The variability of the middle atmosphere is driven by a variety of atmospheric waves covering various spatial and temporal scales. In particular, the northern winter mesosphere/ lower thermosphere at mid- and polar-latitudes shows a huge variability related to planetary waves, which can disturb the polar vortex leading to large scale coupling effects like sudden stratospheric warmings (SSWs) altering the vertical propagation conditions of tides and gravity waves. Here we are going to investigate and diagnose the short time variability of tides (several days) at the MLT using ground-based observations at mid and polar latitudes and data from NAVGEM-HA for selected periods. NAVGEM-HA provides information about the global structure of the zonal mean zonal and meridional wind and the zonal mean temperature as well as the tides. At mid- and high-latitudes the semi-diurnal tide (SW1 and SW2) is the dominating tidal wave during the winter season, which is also seen in meteor radar and lidar climatologies. Further, we analyze local meteor radar and lidar observations at Andenes (polar-latitude) and Juliusruh (mid-latitude) to diagnose the local amplitude and phase variability due to changes in the background mean winds caused by planetary waves and SSWs. We will show that the tidal phase (in UT) can drift significantly within several days and weeks. These local measurements are also compared to NAVGEM-HA applying the same diagnostic as to the observations. In addition to the winter time observations, we will also show results for the phase propagation of tides from summer periods.

High-resolution observations made by the Hubble Space Telescope have developed the modern picture of the Jovian main oval emission as the signature of field-aligned corotation-enforcement currents which keep magnetospheric plasma rotating at the same rate as Jupiter's magnetic field. This model explains the slowly changing behavior and bright emissions of the main oval and allows the magnetosphere to be studied by remote observations, as the auroral oval directly reflects processes in the magnetosphere and properties of the plasma therein. Recent results from the Juno mission have called these results into question, as the strong, field-aligned currents required by the corotation-enforcement current system have not been measured. Where is the corotation-enforcement current-- which must exist to move magnetospheric plasma-- a dominant driver of the main oval emission? Where do other processes drive the main oval aurora instead? We present one of the widest surveys of Jupiter's main oval auroral features to date by combining over 180 hours of Hubble Space Telescope observations to address these questions. This comprehensive survey is the first to measure the corotation rate, an important tool for distinguishing auroral drivers, of all individual auroral features. This analysis is made possible due to the development of automated pipelines to reduce observations, produce keograms, identify discrete auroral emission features, and measure the corotation rates of these features, among other properties. We present the measured properties of emission features as a function of location along the main oval, in terms of longitude, local time, auroral local time, and magnetic local time. These results serve as the foundation for comparison to in-situ measurements from both the Galileo and Juno missions, which will ultimately help reveal which magnetospheric conditions are likely responsible for driving corotating emissions and which are responsible for sub-corotating emissions, such as the dawn storms.

Stratospheric aerosol injection (SAI) can provide global cooling by adding aerosols to the lower stratosphere, and thus is considered as a possible supplement to emission reduction. Previous studies have shown that injecting aerosols at different latitude(s) and season(s) can lead to differences in regional surface climate, and there are at least three independent degrees of freedom (DOF) that can be used to simultaneously manage three different climate goals. To understand the fundamental limits of how well SAI might compensate for anthropogenic climate change, we need to know the possible surface climate responses to SAI by evaluating the SAI design space. This research work quantifies the number of meaningfully-independent DOFs of the SAI design space. This number of meaningfully-independent DOF depends on both the climate metrics that we care about and the amount of cooling. From the available simulation data of different SAI strategies, we observe that between surface air temperature and precipitation, surface air temperature dominates the change of surface climate. The number of injection choices that produce detectably different surface temperature is more than the number of injection choices that produce detectably different precipitation. At low levels of cooling, only a small set of injection choices yield detectably different surface climate responses. As more cooling is needed, more injection choices produce detectably different surface climate. For a cooling level of 1-2C, we find that there are likely between 6 and 12 DOFs. This reveals new opportunities for exploring alternate SAI designs with different distributions of climate impacts and evaluating the underlying trade-offs between different climate goals.

Tides are critical to coastal and oceanic processes. While tidal data are available readily, they are often corrupted by various sources of error. An automated, fast MATLAB toolbox is developed to clean-up tidal timeseries data from estuarine and oceanic locations corrupted by errors. This toolbox will immensely speed up delivery of quality-controlled tidal data. It will also reduce errors in quality control, which typically involves several manual tasks. The toolbox corrects poorly interpolated and noisy data, erroneous outliers, and instrumentation bias such as spurious jumps, drifts, spikes, and modulations in the true signal. Signal clean-up involves multiple stages. First, thresholds are imposed on higher order temporal derivatives of the signal to remove gross interpolations and noise saturated signal chunks, followed by a moving median threshold to remove outliers. Then the surviving signal is filtered into tidal, subtidal and long-period components, and the long-period component is subject to a maximal overlap discrete wavelet transformation, in which the transform coefficients corresponding to multi-scale edge features are removed. Subsequently, local information in the subtidal and tidal components is compared relative to the whole signal to correct spurious amplitude modulations and sudden biases. Consequently, these components are added to recover the uncorrupted signal, and large data gaps are filled with short term harmonic reconstruction. For estuarine locations, the correlation in the spectrogram between two nearby stations is initially used to quantify and remove river influence in the signal. Applications to datasets at multiple global locations demonstrate the value of the toolbox.

Low-lying coastal and estuarine areas are among the most populated regions globally, have high economic significance, and are increasingly threatened by climate change, sea level rise, nuisance flooding, and extreme storms. Nature-based coastal protections are sustainable and sea-level resilient alternatives compared to traditional solutions such as dikes and seawalls. Submerged aquatic vegetation (SAV) or seagrasses can provide coastal flood and erosion protection by attenuating storm wave and current energy and stabilizing seabed sediments. However, more research is needed to understand the interactions between flow, SAVs, and sediments. These dynamic interactions affect flow at different scales and seagrass productivity. In this study, we present field measurements of current and wave evolution over a seagrass meadow in South Bay, Virginia. The high vertical resolution measurements show how currents change from above-canopy to in-canopy waters. Wave measurements indicate the dissipation and frequency modulation over the canopy. The results are compared with hydrodynamic simulations using a two-way coupled flow-vegetation interaction model that simulates nonlinear current and wave evolution as well as dynamics of highly flexible vegetation.

The aim of this study is two-fold: (1) measure solid Earth diurnal and semi-diurnal tidal constituents using non-parametric signal analysis, and (2) calculate the time delay of the Earth’s solid tidal response between two land-based geographic locations. For these goals, high-precision tidal signals were collected from borehole strainmeters at Plate Boundary Observatory (PBO) stations in Yellowstone, WY, USA and Sequim, WA, USA. Signals from synchronized microstrain time series sampled at 10 minute intervals from 1 January 2011 to 31 December 2015 were evaluated with power spectra and harmonic analysis with statistical F-testing. The phasing of the Earth’s tidal response for the two stations was also estimated with a solid Earth tidal model. Differences between the observed and modeled phases are investigated.

Propagation of electromagnetic (EM) waves from radar and communication devices at sea can be significantly affected by the low-altitude atmospheric refractive conditions. Characterizing the spatial and temporal variability of refractivity is thus crucial to many important Navy and civilian applications. Surface layer models based on Monin-Obukhov Similarity Theory (MOST), such as the Navy Atmospheric Vertical Surface Layer Model (NAVSLaM), can be used to estimate the vertical refractive structure of the evaporation duct (ED) from measured or forecasted environmental parameters, assuming a horizontally-homogeneous stratified atmosphere. As air and sea surface temperature are two critical inputs to NAVSLaM, the rapid variation in sea surface temperature (SST) and air-sea temperature difference in the Gulf Stream region provides a relatively controlled environment for investigating the utility of NAVSLaM under inhomogeneous ducting conditions. In this paper, EM propagation in the ED over the Gulf Stream is investigated using measured data from the Coupled Air-Sea Processes and Electromagnetic-ducting Research (CASPER) East Coast experiment conducted off the coast of Duck, NC, during October-November of 2015. Measurements of the one-way propagation loss between a transmitter and receiving array as a function of the range were performed during ship crossings of the Gulf Stream. Concurrent and co-located meteorological and oceanographic measurements were also collected within the marine atmospheric boundary layer (MABL), including air temperature, SST, relative humidity, air pressure and wind speed to be used as inputs to NAVSLaM. The environmental conditions in the region of the Gulf Stream are used to model the low-altitude refractivity profiles as a function of height and range, which are input into the Advanced Propagation Model (APM) for predicting the EM propagation. Of particular focus is the effect of the rapid change in SST across the boundary between the warmer Gulf Stream and the colder surrounding ocean. EM measurements are compared with the simulated propagation loss based on the range-dependent refractivity profile predicted from NAVSLaM, as well as a best-fit Paulus-Jeske ED model. Both stable and unstable conditions encountered during the CASPER East experiment are investigated.

The ice sheet-ocean modeling community is making large strides toward developing coupled models capable of examining the interactions and feedbacks between ice shelves and ocean along the Antarctic margin. We present preliminary results and address some of the challenges that have arisen during the development of a coupled ice sheet-ocean model. The ice sheet model is icepack, a shallow-shelf finite element model written in Python. The ocean model is the Regional Ocean Modelling System (ROMS), a terrain-following vertical (sigma) coordinate model that has been modified to interface with a moving ice shelf. These two models are coupled in an online configuration using the Framework for Ice Sheet Ocean Coupling (FISOC). The use of a model with sigma coordinates for the ocean component introduces a simplification and a complication to modeling a moving ice draft. The sigma coordinate system retains the same number of vertical layers at any depth, eliminating the need to convert grid cells between ice and water, when using a fixed grounding line configuration. However, as the ice shelf draft evolves in time, topographic configurations develop that induce pressure gradient errors in ROMS. We quantify these errors in an idealized set-up with an artificially changing ice draft following the ISOMIP+ geometry. We compare results between an ice draft that is smoothed to meet standard ROMS smoothing criteria (rx0, rx1) and a non-smoothed ice draft. Finally, we present a simple parameterization in a buffer zone near the grounding line that uses interpolated melt rates from the ocean model, allowing us to maintain a steep ice topography in the ice model without inducing pressure gradient errors in the short water column in the ocean model. This model configuration will be applied to Pine Island Glacier and used to examine present and possible future states of the ice sheet-ocean system.

Current General Circulation Models (GCMs) are struggling to capture the observed diurnal cycle of precipitation. One major problem is that GCMs usually have difficulties to simulate nocturnal deep convections. Nocturnal deep convections are usually decoupled with the land surface and are controlled by other factors aloft, which have not been fully understood. The Plains Elevated Convection at Night (PECAN) is a multi-institutional collaborated field experiment conducted at the central Great Plains during summertime (1 June to 15 July) 2015 on the purpose of improving the understanding and simulation of the processes that initial and maintain deep convections at night. During the 45-day PECAN period there are 31 intensive operational periods (IOP) of nighttime deep convections, each last for one night. The unique part of PECAN experiment is the use of 6 fixed and 4 mobile PECAN Integrated Sounding Arrays (PISA) to take detailed measurements for each IOP. These detailed measurements of thermodynamics, wind and water vapor profiles in high temporal resolution (typically 90-min) allow the observation of the evolution of boundary layer and propagating features. We will report results from the analysis of these PISAs using a constrained variational analysis method to understand the large-scale environment that control the nighttime deep convections at the central Great Plains.

The use of stable isotopic tracer methods is becoming a popular approach for in situ evapotranspiration (ET) partitioning studies at the ecosystem scale. Ecosystem evapotranspiration is usually partitioned based on different isotopic composition among the aggregated ET flux (δET) and its two components: physical evaporation process (δE) and biological transpiration process (δT). Uncertainties in calculating these three isotopic compositions, especially δET, are usually not negligible and could propagated to large uncertainty in the ET partitioning outcomes. In this study, we present a new ET partitioning approach utilizing dual isotope-based evapotranspiration partitioning based on d-excess (d-excess = δ2H - 8 × δ18O) . A field deployable laser absorption spectrometer was used for in situ measurements of isotopic composition (δ2H and δ18O) of atmospheric water vapor at different heights within the turbulently mixing ecosystem boundary layer for tallgrass prairie. This study incorporated a new refinement to the Craig-Gordon model to describe δE. During non-growing season, estimates of δET—based on Keeling plot and flux-gradient approaches—were compared against δE values derived by the Craig-Gordon model, under the assumption of no transpiration and thus the equality between δET and δE. During the growing season, coupled with isotopic sampling in plant and soils, we partitioned ET into transpiration and evaporation. This refined dual isotope-based approach of ET partitioning shows promise in reducing the uncertainties of the fractional contributions of evaporation and transpiration, thus enhance our understanding on the mechanisms underlying plant water use efficiency and the role of vegetation ecophysiological processes in eco-hydrologic processes under the changing environment.

Faced with unprecedented growth in earth data volume and demand, NASA has developed the Earth Data Analytic Services (EDAS) framework, a high performance big data analytics and machine learning framework. This framework enables scientists to execute data processing workflows combining common analysis and forecast operations close to the massive data stores at NASA. The data is accessed in standard (NetCDF, HDF, etc.) formats in a POSIX file system and processed using vetted tools of earth data science, e.g. ESMF, CDAT, NCO, Keras, Tensorflow, etc. EDAS utilizes high performance parallel data access, a custom distributed array framework, and a streaming parallel in-memory workflow for efficiently processing huge datasets within limited memory spaces with interactive response times. EDAS services are accessed via a WPS API being developed in collaboration with the ESGF Compute Working Team to support server-side analytics for ESGF. The API can be accessed using direct web service calls, a Python script, a Unix-like shell client, or a JavaScript-based web application. New analytic operations can be developed in Python, Java, or Scala (with support for other languages planned). Client packages in Python, Java/Scala, or JavaScript contain everything needed to build and submit EDAS requests. The EDAS architecture brings together the tools, data storage, and high-performance computing required for timely analysis of large-scale data sets, where the data resides, to ultimately produce societal benefits. It is currently deployed at NASA in support of the Collaborative REAnalysis Technical Environment (CREATE) project, which centralizes numerous global reanalysis datasets onto a single advanced data analytics platform. This service enables decision makers to compare multiple reanalysis datasets and investigate trends, variability, and anomalies in earth system dynamics around the globe. EDAS services include configurable high performance neural network learning modules designed to operate on the products of EDAS workflows. As a science technology driver we have explored the capabilities of these services for long-range forecasting of the interannual variation of important regional scale seasonal cycles. Neural networks were trained to forecast All-India Summer Monsoon Rainfall (AISMR) one year in advance using (as input) the top 8-64 principal components of the global surface temperature and 200 hPa geopotential height fields from NASA’s MERRA2 and NOAA’s Twentieth Century Reanalyses. The promising results from these investigations illustrate the power of easily accessible machine learning services coupled to huge repositories of earth science data.

Burn severity influences various biophysical and biogeochemical processes, and it is projected to increase in the coming decades across high-latitude ecosystems. However, the impact of burn severity on thermokarst (e.g., land subsidence after ground ice melting) is not well understood. We used time-series image analysis to assess the effects of burn severity and ground ice content on thermokarst processes in the Noatak National Preserve, northwestern Alaska. To extend the temporal depth for illustrating fire-thermokarst linkages, we evaluated eight existing fire indices derived from visible and near-infrared (380-1100 nm) spectral bands and developed burn severity maps of historical fires using Landsat MSS sensors (operation between 1972-1992). Our results reveal that tundra fire is a significant factor in creating thermokarst landforms (p<0.01), and that the magnitude of thermokarst varies with burn severity levels and ground ice content (p<0.05). An abrupt increase in thermokarst occurred one year after fire but the rate of thermokarst decreased after three years. The area of thermokarst three years after fire was highest in high-severity burns (385 ± 47 m2 thermokarst area/ha burned area), followed by moderate- (255 ± 32 m2/ha) and low-severity (201 ± 42 m2/ha) burns. Ground ice content interacted with burn severity to affect thermokarst; the area of thermokarst was twice as large in landscapes with high ground ice (356 ± 67 m2/ha) as in landscapes of low ground ice (167 ± 39 m2/ha) three years after fire. Among the eight fire indices, the Global Environmental Monitoring Index (GEMI) demonstrates the strongest correlation with field-based estimates (R2 = 0.8). Burn-severity maps reconstructed with GEMI reveal that over a 40-year study period, thermokarst expansion occurred more rapidly in high-severe burns than in low-severity or unburned areas. Our results suggest that the projected increase in burn severity may result in abrupt and long-lasting permafrost degradation in tundra ecosystems with potential consequences on Arctic carbon stocks.

Azimuthal anisotropy quantified by teleseismic SKS, SKKS, PKS (“XKS”) and Local S wave splitting parameters is used to investigate mantle deformation and flow beneath the boundary of the North American and Caribbean plates and adjacent areas. A total of 2556 XKS and 299 pairs of local S wave splitting parameters were obtained at 23 stations. The observations can be divided into two groups based on the spatial distribution of the resulting fast polarization orientations. Those observed on the Caribbean Plate are mostly WNW-ESE which are mostly trench-parallel. In contrast, the fast orientations observed on the North American Plate are dominantly NNE-SSW which are approximately trench-orthogonal and are consistent with those previously observed in southern Mexico to the north of the area of the current study. At most of the stations at which XKS and local S wave splitting parameters are available, the splitting parameters from the two types of shear waves are comparable, suggesting that the observed azimuthal anisotropy is mostly from the mantle wedge above the slab. The observations especially those obtained at recently deployed stations in Guatemala provide new insights into the complicated mantle flow system associated with slab subduction and rollback, as well as lithospheric shearing along the southern boundary of the North American Plate.

Long term climate change on early Mars is characterized by a shift in the spatial distribution of rivers and lakes. Geological datasets suggest earlier paleo-rivers prefer higher surface elevations compared to rivers that formed later (Kite, 2019). On the other hand, modeling work also suggest a transition of surface lapse rate that comes with atmospheric escape throughout the Martian history (Wordsworth, 2016). The surface lapse rate follows the atmospheric lapse rate, which is close to dry adiabatic, when the CO2 atmosphere is thick, but decouples when the atmosphere is thin. Figuring out the surface temperature distribution on early Mars is critical, because it tells us where the water sources from ice/snowmelt would have been during warming episodes. We use the MarsWRF GCM to explore the transition of river-forming climates. We assume the atmosphere is CO2-only, but allow additional greenhouse warming by a gray gas scheme. To simplify the relation between elevation and surface temperature, we set 0 obliquity and include simulations with both idealized topography and real topography. The range of surface pressure is between 0.01 bar and 2 bar. We use a surface energy budget framework to analyze outputs (Fig. 2). Under the framework, variations in surface emission LWs correspond to surface temperature variations. We find greenhouse heating LWa is the only term that scales with surface temperature under high PCO2, in contrast to predictions from the previous literature that sensible heat SH was the cause of the regime transition (Wordsworth, 2016). This conclusion does not change with switching to realistic topography or switching CO2 radiation to a gray gas scheme. Under the low Ps but high-optical-depth κ gray gas case, the surface lapse rate still follows the atmosphere, so the regime transition can be attributed to the evolution of greenhouse gases other than CO2. In future, we will add a surface liquid water potential algorithm to link the surface energy balance to paleo-river observations. Assuming surface liquid water is formed during transient ice-melting period, surface liquid water potential can be calculated from the Ts and Ps distributions. The output will be compared with different historical epochs to find the best-fit scenario with both CO2 and non-CO2 greenhouse forcing.

The Mekong river is one of the most complex river systems in the world that is shared by six nations in Southeast Asia. The river still remains relatively undammed (most existing dams are in the tributaries and are small), and its hydrology today is dominated by large natural flow variations that support the highly productive agricultural and riverine ecological systems; however, this is changing due to the alterations in land use and construction of new dams both in the tributaries the mainstream. Understanding the changes in surface water dynamics is therefore crucial to provide realistic future predictions of changes in downstream floodplain and riverine ecology due to the construction of dams in the upstream. While the existing dams have caused little impact on mainstream flows, those under construction and planned are likely to cause severe and potentially permanent damage to downstream hydro-agro-ecological systems, and adversely impact the livelihood of millions. Here, using hydrodynamic model simulations (CaMa-Flood), we show that the effects of flow regulation on downstream river-floodplain dynamics are relatively predictable along the mainstream Mekong, but flow regulations could potentially disrupt the flood dynamics in the Tonle Sap River (TSR) and small distributaries in the Mekong Delta. Results suggest that TSR flow reversal could cease if the Mekong flood pulse is dampened by 50% and delayed by one-month. While flood occurrence in the vicinity of the Tonle Sap Lake and middle reach of the delta could increase due to enhanced low flow, it could decrease by up to five months in other areas due to dampened high flow, particularly during dry years. Further, areas flooded for less than five months and over six months are likely to be impacted significantly by flow regulations, but those flooded for 5-6 months could be impacted the least.

The key to reproducible data reduction and data processing in scientific research is the ability to faithfully record every step of the process in a reproducible format that is transparent and easy to communicate. This is not an easy task. Most of the time in experimental research that is not primarily computational in nature, it falls victim to the enormous effort required to design experiments well, run complex analytical procedures rigorously and efficiently, and interpret the results in the proper geologic, geochemical or biological context, with little time left to invest in documenting and constructing a reproducible data reduction workflow. While this is understandable, it introduces a high risk for error, makes it extremely difficult to share and discuss one’s approach or review others’, reproduce the calculations at a later point or even just revisit what was done conceptually. Part of the problem lies inherently with most data processing being difficult to document, part of black box process where the inner workings are inaccessible, or simply too divorced from the narrative of the scientific work it represents. One important obstacle that interferes frequently with attempts to remedy this situation in the stable isotope community is the lack of many basic computational and data access tools that enable the kinds of calculations and data processing isotope geochemists need to do on a day to day basis. Here, we introduce a new suite of software packages that provide efficient and transparent access to raw stable isotope ratio mass spectrometry (IRMS) data formats and enable reproducible data processing straight from raw analytical output through data reduction, quality control, visualization and data reporting that retains the necessary flexibility required for the enormous breadth of analytical goals in the stable isotope community. Presented tools will cover aspects of functionality provided by the isoreader (isoreader.kopflab.org), isoviewer (isoviewer.kopflab.org) and isoprocessor (isoprocessor.kopflab.org) software packages and are 100% open-source and freely available to everyone in the geochemical community and beyond.

Spatial variability of physical properties induced by circulation and stirring remains unaccounted for in the energy pathway of inland waters. Recent efforts in microstructure turbulence measurements have unraveled the overall energy budget in lakes. Yet, a paucity of lake-wide turbulence measurements hinders our ability to assess how representative such budgets are at the basin scale. Using an autonomous underwater glider equipped with a microstructure payload, we explored the spatial variability of turbulence in Lake Geneva. Microstructure analyses allowed turbulent dissipation rates and thermal variances estimations by fitting temperature gradient fluctuations spectra to the Batchelor spectrum. In open waters, results indicate mild turbulent dissipation rates in the surface and thermocline (~10⁻⁸ W kg⁻¹), which weaken towards the deep hypolimnion (~10⁻¹¹ – 10⁻¹⁰ W kg⁻¹). The strong thermal stratification inhibited interior mixing in the thermocline. In contrast, measurements along the coastal slope reveal a notorious enhancement of turbulent dissipation (~5×10⁻⁸ W kg⁻¹) above the sloping topography way above the known extent of the bottom boundary layer. These distinct turbulence patterns result from differing large-scale dynamics in the interior and coastal environments. Current measurements in open waters show dominant internal Poincaré waves. On the coast, three-dimensional numerical results from meteolakes.ch suggest that enhanced bottom dissipations arise from the development of centrifugal instabilities. A process driven by coastal cyclonic circulation interacting with the sloping bottom reported for the ocean but so far overlooked in large lakes. The spatially-distributed turbulence measurements we report here highlight the potential of underwater glider deployments for further lake exploration.

Louisiana is undergoing rapid change from natural and anthropogenic forces, such as sea level rise, subsidence, and eutrophication. Sediment diversions on the lower Mississippi River are proposed as a large-scale restoration strategy to create new wetlands and sustain existing wetland areas in Barataria Basin, Louisiana. This will introduce a large volume of sediment and nutrient rich freshwater from the Mississippi River to the receiving basins. This will result in, at least, short term changes in light and nutrient dynamics and has potential to alter phytoplankton composition. In order to understand nitrogen dynamics in Barataria Basin due to large scale coastal restoration practices, the nitrogen budgets (including particulate and dissolved forms) were calculated from outputs of the Integrated Biophysical Model, which is based on the existing Delft3D model coupled with a water quality model (D-WAQ). Creating nitrogen budgets in estuarine systems allows for better understanding of the major sources, sinks, inputs and exports across the system, increasing understanding of the amount of nitrogen available to drive estuarine primary production. Quantification of nitrogen inputs, outputs and processes is essential because it is the limiting nutrient for most estuarine primary producers (e.g., phytoplankton and emergent macrophytes). Preliminary model results for the existing conditions suggest that the dissolved inorganic nitrogen in the estuarine waters is mainly derived from diffusional sediment fluxes and mineralization of particulate organic nitrogen. Most of the dissolved inorganic nitrogen was assimilated for phytoplankton growth. A relatively small portion of dissolved inorganic nitrogen was removed from the system through denitrification in the water column. More particulate organic nitrogen originated from emergent macrophytes than from phytoplankton primary production. These model results will help better understand how proposed sediment diversions on the lower Mississippi River may change the future ecological conditions of estuarine open water in coastal Louisiana.