DECADAL MORPHODYNAMICS ASSOCIATED WITH SAND AND GRAVEL MINING VARIATIONS IN THE AMITE RIVER AND FLOODPLAIN, LOUISIANA
Abstract
Mining activities have a large topographic footprint and invariably have substantial impacts on ecosystems and local communities. Potential consequences of mining include channel instability, changes in flood risks, increased sediment load, and impacts to infrastructures. This study investigated decadal morphodynamics of the mined Amite River, using three methodologies. The first part of the dissertation focused on methods for identifying the sand and gravel mining depressions located along the study area, inside and outside the floodplain. Results demonstrated that the structure and mean depth of the pits inside the floodplain are more complicated than those located outside the floodplain. By using the Level Set Method and Localized Contour Tree, we were able to characterize the hierarchy of sand and gravel depressions over a 13-year period, spannin the August 2016 historic (~500-year) flood. Results successfully delineated changes in pit depressions in the study area from 2005 to 2018, using DEMs.
The second part of the dissertation focused on spatial autocorrelation between Land Use and Land Cover (LULC) and the erosion and accretion rates at 55 channel planform segments, from 1998 to 2019. Results showed positive correlations between LULC and channel changes.
Also, erosion on the right bank was greater than erosion on the right bank during the study period. That was because mining was concentrated on the right bank of the river and involved removal of large amounts of vegetation and soil, leading to increased vulnerability to erosion.
The third study investigated the influence factors on the bank erosion. The bank locations had been identified using the DoD of the 2005 and 2018, then the investigated four variables; slope, Normalized Different Vegetation Index (NDVI), Topological Wetness Index (TWI), and distance to the pits by using logistic regression analysis. The results show the NDVI has the highest predicted probability indicator of bank erosion in the study area. The results of validation, based on Pseudo R2 include Cox and Snell, Nagelkerke, Chi square, and Relative Operation Characteristic (ROC), attest for acceptable accuracies of the model > 0.2 of Pseudo R 2.
The combination of mining in floodplains, such as removing forests and overburden and creating pits, creates a vulnerable landscape susceptible to dynamic change from river migration and floods. If not properly managed, this landscape is prone to avulsion and sending massive quantities of sediment downstream. Mining activities in floodplains often involve removing trees and vegetation, excavating soil and rocks, and creating pits or ponds. These activities can disrupt the natural processes that help to maintain the stability and resilience of the floodplain ecosystem. The removal of trees and vegetation can lead to soil erosion and increase the risk of landslides, while the excavation of soil and rocks can alter the topography of the floodplain and create areas of unstable ground. One of the key risks associated with mining in floodplains is the potential for river migration and flooding. Rivers naturally shift and change course over time, and this can be exacerbated by the disruption of the floodplain caused by mining activities. If the mining activities have created barriers to the natural flow of the river, such as through the creation of pits or other physical obstructions, then the river may be more likely to shift its course in order to find a new path. This can result in avulsion, where the river suddenly changes course, often with catastrophic consequences. In addition to the risk of avulsion, mining in floodplains can also result in the movement of large quantities of sediment downstream. This can occur when the mining activities remove or disturb the soil and rocks that make up the floodplain, and the sediment is then carried downstream by the river during periods of high flow. This can have serious environmental impacts downstream, such as smothering aquatic habitats and reducing water quality.Proper management of mining activities in floodplains is therefore essential to minimize the risks of river migration, flooding, and sedimentation. This can involve a range of measures, such as maintaining natural drainage patterns, minimizing the size and depth of pits, and implementing erosion control measures such as re-vegetation and slope stabilization. By carefully managing mining activities in floodplains, it is possible to minimize the impact on the environment and ensure the long-term sustainability of these ecosystems.
Description
The described study investigates the long-term impacts of mining activities on the Amite River, with a focus on its morphodynamics and the associated consequences for ecosystems and local communities. The research utilizes three methodologies to analyze various aspects of the river system.
The first part of the study concentrates on identifying sand and gravel mining depressions within and outside the floodplain of the Amite River. The researchers employ the Level Set Method and Localized Contour Tree to characterize the structure and mean depth of these pits over a 13-year period, including the significant flood event that occurred in August 2016. The results reveal that the pits inside the floodplain exhibit a more complex nature compared to those outside the floodplain. The researchers successfully delineate changes in pit depressions between 2005 and 2018 using Digital Elevation Models (DEMs).
The second part of the study investigates the spatial relationship between Land Use and Land Cover (LULC) and erosion and accretion rates along 55 channel planform segments from 1998 to 2019. The findings demonstrate positive correlations between LULC and channel changes. Moreover, the study identifies that erosion on the right bank of the river is more significant than on the left bank. This discrepancy is attributed to the concentration of mining activities on the right bank, which involves extensive removal of vegetation and soil, thereby heightening vulnerability to erosion.
The third part of the research explores the factors influencing bank erosion. Bank locations are determined by comparing the Difference of Digital Elevation Models (DoD) from 2005 and 2018. Logistic regression analysis is then performed using four variables: slope, Normalized Difference Vegetation Index (NDVI), Topological Wetness Index (TWI), and distance to the mining pits. The results indicate that NDVI is the most reliable indicator of bank erosion in the study area. The model's accuracy is validated using various metrics, including Pseudo R2, which demonstrates acceptable accuracies above 0.2.
Mining in floodplains, involving activities such as deforestation, excavation, and pit creation, creates a vulnerable landscape prone to dynamic changes caused by river migration and floods. Inadequate management of such activities can lead to avulsion, where the river abruptly changes its course with potentially catastrophic consequences, and the transportation of large amounts of sediment downstream. These mining activities disrupt the natural processes that maintain floodplain stability and resilience. The removal of vegetation increases the risk of soil erosion and landslides, while soil and rock excavation alters floodplain topography, creating unstable areas.
Mining in floodplains also heightens the risk of river migration and flooding, as it can create barriers to the natural flow of the river. This disturbance can induce the river to shift its course to find a new path. Additionally, mining activities can result in the movement of substantial sediment downstream when soil and rocks are disturbed or removed, impacting aquatic habitats and water quality.
Proper management of mining activities in floodplains is crucial to mitigate the risks of river migration, flooding, and sedimentation. This involves measures such as preserving natural drainage patterns, minimizing the size and depth of pits, and implementing erosion control methods like re-vegetation and slope stabilization. By carefully managing mining activities in floodplains, the adverse environmental impacts can be minimized, ensuring the long-term sustainability of these ecosystems.
Keywords
Sand and Gravel Mining, Level Set Method (LSM), Localized Contour Tree (LCT), Logistic regression, Amite Floodplain