the north of the deposit. The material traveled southwestward until it broke through and over the resistant, cohesive Pliocene sandy clay to build debris fans at the base.
Beginning from the north at Profile A (Figure 8A), the profile was stable between 2007 and 2018, although it shows some long-term retreat or prior bluff erosion of ~20 m since 1960 (Figure 4, A). Profile B (Figure 8B), which goes through part of the landslide, shows considerable change between 2007 and 2018, much more than the 47 years between 1960 and 2007. A small channel routing landslide material is located at an elevation of ~20 m. Profile C (Figure 8C) cuts through a steephead, the mid-portion of which has collapsed; retreat associated with the 11-year period bracketing the landslide approximates the material lost in the prior 47 years. Profile D (Figure 8D) also cuts through the steephead, although this portion is stable and not part of the landslide, even though the bluff here has retreated historically because of previous landslides, river erosion, or a combination. The inflection zone at an elevation of ~33 m corresponds to the impermeable sandy clay layer (Figure 2) and illustrates how this material can create a ledge or bench on the bluff cross section. Profiles E, F, G, and H were also relatively stable between 2007 and 2018, although the 1960 profile shows that 10 to 20 m of lateral erosion occurred between 1960 and 2007 (Figure 8E–H). Note that profiles E and F correspond to the bare areas in the 1999 aerial photography (Figure 5B). Comparing the 1960 survey with the LiDAR cross sections, all the profiles show some erosion of the bluff bottom, and profiles A, B, C, and D show some change in the riverbed between 1960 and 2010.
The changing profile curvature between 2007 and 2018 DEMs shows new and changing concave areas. Away from the landslide, the concave areas are mostly stable, whereas just north of and near the landslide, the concave areas have shifted. The maximum distance of retraction was up to ~28 m on the top (Figure 9). Other concave lines close to bottom of bluff are related to the sandy clay, which can be clearly observed on the 2007 DEM. In the 2018 DEM, more complex concave lines indicate the contact between the sands and sandy clays and landslide scars. Based on the concave line, the upper surface of the sandy clay layer retracted inland up to ~25 m.

5. Discussion

Alum Bluff is not just a geological site, but rather a dynamic area showing signs of change from intermittent landslides, runouts, lateral erosion, and vegetative recovery (Figure 5). The unconsolidated surficial sand and Citronelle Formation that overlie the impermeable clay and clayey sand of the Jackson Bluff Formation create a situation that enables heavy precipitation to trigger bluff activity (Figure 2 and Figure 5). Concave break lines either indicated the bluff crest or change in lithology where the resistant clayey layer begins (Figure 9), shown in prior work to automatically identify landslide deposits [26]. Pore water pressures generated within a transient perched water table formed on top of the clay from the excess rainwater. Precipitation increases the weight of material on the upper portion of landslide and causes the sediment to slide across and over the clay layer through notches which funnel sediment to the lower portion of the bluff, forming debris fans (Figure 6C and Figure 8B,C). Sediment occlusions (Figure 5D–G and Figure 6B–D) from Alum Bluff alter the planform morphology and remain for many years (Figure 5) until removed by river erosion and surficial erosion from rainsplash, sheetflow, rills, and gullies. Failure at the bluff also alters subaqueous topography, leaving a small clay island approximately 20 m in front of the slope. River currents remove and rework sediment at the base of the bluff, preferentially removing sandy portions with less effect on the most resistant clay island (Figure 6C).
Geomorphologists combine evidence from multiple sources to make interpretations of physical landscapes [34]. Curvature deviations (Figure 9) and other land surface parameters such as slope, topographic position, roughness, and aspect are helpful in landform delineation and interpreting geomorphic processes [35,36]. Surface runoff has eroded notches in the clayey layer (Figure 6B,C), which are apices of fans supplied by the sandy materials above. The fans of coarse material are primarily derived from sediments of the Citronelle Formation, which are notable for pigmentation from iron and manganese oxides [37,38]. Regional analysis of the Citronelle deposits note that pale-yellow and reddish-orange hues appear in sandy deposits when mud content reaches 0.9–2.0%, and that increasing clay and silt concentrations result in darker yellowish-brown, reddish-brown, and reddish-orange colors [38]. Because of the potential for additional inputs of sediment and reworking of current landslide deposits, the changes in surficial topography and sediments should be monitored with field surveys, repeat photography, remote sensing, ground-based sensors, and relevant laboratory work to better understand the role of mass wasting, hillslope, and rainfall-related processes that modify landscape topography and sediments.
The runout of sediments was a tool in reconstructing the multiple phases of the landslide. Although much of the runout was underwater and not computed in this study, the visible portion follows the slope, with some protruding into the channel, forming occlusions. Since most of this material is submerged, some may have been reworked and removed by fluvial processes and erosion. To compute the total runout distance, it would be necessary to perform subaqueous mapping using sonar-derived bathymetric datasets as in other studies (e.g., [39]). Prior studies found a power (relatively linear log-log) relationship between the fall height (H), the distance between the initiation and deposition zones, and the runout distance of different types of flows and slides [40]. Additionally, research has suggested that landslide volume (V) drives runout distance [41,42]. In this example, the height is <20 m and the volume of sediment loss in the initial zone is ~72,750 m3; prior studies have shown that the length of the runout for flows between 10 and 20 m averages four to five times larger than the height for flows [40], which in this case would be 40 to 100 m, which seems reasonable given the visible subaerial materials including the occlusions (Figure 5E–G and Figure 6C).
Although the river is impinging on the bluff, floods are not the primary driver of bluff retreat; however, they play a role in reworking runouts. Analysis of nearby hydrology data shows that maximum water levels are ~18 m at Alum Bluff (Figure 2). Most of the subaerial bluff, at least up to the contact with the median flow level (Figure 8), was stable during a series of major rainfall and flow variations (Figure 5 and Figure 8A,D–H). Unlike studies of bluff erosion in the Greater Blue Earth River basin [1] and the Lower Mississippi River at Port Hudson [2], where erosion primarily occurred during large flood events due to basal undercutting and rising water levels, the profile change at Alum Bluff follows a different pattern. High-precipitation events primarily trigger failures at the upper end of the bluff, while years to decades of hydraulic action and entrainment gradually remove sediment that fell from the bluff. The thalweg elevation ranges from 3 to 5 m (Figure 8), and based on the profile morphology, undercutting from the river is not an important process. The Chipola Formation at the base of the exposure is lithified and largely erosion-resistant, and below the Chipola Formation water surface is a hard, competent limestone. In addition, the peak flow levels during the years of bluff failure from 2013 to 2015 (Figure 5) were not as high as the events before and afterwards [43,44]. Our drone imagery (Figure 6B,C) shows that the major flood events exceeding 3800 m3/s that occurred in 2015 and 2016 (R.I. ~ 6 yr) [43] occurred after the second phase but had a minimal influence on moving sediment or changing the shape of occlusions or fans protruding into the water. Most of the subaerial portion of the landslide remains intact.
Based on the landslide size classification of [45], this landslide would be classified as a medium landslide with ~72,749 m3 of loss and was offset by gains of ~14,756 m3 at the subaerial toeslope as of the time and water level on 29 April 2018 LiDAR survey, while the remainder of the runout was underwater. Some of the looser material was removed by fluvial processes before the 2018 LiDAR survey. It was smaller than the ~112,000 m3 event in Greensboro [9], but was one of few that have been documented in the clastic sediments and sedimentary rocks of the panhandle. The development of the landslide occurred over at least two years, with the area affected first documented after 9 February 2013 and then expanding by 14 October 2015 (Figure 5C,F). Although the specific rainfall events triggering landslide development are unknown, rainfall exceeding 60 mm/day occurred on seven occasions between February 2013 and April 2015 (Figure 5I); thus, the initiation and enlargement most likely occurred during this interval. Rainfall events since 2015 may have reworked the slope further, although the bluff shows no new scars and has begun to revegetate (Figure 5F–H). There does not appear to be any notable anthropogenic influence, considering the site is in a state park, as is the case elsewhere [46].
Historical landslides at Alum Bluff have generally been of a smaller magnitude. At least since 1999, all of the landslides at Alum Bluff have been buffered, with no discernible physical contact between the landslide runout and river channel (e.g., [47]). The landslide that happened in early 2013 and was enlarged by 2015 created two occlusions in the river (Figure 5E–G), creating a diversion of the river channel around the convex landslide toe, displacing the channel boundary compared to the channel course upstream and downstream of the contact zone [47]. By 2015, the feeder area, runout, and occlusion had enlarged, and a second smaller slide, runout, and occlusion formed downstream, but there is insufficient information on whether they occurred at the same time (Figure 5). This occlusion is notable only at lower flows below 400 m3/s, as it was exposed in 2015 and 2017 images, was drowned by higher water levels when the 2018 LiDAR was acquired and remained visible in 2021 image (Figure 5).
Alum Bluff and the landslides on it are a source of sediment in a river corridor where a dam traps material ~30 km upstream and reduces sediment compared to historical rates. The hydrographic survey from 1960 gives unique insight into Alum Bluff, as some of the cross sections across the river go partway or completely up the bluff (Figure 4 and Figure 8). The landslide described herein appears in profiles B and C, manifested by a marked change between the 2007 and 2018 LiDAR profiles, in contrast with the remaining profiles A and D through H (Figure 4 and Figure 8). The bluff retreated at all eight profiles depicted since 1960. However, the quantity of change at profiles B and C for the 47 years pre-landslide (1960 to 2007), which includes a smaller slope failure in 1979 (Figure 5A), is less than for the 11 years between the two LiDAR surveys (2007 to 2018). For this event, most of the debris has remained at the base but will likely decrease over time with repeated floods. Given the change from the 1960 profile to the most recent, periodic small landslides coupled with river erosion have caused ~10 m of bluff change over 58 years. More studies of landslides along rivers should seek to integrate hydrographic surveys because they can help decouple mass wasting from riverine processes and provide insights into the subaqueous component of the failure and the extent and scale of current and past runouts.
Some limitations of our analyses are related to the available data, including the lack of field surveys, the timing of aerial photography and LiDAR, and the changing water levels used to compute volume change for the DoD. This site would be ideal for repeated field monitoring with a grid, as conducted elsewhere [4]. The aerial photographs from 2013 are not sufficient to pinpoint the initiation of this failure, but two photographs from that year and a low-resolution satellite image from April (Figure 5D) help to bracket the initial failure between 9 February and April 2013. Because the two sets of LiDAR data were collected at different water levels (453 m3/s in 2007 and 702 m3/s in 2018), we cannot fully document the material at the base of the landslide that is underwater. LiDAR data at lower water levels would be helpful in revealing more details of the bluff bottom and creating a continuous surface from the bluff crest to the river bottom when combined with the multi-beam sonar survey. Thus far, only the 2010 multi-beam sonar survey is available, and it does not cover the entire channel bottom, or any of the bluff, compared to the 1960 survey (Figure 8). A detailed, up-to-date bathymetric survey after the landslide will be necessary to determine the remaining quantity and configuration of subaqueous debris and its effect on nearby riverbed morphology. Future studies of this nature could consider using a green light LiDAR survey, which can penetrate through water and has been applied to seafloor [48], sonar single-beam or multi-beam bathymetric surveys [49,50], or tethered systems such as the Bathy-drone [51]. Additionally, advanced computational techniques, such as machine learning, have been increasingly utilized to detect, map, and predict landslides with high accuracy [52]. These methods integrate various geospatial and environmental factors to enhance hazard assessment, providing deeper insights into landslide susceptibility and risk patterns. Applying such techniques to our study site would enable more detailed and comprehensive analyses.
Based on the evaluation of historical ground and aerial photography, as well as the geomorphic position on a river cutbank and the variable lithology of the strata exposed at Alum Bluff, it is anticipated that mass wasting activity will continue intermittently, with the slope revegetating in the intervening years between mass wasting activity. According to relatively coarse-scale topographic and geologic maps, the site generally falls in a region classified as having low landslide susceptibility and/or incidence, with less than 1.5% of the area involved [10,53]. Given that only one Florida landslide was reported in the literature more than 70 years ago, it makes this story unique and implies that higher slopes and bluffs in low-lying areas are deserving of more attention.
There are other areas of similar geology and setting elsewhere in the Florida panhandle and beyond, where steephead valleys in the Citronelle Formation meet rivers. The authors in [17] describe a few areas in their paper, such as where the Sweetwater Creek meets the Apalachicola River closer to Bristol and Rock Bluff and several smaller valleys near the Yellow River in Florida. Other locations identified using the National Map Viewer include other portions of the Apalachicola and Chipola Rivers. However, at Alum Bluff, the river and steepheads connect, whereas in those other cases, the river is more centered in the valley and not impinging on the valley wall. Further downstream, at Estiffanugla, there is a site where the river impinges on Citronelle sediments, but the bank relief is much lower, there are no steepheads, and thus this location experiences more typical fluvial erosion [30]. This explains why Alum Bluff is more active than elsewhere, and this section of the bluff is likely more active than nearby sections because it has steephead valleys adjacent to the river. Groundwater sapping is an important mechanism elsewhere in the coastal plain, such the Neuse River in North Carolina [54], where the bases of failures were above both the highest surge levels and intact bulkheads.
In the Coastal Plain province of the United States, landslides are uncommon. The case of Port Hudson, Louisiana, adjoining the Mississippi River, is one location of failure, but it is driven by river erosion [2]. There are also three historic landslides along the Cape Fear River in North Carolina (Figure 9.4 in [55]; Figure 6 in [56]; and one in Virginia (Figure 9.4 in [55]), but there is no specific information on the drivers, timing, or other aspects of these specific occurrences. According to [56], there were more than 3000 landslide events from 2007 to 2023 in the USA. The Global Landslide Catalog (URL https://svs.gsfc.nasa.gov/4710, accessed on 30 January 2025), compiled by NASA’s Scientific Visualization Studio, shows the location of 11,033 reported landslides triggered by rainfall for the period 2007–2019. Knowing that the location of the “Williston, Florida” landslide on 21 July 2011 instead occurred at Grotto Spring near Eureka Springs, Arkansas, indicates that the database has events that are not located properly. Also, events such as the Alum Bluff landslides of 2013 and 2015 went unreported. However, with documentation here, there is certainly sufficient evidence to report this, making it potentially the first Florida landslide in the database.
This scenario, with a landslide occurring in a setting with subhorizontal layers of varying lithological characteristics, is quite common globally. For instance, some technical research has been conducted on very similar landslide systems along the south coast of England, where geology is a key determinant of both the location and type of mass movements. Impermeable clays, marls, and silts are capped unconformably by permeable Cretaceous Upper Greensand and Gault, driving the evolution of the British coastline [57]. The main new insights from the remote sensing and field sources are that some sights may be overlooked in large-scale data collection, to pay attention to the changing form of landslide complexes over multiple phases, that erosion on river bluffs may be more driven by mass wasting than river processes, and that larger failures in lowland settings can create occlusions into rivers. Sites such as this should be targeted for change analysis with subaerial and subaqueous monitoring methods to better understand the role of flood events in modifying landslide deposits.

6. Conclusions

Alum Bluff is the tallest of the bluffs adjacent to the upper Apalachicola River and has had periodic mass wasting activity along different sections of the bluff. The strata exposed along the bluff is of mixed lithology, with unconsolidated permeable sandy sediments overlying impermeable cohesive clays, which in turn rest on limestone bedrock. Debris originates from the upper profile, likely associated with wetting from rainfall generating pore water pressures within a transient perched water table on top of the clayey impermeable material from the excess rainwater. Our historical analysis indicates that the landslide occurred during multiple phases between February 2013 and October 2015 and resulted in two occlusions and a clay island into the river. It holds the distinction of being only the second reported landslide in Florida but was omitted during a global survey of landslides covering this interval. The bluff crest near the failure has retreated ~100m, whereas the base has retreated ~10 m, indicating that landslides initiate bluff retreat and lateral river erosion removes sediment at the base over several decades. We expect that this site will be intermittently active in future decades during periods of higher rainfall and will revegetate during the intervening years between mass wasting activity.

Author Contributions

Conceptualization, J.M. and Y.-H.C.; Methodology, J.M. and Y.-H.C.; Software, J.M. and Y.-H.C.; Validation, J.M. and Y.-H.C.; Formal Analysis, J.M.; Investigation, J.M.; Resources, J.M.; Data Curation, J.M. and Y.-H.C.; Writing—Original Draft Preparation, J.M. and Y.-H.C.; Writing—Review and Editing, J.M. and Y.-H.C.; Visualization, J.M. and Y.-H.C.; Supervision, J.M.; Project Administration, J.M.; Funding Acquisition, J.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the U.S. Environmental Protection Agency Gulf of Mexico Program grant number MX-00D68418 to Joann Mossa, PI, Robin McCall, and Jerry Binninger, project managers.

Data Availability Statement

The data presented in this study are available from the sources in Table 1 and on request from the authors.

Acknowledgments

Guy H. Means, Acting Director and State Geologist of the Florida Geological Survey, shared field photographs of Alum Bluff and gave helpful feedback on a recent draft of the manuscript. Garrett Edwards took drone photography. We thank Georgia Ackerman and Dan Tonsmeire of Apalachicola Bay and Riverkeeper for boat transport and other logistical assistance.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Kelly, S.A.; Belmont, P. High resolution monitoring of river bluff erosion reveals failure mechanisms and geomorphically effective flows. Water 2018, 10, 394. [Google Scholar] [CrossRef]
  2. Kesel, R.H.; Baumann, R.H. Bluff erosion of a Mississippi River meander at Port Hudson, Louisiana. Phys. Geogr. 1981, 2, 62–82. [Google Scholar] [CrossRef]
  3. Bracken, L.J.; Turnbull, L.; Wainwright, J.; Bogaart, P. Sediment connectivity: A framework for understanding sediment transfer at multiple scales. Earth Surf. Process. Landf. 2015, 40, 177–188. [Google Scholar] [CrossRef]
  4. Kovács, I.P.; Czigány, S.; Dobre, B.; Fábián, S.Á.; Sobucki, M.; Varga, G.; Bugya, T. A field survey–based method to characterise landslide development: A case study at the high bluff of the Danube, south-central Hungary. Landslides 2019, 16, 1567–1581. [Google Scholar] [CrossRef]
  5. Kesel, R.H.; Dunne, K.C.; McDonald, R.C.; Allison, K.R.; Spicer, B.E. Lateral Erosion and Overbank Deposition on the Mississippi River in Louisiana Caused by 1973 Flooding. Geology 1974, 2, 461–464. [Google Scholar] [CrossRef]
  6. Payne, C.; Panda, S.; Prakash, A. Remote Sensing of River Erosion on the Colville River, North Slope Alaska. Remote Sens. 2018, 10, 397. [Google Scholar] [CrossRef]
  7. Xu, Z.; Stark, T.D. Runout analyses using 2014 Oso landslide. Can. Geotech. J. 2022, 59, 55–73. [Google Scholar] [CrossRef]
  8. Kim, T.-H.; Cruden, D.M.; Martin, C.D.; Froese, C.R.; Morgan, A.J. Landslide movements and their characteristics, Town of Peace River, Alberta. In Proceedings of the 63rd Canadian Geotechnical Conference and 6th Canadian Permafrost Conference, Calgary, AB, Canada, 12–16 September 2010. [Google Scholar]
  9. Jordan, R.H. A Florida landslide. J. Geol. 1949, 57, 418–419. [Google Scholar] [CrossRef]
  10. Radbruch-Hall, D.H.; Colton, R.B.; Davies, W.E.; Lucchitta, I.; Skipp, B.A.; Varnes, D.J. Landslide Overview Map of the Conterminous United States; Professional Paper 1183; U.S. Geological Survey: Reston, VA, USA, 1982.
  11. Means, G.H. Introduction to the geology of the Upper Apalachicola River Basin. In Geologic Exposures Along the Upper Apalachicola River; Field Trip Guidebook; Southeastern Geological Society: Tallahassee, FL, USA, 2002; pp. 4–19. [Google Scholar]
  12. Schmidt, W. Alum Bluff Liberty County, Florida. In Southeastern Section of the Geological Society of America; Neathery, T.L., Ed.; Geological Society of America: Boulder, CO, USA, 1988; Volume 6, p. 13. [Google Scholar]
  13. Johnston, R.H.; Bush, P.W. Summary of the Hydrology of the Floridan Aquifer System in Florida and in Parts of Georgia, South Carolina, and Alabama; US Government Printing Office: Washington, DC, USA, 1988.
  14. Leeder, M.R. Fluviatile fining-upwards cycles and the magnitude of palaeochannels. Geol. Mag. 1973, 110, 265–276. [Google Scholar] [CrossRef]
  15. Miall, A.D. Fluvial Depositional Systems; Springer: Berlin/Heidelberg, Germany, 2014; Volume 14. [Google Scholar]
  16. Abrams, D.M.; Lobkovsky, A.E.; Petroff, A.P.; Straub, K.M.; McElroy, B.; Mohrig, D.C.; Kudrolli, A.; Rothman, D.H. Growth laws for channel networks incised by groundwater flow. Nat. Geosci. 2009, 2, 193–196. [Google Scholar] [CrossRef]
  17. Schumm, S.A.; Boyd, K.F.; Wolff, C.G.; Spitz, W.J. A ground-water sapping landscape in the Florida Panhandle. Geomorphology 1995, 12, 281–297. [Google Scholar] [CrossRef]
  18. Fox, G.A.; Chu-Agor, M.L.; Wilson, G.V. Erosion of noncohesive sediment by ground water seepage: Lysimeter experiments and stability modeling. Soil Sci. Soc. Am. J. 2007, 71, 1822–1830. [Google Scholar] [CrossRef]
  19. Howard, A.D.; McLane, C.F., III. Erosion of cohesionless sediment by groundwater seepage. Water Resour. Res. 1988, 24, 1659–1674. [Google Scholar] [CrossRef]
  20. Devauchelle, O.; Petroff, A.P.; Lobkovsky, A.E.; Rothman, D.H. Longitudinal profile of channels cut by springs. J. Fluid Mech. 2011, 667, 38–47. [Google Scholar] [CrossRef]
  21. Means, G.H. Alum Bluff. In Southeastern Geological Society Guidebook 51; Southeastern Geological Society: Tallahassee, FL, USA, 2010; 19p. [Google Scholar]
  22. Jaboyedoff, M.; Oppikofer, T.; Abellán, A.; Derron, M.-H.; Loye, A.; Metzger, R.; Pedrazzini, A. Use of LIDAR in landslide investigations: A review. Nat. Hazards 2012, 61, 5–28. [Google Scholar] [CrossRef]
  23. Price, F.D.; Light, H.M.; Darst, M.R.; Griffin, E.R.; Vincent, K.R.; Ziewitz, J.W. Change in Channel Width from 1941 to 2004, and Change in Mean Bed Elevation from 1960 to 2001, in the Nontidal Apalachicola River, Florida; Data Series 191; U.S. Geological Survey: Reston, VA, USA, 2006.
  24. Cavalli, M.; Marchi, L. Characterisation of the surface morphology of an alpine alluvial fan using airborne LiDAR. Nat. Hazards Earth Syst. Sci. 2008, 8, 323–333. [Google Scholar] [CrossRef]
  25. ESRI. Curvature Function. Available online: https://desktop.arcgis.com/en/arcmap/10.5/manage-data/raster-and-images/curvature-function.htm (accessed on 5 March 2024).
  26. Leshchinsky, B.A.; Olsen, M.J.; Tanyu, B.F. Contour Connection Method for automated identification and classification of landslide deposits. Comput. Geosci. 2015, 74, 27–38. [Google Scholar] [CrossRef]
  27. Sellards, E.H. Alum Bluff on the Apalachicola River—Florida. Available online: https://www.floridamemory.com/items/show/124327 (accessed on 16 June 2021).
  28. Mossa, J.; Chen, Y.-H. Geomorphic response to historic and ongoing human impacts in a large lowland river. Earth Surf. Process. Landf. 2022, 47, 1550–1569. [Google Scholar] [CrossRef]
  29. U.S. Army Corps of Engineers Mobile District. Proposed Final Navigation Maintenance Plan for the Apalachicola-Chattahoochee-Flint Waterway; United States Army Corps of Engineers: Mobile, AL, USA, 1986; p. 189.
  30. Mossa, J.; Chen, Y.-H.; Walls, S.P.; Kondolf, G.M.; Wu, C.-Y. Anthropogenic landforms and sediments from dredging and disposing sand along the Apalachicola River and its floodplain. Geomorphology 2017, 294, 119–134. [Google Scholar] [CrossRef]
  31. Galay, V.J. Causes of river bed degradation. Water Resour. Res. 1983, 19, 1057–1090. [Google Scholar] [CrossRef]
  32. Light, H.M.; Vincent, K.R.; Darst, M.R.; Price, F.D. Water-Level Decline in the Apalachicola River, Florida, from 1954 to 2004, and Effects on Floodplain Habitats; Scientific Investigations Report 2006-5173; U.S. Geological Survey: Reston, VA, USA, 2006; p. 61.
  33. Amanambu, A.C.; Mossa, J. Machine learning insights of anthropogenic and natural influences on riverbed deformation in a large lowland river. Geomorphology 2024, 446, 108986. [Google Scholar] [CrossRef]
  34. Brierley, G.; Fryirs, K.; Reid, H.; Williams, R. The dark art of interpretation in geomorphology. Geomorphology 2021, 390, 107870. [Google Scholar] [CrossRef]
  35. Evans, I.S. Geomorphometry and landform mapping: What is a landform? Geomorphology 2012, 137, 94–106. [Google Scholar] [CrossRef]
  36. Maxwell, A.E.; Shobe, C.M. Land-surface parameters for spatial predictive mapping and modeling. Earth-Sci. Rev. 2022, 226, 103944. [Google Scholar] [CrossRef]
  37. Mossa, J.; Schumacher, B.A. Fossil tree casts in South Louisiana soils. J. Sediment. Res. 1993, 63, 707–713. [Google Scholar] [CrossRef]
  38. Otvos, E.G. Lithofacies and depositional environments of the Pliocene Citronelle Formation, Gulf of Mexico coastal plain Southeast. Southeast. Geol. 2004, 43, 1–20. [Google Scholar]
  39. Couvin, B.; Georgiopoulou, A.; Amy, L.A. A guide to recognising slow-moving subaqueous landslides in seismic and bathymetry datasets. Earth-Sci. Rev. 2024, 252, 104749. [Google Scholar] [CrossRef]
  40. Devoli, G.; De Blasio, F.V.; Elverhøi, A.; Høeg, K. Statistical Analysis of Landslide Events in Central America and their Run-out Distance. Geotech. Geol. Eng. 2009, 27, 23–42. [Google Scholar] [CrossRef]
  41. Corominas, J. The angle of reach as a mobility index for small and large landslides. Can. Geotech. J. 1996, 33, 260–271. [Google Scholar] [CrossRef]
  42. Rickenmann, D. Runout prediction methods. In Debris-Flow Hazards and Related Phenomena; Jakob, M., Hungr, O., Eds.; Springer: Berlin/Heidelberg, Germany, 2005; pp. 305–324. [Google Scholar]
  43. Chen, Y.-H.; Mossa, J.; Singh, K.K. Floodplain response to varied flows in a large coastal plain river. Geomorphology 2020, 354, 107035. [Google Scholar] [CrossRef]
  44. Mossa, J.; Chen, Y.-H.; Kondolf, G.M.; Walls, S.P. Channel and vegetation recovery from dredging of a large river in the Gulf coastal plain, USA. Earth Surf. Process. Landf. 2020, 45, 1926–1944. [Google Scholar] [CrossRef]
  45. Fell, R. Landslide risk assessment and acceptable risk. Can. Geotech. J. 1994, 31, 261–272. [Google Scholar] [CrossRef]
  46. Bernier, J.-F.; Chassiot, L.; Lajeunesse, P. Assessing bank erosion hazards along large rivers in the Anthropocene: A geospatial framework from the St. Lawrence fluvial system. Geomat. Nat. Hazards Risk 2021, 12, 1584–1615. [Google Scholar] [CrossRef]
  47. Korup, O. Geomorphic imprint of landslides on alpine river systems, southwest New Zealand. Earth Surf. Process. Landf. 2005, 30, 783–800. [Google Scholar] [CrossRef]
  48. Irish, J.L.; White, T.E. Coastal engineering applications of high-resolution lidar bathymetry. Coast. Eng. 1998, 35, 47–71. [Google Scholar] [CrossRef]
  49. Hilldale, R.C.; Raff, D. Assessing the ability of airborne LiDAR to map river bathymetry. Earth Surf. Process. Landf. 2008, 33, 773–783. [Google Scholar] [CrossRef]
  50. Tonina, D.; McKean, J.A.; Benjankar, R.M.; Wright, C.W.; Goode, J.R.; Chen, Q.; Reeder, W.J.; Carmichael, R.A.; Edmondson, M.R. Mapping river bathymetries: Evaluating topobathymetric LiDAR survey. Earth Surf. Process. Landf. 2019, 44, 507–520. [Google Scholar] [CrossRef]
  51. Diaz, A.L.; Ortega, A.E.; Tingle, H.; Pulido, A.; Cordero, O.; Nelson, M.; Cocoves, N.E.; Shin, J.; Carthy, R.R.; Wilkinson, B.E.; et al. The Bathy-Drone: An Autonomous Uncrewed Drone-Tethered Sonar System. Drones 2022, 6, 294. [Google Scholar] [CrossRef]
  52. Tehrani, F.S.; Calvello, M.; Liu, Z.; Zhang, L.; Lacasse, S. Machine learning and landslide studies: Recent advances and applications. Nat. Hazards 2022, 114, 1197–1245. [Google Scholar] [CrossRef]
  53. Mirus, B.B.; Jones, E.S.; Baum, R.L.; Godt, J.W.; Slaughter, S.; Crawford, M.M.; Lancaster, J.; Stanley, T.; Kirschbaum, D.B.; Burns, W.J.; et al. Landslides across the USA: Occurrence, susceptibility, and data limitations. Landslides 2020, 17, 2271–2285. [Google Scholar] [CrossRef]
  54. Phillips, J.D. Geomorphic impacts of Hurricane Florence on the lower Neuse River: Portents and particulars. Geomorphology 2022, 397, 108026. [Google Scholar] [CrossRef]
  55. Wooten, R.M.; Witt, A.C.; Miniat, C.F.; Hales, T.C.; Aldred, J.L. Frequency and Magnitude of Selected Historical Landslide Events in the Southern Appalachian Highlands of North Carolina and Virginia: Relationships to Rainfall, Geological and Ecohydrological Controls, and Effects. In Natural Disturbances and Historic Range of Variation: Type, Frequency, Severity, and Post-disturbance Structure in Central Hardwood Forests USA; Greenberg, C.H., Collins, B.S., Eds.; Springer International Publishing: Cham, Switzerland, 2016; pp. 203–262. [Google Scholar]
  56. Lin, S.; Chen, S.-E.; Tang, W.; Chavan, V.; Shanmugam, N.; Allan, C.; Diemer, J. Landslide Risks to Bridges in Valleys in North Carolina. GeoHazards 2024, 5, 286–309. [Google Scholar] [CrossRef]
  57. Allison, R.J. The Landslides of East Devon and West Dorset. In Landscapes and Landforms of England and Wales; Goudie, A., Migoń, P., Eds.; Springer International Publishing: Cham, Switzerland, 2020; pp. 201–213. [Google Scholar]
Geosciences 15 00130 g001
Figure 1. Study area maps showing the upper reach of the Apalachicola River and its river networks (A). An overview map showing the Apalachicola–Chattahoochee–Flint (ACF) Basin (B), and a zoom-in view of Alum Bluff and its landslide (C). The black rectangle shown in (B) indicates the location of the upper Apalachicola River, and the red rectangle in (A) denotes the location of Alum Bluff.
Figure 1. Study area maps showing the upper reach of the Apalachicola River and its river networks (A). An overview map showing the Apalachicola–Chattahoochee–Flint (ACF) Basin (B), and a zoom-in view of Alum Bluff and its landslide (C). The black rectangle shown in (B) indicates the location of the upper Apalachicola River, and the red rectangle in (A) denotes the location of Alum Bluff.
Geosciences 15 00130 g001
Geosciences 15 00130 g003
Figure 3. Flowchart illustrating the data acquisition, processing, and analysis for this study.
Figure 3. Flowchart illustrating the data acquisition, processing, and analysis for this study.
Geosciences 15 00130 g003
Geosciences 15 00130 g004
Figure 4. Location of cross sections, a single-beam hydrographic survey by the USACE in 1960 (red dots) applied for profile analysis, each ~350 m cross section starting from the right bank. Only profiles B-B’ and F-F’ of 1960 single-beam survey go up the bluff, the 2010 multi-beam sonar survey only covers part of the channel, and the LiDAR does not go underwater.
Figure 4. Location of cross sections, a single-beam hydrographic survey by the USACE in 1960 (red dots) applied for profile analysis, each ~350 m cross section starting from the right bank. Only profiles B-B’ and F-F’ of 1960 single-beam survey go up the bluff, the 2010 multi-beam sonar survey only covers part of the channel, and the LiDAR does not go underwater.
Geosciences 15 00130 g004
Geosciences 15 00130 g005
Figure 5. Series of aerial photographs and satellite image (April 2013) showing recent historic scars and the development of landslides (beginning April 2013 on D) at Alum Bluff, 1979–2019 (A–H). The daily precipitation and cumulative rainfall are presented in (I). Detailed metadata regarding aerial photography are listed in Table 1.
Figure 5. Series of aerial photographs and satellite image (April 2013) showing recent historic scars and the development of landslides (beginning April 2013 on D) at Alum Bluff, 1979–2019 (A–H). The daily precipitation and cumulative rainfall are presented in (I). Detailed metadata regarding aerial photography are listed in Table 1.
Geosciences 15 00130 g005
Geosciences 15 00130 g006
Figure 6. Ground and drone photos of Alum Bluff: (A) after initial failure (taken 18 January 2015), showing many blocks of dark gray semi-consolidated impermeable sandy clay fallen at the base, along with sandier components above; (B) drone photo (taken 2 August 2018) shows part of the headwall and multiple cracks or notches in the clayey layer that form the apex of sediment fans bringing debris and uprooted trees to the base; (C) drone photo taken on the same day as (B) shows the headwall, resistant clayey layer, and subaerial runout emanating from notches in the clay layer. (D) Ground photo (taken 2 June 2019) shows the clay bar (seen in Figure 5D–G) surrounded by water in the foreground.
Figure 6. Ground and drone photos of Alum Bluff: (A) after initial failure (taken 18 January 2015), showing many blocks of dark gray semi-consolidated impermeable sandy clay fallen at the base, along with sandier components above; (B) drone photo (taken 2 August 2018) shows part of the headwall and multiple cracks or notches in the clayey layer that form the apex of sediment fans bringing debris and uprooted trees to the base; (C) drone photo taken on the same day as (B) shows the headwall, resistant clayey layer, and subaerial runout emanating from notches in the clay layer. (D) Ground photo (taken 2 June 2019) shows the clay bar (seen in Figure 5D–G) surrounded by water in the foreground.
Geosciences 15 00130 g006
Geosciences 15 00130 g007
Figure 7. Elevation change based on two LiDAR datasets surveyed in 2007 (A) and 2018 (B). The high-resolution drone photography taken in 2018 shows the landslide, and the red-dashed line polygon denotes the extent applied for the volume change calculation (C). The result of DEM of difference (DoD) was computed by subtracting the 2018 elevation from the 2007 elevation (D).
Figure 7. Elevation change based on two LiDAR datasets surveyed in 2007 (A) and 2018 (B). The high-resolution drone photography taken in 2018 shows the landslide, and the red-dashed line polygon denotes the extent applied for the volume change calculation (C). The result of DEM of difference (DoD) was computed by subtracting the 2018 elevation from the 2007 elevation (D).
Geosciences 15 00130 g007
Geosciences 15 00130 g008
Figure 8. Results of profile change analysis according to the 1960 river profile (cross sections shown in Figure 4), 2007 LiDAR, 2010 multi-beam sonar, and 2018 LiDAR. Three water levels, including the 1st percentile, the 50th percentile, and the 1998 major flooding, are plotted to show the relationship between water levels and bluff profiles. Vertical exaggeration is 5X. Profiles (B,C) show some of the runout debris on the slope and below the high-water line. Profiles (A,D–H) show minimal change between the 2007 and 2018 LiDAR data.
Figure 8. Results of profile change analysis according to the 1960 river profile (cross sections shown in Figure 4), 2007 LiDAR, 2010 multi-beam sonar, and 2018 LiDAR. Three water levels, including the 1st percentile, the 50th percentile, and the 1998 major flooding, are plotted to show the relationship between water levels and bluff profiles. Vertical exaggeration is 5X. Profiles (B,C) show some of the runout debris on the slope and below the high-water line. Profiles (A,D–H) show minimal change between the 2007 and 2018 LiDAR data.
Geosciences 15 00130 g008
Geosciences 15 00130 g009
Figure 9. Profile curvature maps based on 2007 (A) and 2018 (B) DEMs, and the continuous concave lines overlapping with 2019 aerial photos (C). The break in the river-facing concave line is a notch or break in the clay layer that also represents the apex of the largest debris fan.
Figure 9. Profile curvature maps based on 2007 (A) and 2018 (B) DEMs, and the continuous concave lines overlapping with 2019 aerial photos (C). The break in the river-facing concave line is a notch or break in the clay layer that also represents the apex of the largest debris fan.
Geosciences 15 00130 g009
Table 1. Date, flow level, resolution, mapping scale, and sources of data applied in this study.
Table 1. Date, flow level, resolution, mapping scale, and sources of data applied in this study.
DataDate (Flow Level)Resolution/Mapping ScaleSource
Aerial Photography19792.8 mRetrieved from [23]
Aerial Photography19991 mDigital Orthophoto Quadrangle, acquired from USGS Earth Explorer
Aerial Photography9 February 20130.3 mLiberty_FL_2013, acquired from USGS Earth Explorer
Aerial PhotographyOctober 2013, 2015, 2017, 20211 m (2013–2017), 0.6 m (2021)National Agriculture Imagery Program (NAIP), acquired from USDA Geospatial Data Gateway
Drone Photography 31 July 20181 cm (orthophoto)Field survey
Satellite Image20 April 20135 mRapidEye-2, acquired from Planet Labs
LiDAR18 March 2007
(453 m3/s); 29 April 2018
(702 m3/s)		Average point density < 1 point/m2, vertical RMSE < 0.18 m
  • 2007 LiDAR: Northwest Florida Water Management District Apalachicola River LiDAR, and LiDAR, Breaklines and Contours for Gulf County, FL
  • 2018 LiDAR: FL Panhandle QL2 Lidar project
  • Both data were acquired from The National Map (TNM) v2.0
Hydrographic Survey (river profile)1960
  • Average distances of river profiles: 65.4 m
  • Average distances of survey points: 6.6 m
  • Mapping scale: 1:2400
Field survey sheets by U.S. Army Corps of Engineers (USACE), retrieved as scanned files from [23]
Hydrographic Survey (multi-beam
sonar)		2010~0.17 pt/m2Apalachicola, Chattahoochee, and Flint Rivers 2010 Bathymetry Data and Paper, acquired from USACE
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Mossa, J.; Chen, Y.-H. Landslide at the River’s Edge: Alum Bluff, Apalachicola River, Florida. Geosciences 2025, 15, 130. https://doi.org/10.3390/geosciences15040130

AMA Style

Mossa J, Chen Y-H. Landslide at the River’s Edge: Alum Bluff, Apalachicola River, Florida. Geosciences. 2025; 15(4):130. https://doi.org/10.3390/geosciences15040130

Chicago/Turabian Style

Mossa, Joann, and Yin-Hsuen Chen. 2025. "Landslide at the River’s Edge: Alum Bluff, Apalachicola River, Florida" Geosciences 15, no. 4: 130. https://doi.org/10.3390/geosciences15040130

APA Style

Mossa, J., & Chen, Y.-H. (2025). Landslide at the River’s Edge: Alum Bluff, Apalachicola River, Florida. Geosciences, 15(4), 130. https://doi.org/10.3390/geosciences15040130

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop