State Water Resources Research Institute Program (WRRI)
Start Date: 2007-03-01 End Date: 2008-02-29
Total Federal Funds: $19,812 Total Non-Federal Funds: $40,941
Principal Investigators: Zhi-Qiang Deng, Donald Adrian
Abstract: Streams play an important role in retaining and removing nutrients during passage through a stream network. A modeling tool for predicting nitrogen retention and uptake in streams is needed to understand how nitrogen loading from watersheds can be reduced in an efficient and cost-effective way. Although extensive investigations into in-stream nitrogen retention have been conducted, there are few mathematical models which are capable of reproducing nutrient attenuation process in natural streams without resorting to field tracer tests. The primary difficulty of developing such a model lies in the scale-dependent behavior of nutrient removal process in streams. The goal of this project is to develop an efficient and effective mathematical model for predicting scale-dependent nitrogen retention and uptake in natural streams without resorting to field tracer tests. The model is characterized by a varying or scale-dependent residence time and a scale-dependent nitrogen loss rate. The model include (1) a mass conservation-based nitrogen transport and fate equation, (2) an improved methodology for estimation of the transient storage zone volume fraction, (3) a theoretical method for predicting the Fickian dispersion coefficient in rivers and streams, (4) a more precise method for determination of the nitrogen loss rate, and (5) a split-operator based method for numerical solution of the model. The proposed strategy is to combine field tracer tests and numerical modeling. The nitrogen retention model will be developed by using mass conservation principle and a varying residence time. Field tracer test data and other existing nitrogen retention data will be employed to determine the parameters involved in the model. The scale dependent feature of nitrogen loss rate will be described using particle settling velocity and flow depth which are scale-dependent. The storage-zone volume fraction will be expressed as a function of channel sinuosity, friction factor, and the ratio of channel bank length and thalweg length. The Fickian dispersion coefficient Kx will be determined by improving PIs previous method for estimation of longitudinal dispersion coefficient in streams and rivers. The field-scale tracer experiments will be conducted by co-injection of conservative tracer (Rhodamine WT dye) and nonconservative tracer (15N) in the Amite River. The scale-dependent nitrogen retention model will be finally calibrated and tested using the field tracer test data. As a result, the parameters involved in the new scale-dependent nitrogen retention model are calculable from easily available data and the model is capable of predicting nitrogen transport and fate in natural streams without resorting to field tracer tests, significantly reducing the cost of experiments and enhancing the efficiency of nitrogen retention modeling. 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 nitrogen attenuation in streams and thus reduce the uncertainty in nitrogen TMDL calculations. The new model can be used to determine the extent and degree of stream restoration that would be required to significantly reduce nitrogen export from watersheds. Based on the modeling results of the new model we will be able to determine how restoration of natural stream channels might ameliorate the eutrophication problem in Louisianas waterbodies. Although this study focuses on in-stream nitrogen retention, the model and the methods for parameter estimation will be applicable to other nutrients as well. The scale-dependent model to be developed in this project is also of great importance for early warning of toxic chemical spills caused by accidents or terrorist attacks. In addition, the project provides research and educational training opportunities for graduate and undergraduate students.