Geology topics

Research about Maryland

Source-linked reports with geographic coverage including Maryland.

At least 91 records · Page 5Linked to original sources

USGS2020

Quantifying background nitrate removal mechanisms in an agricultural watershed with contrasting subcatchment baseflow concentrations

Numerous studies have documented the linkages between agricultural nitrogen loads and surface water degradation. In contrast, potential water quality improvements due to agricultural best management practices are difficult to detect because of the confounding effect of background nitrate removal rates, as well as the groundwater-driven delay between land surface action and stream response. To characterize background controls on nitrate removal in two agricultural catchments, we calibrated groundwater travel time distributions with subsurface environmental tracer data to quantify the lag time between historic agricultural inputs and measured baseflow nitrate. We then estimated spatially distributed loading to the water table from nitrate measurements at monitoring wells, using machine learning techniques to extrapolate the loading to unmonitored portions of the catchment to subsequently estimate catchment removal controls. Multiple models agree that in-stream processes remove as much as 75% of incoming loads for one subcatchment while removing <20% of incoming loads for the other. The use of a spatially variable loading field did not result in meaningfully different optimized parameter estimates or model performance when compared with spatially constant loading derived directly from a county-scale agricultural nitrogen budget. Although previous studies using individual well measurements have shown that subsurface denitrification due to contact with a reducing argillaceous confining unit plays an important role in nitrate removal, the catchment-scale contribution of this process is difficult to quantify given the available data. Nonetheless, the study provides a baseline characterization of nitrate transport timescales and removal mechanisms that will support future efforts to detect water quality benefits from ongoing best management practice implementation.

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USGS2020

Mapping forested wetland inundation in the Delmarva Peninsula, USA: Use of deep learning model

The Delmarva Peninsula in the eastern United States is dominated by thousands of small, forested depressional wetlands that are highly sensitive to climate change and climate variability but provide critical ecosystem services. Due to the relatively small size of these depressional wetlands and occurrence under forest canopy cover, it is very challenging to map their inundation status based on existing remote sensing data and traditional classification approaches. In this study, we applied a state-of-the-art deep semantic segmentation network to map forested wetland inundation in the Delmarva region by integrating leaf-off Worldview-3 (WV3) multispectral data with fine resolution light detection and ranging (lidar) intensity and topographic data, including digital elevation model (DEM) and topographic wetness index (TWI). Wetland inundation maps generated from lidar intensity were used for model calibration and validation. The wetland inundation map results were also validated by field polygons and compared to the U.S. Fish and Wildlife Service National Wetlands Inventory (NWI) geospatial dataset and a random forest output from a previous study. Our results demonstrate that our deep learning model can accurately determine inundation status with an overall accuracy of 95% against field data and high overlap with lidar mapped inundation. The integration of topographic metrics in deep learning model can improve classification accuracy in depressional wetlands. This study highlights the great potential of deep learning models to map wetland inundation through use of high resolution optical and lidar remote sensing datasets.

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USGS2020

Pavement alters delivery of sediment and fallout radionuclides to urbanstreams

Sediment from urban impervious surfaces has the potential to be an important vector for contaminants, particularly where stormwater culverts and other buried channels draining large impervious areas exit from underground pipes into open channels. To better understand urban sediment sources and their relation to fallout radionuclides, we collected samples of rainfall, urban sediment (pavement sediment, topsoil), streambank sediment, and fluvial sediment (suspended sediment and bed sediment) for 7 Be, 210 Pb ex , and 137 Cs analysis. The results indicate that each rainfall event tags pavement sediment with elevated activities of 7 Be and 210 Pb ex such that runoff from impervious surfaces in the buried channel part of the stream network contains the highest activities. Pavement sediment, because it is characteristically a thin veneer, has a small mass to rainwater ratio resulting in a greater tagging of 7 Be and 210 Pb ex activity than does topsoil on a per gram basis. An unmixing model indicated that suspended-sediment samples collected at the culvert outlet from the buried-channel network are from pavement sediment sources (45 ± 25%) with a smaller component of topsoil (22 ± 19%), and a component from streambanks (32 ± 35%) that we infer to be older channel material and subsoil eroded from within the culvert system. Downstream from the culvert, suspended sediment collected from the open-channel parts of the stream had 7 Be and 210 Pb ex activities that were substantially reduced by the contribution of sediment from streambanks (57 ± 15%), with pavement contributions decreasing to 15 (±9%) and topsoil contributing 28 (±7%). The results highlight the utility of 7 Be, 210 Pb ex , and 137 Cs as tracers of urban sediment sources, resulting in a unique radionuclide signature for urban watersheds compared to other sediment-source settings.

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USGS2020

A within-season approach for detecting early crop stage of corn and soybean using high temporal and spatial resolution imagery

Crop emergence is a critical stage for crop development and crop growth modeling. Mapping crop emergence using remote sensing data is challenging. Previous remote sensing phenology algorithms showed that crop stages could be detected around the V3-V4 (3 to 4 established leaves) vegetative stage. Traditional approaches have a strong assumption regarding the temporal evolution of plant growth and normally require a complete growth period of observations to define seasonal changes. Most approaches were not designed for the within-season mapping in the early growing season. In the current paper, we developed a new within-season emergence (WISE) approach to mapping crop green-up date using satellite observations during early growth stages. The approach was first optimized using high spatiotemporal resolution (10 m, 2 day revisit) imagery from the Vegetation and Environment monitoring New MicroSatellite (VENµS) research mission, and assessed using ground observations of early crop growth stages (emergence VE and one leaf V1 stages for corn, and emergence VE and unifoliolate VC stages for soybeans) collected over the Beltsville Agricultural Research Center (BARC) experimental fields in Beltsville, MD during the 2019 growing season. Results show that early crop growth stages can be reliably detected at sub-field scale about two weeks after crop emergence. The remote sensing green-up dates were about 4-5 days after crop emergence on average. Coefficients of determination (R2) between green-up dates and the mid-point dates of the early growth stages were above 0.90. The mean absolute differences, standard deviations, and root mean square errors comparing to the early growth stage mid-point dates were within six days. The maximum differences were within ±10 days across all fields. The WISE approach was assessed using operational Sentinel-2 data (10 m, 5 day revisit) in BARC. The detected green-up dates from Sentinel-2 were found close to VENµS results. Some fields were not detected due to the lack of observations during emergence dates. For independent evaluation, the WISE approach was applied over an agricultural watershed on the Maryland Eastern Shore using both VENµS and the harmonized Landsat and Sentinel-2 (HLS) data (30 m, 3-4 day revisit). The green-up dates were compared with crop progress reports of crop emergence dates from the National Agricultural Statistics Service (NASS) at the state-level. The WISE -detected green-up dates at the regional scale are within VE stage ranges but slightly earlier than NASS crop progress reports at the state-level. The WISE approach uses remote sensing observations during the early crop growth stages and has potential for operational application within the season using Sentinel-2 and HLS data.

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USGS2020

Using NASA Earth observations and Google Earth Engine to map winter cover crop conservation performance in the Chesapeake Bay watershed

Winter cover crops such as barley, rye, and wheat help to improve soil structure by increasing porosity, aggregate stability, and organic matter, while reducing the loss of agricultural nutrients and sediments into waterways. The environmental performance of cover crops is affected by choice of species, planting date, planting method, nutrient inputs, temperature, and precipitation. The Maryland Department of Agriculture (MDA) oversees an agricultural cost-share program that provides farmers with funding to cover costs associated with planting winter cover crops, and the U.S. Geological Survey (USGS) and the U.S. Department of Agriculture-Agricultural Research Service (USDA-ARS) have partnered with the MDA to develop satellite remote sensing techniques for measuring cover crop performance. The MDA has developed the capacity to digitize field boundaries for all fields enrolled in their cover crop programs (>26,000 fields per year) to support a remote sensing performance analysis at a statewide scal,e and has requested assistance with the associated imagery processing from the National Aeronautics and Space Administration (NASA). Using the Google Earth Engine (GEE) cloud computing platform, scripts were developed to process Landsat 5/7/8 and Harmonized Sentinel-2 imagery to measure winter cover crop performance. We calibrated cover crop performance models using linear regression between satellite vegetation indices and USGS / USDA-ARS field sampling data collected on Maryland farms between 2006 and 2012 (1298 samples). Satellite-derived Normalized Difference Vegetation Index (NDVI) values showed significant correlation with the natural logarithm of cover crop biomass ( p ≤0.01, R 2 = 0.56) and with observed percent vegetative ground cover (p ≤0.01, R 2 = 0.68). The GEE scripts were used to composite seasonal maximum NDVI values for each enrolled cover crop field and calculate performance metrics for the winter and spring seasons of three enrollment years (2014–15, 2015–16, and 2017–18) for four Maryland counties. Results from winter 2017–18 demonstrate that rye and barley fields had higher biomass than wheat fields, and that early planting, along with planting methods that increase seed-soil contact, increased performance. The processing capabilities of GEE will support the MDA in scaling up remote sensing performance analysis statewide, providing information to evaluate the environmental outcomes associated with various agronomic management strategies. The tool can be modified for different seasonal cutoffs, utilize new sensors to capture phenology in winter and spring, and scale to larger regions for use in adaptive management of winter cover crops planted for environmental benefit.

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USGS2020

Fluxes of agricultural nitrogen and metolachlor metabolites are highly correlated in a first order stream in Maryland, USA

Nitrogen pollution in watersheds containing significant cropland area is generally problematic. Conservation practices intended to reduce nitrate-N (NO3--N) export from watersheds are being implemented by many regions without necessary tools to assess effectiveness of these abatement tools. A commonly used herbicide metolachlor degrades in the vadose zone of croplands to form two metabolites (metolachlor ethane sulfonic acid (MESA) and metolachlor oxanilic acid (MOXA)) which are both highly soluble in soils. Study of metabolite fates in a first order watershed provided evidence that transport of these metabolites to stream water is highly correlated to transport of the agricultural NO3--N that also forms in the cropland vadose zone. Linear models describing the relationships of stream flux of MESA and MOXA to NO3--N flux generated goodness of fit values of 0.93 and 0.82 respectively. These findings support a conclusion that both MESA and MOXA act as excellent transport analogs of NO3- and become strongly correlated to agricultural NO3--N leaching from the cropland vadose zone. Moreover, their use as conservative tracers in agricultural watersheds can provide valuable information concerning movement and fate of agricultural nitrogen at watershed scales of observation.

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USGS2020

Potentiometric surface maps of selected confined aquifers in southern Maryland and Maryland's eastern shore, 2019

This report presents potentiometric-surface maps of the Aquia and Magothy aquifers and the Upper Patapsco, Lower Patapsco, and Patuxent aquifer systems using water levels measured during the fall season of 2019. The potentiometric surface maps show water levels ranging from 56 feet above sea level to 163 feet below sea level in the Aquia aquifer, from 87 feet above sea level to 119 feet below sea level in the Magothy aquifer, from 114 feet above sea level to 120 feet below sea level in the Upper Patapsco aquifer system, from 136 feet above sea level to 174 feet below sea level in the Lower Patapsco aquifer system, and from 168 feet above sea level to 184 feet below sea level in the Patuxent aquifer system. Cones of depression have formed around locations with significant aquifer withdrawals. The Aquia aquifer has depressed water levels around well fields at Lexington Park, Solomons Island, and central Talbot County. Cones of depression have formed in the Magothy aquifer around well fields at Waldorf, Arnold, and Easton. The Upper Patapsco aquifer system has depressed water levels around well fields in the Annapolis-Arnold area, Waldorf, the Lexington Park-Leonardtown area, and at Easton. The Lower Patapsco aquifer system has depressed water levels around well fields at Severndale, Broad Creek, Arnold, and Crofton Meadows as well as in central and western Charles County. Cones of depression have formed in the Patuxent aquifer system around well fields at Dorsey Road, Crofton, Arnold, northwestern Charles County, and at the Chalk Point power plant.

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USGS2019

Changes in event‐based streamflow magnitude and timing after suburban development with infiltration‐based stormwater management

Green stormwater infrastructure implementation in urban watersheds has outpaced our understanding of practice effectiveness on streamflow response to precipitation events. Long‐term monitoring of experimental urban watersheds in Clarksburg, Maryland, USA, provided an opportunity to examine changes in event‐based streamflow metrics in two treatment watersheds that transitioned from agriculture to suburban development with a high density of infiltration‐focused stormwater control measures (SCMs). Urban Treatment 1 has predominantly single family detached housing with 33% impervious cover and 126 SCMs. Urban Treatment 2 has a mix of single family detached and attached housing with 44% impervious cover and 219 SCMs. Differences in streamflow‐event magnitude and timing were assessed using a before‐after‐control‐reference‐impact design to compare urban treatment watersheds to a forested control and an urban control with detention‐focused SCMs. Streamflow and precipitation events were identified from 14 years of sub‐daily monitoring data with an automated approach to characterize peak streamflow, runoff yield, runoff ratio, streamflow duration, time to peak, rise rate, and precipitation depth for each event. Results indicated that streamflow magnitude and timing were altered by urbanization in the urban treatment watersheds, even with SCMs treating 100% of the impervious area. The largest hydrologic changes were observed in streamflow magnitude metrics, with greater hydrologic change in Urban Treatment 2 compared to Urban Treatment 1. While streamflow changes were observed in both urban treatment watersheds, SCMs were able to mitigate peak flows and runoff volumes compared to the urban control. The urban control had similar impervious cover to Urban Treatment 2, but Urban Treatment 2 had more than twice the precipitation depth needed to initiate a flow response and lower median peak flow and runoff yield for events less than 20 mm. Differences in impervious cover between the Urban Treatment watersheds appeared to be a large driver of differences in streamflow response, rather than SCM density. Overall, use of infiltration‐focused SCMs implemented at a watershed‐scale did provide enhanced attenuation of peak flow and runoff volumes compared to centralized‐detention SCMs.

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USGS2019

Comparisons of stereological and other approaches for quantifying macrophage aggregates in piscine spleens

Macrophage aggregates (MA s) are focal accumulations of pigmented macrophages in the spleen and other tissues of fish. A central role of MA s is the clearance and destruction of degenerating cells and recycling of some cellular components. Macrophage aggregates also respond to chemical contaminants and infectious agents and may play a role in the adaptive immune response. Tissue damage or physiological stress can result in increased MA accumulation. As a result, MA s may be sensitive biomarkers of environmental stress in fish. Abundance of MA s in tissues has been reported in a variety of ways—most commonly as density, mean size, and relative area—but the utility of these estimates has not been compared. In this study, four different types of splenic MA abundance estimates (abundance score, density, relative area, and total volume) were compared in two fish populations (Striped Bass Morone saxatilis and White Perch M. americana ) with a wide range in ages. Stereological estimates of total volume indicated an increase in MA abundance with spleen volume, which generally corresponded to fish age, and with splenic infections (mycobacteria or trematode parasites). Abundance scores were generally limited in the ability to detect changes in MA abundance by these factors, whereas density estimates were greatly influenced by changes in spleen volume. In some instances, densities declined while the total volume of MA s and spleen volume increased. Experimentally induced acute stress resulted in a decrease in spleen volume and an increase in MA density, although the total volume of MA s remained unchanged. Relative area estimates accounted for the size and number of MA s but not for changes in organ volume. Total volume is an absolute measure of MA abundance irrespective of changes in organ volume or patterns of accumulation and may provide an improved means of quantifying MA s in the spleens of fish.

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USGS2019

Mapping crop residue by combining Landsat and WorldView-3 satellite imagery

A unique, multi-tiered approach was applied to map crop-residue cover on the Eastern Shore of the Chesapeake Bay, USA. Field measurements of crop-residue cover were used to calibrate residue mapping using shortwave infrared (SWIR) indices derived from WorldView-3 imagery for an 8-km x 8-km footprint. The resulting map was then used to calibrate and subsequently classify residue mapping of Landsat imagery at a larger spatial resolution and extent. This manuscript describes how the method was applied and presents results in the form of crop-residue cover maps, validation statistics, and quantification of conservation tillage implementation in the agricultural landscape. Overall accuracy for maps derived from Landsat 7 (ETM+) and Landsat 8 (OLI) were comparable at roughly 92% (+/- 10%). Tillage class specific accuracy was also strong and ranged from 75% to 99%. The approach, which employed a 12-band image stack of six tillage spectral indices and six individual Landsat bands, was shown to be adaptable to variable soil-moisture conditions: under dry conditions (Landsat 7, May 14, 2015) the majority of predictive power was attributed to SWIR indices, and under wet conditions (Landsat 8, May 22, 2015) single band reflectance values were more effective at explaining variability in residue cover. Summary statistics of resulting tillage class occurrence matched closely with conservation tillage implementation totals reported by Maryland and Delaware to the Chesapeake Bay Program. This hybrid method combining WorldView-3 and Landsat imagery sources shows promise for monitoring progress in the adoption of conservation tillage practices and for describing crop-residue outcomes associated with a variety of agricultural management practices.

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USGS2019

Hydrologic study at Farm Creek Marsh, Dorchester County, Maryland, from April 2015 to April 2016

In 2015, the U.S. Geological Survey began a 1-year hydrologic study to investigate the extent and cause of inundation at Farm Creek Marsh, in Dorchester County, Maryland. In combination with a tide and precipitation gage, a representative section of the marsh was instrumented with surface-water monitors and shallow groundwater piezometers to capture the spatial and temporal extent of inundation. In addition, water-quality data (major ions and nutrients) were collected to help discern the cause of inundation. Results indicate that during the year-long study, all sites were periodically inundated, ranging from a total of 108 days to the entire study period of 353 days. The depth of inundation was typically between 0 and 0.2 feet (ft) (above land surface), with the exception of large storm events. Less than 0.5 ft of elevation was the difference between a site being inundated during the entire study period of 353 days and a site being inundated for 36 consecutive days out of 108 total days of inundation during the study period. Water-quality data showed a large difference in pH between marsh surface water (6.1 to 6.9 standard pH units) and shallow groundwater (3.0 to 3.6 standard pH units), with differences also observed in concentrations of silica, iron, manganese, and potassium. Collectively, the combination of water-quality, hydrologic, and soils data indicate that inundation is caused by tide and storm events rather than groundwater discharge.

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USGS2019

River‐valley morphology, basin size, and flow‐event magnitude interact to produce wide variation in flooding dynamics

Inundation dynamics are a key driver of ecosystem form and function in river‐valley bottoms. Inundation itself is an outcome of multi‐scalar interactions and can vary strongly within and among river reaches. As a result, establishing to what degree and how inundation dynamics vary spatially both within and among river reaches can be challenging. The objective of this study was to understand how river‐valley morphology, basin size, and flow‐event magnitude interact to affect inundation dynamics in river‐valley bottoms. We used 2D hydraulic models to simulate inundation in four river reaches from Maryland's Piedmont physiographic province, and qualitatively and quantitatively summarized within‐ and among‐reach patterns of inundation extent, duration, depth, shear stress, and wetting frequencies. On average, reaches from confined valley settings experienced less extensive flooding, shorter durations and shallower depths, stronger gradients of maximum shear stress, and relatively infrequent wetting compared to reaches from unconfined settings. These patterns were generally consistent across flow‐event magnitudes. Patterns of within‐reach flooding across event magnitudes revealed complex interactions between hydrology and surface topography. We concluded that valley morphology had a greater impact on flooding patterns than basin size: Inundation patterns were more consistent across reaches of similar morphology than similar basin size, but absolute values of inundation characteristics varied between large and small basins. Our results showed that the manifestation of out‐of‐bank flows in valley floors can vary widely depending on geomorphic context, even within a single physiographic province, which suggests that hydrologic and hydraulic conditions experienced on the valley floor may not be well represented by existing hydrologic metrics derived from discharge data alone. We thus support the notion that 2D hydraulic models can be useful hydrometric tools for cross‐scale investigations of floodplain ecosystems.

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USGS2019

The effects of restored hydrologic connectivity on floodplain trapping vs. release of phosphorus, nitrogen, and sediment along the Pocomoke River, Maryland USA

River channelization and artificial levees have decreased the hydrologic connectivity of river-floodplain systems around the world. In response, restoration through enhancing connectivity has been advocated to improve the functions of floodplains, but uncertain benefits and the possibility of phosphate release from re-flooded soils has limited implementation. In this study, we measured change in floodplain P, N, and sediment mass balances after restoration along channelized reaches in the lowland Pocomoke River, Maryland USA. Two floodplains (one headwater, one mainstem) restored through partial levee breaches were compared to two additional mainstem floodplains (one natural unchannelized, one unrestored channelized). Potential soluble reactive P (SRP) release from soil cores during experimental laboratory floods; soil P, Fe, and Al fractionation; and deposition and P and N content of sediment were measured before and after the restoration period, as well as in situ inputs and release of SRP and dissolved inorganic N from soils after restorations. Potential SRP release, during both the before and after restoration period, was greatest at the channelized mainstem and restored mainstem sites, lower at the restored headwater site, and small at the natural mainstem site. Both restored sites had smaller potential SRP release after restoration compared to before restoration. In situ SRP release slightly exceeded inputs to soils at connected sites during the post-restoration period, with less net release at the restored sites compared to the natural mainstem site. The magnitude of gross and net SRP release from soils in the field was smaller than, and uncorrelated with, potential SRP release estimated from laboratory experimental floods. Gross soil SRP release rates in the field were predictable using the ratio of soil oxalate-extractable P/Al. Sedimentation inputs of P and N increased at all sites during the post-restoration period, with rates at restored sites intermediate compared to the much higher rates at the natural mainstem site and somewhat lower rates at the channelized mainstem site. These sediment inputs of nutrients were much larger than rates of inorganic P and N release from soils, indicating net trapping of P and N after restoration. Restoring floodplain hydrologic connectivity showed moderate success at increasing the trapping of P, N, and sediment, with relatively little phosphate release, and therefore improving water quality.

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USGS2019

Eviction notice: Observation of a Common Tern (Sterna hirundo) usurping an active Least Tern (Sternula antillarum) Nest

Although nest usurpation is common in some species and orders of birds, usurpation has rarely been reported for Sterninae. We observed a Sterna hirundo (Common Tern) egg in an active Sternula antillarum (Least Tern) nest with a complete clutch in a mixed-species Sterninae colony in Chesapeake Bay, MD, in May 2018. Based on observations from a game camera following usurpation, Common Terns incubated the mixed-species clutch, with no further parental care provided by the usurped Least Tern. The clutch never hatched, as the Common Terns abandoned the nest prior to the hatching. While we suspect that Common Terns usurped the Least Tern nest, alternative scenarios may explain how the Common Tern egg was documented in a Least Tern nest.

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USGS2019

Estimating occurrence, prevalence, and detection of amphibian pathogens: Insights from occupancy models

Understanding the distribution of pathogens across landscapes and their prevalence within host populations is a common aim of wildlife managers. Despite the need for unbiased estimates of pathogen occurrence and prevalence for planning effective management interventions, many researchers fail to account for imperfect pathogen detection. Instead raw data are often reported, which may lead to ineffective, or even detrimental, management actions. We illustrate the utility of occupancy models for generating unbiased estimates of disease parameters by 1) providing a written tutorial describing how to fit these models in Program PRESENCE and 2) presenting a case study with the pathogen ranavirus. We analyzed ranavirus detection data from a wildlife refuge (Maryland, US) using occupancy modeling, which yields unbiased estimates of pathogen occurrence and prevalence. We found ranavirus prevalence was underestimated by up to 30% if imperfect pathogen detection was ignored. The unbiased estimate of ranavirus prevalence in larval wood frog ( Lithobates sylvaticus ; 0.73) populations was higher than in larval spotted salamander ( Ambystoma maculatum ; 0.56) populations. In addition, the odds of detecting ranavirus in tail samples were 6.7 times higher than detecting ranavirus in liver samples. Therefore, tail samples presented a nonlethal sampling method for ranavirus that may be able to detect early (nonsystemic) infections.

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USGS2018

Geomorphic characteristics of Tenmile Creek, Montgomery County, Maryland, 2014–16

Data collected from April 2014 through September 2016 were used to assess geomorphic characteristics and geomorphic changes over time in a selected reach of Tenmile Creek, a small rural watershed near Clarksburg, Maryland. Longitudinal profiles of the channel bed, water surface, and bank features were developed from field surveys. Changes in cross-section geometry between field surveys were documented. Grain-size distributions for the channel bed were developed from pebble counts. Continuous-record streamflow and precipitation data were also collected in the Tenmile Creek watershed and used to supplement the geomorphic analyses. The Rosgen system of stream classification was used to classify the stream channel according to morphological measurements of slope, entrenchment ratio, width-to-depth ratio, sinuosity, and median particle diameter of the channel materials. Boundary shear stress near the U.S. Geological Survey (USGS) streamflow-gaging station was assessed by using hydraulic variables computed from the cross-section surveys and slope measurements derived from crest-stage gages and temporary data loggers installed along the study reach. Analysis of the longitudinal profiles indicated relatively small changes in the percentage and distribution of riffles, pools, and runs in the study reach between April 2014 and March 2015. More noticeable changes were observed during surveys conducted in March 2016 and September 2016. The channel-bed slope showed a net reduction over time from 0.0072 to 0.0040 feet per foot (ft/ft). The low-flow water-surface slope also showed a net reduction over time from 0.0065 to 0.0045 ft/ft. Net aggradation in the lower section of the study reach combined with net degradation in the upper section of the study reach contributed to the net reduction in channel-bed and water-surface slope. The large storm and resulting flood on July 30, 2016 was a major factor in observed changes in the longitudinal profiles between the March 2016 and September 2016 surveys. Comparison of data from the cross-sectional surveys indicated vertical changes in all cross sections, with more extreme changes observed between surveys in the lower section of the study reach due in part to alternating periods of net storage and transport of sand. Lateral erosion was not a major factor in the study reach, with the exception of cross section Dd, where considerable lateral erosion was documented during the study period. The flood that resulted from the large storm on July 30, 2016 was a major factor in some of the vertical changes observed in the channel bed of the study reach cross sections. Particle-size analyses of the channel bed from pebble counts indicated median particle diameters ranging from 15.5 millimeters (mm) to 23.1 mm, which is characterized as medium to coarse gravel. Sand percentages ranging from 3.4 percent to 16.4 percent of the total counts were observed over time. Net increases in storage of fine sediment in the reach were observed between April 2014 and March 2016, and a considerable reduction in storage was observed between March 2016 and September 2016. The Tenmile Creek stream channel was classified as a C4 channel, based on morphological descriptions from the Rosgen system of stream classification. The C4 classification describes a single-thread channel with a slight entrenchment ratio; a moderate to high width-to-depth ratio; moderate to high sinuosity; a water-surface slope of less than 2 percent; and a median particle diameter in the gravel range of 2 to 64 mm. The analysis of boundary shear stress indicated a range of 0.35 to 1.18 pounds per square foot for instantaneous streamflow ranging from 79 to 2,860 cubic feet per second during the study period. The relation between discharge and boundary shear stress for Tenmile Creek was compared to similar relations that were previously developed for Minebank Run, a small, urban watershed in the eastern section of the Piedmont Physiographic Province in Baltimore County, Md. that was physically restored during 2004–05. The comparison indicated a much flatter slope in the relation for Minebank Run in both its unrestored and restored conditions. This difference in the relations indicates that the erosive power in the urban watershed of Minebank Run is much more sensitive to increases in discharge magnitude than in the non-urban watershed of Tenmile Creek.

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USGS2018

Mapping crop residue and tillage intensity using WorldView-3 satellite shortwave infrared residue indices

Crop residues serve many important functions in agricultural conservation including preserving soil moisture, building soil organic carbon, and preventing erosion. Percent crop residue cover on a field surface reflects the outcome of tillage intensity and crop management practices. Previous studies using proximal hyperspectral remote sensing have demonstrated accurate measurement of percent residue cover using residue indices that characterize cellulose and lignin absorption features found between 2100 nm and 2300 nm in the shortwave infrared (SWIR) region of the electromagnetic spectrum. The 2014 launch of the WorldView-3 (WV3) satellite has now provided a space-borne platform for the collection of narrow band SWIR reflectance imagery capable of measuring these cellulose and lignin absorption features. In this study, WorldView-3 SWIR imagery (14 May 2015) was acquired over farmland on the Eastern Shore of Chesapeake Bay (Maryland, USA), was converted to surface reflectance, and eight different SWIR reflectance indices were calculated. On-farm photographic sampling was used to measure percent residue cover at a total of 174 locations in 10 agricultural fields, ranging from plow-till to continuous no-till management, and these in situ measurements were used to develop percent residue cover prediction models from the SWIR indices using both polynomial and linear least squares regressions. Analysis was limited to agricultural fields with minimal green vegetation (Normalized Difference Vegetation Index < 0.3) due to expected interference of vegetation with the SWIR indices. In the resulting residue prediction models, spectrally narrow residue indices including the Shortwave Infrared Normalized Difference Residue Index (SINDRI) and the Lignin Cellulose Absorption Index (LCA) were determined to be more accurate than spectrally broad Landsat-compatible indices such as the Normalized Difference Tillage Index (NDTI), as determined by respective R 2 values of 0.94, 0.92, and 0.84 and respective residual mean squared errors (RMSE) of 7.15, 8.40, and 12.00. Additionally, SINDRI and LCA were more resistant to interference from low levels of green vegetation. The model with the highest correlation (2nd order polynomial SINDRI, R 2 = 0.94) was used to convert the SWIR imagery into a map of crop residue cover for non-vegetated agricultural fields throughout the imagery extent, describing the distribution of tillage intensity within the farm landscape. WorldView-3 satellite imagery provides spectrally narrow SWIR reflectance measurements that show utility for a robust mapping of crop residue cover.

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USGS2018

Changes in long-term water quality of Baltimore streams are associated with both gray and green infrastructure

The steadily rising global urban population has placed substantial strain on urban water quality, and this strain is projected to increase for the foreseeable future. Considerable attention has been given to the hydrological and physico-chemical effects of urbanization on stream ecosystems. However, due to the relative infancy of the field of urban ecology, long-term water quality analyses in urban streams are sparse. Using a 15-year stream chemistry monitoring record from Baltimore, MD, USA, we quantified long-term trends in nitrate, phosphate, total nitrogen, total phosphorus, chloride, and sulfate export at several sites along a rural-urban gradient. We found no significant change in solute export at most sites, although we did find specific patterns of interest for certain solutes. For example, nitrogen export declined at the most headwater urban site, while phosphorus export declined at the most downstream urban site. Coupling long-term monitoring with data on gray and green infrastructure management throughout the landscape, we established relationships between solute export at the most downstream urban monitoring site and sanitary sewer overflows (SSOs), best management practice (BMP) implementation, and road salt application rates. Phosphorus export was correlated with BMP implementation in the watershed, whereas nitrogen export was related to SSOs. Despite highly urbanized watersheds, water quality does not appear to be declining at most of these sites, suggesting that current management may have limited further impairment. Results of our study suggest that both gray and green infrastructure are key for maintaining and improving water quality in this highly urbanized watershed.

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