Optimal selection of hydraulic indexes with classical test theory to compare hydraulic performance of constructed wetlands
Introduction
Flow pattern inside constructed wetlands (CWs) is identified to affect pollutants removal rates significantly (Schuetz et al., 2012; Wahl et al., 2010). Normally, flow in CWs is assumed to be ideal in the form of either plug flow or completely mixed flow (Persson et al., 1999). In plug flow, all fluid particles move from inlet to outlet with the same velocity. In completely mixed flow, fluid properties are spatially and temporally uniform within CWs. However, neither of these ideal conditions is achievable in the field; actual flow is represented best as a combination of plug flow and several continuously stirred tank reactors (Persson et al., 1999; Teixeira and Siqueira, 2008. Tracer experiments can reveal actual flow pattern within CWs and residence time distributions (RTDs), obtained from tracer experiments, are one of main tools investigating hydraulic performance of CWs (Khan et al., 2013). Numerous studies about the effect of CW design on hydraulic performance (Headley and Kadlec, 2007; Holland et al., 2004; Ioannidou and Pearson, 2019; Nuel et al., 2017; Sabokrouhiyeh et al., 2017; Schuetz et al., 2012) use various hydraulic index to compare hydraulic performance.
However, the existence of various hydraulic indexes derived from RTDs led to inconsistency in their application to compare hydraulic performance of CWs. The diversity of hydraulic indexes is shown in their different categories. Teixeira and Siqueira, 2008 collected 14 hydraulic indexes, and divided them into short-circuiting index (SI) and mixing index (MI) with 8 and 6 indexes included, respectively, according to their physical meaning. Wahl (2013) collected 16 indexes and categorized as single value indexes, composite indexes, global indexes, conditional probability functions according to their definition formula. Stamou and Noutsopoulos (1994) also divided hydraulic indexes into four categories, namely SI, MI, the degree of plug flow, and efficiency. Hence, in the study of effect of CW design (water depth, wetland shape, the aspect ratio, number and position of obstacles, vegetation and climate) on hydraulic performance of CWs (Ioannidou and Pearson, 2019), there is little consistency in the application of hydraulic indexes and researchers have different preference for hydraulic indexes (Bodin et al., 2012; Guzman et al., 2018; Holland et al., 2004; Persson et al., 1999). Moreover, different hydraulic indexes may render inconsistent conclusions. For example, Khan et al. (2013) obtained inconsistent ranks of CWs in hydraulic efficiency according two hydraulic efficiency indexes (HEIs) when studying how the layout of floating CW affected hydraulic performance.
Confronted with this situation, we urgently need to optimize the hydraulic indexes to appropriately represent the hydraulic performance. In this paper, eight hydraulic indexes were firstly selected, which were then divided into three categories based on their physical meaning. These hydraulic indexes were then evaluated using classical test theory (CTT) for compatibility, discrimination, and difficulty. Finally, relationships between hydraulic indexes in the different categories were explored. This paper can bring clarity to the application of hydraulic indexes derived from RTDs, and provide uniform standards for the quantification of the hydraulic performance of CWs.
Section snippets
Data sources
Many RTDs covering a wide range of hydraulic performance are needed for such research. Previously, Teixeira and Siqueira (2008) obtained these RTDs by tracer experiments conducted on five significantly different types of CWs. However, those CWs were unique and did not represent the diversity of CWs. The better option is to acquire these RTDs through tracer experiments on CWs under different factors, because CWs under different factors, such as layout of inlet and outlet, vegetation, aspect
Results
For revelation of inconsistency of hydraulic indexes, CWs were firstly ranked according to their value. Then, compatibility, discrimination, and difficulty of hydraulic indexes were evaluated by CTT. Finally, the relationships between HEIs and SIs, MIs were explored, as well as the relationships between SIs and MIs.
Analysis of hydraulic efficiency indexes
The characteristics of HEIs were explored to explain connection between them. Traditionally, the range of λm is between zero and one, meaning that the average residence time is not greater than the nominal residence time. However, of the CWs surveyed, there are four for which λm exceeds unity. Kjellin et al. (2007) reasoned that such a situation would be due to errors in measuring the flow rate and volume. Bodin et al. (2013) found that λm could exceed one when a tracer experiment was ended at 3
Conclusions
Eight hydraulic indexes were selected and classified as HEIs, SIs, MIs. Inconsistency of hydraulic indexes was revealed using ranks of wetlands, based on a large number of RTDs. Hydraulic indexes were optimized so as to represent the hydraulic performance. Compatibility, discrimination, and difficulty of hydraulic indexes were evaluated using CTT. The relationships between HEIs, SIs and MIs were analyzed. A significant correlation between short-circuiting flow and hydraulic efficiency was
Author contributions section
Junjie Liu: Conceptualization, Methodology, Writing-Original draft preparation,
Bin Dong: Writing-Review and Editing, Supervision, Funding acquisition.
Wangzi Zhou: Data curation, Investigation.
Zhongdong Qian: Supervision.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
This material is based upon work supported by the National Natural Science Fundation of China under Grant No. 51779181. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. The data and parameters used in this study are listed in the manuscript, supporting information, or available from the cited public sources. The supporting information additionally provides
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