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Climate and vegetation change in a coastal marsh: two snapshots of groundwater dynamics and tidal flooding at Piermont Marsh, NY spanning 20 years

Authors: Watson, Elizabeth; Courtney, Sofi; Montalto, Franco;

Climate and vegetation change in a coastal marsh: two snapshots of groundwater dynamics and tidal flooding at Piermont Marsh, NY spanning 20 years

Abstract

Hydrological measurements were collected during the spring and summer of 1999 and 2019 in Piermont Marsh (coordinates 41.0361°, -73.9105°). These measurements covered a transect that was laid out perpendicular to a tidal channel. The objective of this study was to compare the current tidal flooding and groundwater table levels with the data from 1999. The goal was to assess the differences in tidal hydrology between these two distinct time periods, which also differed in terms of marsh and water level elevations. To determine groundwater levels and tidal flooding across the marsh, we installed seven water level loggers along a gradient, ranging from the tidal channel to the upland area. We constructed wells by suspending pressure transducers within 7.5 cm diameter perforated PVC pipes lined with screening to prevent sediment from entering the well. These wells were positioned one meter below the marsh surface, 0.6 meters above the soil surface, vented to the atmosphere, and only the section below the soil surface was perforated. Additionally, we installed concrete collars at the marsh surface around the wells to prevent preferential water flow down the well sides. These seven wells were placed along the original transect, perpendicular to the creek, with increasing distances (0 meters, 6 meters, 12 meters, 18 meters, 24 meters, 36 meters, and 48 meters). We installed and monitored the wells from May 5 to June 30, 2019, and from April 6 to May 26, 1999. In 2019, we measured the absolute elevation of the top of each well using RTK-enabled static GPS measurements from Leica GNSS GS14 rover units and static measurements with an AX1202 GG base station unit to reference water levels to the NAVD88 vertical datum. We measured reference water levels each time data was collected, which involved determining the distance from the top of the well to the water surface and converting it to elevation relative to the NAVD88 datum. To relate marsh elevation to water elevations, GPS surveys were conducted along the transect using a Leica GNSS GS14 rover unit. In 1999, elevation control for the wells and water levels was similarly measured using survey-grade GPS. We compared changes in the marsh water table with significant potential hydrological and vegetation changes that have occurred over the past 20 years. We calculated the rates of change in monthly water levels at Battery, NY for the period from 1999 to 2019 using two different methods. We modeled changes over time in monthly highest water levels, mean high water (MHW), mean tide level (MTL), and mean low water (MLW) using an ordinary least squares regression model with ARIMA errors to account for the autoregressive structure of tide data. We removed the annual cycle first using a curve with a 1-year periodicity. The ARIMA errors model was fitted using the "auto.arima" function from the "forecast" package. We calculated the squared correlation of fitted values to actual values to produce a pseudo-r2. For comparison, we calculated trends using ordinary least squares regression for the 1999-2019 period, although it's important to note that the temporal autocorrelation likely results in underestimated uncertainty. We obtained vegetation maps from the HRNERR for 1997, 2005, 2014, and 2018 to help assess changes in the coverage of plant species over time, as these changes could impact evapotranspiration and water table patterns. A 20-meter buffer zone was created around each well location, and the composition of vegetation within this buffer zone was quantified using QGIS version 3.30.2. While four time-points may not be sufficient for statistically identifying trends, we analyzed the changes observed. To put the measurement time periods in context and ensure that our selected seasons were not anomalous, we compared water levels in spring 1999 and 2019 relative to the astronomical cycles driving interannual sea level variability using data from the Battery tide gauge. We also compared spring high tide levels in 1999 and 2019 with surrounding years. The main astronomical cycles thought to influence tides include the 18.6-year lunar nodal cycle and the 4.4-year subharmonic of the 8.85-year lunar perigee cycle. As our 1999 and 2019 measurements were collected during slightly different time periods (April/May 1999 vs. May/June 2019), we also examined mean monthly water levels (1980-2022) from the NOAA Battery tidal gauge to identify potential artifacts. We obtained rainfall data from spring 1999 and 2019 from the nearest precipitation monitoring station (Westchester airport) to determine whether the measurements were made during an unusually wet or dry period. The sampling periods were 20 years apart, so they occurred at approximately the same point in the 18.6-year lunar nodal cycle. Pressure transducer data was processed using HOBOware Pro (Version 3.7.16, Onset Computer Corporation, Bourne, MA) with reference water levels collected in the field. The data were corrected for atmospheric pressure using the HOBOware barometric compensation assistant, using data from the Hudson River National Estuarine Research Reserve. Raw water elevation data from 1999 was analyzed in conjunction with the 2019 data. Water level data from 1999 were converted from the NVGD29 to NAVD 88 datum using NOAA VDatum v4.0.1 prior to analysis. Well seven's transducer experienced three brief malfunctions from May 30 to June 3, 2019, resulting in inaccurate elevation measurements for a total of 19.5 hours. These data were excluded from the analysis. In 1999, well seven also experienced malfunctions, which were corrected by Montalto into smoothed six-hour increments using average water elevation measurements and calculated error, calibrated using regression. No other well transducers appeared to have malfunctioned.

Groundwater hydrology plays an important role in coastal marsh biogeochemical function, in part because groundwater dynamics drive the zonation of macrophyte community distribution. Changes that occur over time, such as sea level rise and shifts in habitat structure are likely altering groundwater dynamics and eco-hydrological zonation. We examined tidal flooding and marsh water table dynamics in 1999 and 2019 and mapped shifts in plant distributions over time, at Piermont Marsh, a brackish tidal marsh located along the Hudson River Estuary near New York City. We found evidence that the marsh surface was flooded more frequently in 2019 than in 1999, and that tides were propagating further into the marsh in 2019, although marsh surface elevation gains were largely matching that of sea level rise. The changes in groundwater hydrology that we observed are likely due to the high tide rising at a rate that is greater than that of mean sea level. In addition, we reported on changes in plant cover by P. australis, which has displaced native marsh vegetation at Piermont Marsh. Although P. australis has increased in cover, wrack deposition and plant die off associated Superstorm Sandy allowed for native vegetation to rebound in part of our focus area. These results suggest that climate change and plant community composition may interact to shape ecohydrologic zonation. Considering these results, we recommend that habitat models consider tidal range expansion and groundwater hydrology as metrics when predicting the impact of sea level rise on marsh resilience.

Funding provided by: National Science FoundationCrossref Funder Registry ID: https://ror.org/021nxhr62Award Number: 1946302 Funding provided by: Hudson River FoundationCrossref Funder Registry ID: https://ror.org/04x0tcn90Award Number: Polgar Award

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Keywords

eco-hydrological zonation, marsh macrophyte, groundwater hydrology, Climate change, coastal wetland, Sea level rise

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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