Effects of land use, climate, and imperviousness on urban stormwater quality: A meta-analysis

Many natural and anthropogenic factors cause degradation of urban stormwater quality, resulting in negative consequences to receiving waters. In order to improve water quality models at a variety of scales, accurate estimates of pollutant (nutrients, total suspended solids, and heavy metal) concentrations are needed using potential explanatory variables. To this end, a meta-analysis was performed on aggregated stormwater quality data from the published literature from 360 urban catchments worldwide to understand how urban land use and land cover (LULC), climate (i.e., Koppen-Geiger zone), and imperviousness (1) affect runoff quality, and (2) whether they are able to predict stormwater pollutant concentrations. Runoff pollutant concentrations were more influenced by LULC and climate than imperviousness. Differences in LULC significantly affected the generation of metals and some nitrogen species. Road, city center, and commercial LULCs generally produced the most elevated pollutant concentrations. Changes in climate zones resulted in significant differences in concentrations of nutrients and metals. Continental and arid climate zones produced runoff with the highest pollutant concentrations. Rainfall patterns seemed to have a more important role in affecting runoff quality than seasonal temperature. Differences in imperviousness only significantly affected chromium and nickel concentrations, although increased imperviousness led to slightly (not significantly) elevated concentrations of nutrients, suspended solids, and other heavy metals. Multiple linear regression models were created to predict the quality of urban runoff. Predictive equations were significant (p < 0.05) for 67% of the pollutants analyzed (ammonia, total Kjeldahl nitrogen, total nitrogen, total phosphorus, cadmium, nickel, lead, and zinc) suggesting that LULC, climate, and imperviousness are useful predictors of stormwater quality when local field monitoring or modeling is not practical. This study provides useful relationships to better inform urban stormwater quality models and such as total maximum loads.