Anna-Maria Gustafsson

Simulating future trends in urban stormwater quality for changing climate, urban land use and environmental controls.

The effects of climatic changes, progressing urbanization and improved environmental controls on the simulated urban stormwater quality in a northern Sweden community were studied. Future scenarios accounting for those changes were developed and their effects simulated with the Storm Water Management Model (SWMM). It was observed that the simulated stormwater quality was highly sensitive to the scenarios, mimicking progressing urbanization with varying catchment imperviousness and area. Thus, land use change was identified as one of the most influential factors and in some scenarios, urban growth caused changes in runoff quantity and quality exceeding those caused by a changing climate. Adaptation measures, including the reduction of directly connected impervious surfaces (DCIS) through the integration of more green spaces into the urban landscape, or disconnection of DCIS were effective in reducing runoff volume and pollutant loads. Furthermore, pollutant source control measures, including material substitution, were effective in reducing pollutant loads and significantly improving stormwater quality.

Review of models and procedures for modelling urban snowmelt

A literature review of selected snowmelt models or algorithms was undertaken to identify which of these tools could be readily used, or easily modified, for simulating urban snowmelt. In this context, the urban factors influencing snowmelt were classified into three categories: human activities, land use, and the origin of deposited snow; and served to develop a classification of urban snow covers with characteristic properties influencing snowmelt. Finally, the assessment of capabilities of the surveyed models or algorithms to simulate snowmelt for these covers indicated that: (i) only two of the tools addressed the critical characteristics of urban snow covers (for specific cases only), (ii) urban runoff models with snowmelt subroutines offered best operational flexibility, though modifications and/or guidance on input values would be required for satisfactory simulations, and (iii) the review findings should help modellers in choosing a snowmelt simulation tool best serving their task with respect to urban conditions.