Theses and Dissertations from UMD
Permanent URI for this communityhttp://hdl.handle.net/1903/2
New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
More information is available at Theses and Dissertations at University of Maryland Libraries.
Browse
38 results
Search Results
Item GEOMORPHIC AND HYDROLOGIC CHARACTERISTICS OF SMALL URBANIZED TRIBUTARIES TO A FALL ZONE STREAM(2024) Harris, John Allen; Prestegaard, Karen; Geology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Many rivers along the Atlantic Coast contain major knickpoints, which define the Fall Zone. These often-urbanized rivers straddle multiple physiographic regions with spatial variations in lithology, topography, and hydrology. This research evaluates the effects of mainstem channel incision and urbanization on channel and catchment morphology, bed substrate mobility, catchment water storage dynamics, and hydrologic response in tributaries of the Northwest Branch of the Anacostia River above and below the Fall Zone knickpoint. Topographic analyses show that differential incision below the mainstem knickpoint has initiated steep secondary channels incised into bedrock. Measurements at representative reaches show that bankfull shear stress exceeds critical shear stress in these newly initiated tributaries, resulting in erosive channels outside of threshold conditions. Increased urban runoff introduced at storm drain outfalls maintains these non-steady state conditions. Geophysical surveys reveal that regolith depth for water storage capacity is primarily below the flatter ridgetops of the tributary catchments, where development is concentrated. The secondary tributaries cannot access these upland storage zones, and thus have limited infiltration and recharge capacity. I installed streamgages in the tributaries and constructed catchment water balances to study storage dynamics and hydrologic response. Hydrologic consequences of urbanizing the steep secondary tributaries include flashy, elevated stormflows, greater total runoff, and reduced baseflows that are not maintained during drought periods. The combination of steep channels, thin regolith, and urban overprint limits infiltration to moderate storm responses and recharge storage. These effects were not seen in non-urbanized secondary tributaries, urbanized tributaries above the knickpoint, or the forested reference streams above the Fall Zone. These findings define the geomorphic adjustment of tributaries to differential mainstem incision and explore the hydrologic impacts of urbanizing small steep catchments with limited effective storage capacity. Supplementary files:S1: Table with the location, drainage area, stream gradient, bankfull hydraulic values, and grain size values at each Northwest Branch tributary and reference reach used in the study. S2: Spreadsheet with the water level logger gage height values collected at 5-minute intervals from April 2023-March 2024 and calculated discharge from the Northwest Branch tributary streamgages. S3: Spreadsheet with the monthly water balance values for the Northwest Branch tributary catchments and reference watersheds from April 2023-March 2024. S4: Table with the depth to bedrock values and corresponding slope angles measured from the seismic profiles and LiDAR-derived digital elevation models.Item USING BAYESIAN ELECTRICAL RESISTIVITY INVERSION TO REVEAL HILLSLOPE DRY-UP PROCESS IN A MEDITERRANEAN CLIMATE(2024) Shahid, Saffat; Huang, Mong-Han; Geology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Hydrologic dynamics in hillslopes is essential for comprehending the processes that shape landscape evolution and sustain the Earth’s critical zone. Electrical resistivity (ER) is considered as one of the best geophysical methods to observe these dynamics due to its sensitivity to subsurface water content. To understand hillslope water dynamics and mitigating the risks of slope instability caused by extreme weather events, we studied how subsurface hydrological processes are being influenced by variations in vegetation type across different aspects of hillslopes. Thus, how accurately ER can quantify the dry-up process during the growing season on hillslopes becomes critical, particularly in regions with distinct dry summers and wet winters (i.e. Mediterranean climates). The Blue Oaks Ranch Reserve (BORR) in Central California provides an ideal location for this study due to its consistent ridge-valley systems, which well represents the regional climatic and topographic conditions. Previous work at BORR used active source seismic refraction (SR) to constrain subsurface structure. To additionally investigate moisture content in regolith, we conduct ER surveys with Schlumberger and Dipole-Dipole configurations to invert for resistivity using Transdimensional Hierarchical Bayesian (THB) inversion framework with reversible-jump Markov Chain Monte Carlo (THB rj-MCMC). We also performed 2D synthetic tests to evaluate how well THB can recover a synthetic model with imposed data uncertainty. The results indicate that Schlumberger outperforms Dipole-Dipole in the THB rj-MCMC inversion. However, these results also reveal limited depth resolution to ~10 m depth using current ERT configurations. Finally, we adopt the THB approach for a series of ER surveys at BORR between June and September 2023. The findings suggest a distinct increase in resistivity on the North-facing slope during growing seasons, indicating reduced moisture content particularly in areas with presences of oak trees as they draw water from deep regolith. On the South-facing slope, resistivity remained stable due to the dominance of grass that lacks deep roots for consuming deep moisture. Our resistivity results show that vegetation type particularly trees play a critical role in regolith moisture distribution. To compare and correlate changes in resistivity over dry periods, we analyzed soil probe data previously collected at the site. The correlation suggested that increases in resistivity are related to decreases in volumetric moisture content. Additionally, we compared ERT data with seismic survey data to better understand changes in subsurface properties like porosity and saturation along depth, as ERT and seismic velocity is sensitive to moisture content and material porosity.Item BEYOND PEAK RATE FACTOR 484: USING RADAR RAINFALL, GAUGED STREAMFLOW, AND DISTRIBUTED WATERSHED MODELING TO INVESTIGATE PARAMETERS OF THE NATURAL RESOURCES CONSERVATION SERVICE CURVILINEAR UNIT HYDROGRAPH(2024) Shehni Karam Zadeh, Mani; Brubaker, Kaye L.; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Accurate estimation of runoff and peak discharge is crucial in hydrology for engineering design and flood management. The Natural Resources Conservation Service’s (NRCS) Unit Hydrograph (UH) is a widely used model to predict the runoff response of an ungauged watershed to a precipitation event. The NRCS UH model makes use of a Peak Rate Factor (PRF) to quantify the peak discharge. The standard value of PRF is 484; however, PRF can be adjusted as a user input variable in NRCS tools such as the WinTR-20 software. Little guidance is available to appropriately estimate PRF for specific regions and evaluate its overall usefulness in the runoff and peak discharge estimation. Time of concentration (tc) is another input variable in the NRCS UH model; inconsistent definitions of tc and diverse methods of calculating it contribute to uncertainty in hydrologic estimates and predictions. The NRCS UH approach assumes that the watershed’s temporal runoff response to each increment of precipitation is identical in shape and proportional to precipitation excess in that increment of time. The UH, PRF, and tc are often assumed to be time-invariant properties of a watershed. This dissertation sought to improve the knowledge and understanding of PRF and tc. First, it evaluated if a unique UH and tc exist for a given watershed from various storm events. It then assessed whether variations in PRFs can be explained by watershed predictor variables and if PRFs in neighboring watersheds followed a local trend. This phase of study employed a gamma function representation of the NRCS UH, with two parameters: time to peak (tp) and shape (m). Precipitation inputs were watershed-averaged time series of NEXRAD level III data, and streamflow data were obtained from the United States Geological Survey (USGS) National Water Information System (NWIS). The UHs were derived from a constrained optimization approach, and PRF and tc were estimated for each event. Subsequently, a fully distributed model was created to provide insight on PRF and tc, and investigate the impact of detailed soil profiles on runoff and peak discharge. Finally, a fully distributed model was applied to simple, synthetic watersheds to investigate the impact of selected watershed parameters on PRF, time to peak, peak discharge and overall shape of the UH. To the best of the author's knowledge, this study is the first attempt to generate UHs from a simple distributed model and estimate associated PRFs. The findings suggest that there is no unique UH and tc for a given watershed, and UH shape and parameters change for every event in a given watershed. Additionally, the variations in PRFs cannot be explained by variations in selected watershed predictor variables. The distributed model results provided insights about the application of detailed soil profiles in runoff and peak discharge estimation. The findings also suggest that, except for Manning's roughness, selected watershed characteristics cannot be used to estimate PRF in a synthetic V-shaped watershed. These findings suggest that the application of PRF to estimate peak discharge should be used with caution due to the inherent uncertainties and lack of physical meaning of the parameter.Item A Data Assimilation System for Lake Erie Based on the Local Ensemble Transform Kalman Filter(2024) Russell, David Scott; Ide, Kayo; Applied Mathematics and Scientific Computation; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Data assimilation (DA) is the process by which a model forecast is adjusted to account for recent observations, taking into account both forecast and observation uncertainties. Although DA is common in numerical weather prediction (NWP) and other applications at global and regional scales, DA for large lakes such as North America's Great Lakes is still at an early stage of research and is not yet used operationally. In particular, the use of an ensemble-based approach to DA has scarcely been explored for large lakes, despite its growing popularity in operational NWP centers worldwide due to its dynamic estimation of the forecast covariance. Using Lake Erie as a test case, this study investigates the potential of ensemble DA to i) propagate forecast improvements throughout the lake and across forecast variables, and ii) inform the design of in-situ observing systems. The local ensemble transform Kalman filter (LETKF) is an efficient, localized, flexible variant of the ensemble Kalman filter (EnKF) that is used in multiple operational NWP centers. This work presents the development of a DA system for Lake Erie, which uses the LETKF to adjust forecasts of temperatures, currents, and water levels throughout the lake, using only lake surface temperature (LST) and temperature profile (TP) observations. The impact of both types of observations on all three forecast variables is evaluated within the framework of observing system simulation experiments (OSSEs), in which a DA system attempts to reconstruct a nature run (NR) by assimilating simulated observations of the NR. Observing system design questions are explored by comparing three different TP configurations. Assimilation of LST observations alone produces strong improvements to temperatures throughout the epilimnion (upper layer), while assimilation of TP observations extends these improvements to the hypolimnion (lower layer) near each profile. TP assimilation also shows improved representation of strong gyre currents and associated changes to thermocline depth and surface height, particularly when profiles sample from locations and depths where the thermal stratification in the forecast has been strongly affected by erroneous gyre currents. This work shows that the LETKF can be an efficient and effective tool for improving both forecasts and observing systems for large lakes, two essential ingredients in predicting the onset and development of economically and ecologically important phenomena such as harmful algal blooms (HABs) and hypoxia.Item NON-GAUSSIAN ENSEMBLE FILTERING AND ADAPTIVE INFLATION FOR SOIL MOISTURE DATA ASSIMILATION(2024) Dibia, Emmanuel; Liang, Xin-Zhong; Atmospheric and Oceanic Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The forecast error distribution in modern day land data assimilation systems is typically modeled as a Gaussian. The explicit tracking of only the first two moments can be problematic when trying to assimilate bounded quantities like soil moisture that are more accurately described using more general parameterizations. Given this issue, it is worthwhile to test how performance of land models is affected when the accompanying data assimilation system abides by a relatively more relaxed set of underlying assumptions. To study this problem, we perform experiments using the ensemble Kalman filter (EnKF) and rank histogram filter (RHF) to assimilate surface soil moisture content observations into the NASA Catchment land surface model. The EnKF acts as the traditional (Gaussian) standard of comparison whereas the RHF represents the novel and more general data assimilation method. An additional parameter of our tests is the usage of an adaptive inflation scheme that is only applied to the ensemble prior. This is done in an attempt to mitigate the negative effects of systematic deficiencies not accounted for by either filter. The examinations were carried out at a number of globally-distributed test locations, deliberately coinciding with sites used to validate NASA SMAP soil moisture retrieval products. Initial comparisons of the two filtering approaches in a perfect model context show both filters to provide significant benefits to the soil moisture modeling problem, with the RHF edging out the EnKF as the more performant filter. The relative performance gain of the RHF was most noticeable with respect to bias mitigation metrics and to the surface-level anomaly correlation scores, an interesting result given that neither filter is formulated to explicitly accommodate a systematic bias. When additionally applying adaptive inflation, both filters showed improvement in skill but such improvements were not significant. The use of synthetic observations and lack of a bias correction implementation may have led to exaggerated results. To address this concern, the experiments were performed again but using real observations from SMAP soil moisture retrievals, with in situ validation data proxying as truth. A robust bias correction scheme was used as well to more closely approximate practices used in operational settings. The RHF continues to show better metrics than the EnKF, but no longer in a statistically significant sense. A similar result was noted with respect to inflation usage. The most likely reason for this outcome is the low observation count. The findings obtained from the data assimilation experiments in this dissertation offer insight on how best to focus development efforts in soil moisture modeling and land data assimilation.Item MOBILIZATION OF CHEMICAL COCKTAILS BY FRESHWATER SALINIZATION SYNDROME IN THE CHESAPEAKE BAY WATERSHED(2023) Galella, Joseph George; Kaushal, Sujay S; Geology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Increasing trends in base cations, pH, and salinity of urbanizing freshwaters have been documented in U.S. streams for over 50 years. These patterns, collectively known as Freshwater Salinization Syndrome (FSS), are driven by multiple processes, including applications of road salt and human-accelerated weathering of impervious surfaces, reductions in acid rain, and other anthropogenic legacies of change. FSS mobilizes chemical cocktails of distinct elemental mixtures via ion exchange, and other biogeochemical processes. Urban streams in temperate areas experience chronic salinization throughout the year punctuated by acute salinization during winter storms with associated road salting. My research analyzed impacts of FSS on stream water chemistry in the field with routine bi-weekly and targeted high frequency sampling during road salting events. Field sites were proximal to USGS stream sensors using multiparameter datasondes, allowing for additional parameters to be monitored at 5-15 minute resolution. In the laboratory incubation analyses were also conducted using sediment and water samples to assess the function of stormwater best management practices (BMPs) during road salting events. Acute FSS associated with road salting was found to mobilize chemical cocktails of metals (Mn, Cu, Sr²⁺), base cations (Na+, Ca²⁺, Mg²⁺, K⁺), nutrients (TDN), and organic matter (NPOC). Regression relationships were developed among specific conductance and major ion and trace metal concentrations. These linear relationships were statistically significant in most of the urban streams studied (e.g., R2 = 0.62 and 0.43 for Mn and Cu, respectively), and showed that specific conductance could be used as a proxy to predict concentrations of major ions and trace metals. Principal component analysis (PCA) showed co-mobilization (i.e., correlations among combinations of specific conductance, Mn, Cu, Sr²⁺, and all base cations during certain times of year and hydrologic conditions). Co-mobilization of metals and base cations was strongest during peak snow events but could continue over 24 hours after specific conductance peaked, suggesting ongoing cation exchange in soils and stream sediments. Increased salt concentrations of all three major road salts (NaCl, CaCl₂, and MgCl₂) had profound effects on major and trace element mobilization, with all three salts showing significant positive relationships across nearly all elements analyzed. Salt type showed preferential mobilization of certain elements. NaCl mobilized Cu, a potent toxicant to aquatic biota, at rates over an order of magnitude greater than both CaCl₂ and MgCl₂. Hourly mass fluxes of TDN in streams were also found to be elevated during winter months with peaks coinciding with road salting events. Targeted winter snow event sampling and high-frequency sensor data suggested plateaus in NO₃⁻ / NO₂⁻ and TDN concentrations at the highest peak levels of SC during road salt events between 1,000 and 2,000 μS/cm, which possibly indicated source limitation of TDN after extraction and mobilization of watershed nitrogen reservoirs by road salt ions. My results may help guide future regulations on road salt usage as there are currently no federally enforceable limits. NaCl is the most commonly used deicer in the United States, largely because it is often the least expensive option. Other technologies such as brines and other more efficient deicers (CaCl₂ and MgCl₂) should be considered in order to lessen the deleterious effects of FSS.Item Freshwater salinization syndrome limits management efforts to improve water quality(2022) Maas, Carly Marcella; Kaushal, Sujay S; Geology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Freshwater Salinization Syndrome (FSS) refers to the interactive effects of salt ions on the degradation of the natural, built, and social systems. FSS can mobilize chemical mixtures, termed ‘chemical cocktails’, in watersheds. The formation of chemical cocktails across space and time depends on the amounts and types of salt pollution, the surrounding land use including conservation and restoration areas, and the location along the flowpath in the watershed. We investigated (1) the formation of chemical cocktails temporally and spatially and (2) the natural capacity of watersheds and streams to attenuate salt ions along flowpaths with conservation and restoration efforts. We monitored high-frequency temporal and longitudinal spatial chemical changes in stream water in response to different pollution events (i.e., road salt, stormwater runoff, wastewater effluent, and baseflow conditions) and several types of watershed management efforts (i.e., national parks, regional parks, and floodplain reconnection) in six urban watersheds in the Chesapeake Bay region. There were significant relationships between watershed impervious surface cover and mean concentrations of salt ions (Ca2+, K+, Mg2+), metals (Fe, Mn, Sr2+), and nutrients (total dissolved nitrogen) (p < 0.05). Principal component analysis (PCA) indicates that chemical cocktails which formed along flowpaths in response to winter road salt applications were enriched in salts and metals (e.g., Na+, Mn, and Cu). During most baseflow and stormflow conditions, chemical cocktails that were less enriched in salt ions and trace metals were attenuated downstream. There was also downstream attenuation of FSS ions during baseflow conditions through management efforts including a regional park, national park, and floodplain restoration. Conversely, chemical cocktails that formed in response to multiple road salt applications or prolonged road salt exposure did not show patterns of attenuation downstream. The spatial patterns were quite variable, with increasing, plateauing, or decreasing patterns based on the magnitude, timing, duration of road salt loading, and extent of management efforts. Our results suggest that FSS can mobilize multiple contaminants along watershed flowpaths, however, the capacity of current watershed management strategies such as restoration and conservation areas to attenuate FSS is limited.Item Deciphering Core Records of Carbon and Nitrogen in Typha-Dominated Freshwater Wetlands(2022) Ravi, Rumya; Prestegaard, Karen; Geology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)I conducted decomposition experiments and examined soil characteristics in restored and natural freshwater marsh platform sites to decipher core records of soil C and N. Carbon loss rates and changes in ẟ13C and ẟ15N were obtained from decomposition experiments. Core samples at each site were analyzed for bulk density, weight %C, %N, ẟ13C, and ẟ15N. Typha C loss rates were similar among sites, and there was little change in ẟ13C composition, suggesting that DOC leaching is significant. Core carbon storage is higher in natural wetland sites. Initial Typha %N and ẟ15N reflect local N concentrations and sources to each wetland. ẟ15N increases between decomposed vegetation and upper cores in the tidal wetlands, possibly indicating denitrification. In N-rich wetlands, core %N and ẟ15N reflect differences in N sources and changes in N sources over time. In a wetland limited by N transport, core %N and ẟ15N may reflect vegetation N uptake.Item Characterizing a Multi-Sensor System for Terrestrial Freshwater Remote Sensing via an Observing System Simulation Experiment (OSSE)(2022) Wang, Lizhao; Forman, Barton A; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Terrestrial freshwater storage (TWS) is the vertically-integrated sum of snow, ice, soilmoisture, vegetation water content, surface water impoundments, and groundwater. Among these components, snow, soil moisture, and vegetation are the most dynamic (i.e., shortest residence time) as well as the most variable across space. However, accurately retrieving estimates of snow, soil moisture, or vegetation using space-borne sensors often requires simultaneous knowledge of one or more of the other components. In other words, reasonably characterizing terrestrial freshwater requires careful consideration of the coupled snow-soil moisture-vegetation response that is implicit in both TWS and the hydrologic cycle. One challenge is to optimally determine the multi-variate, multi-sensor remote sensing observations needed to best characterize the coupled snow-soil moisture-vegetation system. Different types of sensors each have their own unique strengths and limitations. Meanwhile, remote sensing data is inherently discontinuous across time and space, and that the revisit cycle of remote sensing observations will dictate much of the efficacy in capturing the dynamics of the coupled snow-soil moisture-vegetation response. This study investigates different snow sensors and simulates the sensor coverage as a function of different orbital configurations and sensor properties in order to quantify the discontinuous nature of remotely-sensed observations across space and time. The information gleaned from this analysis, coupled with a time-varying snow binary map, is used to evaluate the efficacy of a single sensor (or constellation of sensors) to estimate terrestrial snow on a global scale. A suite of different combinations, and permutations, of different sensors, including different orbital characteristics, is explored with respect to 1-day, 3-day, and 30-day repeat intervals. The results show what can, and what cannot, be observed by different sensors. The results suggest that no single sensor can accurately measure all types of snow, but that a constellation composed of different types of sensors could better compensate for the limitations of a single type of sensor. Even though only snow is studied here, a similar procedure could be conducted for soil moisture or vegetation. To better investigate the coupled snow-soil moisture-vegetation system, an observing system simulation experiment (OSSE) is designed in order to explore the value of coordinated observations of these three separate, yet mutually dependent, state variables. In the experiment, a “synthetic truth” of snow water equivalent, surface soil moisture, and/or vegetation biomass is generated using the NoahMP-4.0.1 land surface model within the NASA Land Information System (LIS). Afterwards, a series of hypothetical sensors with different orbital configurations is prescribed in order to retrieve snow, soil moisture, and vegetation. The ground track and footprint of each sensor is approximated using the Trade-space Analysis Tool for Constellations (TAT-C) simulator. A space-time subsampler predicated on the output from TAT-C is then applied to the synthetic truth. Furthermore, a hypothesized amount of observation error is injected into the synthetic truth in order to yield a realistic synthetic retrieval for each of the hypothetical sensor configurations considered as part of this dissertation. The synthetic retrievals are then assimilated into the NoahMP-4.0.1 land surface model using different boundary conditions from those used to generate the synthetic truth such that the differences between the two sets of boundary conditions serve as a realistic proxy for real-world boundary condition errors. A baseline Open Loop simulation where no retrievals are assimilated is conducted in order to evaluate the added utility associated with assimilation of one (or more) of the synthetic retrievals. The impact of the assimilation of a given suite of one or more retrievals on land surface model estimates of snow, soil moisture, vegetation, and runoff serve as a numeric laboratory in order to assess which sensor(s), either separate or in a coordinated fashion, yield the most utility in terms of improved model performance. The results from this OSSE show that the assimilation of a single type of retrieval (i.e., snow or soil moisture or vegetation) may only improve the estimation of a small part of the snow-soil moisture-vegetation system, but may also degrade of other parts of that same system. Alternatively, the assimilation of more than one type of retrieval may yield greater benefits to all the components of the snow-soil moisture-vegetation system, because it yields a more complete, holistic view of the coupled system. This OSSE framework could potentially serve as an aid to mission planners in determining how to get the most observational “bang for the buck” based on the myriad of different sensor types, orbital configurations, and error characteristics available in the selection of a future terrestrial freshwater mission.Item INVESTIGATING WATERSHED-SCALE CONTROLS ON STREAMWATER NITRATE EXPORT USING STABLE ISOTOPES(2022) Bostic, Joel; Nelson, David M; Marine-Estuarine-Environmental Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Dramatic increases in anthropogenic nitrogen inputs to watersheds over the past century have elevated riverine nitrate (NO3¯) loads, impairing downstream ecosystems. Impacts to receiving waters are largely determined by the amount and timing of streamwater NO3¯ export, and knowledge of the watershed-scale controls on spatiotemporal patterns of NO3¯ export is thus critical for effective mitigation. Land-use activities produce generalizable patterns of streamwater NO3¯ in specific watersheds but it remains unclear how land use might modulate more widespread nitrogen inputs, such as atmospheric deposition, and regulate temporal dynamics of streamwater NO3¯ export. To address these questions, I quantified nitrogen sources and inferred watershed-scale nitrogen cycling processes using stable nitrogen and oxygen isotopes and concentrations of NO3¯ in Chesapeake Bay watersheds. In my first chapter, I quantified streamwater export of atmospheric NO3¯ using triple oxygen isotopes (Δ17O) of NO3¯ in 832 streamwater samples collected from 14 sub-watersheds of diverse land use, nitrogen input rates, size, and lithology across two years during a range of hydrologic conditions. Results indicate that watersheds with either greater impervious surface areas or higher terrestrial nitrogen input rates associated with agricultural practices retain less unprocessed atmospheric NO3¯. I use these results to extend the kinetic nitrogen saturation conceptual model to atmospheric NO3¯ streamwater export and from forested to non-forested systems. In my second chapter, I used seasonal patterns of, and relationships between, NO3¯ concentrations, δ15N of NO3¯, and discharge in the same 832 samples to assess the relative importance of watershed-scale controls on spatiotemporal patterns of streamwater NO3¯ export. Surprisingly, similar seasonal patterns of δ15N-NO3¯ were measured across all watersheds. Similar seasonality of δ15N-NO3¯ suggests consistent temporal variation in biological processes, such as denitrification and/or assimilation, across diverse watersheds. In my third chapter, I used δ15N and Δ17O of NO3¯, as well as isotopes of water, to investigate NO3¯ source export in storm events relative to baseflow in two Baltimore County, Maryland, watersheds with contrasting land use. In the more developed watershed I found that storms had a disproportionate impact on atmospheric NO3¯ export, and the amount of NO3¯ deposited on impervious surfaces was approximately equivalent to the amount of atmospheric NO3¯ streamwater export during storms, while atmospheric NO3¯ exhibited approximately chemostatic behavior in the less developed watershed. These results highlight the importance of reducing hydrologic effects of impervious surfaces to limit atmospheric NO3¯ export, especially given predictions that increasing precipitation intensity will be associated with future climate change. In conclusion, my results demonstrate that land use modulates the retention of atmospheric NO3¯, but biological processes impart a consistent seasonal signal on streamwater NO3¯ irrespective of land use.