Possibility of using the STORAGE rainfall generator model in the flood analyses in urban areas

In this investigation, we evaluated the applicability of the Stochastic Rainfall Generator (STORAGE) as a data source for deriving design hydrographs in urban catchments. This assessment involved a comparison with design rainfall calculated using Intensity-Duration-Frequency (IDF) curves derived from observed time-series data. The resulting design rainfall values from both methods were incorporated into a hydrodynamic model of the storm sewer network. To simulate peak discharge and flood areas, the Storm Water Management Model (SWMM) program was employed in conjunction with SCALGO. Our findings indicate that design rainfall values obtained from the STORAGE model exceeded those derived from the observed time-series, with a more pronounced difference for shorter rainfall durations. Simulations further revealed that peak runoff disparities between the two approaches were most evident at a 0.10 probability of exceedance compared to a 0.01 probability. Hydrodynamic simulations demonstrated that the flooding volume induced by design rainfall based on the STORAGE model surpassed that resulting from observed rainfall. Across all events, both the flooding volume and area from STORAGE were consistently greater than those derived from IDF curves. The integration of the SWMM model with the SCALGO application introduced a novel functionality for dynamic visualization of flooding, offering valuable insights for effective flood management in urban areas.

Understanding nutrient dynamics for effective stormwater treatment design

Current stormwater quality modelling tools lack robust mathematical replication of nutrient entrainment in runoff. This makes it challenging to design effective stormwater treatment systems such as nature based solutions with adequate resilience to future changes in nutrient inputs in urban environments. Consequently, poorly treated stormwater can be discharged into receiving waters, leading to nutrient enrichment and in turn, environmental and human health impacts. This study integrated empirically based with statistical modelling techniques to incorporate nutrient dynamics into commonly used Intensity-Frequency-Duration (IFD) distributions of design rainfall. Field based nutrient wash-off experiments were conducted to understand nutrient behaviour during a runoff event. New mathematical formulations were derived to describe the decay (wash-off) of nutrients. Rainfall intensity, duration and initially accumulated pollutant load exert positive influence on the decay of nitrogen and phosphorous, while organic carbon has a negative impact on phosphorus decay. It was also evident that nitrogen species would decay at a similar rate, while phosphorus species may decay at different rates. Compared to nitrogen species, phosphorous species were found more likely to be washed-off during a rainfall event. Using the mathematical formulations developed, wash-off of nitrogen and phosphorous was simulated for 435 very frequent and frequent/infrequent design rainfall events leading to the creation of Intensity-Frequency-Duration-Wash-off (IFDW) curves. Analysis of uncertainty associated with IFDW indicated that total phosphorous could be completely washed-off during most of the design rainfall events, while total nitrogen would only be completely washed-off by very few events that are rarer than 10 % AEP (annual exceedance probability). IFDW can act as a tool for supporting effective stormwater treatment design in order to promote sustainable stormwater management and reuse.

The influence of climate change and variability on the IFD Curves in NSW, Australia

In this study, the possible impacts of climate change and multi-decadal climate variability on intensity-frequency-duration (IFD) curves were investigated using both stationary and non-stationary generalized extreme value (GEV) distributions. The current study covers rainfall data recorded over 41 years for two rainfall stations, namely, Gowrie-055194 and Sydney Airport-066037, located within New South Wales state in Australia. Three future times (2030, 2060, and 2100), as well as 15 rainfall durations ranging from 6 min to 3-days, are considered. Consideration of the location parameter of the GEV distribution is influenced by climatic change and/or climate variability, providing a more consistent set of IFD curves. It is found that when the future period increases, the relative differences between the stationary and non-stationary IFD curves generally increase. When the new IFD curves (i.e., derived from the stationary and non-stationary approaches) are compared to the Australian Rainfall and Runoff (ARR) IFD curves, it is clear that the ARR IFD curves and the new stationary IFD curves are more closely aligned compared to the non-stationary IFD curves. The findings of this research are useful and provide valuable information for future planning of water resources, environmental and urbanization plans. It is essential to understand the expected behavior of hydro-meteorological processes regarding the possible changes in the rainfall design.