Satellite-derived Temperature Data for Monitoring Water
Status in a Floodplain Forest of the Upper Sabine River,
Texas
Mary Grace T. Lemon, Scott T. Allen, Brandon L. Edwards, Sammy L. King, and Richard F. Keim
Southeastern Naturalist, Volume 16, Special Issue 9 (2016): 90–102
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Satellite-derived Temperature Data for Monitoring Water
Status in a Floodplain Forest of the Upper Sabine River,
Texas
Mary Grace T. Lemon1,*, Scott T. Allen1, Brandon L. Edwards1, Sammy L. King2,
and Richard F. Keim1
Abstract - Decreased water availability due to hydrologic modifications, groundwater
withdrawal, and climate change threaten bottomland hardwood (BLH) forest communities.
We used satellite-derived (MODIS) land-surface temperature (LST) data to investigate spatial
heterogeneity of canopy temperature (an indicator of plant-water status) in a floodplain
forest of the upper Sabine River for 2008–2014. High LST pixels were generally further
from the river and at higher topographic locations, indicating lower water-availability. Increasing
rainfall-derived soil moisture corresponded with decreased heterogeneity of LST
between pixels but there was weaker association between Sabine River stage and heterogeneity.
Stronger dependence of LST convergence on rainfall rather than river flow suggests
that some regions are less hydrologically connected to the river, and vegetation may rely on
local precipitation and other contributions to the riparian aquifer to replenish soil moisture.
Observed LST variations associated with hydrology encourage further investigation of the
utility of this approach for monitoring forest stress, especially with considerations of climate
change and continued river management.
Introduction
Bottomland hardwood (BLH) forests are high-value, high-productivity wetland
ecosystems, (Tockner and Stanford 2002), but many are under threat of ecosystem
conversion due to current water-management strategies and changing climatic
conditions (Graf 2001, Olson and Dinerstein 1998). Many of these forests were
converted to agriculture in the latter half of the 20th century (Turner et al. 1981),
and those that remain have become degraded due to hydrologic modifications to
large rivers, among other causes (King et al. 2012). Hydrologic modifications that
reduce water availability to floodplain vegetation during the growing season (e.g.,
dams, levees, and channelization; Hupp et al. 2009, Wharton et al. 1982) may be
particularly detrimental because wetland trees tend to be poorly adapted to dry
conditions. Wetland trees tend to have shallow roots (Kozlowski 1997), especially
those developed during flooding, which may not be ideal for accessing soil water
(Burke and Chambers 2003). In general, trees that are well adapted to one stress are
vulnerable to other stressors (Niinemets 2010). Predicted increases in drought frequency
(Georgakakos and Zhang 2011, Hay et al. 2011, Orlowsky and Seneviratne
1School of Renewable Natural Resources, Louisiana State University Agricultural Center,
Baton Rouge, LA, 70803. 2US Geological Survey, Louisiana Cooperative Fish and Wildlife
Unit, Louisiana State University Agricultural Center, Baton Rouge, LA, 70803. *Corresponding
author - mlemon7@tigers.lsu.edu.
Manuscript Editor: Jerry Cook
Proceedings of the 6th Big Thicket Science Conference: Watersheds and Waterflow
2016 Southeastern Naturalist 15(Special Issue 9):90–102
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2012) and anthropogenic water use (Brown et al. 2014) will further decrease water
levels in rivers, and thus, water availability for BLH forests, potentially converting
hydrological conditions to those favored by species associated with drier habitats
(Gee et al. 2014, Kroes and Brinson 2004, Shankman et al. 2012)
Water available to floodplain vegetation is controlled by river discharge, precipitation,
and shallow-groundwater flow, but relative contributions to water accessible
by vegetation are still poorly understood (e.g., Kaplan and Muñoz-Carpena 2011,
Krause et al. 2007). The physiological effects of flooding have been well documented
in BLH forests (reviewed by Kozlowski 1997), but few studies have focused on the
importance of water availability and deficit during low-flow periods, when floodplains
become hydrologically disconnected from their associated rivers. Recent
research suggests that even in floodplains typically defined by annual water excess,
periods of limited availability can result in reduced water-use by trees (Allen et
al. 2014, Bosch et al. 2013), an indicator of stress and reduced productivity (Lu et al.
2004). Identification of areas within the floodplain where water availability to vegetation
is limited can provide valuable information about floodplain hydrology that
can lead to improved understanding of BLH ecology and management.
Decreased water availability reduces tree hydraulic-conductance (Meinzer
2001), limiting transpiration and causing an increase in canopy temperature (Jones
1998, Monteith 1965). Many researchers have employed a variety of methods for
efficiently determining plant stress (Akhtar et al. 2013, Jackson et al. 1981) in crops
and forests (e.g., Luvall and Holbo 1989, Nemani and Running 1989, Sun and Mahrt
1994). In particular, remotely sensed canopy temperature is useful as an index of
water stress (Berni et al. 2009, Moran and Jackson 1991, Nagler et al. 2003). Areas
with comparatively high land-surface temperature (LST) are assumed to have less
available water. In addition, diel fluctuation in LST is greater in moisture-limited
areas (e.g., Carlson 1986, Carlson et al. 1981, Gauthier and Tabbagh 1994), and
accordingly used to identify areas of moisture stress (Tramutoli et al. 2001).
In this study, we used satellite-derived (MODIS) LST data to investigate spatial
heterogeneity of water stress in a floodplain forest of the upper Sabine River. The
first objective was to determine whether the spatial patterns of diel LST fluctuations
were comparable to spatial patterns identified by daytime LST anomaly. The
second objective was to identify inter-annual spatial patterns in LST during the
growing season, and determine whether years defined by water scarcity result in
greater spatiotemporal variability of LST. The location of the study site in eastern
Texas, is characterized by periods of extended drought, including during the study
period. We hypothesized that the LST would be relatively spatially homogeneous
(LST anomaly is convergent between groups) during relatively wet years, but that
it would exhibit more spatial variability in drought years (LST anomaly is divergent
between groups) as water sources become localized within the flo odplain.
Field Site Description
The study area includes 2 sections of BLH forests that lie adjacent to the Sabine
River: Old Sabine Bottoms Wildlife Management Area (OSB WMA) and
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the neighboring Little Sandy National Wildlife Refuge (LS NWR) (Fig. 1a, b).
Dominant tree species include Planera aquatica J.F. Gmel. (Water Elm), Fraxinus
pennsylvanica Marsh. (Green Ash), Celtis laevigata Willd. (Sugarberry), Ulmus
crassifolia Nutt. (Cedar Elm), Quercus nigra L. (Water Oak), Quercus phellos L.
(Willow Oak), Quercus lyrata Walter (Overcup Oak), and several Carya (hickory)
species (Alden 1998). Soils are dominated by vertisols (shrink–swell clays), with
bands of coarser soils that outline former channels of the Sabine. There have been
substantial hydrological modifications in the Sabine watershed throughout the 20th
century, mainly reservoir construction, leading to reduced flood-peak stages and
Figure 1. (a) Location and grouping of study pixels within the study area. Darker pixels
are cool in temperature while brighter pixels are warm. (b) Approximate location of the
study area within East Texas and along the Sabine Riverwithin East Texas and along the
Sabine River. (c) Topographic map of the study area derived from USGS National Elevation
Dataset with shading indicating 1-m changes in elevation within in the floodplain. Lowest
elevations are shaded black. Stars indicate point locations of observed mortality during the
2011 drought.
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lower variability in river flows. Two large reservoirs, Lake Fork, on a large tributary
of the Sabine and Lake Tawakoni on the main stem Sabine, are directly upstream
from the study site. Sabine River modifications and increased frequency of drought
conditions over the past decade have presumably caused water stress in some
floodplain trees, as demonstrated by large tree-mortality events (Christopher Farrell,
Texas Parks and Wildlife Department, OSBWMA, Lindale, TX, pers. comm.)
concurrent with the severe drought conditions in 2011 (Figs. 1 and 2). In addition,
regeneration of hydric-adapted tree species has been minimal in these locations
(March et al. 2012).
Methods
Data acquisition and processing
We used MODIS (1 km ×1 km resolution) MOD11A2 8-d average LST data from
2008–2014 (USGS 2014). Although a finer spatial scale is preferable, other thermal
sensors do not provide the temporal resolution required for this analysis. The development
and processing of this MODIS product includes corrections for emissivity
Figure 2. Mean land-surface temperature (LST) calculated across all pixels from 1 May
2008 to 1 November 2014.
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variation and removal of periods with clouds (Wan et al. 2002). To minimize thermal
contamination, we removed pixels within the study-area boundary if they contained
more than 20% permanent surface-water, any upland area, or recent clear-cut forest.
This yielded a total of 30 pixels (Fig. 1). We included only imagery captured from 1
May through 1 November to restrict the analysis to the growing season.
We acquired weather data from the National Climate Data Center
(GHCND:USC00414020), which were collected ~2 km away from the study site
in Hawkins, TX. River stage was measured at USGS gage 08019200 on the Sabine
River near Mineola, TX, during the study period.
Analyses
For each pixel and each 8-d LST composite, we subtracted day LST from night
LST to calculate the magnitude of mean diel fluctuation for each pixel across the
study period. We performed a principal component analysis (PCA) on these data
(rows: pixels; columns: 8-d mean diel fluctuation). We ordered pixels by mean
diel fluctuation according to first principal component scores, which we compared
against mean daytime LST anomaly (mean deviation of each pixel from the
median LST of all pixels for each 8-d period) to test the hypothesis that daytime
LST anomaly arises because of diel fluctuation, as would be expected in waterlimited
canopies.
We compared the spatial mean LST anomaly for the warmest 10, middle 10,
and coolest 10 pixels (based on first principal component scores) through time and
against river stage and recent rainfall. We estimated the effect of rainfall on soil
moisture using the antecedent precipitation index (API) as APIi = R + k × APIi-1,
where R is rainfall occurring on day i and k is 0.9 (Linsley et al. 1949). All analyses
were performed in MATLAB (Mathworks, Inc., Natick, MA).
Results
Overbank flooding only occurred 5 times throughout the 7-y study period (Fig.
3a). Pulses were short in duration except in 2008, fall of 2009, and during late
winter of 2010. In some growing seasons, there were only a few, small, peak flows
well below bankfull, and in 2011, the river remained at low base-flow for the entire
growing season. Rainfall-controlled soil moisture (API) was highest during the
growing season of 2009 and lowest during 2011 (Fig. 3b). Peak soil moisture was
typically higher during the late growing season; however, there were short pulses
of elevated soil moisture near the beginning of the growing seasons in 2008, 2010,
and 2014. The combined results from river flow and API distinctly showed greater
water scarcity in 2011 than other years. The wettest period occurred from the beginning
of the 2009 growing season through the start of the 2010 growing season.
The first eigenvector in the PCA analysis accounted for 90.5% of the variance of
diel LST variation, and was thus an appropriate variable for differentiating pixels.
Rank by diel variation was also correlated with mean LST anomaly (Fig. 4).
Pixels ranked by the first component of diel variation showed consistent behavior
throughout the study period, and the difference in LST anomaly between the
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Figure 3. (a) 8-day mean Sabine River hydrograph at USGS gage 08018500 near Mineola,
TX, from 1 November 2007 to 1 November 2014. Asterisks indicate overbank events at the
study location (>5.18 m at gage 08018500) and (b) 8-day mean antecedent precipitation
index (API) for soil moisture from 1 November 2007 to 1 November 2014.
Figure 4. Land-surface temperature (LST) anomaly for each pixel sorted by the weight of
the first eigenvector of the diel variation from 1 May 2008 to 1 November 2014. Color scale
has been set from -2 to 2 ºC in order to aid visualization but ranged from approximately -4
to 4 ºC.
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warmest 10 pixels and the remaining pixels was greater than the differences among
the 2 other pixel groups (Fig. 5). Similarly, LST anomaly of the warmest pixels
was more variable than cooler pixels. The largest divergence (highest variability)
in LST anomaly was during the droughty 2011 growing season, with a mean difference
between the warmest and coolest groups reaching 1.60 °C, the largest of all
years (Fig. 5).
Among-year trends in LST anomaly (Fig. 5) match among-year trends in LST
(Fig. 2). Both LST anomaly for the warmest pixels and raw LST values reflect the
severity of drought in 2011 compared to all other years; pixel mean LST reached
36.5 ± 1.7 °C during the growing season (Fig. 2).
Increasing rainfall-controlled soil moisture corresponded with convergence of
LST anomaly between the warmest and coolest pixels (Fig. 6). For river stages at
or below baseflow (~0.5 m), LST heterogeneity was high; however, above baseflow
there was an increasing trend toward homogeneity in terms of LST (Fig. 7). For
stages near or above bankfull (~5.2 m), there was convergence of LST; however, the
sample size of surface-flooding events during the growing season across the study
period was extremely small (Fig. 7). The spatial distribution of the first eigenvector
weights across the floodplain generally corresponded to relative disconnection from
the river in terms of topographic position and distance (Fig. 1a).
Discussion
The results indicate that heterogeneity of floodplain temperature generally increased
in drought years, which supports our hypotheses. Convergence to a more
homogeneous condition was related to rainfall and stage of the Sabine River;
Figure 5. Land-surface temperature (LST) anomaly for 3 groups of pixels from 1 May 2008
to 1 November 2014. The pixels were sorted in ascending order of the weight of the first
eigenvector of the diel variation with the low LST making up the first 10 pixels, the median
LST making up the middle 10 pixels, and the high LST group making up the last 10 pixels.
Numbers below data along x axis indicate mean difference of actual daytime LST between
low and high groups (ºC).
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however, pixel temperature was loosely organized by floodplain topography—the
warmest pixels were generally at higher topographic positions, which were loosely
related to distance from the river. The relative lack of overbank flooding events
at the study site during the growing season could explain why the relationship
between growing season LST and river stage is not stronger, but the river still seemingly
affected the floodplain forest. This dichotomy remains unexplained for our
study floodplain, but is likely related to topographic variability controlling water
availability from multiple sources that were not well quantified by the simple hydrologic
analyses we conducted for this work.
Although our analysis relied on the correlation between temperature and water
stress, leaf-level processes link carbon- and water-exchange; thus, increasing temperature
anomalies are likely coupled to reduced photosynthetic capability. Further
research is needed to match canopy temperature to specific stress thresholds. Given
that there was substantial tree-mortality in 2011 (March et al. 2012), the high LST
observed at that time was certainly indicative of high-stress events. However, mortality
is usually associated with multiple-year droughts (e.g., Nepstad et al. 2007),
so maximum temperatures alone are not necessarily useful indicators.
Figure 6. Spatial variation in 8-d mean land-surface temperature (LST) anomaly (ºC) as a
function of 8-d mean, rainfall-derived soil moisture (API).
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Dams and resulting hydrologic changes generally reduce peak-flow frequency
and magnitude while increasing low-flow frequency and magnitude (Brandt 2000,
Graf 2001, Williams and Wolman 1984). Similarly, Magilligan and Nislow (2005)
found that dams can increase low-magnitude high-frequency hydrograph variations
and decrease the average length of high pulses downstream. This type of pre-dam–
post-dam analysis has not been completed for the upper Sabine River. Although
Phillips (2001) found no evidence of a reduction in peak annual discharge of the
Sabine River at the lowermost gaging station (USGS no. 08030500) near Ruliff,
TX, despite multiple upstream dams, local effects on floodplain forests have been
documented in the lower Sabine River (Alldredge and Moore 2012) and are likely
also present on our study site due to its proximity to 2 large upstream reservoirs.
This conclusion is supported by the low frequency of over-bank flooding events
that were not sufficient to routinely cause floodplain-wide alleviation of drought
stress (Fig 3a).
Alluvial aquifers are replenished during surface-flooding events in floodplains
(Winter 1999), and changes in the frequency, timing, and magnitude of these events
can reduce water availability to floodplain ecosystems. Additionally, short-duration,
Figure 7. Spatial variation in 8-d mean LST anomaly (ºC) as a function of Sabine River
stage. Asterisks indicate time intervals where stages at or above 5.18 m occurred.
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high-flow pulses may not cause long-distance propagation of the floodplain watertable
as compared to long-duration, high-flow pulses, even when considering
sub-bankfull flows (Jung et al. 2004). Therefore, the modifications upstream of our
study site may be affecting subsurface hydrology and water availability to vegetation,
particularly in floodplain areas with low subsurface hydraulic connectivity to
the river (e.g., distant and microtopographically higher in elevation). Demonstrated
dependence of LST on rainfall instead suggests that vegetation relies on local
precipitation and other contributions to the riparian aquifer (Kroes and Brinson
2004) to replenish soil moisture during times of low flows resulting from increased
regional demand for water during drought periods. Increased drought frequency is
predicted for eastern Texas over the next century (Orlowsky and Seneviratne 2012);
thus, further mortality events may be observed during severe drought years in areas
of low connectivity to the river.
In this study, decreasing connectivity in terms of elevation and distance from
the river was generally associated with decreased water availability as interpreted
by high LST anomaly; however, in other floodplains, spatially diverse geomorphic
features and complex groundwater connections may result in more complex canopy-
temperature patterns. The coarse spatial resolution of the study limits inferences
about smaller floodplain features (i.e., sloughs, back-swamp ponding). Higher
spatial-resolution (less than 1 km) thermal imagery is required to investigate canopy-temperature
patterns related to smaller-scale connectivity, and therefore, could not be
addressed by our study. Remote sensing allows inference with greater spatial and
temporal frequency than field-based methods. In addition to field measurements,
this tool enables identification of specific mechanisms and development of detailed
ecological conclusions without limiting spatial extent. To increase the value of both
techniques for purposes of research and monitoring, coupled ground-based and
remote-sensing data-collection and analysis is needed.
Conclusions
LST (a surrogate for plant water-status) in the floodplain of the upper Sabine
River is most spatially variable during times of drought. Dependence of LST on
rainfall and spatial patterns suggests that vegetation in some parts of the floodplain
is less hydrologically connected to the river than in others. Areas less connected to
the river and its influence had greater temperature variations, indicating greater vulnerability
to climatological drought. Remotely sensed LST shows promise as a tool
for better understanding the spatial distribution of water stress within floodplains,
which is expected to increase in relevance during times of increased water scarcity
due to water-management projects and climate change.
Acknowledgments
We thank Christopher Farrell from TPWD for information about the site, particularly
in determining bankfull stages. Any use of trade, firm, or product names is for descriptive
purposes only and does not imply endorsement by the US Government.
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