Article pubs.acs.org/est
Understanding Water Column and Streambed Thermal Refugia for Endangered Mussels in the Delaware River Martin A. Briggs,*,† Emily B. Voytek,† Frederick D. Day-Lewis,† Donald O. Rosenberry,‡ and John W. Lane† †
Office of Groundwater, Branch of Geophysics, U.S. Geological Survey, 11 Sherman Place, Unit 5015, Storrs, Connecticut 06269, United States ‡ National Research Program, Central Branch, U.S. Geological Survey, MS 413, Bldg. 53, DFC, Lakewood, Colorado 80225, United States S Supporting Information *
ABSTRACT: Groundwater discharge locations along the upper Delaware River, both discrete bank seeps and diffuse streambed upwelling, may create thermal niche environments that benefit the endangered dwarf wedgemussel (Alasmidonta heterodon). We seek to identify whether discrete or diffuse groundwater inflow is the dominant control on refugia. Numerous springs and seeps were identified at all locations where dwarf wedgemussels still can be found. Infrared imagery and custom high spatial resolution fiber-optic distributed temperature sensors reveal complex thermal dynamics at one of the seeps with a relatively stable, cold groundwater plume extending along the streambed/water-column interface during midsummer. This plume, primarily fed by a discrete bank seep, was shown through analytical and numerical heat-transport modeling to dominate temperature dynamics in the region of potential habitation by the adult dwarf wedgemussel.
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dispersion of wedgemussel juveniles.3 The combination of low flows and high temperatures during the summer of 2002 likely caused the documented elevated stress of wedgemussel in the upper Delaware River compared to other native mussels at that time.6 Wedgemussel populations in the upper Delaware River have been shown to select streambed areas with lower shear stress and velocity than average river conditions (hydrologic refuge hypothesis),4 yet these locations may be more prone to stagnation and warming during summer low-flow events, so the ultimate refugia may offer a combination of hydraulic protection and cold GW inflows. In fact, three known wedgemussel beds in the upper Delaware, including that investigated for this study, have shown qualitative evidence of GW seepage (written communication Jeffery Cole and Heather Galbraith, USGS, 2013), but quantitative analysis of thermal anomalies and potential refugia has proven difficult. The emergence of fiber-optic and infrared thermal sensing technologies at a scale and precision applicable to environmental phenomena are particularly useful for examining SW/ GW exchange and thermal refugia7,8 because of the large potential contrast in temperature between water sources.9 Infrared images can be collected by both ground and air-based systems, offering multiscale remote sensing capabilities. However, unless accompanied by in situ temperature measure-
INTRODUCTION Groundwater inflow to small streams, both through discrete bank seeps and diffuse streambed fluid flux, can affect stream ecosystem dynamics by moderating water temperature,1 but the stability of thermal niche environments in large rivers is poorly understood. Thermal refugia in both the water column and shallow streambed provide sanctuary for benthic organisms during extreme and variable temperatures,2 particularly during warm, summer low-flows. The endangered dwarf wedgemussel (Alasmidonta heterodon) is particularly sensitive to temperature compared to other native mussels (written communication Heather Galbraith, USGS, 2012) and survives in patches in the upper Delaware River qualitatively associated with groundwater discharge. The river resource is dam regulated and shared by the states of New Jersey, Pennsylvania, and New York. As a result, numerous management considerations govern dam operation, one of which is providing suitable summer flows to support surviving dwarf wedgemussel, a process that is likely influenced by surface water/groundwater (SW/GW) exchange. Many freshwater mussel populations are in strong decline; a contributing factor to this collapse is anthropogenic stream impoundment and water management practices that can accentuate low-flow events and increase stream temperature.3,4 The critical thermal maximum for mussels and other aquatic life may be related to the decrease in oxygen solubility with water temperature combined with relatively high animal metabolic activity5 (high oxygen demand) with water temperature; therefore, extreme warm events influence the survival of both the dwarf wedgemussel and the host fish that support the This article not subject to U.S. Copyright. Published 2013 by the American Chemical Society
Received: Revised: Accepted: Published: 11423
April 29, 2013 August 15, 2013 September 9, 2013 September 9, 2013 dx.doi.org/10.1021/es4018893 | Environ. Sci. Technol. 2013, 47, 11423−11431
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Figure 1. The location of the field site in Equinunk, Pennsylvania, USA along the upper Delaware River in an area known to support dwarf wedgemussel populations. A snapshot of river water column temperatures interpolated from data collected on day 204 with the high precision handheld probe is shown, with a notable thermal anomaly adjacent to a discrete bank seep. The streambed thermal anomaly at 0.05-m depth (areal extent shown by gray line) was approximately twice as large as the surface water cold plume. The high-resolution temperature sensor locations along Transects A and B are shown.
to modify mixed channel temperature.16,17 Despite these successes, the standard minimum FO-DTS spatial resolution is not fine enough to describe centimeter-scale mixing processes within the water column or to monitor heat transport within the streambed for quantitative fluid-flux modeling. To improve FO-DTS spatial resolution to the centimeter scale, optical fibers are wrapped around a longitudinal core to create a high-resolution temperature sensor (HRTS). This concept has been recently used to record high-resolution temperature profiles in snowpack,8 hyporheic fluid flux in the streambed,18,19 shallow aquifer exchange with the riparian zone,20 and stratification in thermohaline-driven ponds.21 Opportunity exists to deploy HRTS in flowing waters to assess SW/GW mixing processes by utilizing the ambient temperature of GW, which is often colder than SW in summer months, as a tracer. Mixing phenomena are important to ecology because distribution, temperature, and stability of thermal refugia in rivers during warm summer flows may dictate whether stressed benthic animals are able to survive. Furthermore, if HRTS profiles are simultaneously collected in the underlying streambed, a quantitative evaluation of upwelling GW contributions to water column thermal anomalies can be made based on the propagation of the diurnal signal with streambed depth.22,23
ments within the water column [e.g., Loheide and Gorelick, 2006], infrared technology applied to SW/GW exchange is largely restricted to qualitatively identifying GW seepage areas at specific times of the year (commonly summer and winter) when SW/GW temperature contrast is substantial [e.g., Deitchman and Loheide, 200910]. Although some recent work has indicated infrared images alone can be used to quantify seepage along faces under specific conditions,11 only surface “skin” temperatures are measured with infrared; therefore, mixing processes within the water column of large streams cannot be quantified. Fiber-optic distributed temperature sensing (FO-DTS) methods enable the collection of continuous (space and time) thermal data in streams along kilometer-scale fiber-optic cables by using the temperature-dependent optical properties of glass.8,12 FO-DTS systems transmit a light pulse from a control unit down optical fiber and record the timing and counts of Raman backscatter, of which the anti-Stokes frequencies are temperature dependent.13 The timing of backscatter returns determines distance along the fiber, generally to the 0.5-m scale. Longitudinal deployments of FO-DTS cable along the streambed have successfully identified locations of anomalously cold GW inflows14,15 and have been used to quantify these inflows when they are large enough relative to total streamflow 11424
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Table 1. Description of the Methods Used To Collect Thermal and Fluid Flux Data, Including the Typical Time Scales of Implementation and General Strengths and Weaknesses of Each in Reference to This Study method
time scale
Temperature Measurement Methods thermal data logger profiles daysmonths digital thermometer hours infrared camera instantdays fiber-optic HRTS minutesmonths Fluid Flux Measurement Methods seepage meter (manual) minuteshours temperature-based analytical daysmodel (VFLUX) months temperature-based numerical daysmodel (1DTempPro) months
strengths
weakness
long-term record which can be modeled to determine fluid flux, high precision spatially extensive thermal surveys at high precision complete spatial coverage, can be recorded in video format data to be collected at high spatial and temporal resolution throughout water column
point measurements, practical limit on spatial resolution
physical measure of water crossing the streambed interface easy to collect, multidepth thermal records can be converted to fluid flux easy to collect, multidepth thermal records can be converted to fluid flux
labor intensive, only yields information at interface
little temporal information for water, only surface temperature is measured series of point measurements, infrastructure requirements
indirect measure subject to model assumptions, only vertical flux component difficult to simultaneously fit thermal records at many depths and determine changes through time
Figure 2. Panel (A) displays the HRTS Transect A configuration, 2 m out from where the discrete bank groundwater seep enters the river, Panel (B) shows the infrared image of surface temperatures from a subset of the Panel (A) image, the cold water plume entering the river seems to mix by approximately the location of HRTS1A. See Supplemental Video 1 of this process in the Supporting Information.
For this investigation, we installed five vertical HRTS, along two perpendicular transects. Each HRTS extended from the air, through the water column, and into the streambed adjacent to a discrete bank seep along the upper Delaware River. Data collected from these sensors, installed in a zone known to support dwarf wedgemussel survival, was combined with a suite of complementary methods and modeling to evaluate the stability and extent of water column and streambed cold thermal anomalies (potential thermal refugia) and the primary sources of cold water to those anomalies.
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mussel area that showed the highest animal count in recent years was chosen for this study. Thermal Data Collection. Biologists documenting wedgemussel occurrence in the summers of 2008 and 2010 found clustering adjacent to where a bank seep discharges into the river (Figure 1). Thermal data were collected at this site using a variety of tools to evaluate the properties and sources of any cold water anomalies within the water column and shallow streambed. A forward-looking infrared camera (FLIR, FLIR Systems, Inc.), high resolution FO-DTS, discrete temperature loggers in profile, and a hand-held high-precision thermometer provided data over a range of temporal and spatial scales; Table 1 describes the general strengths and limitations of each method used for this study. The resulting data set of complementary thermal observations was used to construct a thorough description of thermal anomalies through time, and to evaluate ecologically relevant variables. Data were collected at various intervals over the period June 27−July 25 2012, or ordinal days 179−207, depending on the requirements and limitations of each individual method. The FLIR camera was used in initial reconnaissance to find the main bank seep at the site, which appeared as a strong cold anomaly compared to surrounding bank material, surface water, and vegetation. The temperature of a discrete bank seep was recorded at its emergence, using i-Button thermal data loggers (Maxim Integrated) run at 0.06 °C resolution. The thermal loggers, which offer the advantage of long-term data collection, recorded from 179−206 (June 27-July 24). Thermal loggers were also installed in the streambed along vertical profiles at
MATERIALS AND METHODS
Site Description. The upper Delaware River drains approximately 4700 km2 of New York and Pennsylvania (Figure 1), forming the boundary between these two states. River discharge in this region is dam-regulated and generally ranges 28−34 m−3 s−1 over July and August (USGS gage: 01427510, Callicoon, New York), with occasional lower flows, which are thought to particularly impact wedgemussel survival.6 Median stream temperature at the USGS gage in the summer months is 21.5 °C, while the peak temperature observed in the record is 30.5 °C at a time of relatively low discharge. In contrast, local GW is approximately 11 °C during the summer months, providing thermal refuge for sensitive aquatic life where it enters the river in discrete zones. Dwarf wedgemussel occurrence has been mapped by the USGS along two stretches of the river in the town of Equinunk since the year 2000, both of which have been qualitatively associated with GW inflow; the 11425
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additional data are collected, such as streambed pressure at multiple locations, but for the temperature-only Delaware data set these parameters could not simultaneously be estimated due to nonuniqueness of parameter sets. First, 1DTempPro was used to calibrate streambed thermal parameters to physically measured fluid flux using a seepage meter (Supporting Information, pg S2). Once the site-specific streambed thermal parameters were estimated, VFLUX was used to model streambed fluid flux (diffuse seepage) based on HRTS data. The calibrated thermal parameters were used for the 1-D temperature amplitude attenuation-based analytical model for determining fluid flux;22 this model was applied to all shallow streambed HRTS data from Transect A. VFLUX was used in part because of the relatively large number of HRTS data points to fit (which is done manually in 1DTempPro), and because the nonideal diurnal signals in the streambed as influenced by water column thermal anomalies above could be filtered using the dynamic harmonic regression technique.28 We then transition back to the 1DTempPro numerical domain, incorporating the VFLUX-based fluid flux estimates, to assess the relative influence of water column thermal anomalies (unmixed cold GW plume) and diffuse streambed GW seepage on potential wedgemussel streambed habitat and thermal refugia (Supporting Information, pg S3). Four hypothetical scenarios were simulated: (A) ambient (similar to average observed data), (B) no streambed GW seepage, ambient coldplume, (C) no cold-plume, ambient streambed GW seepage, and (D) no cold-plume, no streambed GW seepage. By sequentially removing cold GW seepage (fluid flux) through the streambed and cold-plume thermal anomalies in the water column, a simple analysis can be made concerning the importance of these two different GW inflow mechanisms on shallow streambed wedgemussel habitat. The “no plume” simulations were created by exchanging the measured thermal anomalies at the upper boundary condition with the mixed water column time series from HRTS5A. The numerically simulated 1-D thermal profiles were used to create interpolated 2-D cross sections of bed temperature for each simulation series using the ArcMap 10 (Esri) “nearest neighbor” method; this same interpolation method was used to analyze the highprecision point measurements of temperature.
0.01-, 0.04-, and 0.11-m depths and at control points along the deployed FO-DTS cable to aid in calibration. The five custom fiber-optic HRTS were constructed in a manner specified in the Supporting Information (pg S1). The HRTS were gently pounded into predrilled holes in the sediment so they extended vertically across both the river-air and river-streambed interfaces. The sensors were connected in series to create one continuous length of fiber that ran out from and back to the FO-DTS control unit. The HRTS were installed along two transects in the zone of interest: one normal to the bank directly adjacent to the major discrete bank seep for ordinal days 200.5−205.3 (Transect A, Figures 1, 2), and one parallel to the bank for days 205.6−207.4 (Transect B, Figure 1). The intersection of the two transects was 6 m directly offshore from the bank seep so that the location of HRTS2B coincided with HRTS3A (Figures 1, 2). Temperature data (over 500 positions) along each transect were collected at either 4- or 10-min intervals by an Oryx FO-DTS control unit (Sensornet Ltd.), and calibration for thermal drift was performed using a continuously mixed ice-bath monitored dynamically by a Sensornet Ltd. thermistor. The calibration cable length in the ice bath was approximately 30 m as recommended12 and was also used to estimate the realized precision of the FO-DTS data set at 0.07 °C, based on the standard deviation of temperature in the stable bath. Additionally, snapshots of water column temperature just above the streambed interface (N = 107), and at a corresponding location at 0.04-m depth beneath the streambed (N = 107), were collected over ∼2 h on the evening of ordinal day 204 using a high-precision (0.01 °C) digital thermometer (Traceable). Manually operated seepage meters adapted for flowing water24 also were deployed in the area to complement the temperature-based fluid flux estimates described below; replicate measurements were made at each seepage meter with an estimated method-based error of 10%.24 Thermal Data Processing and Modeling. Data collected with the fiber-optic HRTS from the water-column and streambed were independently interpolated along the two transect orientations using MATLAB (Mathworks, Inc.) at resampled 40-min intervals. Interpolated water-column and streambed cross sections were “stitched” together at the streambed interface to create the composite 2-D cross sections of temperature; hence all interpolated cold anomalies that appear within the water column (or streambed) are based on actual measured water column (or streambed) temperatures. The mean, maximum, minimum, and standard deviation of temperature were determined for the 2-D transects in MATLAB. Additionally, the 40-min time-lapse cross sections were strung together to generate a video format that is intuitive to interpret, clearly showing the temporal dynamics of thermal refugia within the streambed and water column. Thermal data from the streambed were modeled in two different ways: (1) numerically, using 1DTempPro,25 a new graphical user interface to the model VS2DH that solves the flow and heat-transport equations in porous media,26 and (2) analytically, using the new MATLAB-based VFLUX program27 that solves approximations of the advection-conductiondispersion equation to calculate vertical fluid flux in shallow, saturated porous media. Each method has its particular strengths and application to the Delaware River data set, and they provide complementary information. It is potentially possible to estimate both the desired thermal parameters and flux magnitudes using numerical modeling alone when
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RESULTS AND DISCUSSION Cold, Plunging Groundwater Plume. A cold, plunging plume of groundwater was observed in the upper Delaware River during midsummer within a larger streambed region known to support a dwarf wedgemussel population, and on the upstream edge of a prominent cluster of wedgemussel individuals found during the 2008 and 2010 animal surveys (written communication Jeffery Cole, USGS, 2013). This GW plume was located adjacent to, and downstream from, a discrete bank seep that was flowing at 129 m3d−1 during the time of the study (Figures 1, 2). The spatial extent of the seep discharge along the bank was indicated by FLIR reconnaissance, clearly showing an area approximately 10 °C colder than the surrounding bank sediments and vegetation (Figure 2, Supplemental Video 1); this easy-to-collect thermal survey allowed the seep to be quickly identified. The FLIR imagery also showed that once water from the cold seep entered the river the surface expression of the plume disappeared by approximately 2.3 m from the bank, near the location of HRTS1A along transect A (Figure 1), with no noticeable downstream thermal influence at the water surface (Figure 2, 11426
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Video 1). FLIR video (Video 1) captured the seep’s interaction with river water and the limited thermal influence on surface temperatures. In contrast to stream surface temperatures, the areal extent of the footprint of the thermal anomaly within the water column just above the streambed interface (instream plume), defined here as at least 1.5 °C colder than the mean mixed stream temperature of 24.1 °C, was 68 m2 at one snapshot in time (day 204, ∼17:30) (gray line in Figure 1). This result, based on an interpolation of high-precision thermal probe data, illustrates the limitations of infrared in evaluating mixing within the water column, further validating the emphasis on surface “skin” temperatures; therefore, caution must be emphasized in using FLIR data to calibrate stream temperature models.29 Further, FLIR data from the water surface are commonly affected by reflection of other infrared sources, as shown here by the “hot” white reflection of trees on the far shore. For this study, the strength of the FLIR data was in reconnaissance, allowing us to clearly identify the discrete cold seep along the bank and discriminate from other similar-looking (but warmer) seeps that did not provide thermal refugia within the river. The plume at the streambed contained temperatures up to 9.5 °C less than the mixed stream temperature, creating a strong potential thermal refuge for thermally stressed wedgemussels. The areal extent of the instream plume is smaller than the underlying streambed plume of 147 m2, defined by a corresponding snapshot of bed temperatures at 0.05-m depth (Figure 1). The larger (approximately 2×) area of the streambed thermal anomaly, defined as at least 1.5 °C colder than unaffected mean bed temperatures of 23.4 °C, indicates the discrete bank seep and cold water plume may not be the only mechanism generating cold bed temperatures. In addition to discrete flow from the seep, we infer from the streambed thermal anomaly the role of diffuse cold GW upwelling in this zone that is known to support wedgemussel populations. The “snapshot” thermal surveys collected with the hand-held probe may be useful for going beyond the surface temperature FLIR images, but temporal mixing dynamics and persistence is difficult to capture with this method (Table 1). FO-DTS in the HRTS configuration allows thermal data to be collected at high spatial and temporal resolution, indicating the stability and permanence of thermal niche habitat, which is ultimately of great importance to ecology. A wealth of data are collected along a HRTS profile that passes through three different ecological compartments: air, water column, and streambed. An example of such a data set is shown in Figure 3 and described here. Diurnal air temperature swings are shown here as the signals of highest variance, and are a primary forcing mechanism of stream and bed thermal variance; the cooling evaporative signal caused by water splashing onto the exposed HRTS is also evident in the plot. The mixed water column above the plume is indicated by multiple (∼10) analogous (overlying) thermal signals. Below the mixed water column temperature time series there are multiple thermal signals that describe the plume, which are reduced in absolute temperature and amplitude from the overlying mixed water, with the coldest signals collected just above the streambed. Finally, the temperature in the streambed is muted and lagged in time compared to temperature in the overlying plume. How the diurnal temperature fluctuations attenuate and shift in time with depth is controlled by the direction and magnitude of flow through the streambed;9,23 hence it is possible using vertical
Figure 3. The 0.014-m spatial resolution HRTS3A data collected over 5 days along a vertical profile installed through the air, water, and streambed domains, exemplifying the wealth of data the new HRTS sensors provide regarding various environmental processes of interest. Each line on the plot depicts temperature at a specific elevation on the HRTS, and the lack of diurnal signal amplitude on day 202 results primarily from a large, cold storm system.
temperature profiles to estimate 1-D fluid flux using either numerical or analytical models.22,25,27,30 Data collected along HRTS Transect A (normal to the streambank, 2 m directly out from the bank seep) were interpolated at 40-min intervals over 5 d to create a 2-D animation (Supplementary Video 2). The video shows the relative stability of the cold water plume within the water column along this axis, even as stage increased by 0.15 m due to a large rainstorm on day 202. Although there is some fluctuation to the depth and length of the plume, a streambed interface area extending to approximately 7 m from the bank is clearly influenced, even though the surficial expression of this colder water disappeared by approximately 2.3 m from the bank (Figure 2). At times the plume is colder than both the streambed below and the mixed water column above, indicating a dominant contribution of the discrete bank seep, which had a mean and standard deviation temperature over the period of 10.8 and 0.07 °C, respectively; the seep is thus much colder than the streambed at 0.55-m depth (mean 16.9, standard deviation 0.2 °C), which presumably represents the diffuse GW source. The relatively stable cold GW plume within the water column of this large river underscores how incomplete mixing of waters must be considered during environmental monitoring of river temperature, often a regulated parameter, using point data as thermal anomalies within the water column may strongly contrast the general thermal regime of the river. Statistical analyses across the A transect plume axis were performed for factors thought to affect wedgemussel lifeprocesses and influence survival; these include maximum, minimum, mean, and standard deviation of temperature in midsummer when mussels may be particularly thermally stressed (Figure 4). Figure 4A shows that maximum temperatures in the upper-streambed horizon (where adult mussels live) are up to 10 °C colder beneath the plume compared to the streambed farther along the transect underlying the mixed water column. The minimum temperature in Figure 4B shows the lateral influence of the colder discrete bank seep to water column temperatures, indicating this input may dominate plume thermal dynamics. The mean temperature shown in Figure 4C confirms the qualitative analysis from Video 2 that 11427
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Video 3). Between days 205 to 207 there is relatively little water-column expression of the cold anomaly as shown in the maximum and mean temperatures in Figures 5A and 5C, respectively, with the plume existing as a thin veneer at the centimeter scale. More dramatically captured is a colder streambed zone generally located where Transect B intersects the plume’s perpendicular axis (Transect A), likely affected by conduction from the adjacent plume as discussed above, again indicating the effect of the plume on streambed temperature and mussel habitat extends beyond the obvious surface expression. The minimum transect temperatures in Figure 5B shows cold anomalies extending at least 10 m downstream of the plume axis in what seems to be a topographic low, where cold, dense water may temporarily collect; Video 3 shows this collection of cold water to be short-lived. These data indicate thermal refugia may be partially controlled by streambed topography changes on the order of centimeters, even in this large river. Although all of the methods presented above yield important information regarding GW discharge to the Delaware River, the emerging high-resolution fiber-optic method provides an unprecedented description of the characteristics of thermal refugia. The time-lapse 2-D mapping of the cold water plume, which can be displayed in a user-friendly video format, not only contains valuable information regarding the fine-scale details of thermal mixing for research purposes but also makes this information visually accessible to the general public. This combination of good science and presentation quality is needed to develop public interest in the protection of ecological niches that support the survival of endangered aquatic species. Plume Sources. The plunging plume of cold water observed within the water column is fed by GW discharge into the river; the plunging behavior is caused by density differentials (approximately 0.2%) between the unmixed plume and the relatively warm river water. Thermal data collected with the HRTS and hand-held probe indicated two mechanisms of GW discharge at this location: a discrete bank seep and diffuse GW upwelling through the streambed. The HRTS data were used to quantitatively evaluate which mechanism is the primary source of the observed cold-water plume by using a 1-D analytical thermal model to determine vertical streambed fluid flux. There is a clear pattern of GW upwelling to the river, noted by (-) sign convention, for the four profiles closest to shore (HRTS1A‑4A); upwelling flux ranged from −0.12 to −0.35 md−1 and generally diminished with increasing distance from shore, until shallow downwelling is observed along HRTS5A, 10 m from the bank. This directional switch from GW upwelling
Figure 4. Thermal time-series statistics over 5 days from the water column and streambed (interface is the black line) over a 2-D crosssection along Transect A describing: Panel (A) maximum temperature, (B) minimum temperature, (C) mean temperature, and (D) standard deviation. Elevation is expressed as 25X.X, where the X is replaced by the corresponding value on the Y-axis.
the plume generally affects water column temperatures up to 7 m from the bank, while the streambed below shows a similar pattern. All three of these metrics speak to the stability of the GW-induced thermal refugia in this large river, even as flow conditions changed, and may explain why wedgemussels seek out this specific area. Finally, Figure 4D shows how temperature variance is much lower within the plume, whereas mixing between warm and cold waters in the upper-water column adjacent to where the bank seep enters the river yields the highest thermal variance. The variance in the streambed is reduced relative to the stream and with depth as expected9 but appears to be more greatly dampened close to the plume compared to the farthest reaches of the profile (9.7−10 m); thus, the influence of GW discharge on streambed temperature may extend beyond the extent of the water column cold plume via conduction, partially explaining why the streambed thermal anomaly is larger. Thermal stability is thought to encourage mussel survival,3 so the GW inflow at this location may provide thermal variance refugia as well as cold-water thermal refugia. The HRTS were reorientated over Transect B for 2 d, crossing at the outer reaches of plume influence as observed along Transect A over the previous 5 d (Figure 5, Supplemental
Figure 5. Thermal time-series statistics over 1.8 days from the water column and streambed (interface is the black line) over a 2-D cross-section along Transect B, oriented normal to Transect A, describing the following: Panel (A) maximum temperature, (B) minimum temperature, (C) mean temperature; standard deviation was not calculated due to the shorter time period. Elevation is expressed as 25X.X, where the X is replaced by the corresponding value on the Y-axis. Note, the location of HRTS2B coincides with HRTS3A of Transect A. 11428
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closer to shore to hyporheic downwelling farther into the steam agrees with adjacent seepage meter data, and likely describes a transition in control on shallow streambed fluid pressure from GW regional discharge to local bedform−induced exchange. When the mean GW upwelling rates along Transect A are integrated over the 2 m × 9 m swath of streambed that might be assumed to contribute directly to the plume, the resulting approximate 4.5 m3 d−1 of diffuse GW inflow to the water column is much less than the 129.0 m3 d−1determined to be flowing from the discrete bank seep through repeat direct measurement. As discussed above, the seep water (10.8 °C) was much colder over this time period than the diffuse GW flow (16.9 °C); therefore, we infer that the cold, plunging water column plume is dominated by the discrete bank source. The 1D analytical models used to determine upwelling flux have many potential sources of error such as the violation of model assumptions,31,32 in particular the expected existence of lateral GW flow,19 but the disparity in magnitude of diffuse seepage estimates and discrete discharge here clearly indicates the bank seep is of greatest volumetric discharge. If the wedgemussel populations in the upper Delaware River are supported in part by thermal refugia within the water column, which is siphoned through the animal during feeding and provides oxygen, then river stage should be maintained at a level which supports continued direct hydrologic connection between bank seeps and the water column. Further, the importance of bank seeps, and their distinct thermal signature to infrared during summer months, encourages a broader reconnaissance of the river corridor using a thermal camera to perhaps locate and protect currently unknown mussel clusters. Interestingly, the accumulation of fine silt sediments was qualitatively associated with seep locations, but the wedgemussel is thought to prefer more stable substratum;4 this may explain why mussel surveys have tended to show individuals on the edge and downstream of the plume-affected areas where the streambed is larger grained, in essence the wedgemussel is likely optimizing hydraulic, thermal, and morphologic parameters simultaneously. The strongly differing GW temperatures between the relatively warmer diffuse flow and colder discrete flow may indicate fundamental source differences. Alternatively, they may be of the same source, but the diffuse discharge is affected by warm conduction from the surface as it flows more slowly through the streambed. Assuming an effective porosity of 0.2, the residence time of diffuse GW in the upper 1 m of bank/ streambed is at least 0.5 d, compared to seconds for the discrete source, which better reflects the original GW source temperature of ∼11 °C. The general chemical signatures of the two GWs based on major-ion chemistry, discussed in detail in the Supporting Information (pg S3), were similar, indicating a single initial GW source which is likely controlled by the regional geology. Thermal Control on Streambed Mussel Habitat. Despite the cold water column refugia being dominated by discrete seep discharge, relatively cold diffuse flow upward through the streambed could potentially still affect streambed temperatures where the adult mussels live (mussel depth = ∼0.0−0.04 m). To tease apart the influence of conduction from the cold overlying water column from GW upwelling through the streambed, numerical simulations were performed using 1DTempPro. Model results are shown in Figure 6 and Supplemental Figure 1. For Scenario 1 (discussed above), observed streambed temperature was simulated, with temperatures at the mussel depth showing close agreement with mean
Figure 6. Four simulated temperature cross sections of the streambed along Transect A created by turning off advective transport (no-flux) and/or changing the upper boundary condition to mixed stream temperature (no-plume) shown here by panel: (A) Ambient (similar to average observed data), (B) No streambed GW seepage, ambient cold-plume, (C) No cold-plume, ambient streambed GW seepage, and (D) No cold-plume, no streambed GW seepage. Elevation is expressed as 25X.X, where the X is replaced by the corresponding value on the Yaxis.
measured temperatures (Figure 6A, Supplemental Figure 1). When the diffuse GW seepage to the river is turned off in Scenario 2 (i.e., conduction-only heat transport), there is relatively little change in temperature at the mussel depth. However, when upwelling GW is restored in Scenario 3, but the cold plume is removed from the overlying water column, temperatures increase at the mussel depth considerably. Finally, when upwelling is also removed from the no-plume condition in Scenario 4, the shallow streambed warms only slightly but warms greatly at depth. Based on the numerical modeling results, it is evident that directly under the plume, the overlying cold anomaly has the greatest impact on shallow streambed temperatures and potential adult mussel habitat. Although the modeling results do indicate that diffuse GW flow has a strong influence on streambed temperatures at greater depths (approximately >0.06 m), which may be important to other benthic organisms, and to the mussels themselves at early life stages. Additionally, diffuse GW flow may help keep the streambed saturated in the mussel zone when river stage drops drastically during periodic events, promoting wedgemussel survival through extreme low-flow events. The wedgemussel in the upper Delaware River has been shown to preferentially select protected areas with low shear stress and velocity relative to the main channel,4 but a constant 11429
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(3) Galbraith, H. S.; Blakeslee, J.; Lellis, W. A. Recent thermal history influences thermal tolerance in freshwater mussel species (Bivalvia:Unionoida). Freshwater Sci. 2012, 31, 83−92. (4) Maloney, K. O.; Lellis, W. A.; Bennett, R. M.; Waddle, T. J. Habitat persistence for sedentary organisms in managed rivers: the case for the federally endangered dwarf wedgemussel (Alasmidonta heterodon) in the Delaware River. Freshwater Biol. 2012, 57, 1315− 1327. (5) Portner, H. O.; Dimock, R. V. J. Climate change effects marine fishes through the oxygen limitation of thermal tolerance. Science 2007, 315, 95−97. (6) Cole, J. C.; Townsend, P. A.; Eshleman, K. N. Predicting Flow and Temperature Regimes at Three Alasmidonta heterodon Locations in the Delaware River; 2008; p 66. (7) Loheide, S. P.; Gorelick, S. M. Quantifying stream-aquifer interactions through the analysis of remotely sensed thermographic profiles and in situ temperature histories. Environ. Sci. Technol. 2006, 40, 3336−3341. (8) Selker, J. S.; Thévenaz, L.; Huwald, H.; Mallet, A.; Luxemburg, W.; van de Giesen, N.; Stejskal, M.; Zeman, J.; Westhoff, M.; Parlange, M. B. Distributed fiber-optic temperature sensing for hydrologic systems. Water Resour. Res. 2006, 42, 1−8. (9) Constantz, J. Heat as a tracer to determine streambed water exchanges. Water Resour. Res. 2008, 44, 1−20. (10) Deitchman, R. S.; Loheide, S. P. Ground-based thermal imaging of groundwater flow processes at the seepage face. Geophys. Res. Lett. 2009, 36, 1−6. (11) Pandey, P.; Gleeson, T.; Baraer, M. Toward quantifying discrete groundwater discharge from frozen seepage faces using thermal infrared images. Geophys. Res. Lett. 2013, 40, 123−127. (12) Tyler, S. W.; Selker, J. S.; Hausner, M. B.; Hatch, C. E.; Torgersen, T.; Thodal, C. E.; Schladow, S. G. Environmental temperature sensing using Raman spectra DTS fiber-optic methods. Water Resour. Res. 2009, 45, 1−11. (13) Dakin, J. P.; Pratt, D. J.; Bibby, G. W.; Ross, J. N. Distributed optical fibre raman temperature sensor using a semiconductor light source and detector. Electron. Lett. 1985, 21, 569−570. (14) Moffett, K. B.; Tyler, S. W.; Torgersen, T.; Menon, M.; Selker, J. S.; Gorelick, S. M. Processes controlling the thermal regime of saltmarsh channel beds. Environ. Sci. Technol. 2008, 42, 671−676. (15) Lowry, C. S.; Walker, J. F.; Hunt, R. J.; Anderson, M. P. Identifying spatial variability of groundwater discharge in a wetland stream using a distributed temperature sensor. Water Resour. Res. 2007, 43, 1−9. (16) Briggs, M. A.; Lautz, L. K.; McKenzie, J. M. A comparison of fibre-optic distributed temperature sensing to traditional methods of evaluating groundwater inflow to streams. Hydrol. Processes 2012, 26, 1277−1290. (17) Selker, J.; van de Giesen, N. C.; Westhoff, M.; Luxemburg, W.; Parlange, M. B. Fiber optics opens window on stream dynamics. Geophys. Res. Lett. 2006, 33. (18) Vogt, T.; Schneider, P.; Hahn-Woernle, L.; Cirpka, O. A. Estimation of seepage rates in a losing stream by means of fiber-optic high-resolution vertical temperature profiling. J. Hydrol. 2010, 380, 154−164. (19) Briggs, M. A.; Lautz, L. K.; McKenzie, J. M.; Gordon, R. P.; Hare, D. K. Using high-resolution distributed temperature sensing to quantify spatial and temporal variability in vertical hyporheic flux. Water Resour. Res. 2012, 48, 1−16. (20) Vogt, T.; Schirmer, M.; Cirpka, O. A. Investigating riparian groundwater flow close to a losing river using diurnal temperature oscillations at high vertical resolution. Hydrol. Earth Syst. Sci. 2012, 16, 473−487. (21) Suárez, F.; Aravena, J. E.; Hausner, M. B.; Childress, A. E.; Tyler, S. W. Assessment of a vertical high-resolution distributed-temperaturesensing system in a shallow thermohaline environment. Hydrol. Earth Syst. Sci. 2011, 15, 1081−1093. (22) Hatch, C. E.; Fisher, A. T.; Revenaugh, J. S.; Constantz, J.; Ruehl, C. Quantifying surface water-groundwater interactions using
source of cold GW in these more stagnant areas may also be necessary for the survival of a species that has been pushed to the brink. Emerging thermal sensing methods, coupled with models of heat transport, have made it possible to evaluate the stability and extent of potential thermal refugia for dwarf wedgemussel in a zone of endangered mussel habitation and to assess the relative contributions between discrete bank GW seeps and diffuse GW upwelling through the streambed. The particular relevance of riparian seeps to creating niche habitat may have important management considerations for this large, damregulated river, and the thermal signature of these seeps can serve as an important indicator of presently unknown dwarf wedgemussel habitat.
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ASSOCIATED CONTENT
S Supporting Information *
Supplemental Text: This text describes in greater technical detail: pg S1) High-Resolution Temperature Sensor Construction and Deployment, pg S2) Calibration of Thermal Parameters to Seepage Meter Data, pg S2) Numerical Models to Assess the Controls on Wedgemussel Thermal Refugia, and pg S3) Discrete Seep and Diffuse Groundwater Chemistry. Figure S1 (appended to supplemental text). Measured and modeled thermal statistics from the 0.03 m depth which is generally the extent of adult mussel bed penetration, shown here the panels are the (A) mean, (B) standard deviation, (C) maximum, and (D) minimum. Supplemental videos: (1) Infrared animation of the discrete bank seep flowing into the Delaware River; (2) Interpolated animation of the HRTS water column and streambed data along Transect A at 40-min intervals; and (3) Interpolated animation of the HRTS water column and streambed data along Transect B at 40-min intervals. This material is available free of charge via the Internet at http://pubs.acs.org.
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AUTHOR INFORMATION
Corresponding Author
*Phone: (860) 487-7402 x19. E-mail:
[email protected]. Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS We thank Heather Galbraith, Jeffery Cole, Carrie Blakeslee, Celicia Boyden, Chris Peterson, Amanda Lanning, Eric White, Don Hamilton, and Sean Buckley for assistance in the field. The Laura Lautz Lab at Syracuse University provided material support instrumental to this study. This work was funded by U.S. Fish and Wildlife Service, with additional support from the U.S. Geological Survey Toxic Substance Hydrology and Groundwater Resources Programs. 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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