State Water Resources Research Institute Program (WRRI)

Details for Project ID 2010LA73B, 2010

Scale-dependent behavior and modeling of dissolved oxygen in coastal Louisiana rivers

Institute: Louisiana
Start Date: 2010-03-01 End Date: 2011-02-28
Total Federal Funds: $13,689 Total Non-Federal Funds: $37,457

Principal Investigators: Zhi-Qiang Deng

Abstract: The dissolved oxygen variation displays a strong scale-dependent behavior. At the seasonal scale, the DO becomes low in summer and high in winter following seasonal temperature change. At event (e.g. floods) scale, DO fluctuations in coastal Louisiana rivers with fine-grained sediment are significantly affected by flood events. The seasonal variation in DO is already well known. However, the DO fluctuation in response to flood events is still poorly understood, making it impossible to quantify the uncertainty and thereby the margin of safety (MOS) involved in the DO TMDL (Total Maximum Daily Load) development. This is a critical regional and state water quality problem needing to be addressed. The primary goal of this project is to understand the linkage between the episodic sediment resuspension and DO cycling in finegrained coastal Louisiana rivers. Specifically, the proposed project aims to characterize cycling frequency, intensity, and duration of sediment-water interface and associated DO fluctuation by developing an efficient and effective mathematical model for simulating scale-dependent behavior of dissolved oxygen in coastal Louisiana rivers characterized with fine-grained sediment. To achieve the goal, the research is split into five specific objectives: (1) Gathering and processing of historical water quality and remote sensing data; (2) Ground-based in-situ monitoring of water quality parameters; (3) Spaceborne satellite remote sensing of water quality; (4) Development of retrieval algorithm for dissolved oxygen; and (5) Mathematical modeling of episodic DO cycling in response to flow. The objectives will be addressed through a combined approach of sensor-based field monitoring, numerical modeling, and probabilistic analysis. Remote sensing technology will be utilized to capture spatial variation in DO while the in-situ sensing technology will be employed to capture temporal variation in DO and thereby to characterize scale-dependent behavior of DO. The proposed research has broader implications for environmental restoration of stream and coastal ecosystems in Louisiana. This project will provide an efficient and cost effective tool for predicting DO variation in streams and thus reduce the uncertainty in DO TMDL calculations. Although this study focuses on in-stream DO variation, the model and the methods can be easily extended to other water quality parameters. In addition, the project provides research and educational training opportunities for a graduate student.