Generation of a Heatmap to Evaluate MS4 Sampling Locations

Clean Water Services (CWS) is a water resources management district responsible for wastewater treatment and stormwater management serving over 600,000 residents and several major industries in Washington County, Oregon. CWS holds the nation's first watershed-based permit that includes four water resource recovery facilities (WRRFs) discharging to the Tualatin River and the Municipal Separate Storm Sewer System (MS4). Stormwater runoff is a contributor to pollution on creeks and rivers. CWS' stormwater management program includes the standards for design and construction of best management practices, maintenance and expansion of the stormwater conveyance system, and the regulatory monitoring of the stormwater runoff quality of the MS4 discharges to the nearby creeks and river. These activities are implemented in collaboration with twelve co-implementor cities and Washington County. To comply with the permit-required monitoring requirements, CWS has sampled five MS4 outfalls representing five different land use combinations (Table 1) for at least three storm events per year over twelve years. These outfalls aimed to be a sample that represents the different landuse types for the service area. The samples are analyzed for twenty different water quality constituents (Table 2) to characterize the runoff from the land use contributing to each stormwater outfall and their potential impact to the urban creeks and the Tualatin River. However, the drainage area to the monitoring sites represents just 0.4% of CWS' total MS4 service area. In addition, a recent analysis of the current MS4 sampling sites showed inconsistent patterns and trends, as well as a lack of representation for the dynamic state of the region. For example, Figure 1 shows the time series of E. coli data collected from the five monitoring sites. The two sites with industrial land use drainage basins have very different E. coli concentrations suggesting the sites do not represent the industrial land use well or that the industrial land use is not well understood. The limited number of sampling site's locations may not capture the variability and complexity of the service area. Classifying and monitoring drainage basins by land use alone may not be a sufficient way to capture the drivers of stormwater runoff pollutants. Similarly, Figure 2 shows a time series of zinc data collected at each site. Inconsistent outliers occur at one of the residential sites demonstrating that there is a driver for zinc spikes not being well-represented by using 'residential' drainage basins alone. Finally, there is poor paired sample between the MS4 water quality data and the routine ambient sampling locations downstream of these locations. This is potentially because none of the sampling sites are located directly upstream of the ambient sampling sites. Therefore, it makes it difficult to understand the contributions of different land uses to runoff water quality and their effects on receiving waterbodies, as well as suggesting that the selected MS4 sites do not represent the service area well. As part of the effort to create and maintain resilient watersheds, CWS is working to develop a stormwater monitoring plan that strategically optimizes sampling locations and sampling frequency to better represent the service area, better identify the drivers and sources of pollutants, and makes better use of ratepayer funds to understand how to address pollutants. CWS' most recent work includes the generation of a GIS 'heatmap' to identify the areas that are prone to show higher pollutant loading. In addition, CWS would like to identify locations that provide a better correlation with the ambient sampling locations. Several versions of the heatmap have been completed to identify the areas by their physical characteristics. Currently, the approach combines spatial data including land use, traffic counts, age of development, drainage area size, impervious surfaces, current ambient sampling locations, future development areas, and demographic information. The final product, which is estimated to be ready in May, seeks to inform the development of a flexible and adaptive stormwater monitoring program and provide more relevant information to support both CWS' and the co-implementers' decisions regarding stormwater runoff water quality and its impact to nearby waterbodies. In this work, we will present the framework that led to the generation of the heatmap, the advantages of its use, and the steps followed to create the tool.