Marsh Loss Due to Cumulative Impacts of Hurricane Isaac and the Deepwater Horizon Oil Spill in Louisiana

Khanna, Shruti; Santos, Maria J.; Koltunov, Alexander; Shapiro, Kristen D.; Lay, Mui; Ustin, Susan L.

doi:10.3390/rs9020169

Cited by 15 publications

(11 citation statements)

References 63 publications

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“…That could be the reason why we noticed another delayed dormancy onset in 2013. Our observations are consistent with those made by Khanna et al [92]. Any residual oil effects in 2011 or 2012 might have been localized, as the marshes had started to recover or had already recovered from the effects of the oil spill.…”

Section: Sos and Eos Validation Through Analysis Of Fluctuationssupporting

confidence: 82%

Analyzing the Long-Term Phenological Trends of Salt Marsh Ecosystem across Coastal LOUISIANA

Ghosh

Mishra

2017

Remote Sensing

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Abstract:In this study, we examined the phenology of the salt marsh ecosystem across coastal Louisiana (LA) for a 16-year time period (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) using NASA's Moderate Resolution Imaging Spectroradiometer's (MODIS) eight-day average surface reflectance images (500 m). We compared the performances of least squares fitted asymmetric Gaussian (AG) and double logistic (DL) smoothing functions in terms of increasing the signal-to-noise ratio from the raw phenology derived from the time-series composites. We performed derivative analysis to determine the appropriate start of season (SOS) and end of season (EOS) thresholds. After that, we extracted the seasonality parameters in TIMESAT, and studied the effect of environmental disturbances/anomalies on the seasonality parameters. Finally, we performed trend analysis using the derived seasonality parameters such as base green biomass (GBM) value, maximum GBM value, seasonal amplitude, and small seasonal integral. Based on root mean square error (RMSE) values and residual plots, we selected the best thresholds for SOS (5% of amplitude) and EOS (20% of amplitude), along with the best smoothing function. The selected SOS and EOS thresholds were able to capture the environmental disturbances that have affected the salt marsh ecosystem during the 16-year time period. Our trend analysis results indicate positive trends in the base GBM values in the salt marshes of LA. However, we did not notice as much of a positive trend in the maximum GBM levels. Hence, we observed mostly negative changes in the GBM amplitude and small seasonal integral values. These negative changes indicated the overall progressive decline in the rates of photosynthesis and biomass allocation in the LA salt marsh ecosystem, which is most likely due to elevated atmospheric carbon dioxide levels and sea level rise. The results illustrate both the relative efficiency of MODIS-based biophysical models for analyzing salt marsh phenology, and performances of the smoothing techniques in terms of improving the signal-to-noise ratio of the MODIS-derived phenology.

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Section: Sos and Eos Validation Through Analysis Of Fluctuationssupporting

confidence: 82%

Analyzing the Long-Term Phenological Trends of Salt Marsh Ecosystem across Coastal LOUISIANA

Ghosh

Mishra

2017

Remote Sensing

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“…Several recent studies have used remote sensing techniques to assess the impacts of oiling on salt marsh vegetation [ 30 , 41 , 64 , 65 , 66 ] and marsh land loss [ 41 , 42 , 43 , 67 ]. Herein, we take a unique approach to quantifying the impact of oiling on reach-scale and bay-wide loss rates, while controlling for temporal variability in natural background erosion rates.…”

Section: Discussionmentioning

confidence: 99%

Oiling accelerates loss of salt marshes, southeastern Louisiana

et al. 2017

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The 2010 BP Deepwater Horizon (DWH) oil spill damaged thousands of km2 of intertidal marsh along shorelines that had been experiencing elevated rates of erosion for decades. Yet, the contribution of marsh oiling to landscape-scale degradation and subsequent land loss has been difficult to quantify. Here, we applied advanced remote sensing techniques to map changes in marsh land cover and open water before and after oiling. We segmented the marsh shorelines into non-oiled and oiled reaches and calculated the land loss rates for each 10% increase in oil cover (e.g. 0% to >70%), to determine if land loss rates for each reach oiling category were significantly different before and after oiling. Finally, we calculated background land-loss rates to separate natural and oil-related erosion and land loss. Oiling caused significant increases in land losses, particularly along reaches of heavy oiling (>20% oil cover). For reaches with ≥20% oiling, land loss rates increased abruptly during the 2010–2013 period, and the loss rates during this period are significantly different from both the pre-oiling (p < 0.0001) and 2013–2016 post-oiling periods (p < 0.0001). The pre-oiling and 2013–2016 post-oiling periods exhibit no significant differences in land loss rates across oiled and non-oiled reaches (p = 0.557). We conclude that oiling increased land loss by more than 50%, but that land loss rates returned to background levels within 3–6 years after oiling, suggesting that oiling results in a large but temporary increase in land loss rates along the shoreline.

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“…Among other VIs, a recent study by Khanna et al [45] used a modified NDVI (mNDVI) to evaluate the recovery of the salt marshes in Barataria Bay, LA, USA, after Hurricane Isaac in 2012 and the DeepWater Horizon oil spill in 2010 [45]. In 2012, after Hurricane Isaac, there was a significant loss of green vegetation to water, soil and non-photosynthetic vegetation (NPV) in both oiled and oil-free sites.…”

Section: Other Vegetation Index Studiesmentioning

confidence: 99%

“…As stated previously, Barataria Bay in Louisiana was severely impacted in consecutive years by both the Deepwater Horizon oil spill in 2010 and Hurricane Isaac in 2011. Khanna et al [45] used AVIRIS hyperspectral imagery over this area just after the oil spill in September 2010, a year later in August 2011 and post-hurricane in October 2012. They found that, after hurricane Isaac, the oiled shorelines (up to the 7 m topographic contour) experienced a 17.8%, while the land loss on oil-free shorelines was 13.6%.…”

Section: Hyperspectral Remote Sensor (Hrs)mentioning

confidence: 99%

Assessing the Resilience of Coastal Wetlands to Extreme Hydrologic Events Using Vegetation Indices: A Review

2018

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Coastal wetlands (CWs) offer numerous imperative functions that support a diverse array of life forms that are poorly adapted for other environments and provide an economic base for human communities. Unfortunately, CWs have been experiencing significant threats due to meteorological and climatic fluctuations as well as anthropogenic impacts. The wetlands and marshes in Apalachicola Bay, Florida have endured the impacts of several extreme hydrologic events (EHEs) over the past few decades. These extreme hydrologic events include drought, hurricane, heavy precipitation and fluvial flooding. Remote sensing has been used and continues to demonstrate promise for acquiring spatial and temporal information about CWs thereby making it easier to track and quantify long term changes driven by EHEs. These wetland ecosystems are also adversely impacted by increased human activities such as wetland conversion to agricultural, aquaculture, industrial or residential use; construction of dikes along the shoreline; and sprawl of built areas. In this paper, we review previous works on coastal wetland resilience to EHEs. We synthesize these concepts in the context of remote sensing as the primary assessment tool with focus on derived vegetation indices to monitor CWs at regional and global scales.

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Marsh Loss Due to Cumulative Impacts of Hurricane Isaac and the Deepwater Horizon Oil Spill in Louisiana

Cited by 15 publications

References 63 publications

Analyzing the Long-Term Phenological Trends of Salt Marsh Ecosystem across Coastal LOUISIANA

Analyzing the Long-Term Phenological Trends of Salt Marsh Ecosystem across Coastal LOUISIANA

Oiling accelerates loss of salt marshes, southeastern Louisiana

Assessing the Resilience of Coastal Wetlands to Extreme Hydrologic Events Using Vegetation Indices: A Review

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