Discussion: Prediction of long-term urban stormwater loads at single sites

Abstract

May and Sivakumar (2013) have predicted the long-term urban stormwater loads at single sites, using five different measures of central tendency. They have stated that their motivation in using measures of central tendency is one in which, in contrast to regression and process-based methods, there is no need for correlating urban stormwater loads with other variables (e.g. discharge), as well as less complexity. Overall, the flow-weighted mean concentration has produced the most accurate predictions of long-term loads. However, the following points are worth discussing:The definite superiority of the flow-weighted mean method obviously shows that there is sufficient correlation between loads and runoff, and therefore it suggests that regression methods could derive more accurate results. Interestingly, the authors claim in a different study (May and Sivakumar, 2009a) that the comparison between different statistical models shows that regression models are more applicable than simple estimates of mean concentration in urban areas. Therefore, here, May and Sivakumar should compare different mean functions at least with a simple regression model to support their new claim.From an environmental point of view, evaluating the trends, extreme events, dispersion tendency characteristics and bias are usually more effective than using a single value (e.g. long-term mean) for analysing/mitigating natural or human-induced side effects. For instance, Colin (1995) reports that urban stormwater loads have bias, which means the mode and arithmetic mean of samples are not related to the same load value; hence, pollution management for an area can be adjusted depending on the side of bias. In a different example, Vogel et al. (2005) state that the natural characteristics of long-term stormwater loads, at least in their case studies, are more sophisticated than using simple statistical methods. Therefore, Vogel et al. (2005) introduce a multivariate probability distribution function to model loadconcentration-discharge relationships in order to predict short and long-term stormwater loads. Furthermore, they derive benefit from using L-moment statistical analysis to discover the complexities of this phenomenon.Overall, the current study presents valuable points; however, the title and concepts should clarify that the aim of the research is simply to compare the performance of different measures of central tendency in deriving site mean concentration, and not to predict long-term urban stormwater loads. Authors' replyThe goal of the study by May and Sivakumar (2013) was to derive estimates of long-term load at a given catchment using a variety of estimates of site mean concentration (SMC) based on different measures of central tendency. The methodology was chosen for its inherent simplicity, making it readily applicable at sites with limited sampling.Regression and/or process-based models are not solely limited by the absence of strong correlations between concentration and explanatory variables such as discharge, but also by a spars...