768 research outputs found

    The Roles of Tidal Marshes in the Estuarine Biochemical Processes: A Numerical Modeling Study

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    Observations suggest that the existence of tidal marsh can alter the oxygen and nutrient dynamics in adjacent water bodies, but assessing the impacts of large tidal marshes on an estuary is challenging. In this study, we use a modeling approach to investigate the roles of tidal marshes on the estuarine biochemical processes. The marsh model, which simulates the ecological functions of marshes at seasonal and annual time-scales, is embedded inside an unstructured-grid three-dimensional hydrodynamic and eutrophication model (SCHISM-ICM). This modeling system simulates the growth and metabolism of the tidal marshes and links biological processes to nutrient dynamics in the water column and sediment. This model dynamically simulates nutrient recycling and physical transport of the materials between marshes and open water through wetting-drying processes. This coupled model system is validated and successfully applied to the York River Estuary. Model results suggest that tidal marshes influence the local diurnal dissolved oxygen (DO) cycle by exporting dissolved organic carbon and high sediment oxygen demand in the marsh system through the tidal exchange. The high deposition rates of organics and diurnal DO cycle enhance the sediment release of phosphorus. On the other hand, marshes tend to decrease dissolved inorganic nitrogen in the water column by settling particulate nutrients and enhancing the denitrification process. The study demonstrates that tidal marshes exert substantial impacts on the estuarine biochemical processes. The developed tidal marsh model enhances eutrophication modeling and advances the understanding of the feedback effects between marsh biogeochemistry and estuarine eutrophication processes on a systemic scale

    Impact of Submerged Aquatic Vegetation on Water Quality in Cache Slough Complex, Sacramento-San Joaquin Delta: a Numerical Modeling Study

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    Submerged aquatic vegetation (SAV) plays a significant role in many aquatic systems, and impacts both physical and ecological quantities. It can baffle currents, attenuate waves, recycle nitrogen and phosphorus from the sediment bed, perform ecosystem function as a primary producer, and provide critical habitat for many aquatic species. Conversely, the invasive SAV, Egeria densa (Brazilian waterweed), in the San Francisco Bay & Delta has been a nuisance since its introduction into the system in the 1960s. It has displaced most of the native submersed aquatic plant species in the Delta and restructured the ecosystem, thus threatening the survival of several endangered native fishes such as Delta Smelt. Its impacts on the ecological system remain largely unknown and the need for assessment is growing. This multi-interdisciplinary study, incorporating biogeochemistry, hydrodynamics, and numerical computing and field survey data, accomplishes two main goals. The first goal is to develop a new SAV model imbedded into the unstructured-grid SCHISM-ICM framework. in addition to the advantages of directly simulating the SAV impact on hydrodynamics using high-resolution unstructured grids, this new SAV model can also simulate the competition between SAV and phytoplankton for light and nutrient supplies. The second goal is to apply the new model to Cache Slough Complex, Sacramento-San Joaquin Delta, to estimate the impact on the water quality from intervening SAV removal. Removal of SAV is already being studied in Little Hastings Tract and this study can serve to develop hypotheses for monitoring and ultimately guidance for managing SAV removal in the Bay-Delta region. We benchmark the new SAV model with the tests on the SAV biomass, growth and impacts on light supply and nutrient budget in the water column and sediment bed, respectively. Starting from a uniform biomass distribution, we simulate the evolution of biomass over seasonal scales and validate the calculated distribution with the observed distribution. The model is able to successfully simulate the SAV die-off process in areas where it is known to be unable to colonize. By applying the fully coupled SCHISM-ICM-SAV model in the Cache Slough Complex area, the changes of the water quality state variables due to SAV are estimated over spatial and seasonal scales. Generally, SAV increases the accumulation of phytoplankton by locally reducing flushing and thus increasing the residence time, but in the meantime, reduces its local growth rate due to light shading and nutrient competition. A combination of direct impact from SAV and indirect impact through changed phytoplankton results in changes in other water quality variables: dissolved oxygen and nutrients. SAV tends to increase oxygen and organic nutrients while decreasing inorganic nutrients. For this system, the feedback loop from SAV to the hydrodynamics plays the most important role in the water quality variables among all feedback loops

    Controllability Analysis and Degraded Control for a Class of Hexacopters Subject to Rotor Failures

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    This paper considers the controllability analysis and fault tolerant control problem for a class of hexacopters. It is shown that the considered hexacopter is uncontrollable when one rotor fails, even though the hexacopter is over-actuated and its controllability matrix is row full rank. According to this, a fault tolerant control strategy is proposed to control a degraded system, where the yaw states of the considered hexacopter are ignored. Theoretical analysis indicates that the degraded system is controllable if and only if the maximum lift of each rotor is greater than a certain value. The simulation and experiment results on a prototype hexacopter show the feasibility of our controllability analysis and degraded control strategy.Comment: 21 pages, 7 figures, submitted to Journal of Intelligent & Robotic System

    Transforms for intra prediction residuals based on prediction inaccuracy modeling

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    In intra video coding and image coding, the directional intra prediction is used to reduce spatial redundancy. Intra prediction residuals are encoded with transforms. In this paper, we develop transforms for directional intra prediction residuals. Specifically, we observe that the directional intra prediction is most effective in smooth regions and edges with a particular direction. In the ideal case, edges can be predicted fairly accurately with an accurate prediction direction. In practice, an accurate prediction direction is hard to obtain. Based on the inaccuracy of prediction direction that arises in the design of many practical video coding systems, we can estimate the residual variance and propose a class of transforms based on the estimated variance function. The proposed method is evaluated by the energy compaction property. Experimental results show that with the proposed method, the same amount of energy in directional intra prediction residuals can be preserved with a significantly smaller number of transform coefficients

    Adaptive Backstepping-based H∞ Robust controller for Photovoltaic Grid-connected Inverter

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    To improve the robustness and stability of the photovoltaic grid-connected inverter system, a nonlinear backstepping-based H∞ controller is proposed. A generic dynamical model of grid-connected inverters is built with the consideration of uncertain parameters and external disturbances that cannot be accurately measured. According to this, the backstepping H∞ controller is designed by combining techniques of adaptive backstepping control and L2-gain robust control. The Lyapunov function is used to design the backstepping controller, and the dissipative inequality is recursively designed. The storage functions of the DC capacitor voltage and grid current are constructed, respectively, and the nonlinear H∞ controller and the parameter update law are obtained. Experimental results show that the proposed controller has the advantage of strong robustness to parameter variations and external disturbances. The proposed controller can also accurately track the references to meet the requirements of high-performance control of grid-connected inverters
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