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The purpose of this User's Guide is to provide guidance on modeling watershed-scale problems associated with decentralized wastewater-treatment systems (DWTS), with a particular focus on onsite wastewater systems (OWS). The guide focuses on modeling transport and fate of the nutrients nitrogen (N) and phosphorus (P) because these are the most common OWS constituents of concern, and because these pollutants are regulated in surface waters (N and P) and in ground water (N). However, limited but useful information is also provided regarding the modeling of organic wastewater contaminants, such as pharmaceuticals, pesticides, and other household products. It provides some general information on modeling bacterial pollutants. The guide can be used by decision makers to determine whether relatively simple screening models (presented in Appendix A) are sufficient for use in the decision-making process, or if sophisticated models (presented in Appendix B) are more appropriate The document will provide guidance about the type of model that should be used for particular scenarios, and the data requirements for model implementation. The guide is also useful to modeling experts by providing guidance on important issues such as conceptual-model development, mathematical-model selection, modelsensitivity analyses, model uniqueness, and calibration. Finally, the guide provides some real-world and hypothetical case studies that can demonstrate the usefulness of using watershed-scale models, and provide templates for certain common scenarios relevant to the decentralized wastewater treatment community.
The literature review described in this report is part of a larger research project to assess STU performance with respect to treatment of important wastewater constituents. The overall goal of the project is to provide a toolkit and tool-use protocol that is easy to implement and available to a wide range of users to assess STU performance. This literature review is not a preview of tools that we will develop and propose, but rather an analysis of the information and data and the literature, to help guide our tool development. All tools developed will be based on rigorous experimental data and quantitative models verified with field data from operating systems. In some cases, more sophisticated tools (e.g., complex mathematical models) may be warranted depending on the relative complexity of the problem and the relative risk associated with a poor design. This literature review focused on STU performance, key conditions or factors potentially affecting STU performance, and the current best practices for using models and other available tools to predict expected STU performance. The information gained during this literature review will guide the future direction of the project. Constituents of interest include nitrogen (N), phosphorus (P), microbial pollutants, and emerging organic wastewater contaminants (OWCs). Based on this literature review, it is clear that due to the variability of data collected at field sites, simple binary relationships (e.g., C/Co versus depth for various soil types) for statistical predictions of the attenuation of N, P, microorganisms or OWCs cannot be justified. Specific to N, hydraulic loading rate appears to be more important than soil texture or soil depth within the first 30-60 cm, although both soil depth and texture remain important variables. Most of the reported results related to the interaction of P with soil appear to be from laboratory batch tests. Similarly, field-scale evaluations of pathogen removal are limited. Finally, most of the existing OWC work has focused on the occurrence and concentrations of selected compounds in streams, lakes, and groundwater impacted by wastewater treatment plant effluents. Currently very few models have been developed for movement and treatment processes of N or P in OWTS. However, adapting the CW2D model for STUs that will predict the effect of different soil types (texture, structure, and drainage class) appears promising. CW2D is a module of the well known HYDRUS model designed to simulate nitrogen treatment in a sand filter. This model incorporates most of the features one might consider, including a comprehensive treatment of microbial growth, the impact of oxygen mass transfer on nitrogen transformation, and variable rates of denitrification due to changes in dissolved oxygen concentrations, dissolved organic matter, and microbial growth. The review of existing models demonstrates that simulation of microbial characteristics in OWTS is still largely uncharted territory.
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