Storm Water Runoff from an Urban Watershed in Southern California: Top-Down Approach for Characterizing and Modeling Pollutant Loading Rates

Abstract

In southern California, storm water runoff from urban watersheds impacts coastal water quality. At the present time, coastal water quality impairments are usually managed through the development and implementation of a total maximum daily load (TMDL) plan, for which waste load allocations (WLA) and load allocations (LA) are developed, respectively, for the primary point and non-point sources of pollution in the watershed. The WLA and LA values are developed after weighing different pollutant source management scenarios, typically with the help of a distributed model of the watershed — for example, the geographical information system (GIS) model called BASINS. Because of challenges associated with this approach, we explore an alternative paradigm for modeling pollutant flow out of large watersheds that we term top-down , as opposed to the bottom-up approach employed by distributed models described above. In this alternative approach, the emphasis is on developing scaling relationships for pollutant loading rates that apply at the scale of large sub-drainages and the watershed as a whole. These scaling relationships could, in principle, be used for engineering calculations (e.g., for the design phase of storm water treatment facilities), to assess the contribution of individual watersheds to coastal pollution, and as a benchmark against which distributed models can be compared and tested. To this end, a series of studies were carried out at three sites in the Santa Ana River watershed, a large urban watershed encompassing in southern California. From the data, fecal indicator bacteria loading rates appear to scale as a power law with volumetric flow in a manner that varies by site, but is robust within, and between, storms at a single site. The physical basis for these scaling relationships, as well as the relationship between contaminants and particles eroded during storm events, are explored and developed.