Adaptive measurements of urban runoff quality

Abstract

An approach to adaptively measure runoff water quality dynamics is introduced, focusing specifically on characterizing the timing and magnitude of urban pollutographs. Rather than relying on a static schedule or flow-weighted sampling, which can miss important water quality dynamics if parameterized inadequately, novel Internet-enabled sensor nodes are used to autonomously adapt their measurement frequency to real-time weather forecasts and hydrologic conditions. This dynamic approach has the potential to significantly improve the use of constrained experimental resources, such as automated grab samplers, which continue to provide a strong alternative to sampling water quality dynamics when in situ sensors are not available. Compared to conventional flow-weighted or time-weighted sampling schemes, which rely on preset thresholds, a major benefit of the approach is the ability to dynamically adapt to features of an underlying hydrologic signal. A 28 km 2 urban watershed was studied to characterize concentrations of total suspended solids (TSS) and total phosphorus. Water quality samples were autonomously triggered in response to features in the underlying hydrograph and real-time weather forecasts. The study watershed did not exhibit a strong first flush and intraevent concentration variability was driven by flow acceleration, wherein the largest loadings of TSS and total phosphorus corresponded with the steepest rising limbs of the storm hydrograph. The scalability of the proposed method is discussed in the context of larger sensor network deployments, as well the potential to improving control of urban water quality.

Real‐Time Control of Urban Headwater Catchments Through Linear Feedback: Performance, Analysis, and Site Selection

“…Water Resources Research Martinez, 2006;Wong & Kerkez, 2014), field-deployed devices are able to stream unprecedented amounts of real-time measurements about the health and performance of large watersheds (Bartos et al, 2017;Wong & Kerkez, 2016b). The resulting real-time data streams become particularly important when used in a bidirectional fashion.…”

Hydrograph peak-shaving using a graph-theoretic algorithm for placement of hydraulic control structures

“…The controller placement algorithm presented in this study provides a tool for designing stormwater control systems to better mitigate floods, regulate contaminants, and protect aquatic ecosystems. By reducing peak discharge, optimized placement of benefits, such as decreased first flush contamination [68], decreased sediment transport [69], improved potential for treatment in downstream green infrastructure [1,17], and regulation of flows in sensitive aquatic ecosystems [70].…”

Recent Advances in Information and Communications Technology (ICT) and Sensor Technology for Monitoring Water Quality

“…A more advanced sampling technology that includes ICT and the development of a model algorithm adjusts the sampling interval according to the flood status. Thus, it provides more precise information on the pollutant load during flood events [79,80]. This real-time flow-rate-sensing technology enables the proper management of water distribution systems during flood events in urban watersheds [81].…”

“…In addition, wireless sensors are one of the most efficient methods for collecting field data [15,105]. Wong and Kerkez (2016) suggested several factors (e.g., the interoperability, power consumption, reliability, usability, and security) that should be considered for the widespread usage of in situ sensing technologies for water quality management [79]. First, they emphasize the importance of the interoperability between real-time data and hardware platforms of users to minimize additional adjustments.…”