Civil engineering infrastructure like roads, bridges, railway tracks, and building structures constructed on fat clay becomes suspicious due to adverse change in the behavior of such soil on interaction with water. To solve such problems especially in underdeveloped countries, application of industrial waste like glass is associated with technical, financial, and environmental benefits. Emphasis of current study is to determine the consequences of powdered glass (GC) on mechanical behavior of fat clay. A fat clayey sample was collected from location of Nandipur, and glass was taken from local glass market in powdered form. Samples were remolded at optimum moisture content and maximum dry unit weight by mixing GC up to 14%. Soil classification tests, modified compaction tests, unconfined compression tests, one-dimensional consolidation tests, California bearing ratio (CBR) tests, and scanning electron microscope were performed. With increasing GC, the consistency limits, compression characteristics, swell characteristics, and optimum moisture content decreased while maximum dry unit weight, yield stress, CBR, and unconfined compression strength increased. Influence of GC is also observed on microstructure of treated clay. After 12% GC, aforementioned geotechnical characteristics behave inversely for selected clay. The optimum GC-value for the tested clay is about 12%, however, this value may vary from clay to clay.

The conveyance of stormwater has become a major concern for urban planners, considering its harmful effects for receiving water bodies, potentially disturbing their ecosystem. Therefore, it is important to characterize the quality of catchment outflows. This information can assist in planning for appropriate mitigation measures to reduce stormwater runoff discharge from the catchment. To achieve this aim, the article reports the field data from a typical urban catchment in Australia. The pollutant concentration from laboratory testing is then compared against national and international reported values. In addition, a stochastic catchment model was prepared using MUSIC. The study in particular reported on the techniques to model distributed curbside leaky wells with appropriate level of aggregation. The model informed regarding the efficacy of distributed curbside leaky well systems to improve the stormwater quality. The results indicated that catchment generated pollutant load, which is typical of Australian residential catchments. The use of distributed storages only marginally improves the quality of catchment outflows. It is because ability of distributed leaky wells depended on the intercepted runoff volume which is dependent on the hydrological storage volume of each device. Therefore, limited storage volume of current systems resulted in higher contributing area to storage ratio. This manifested in marginal intercepted volume, thereby only minimum reduction in pollutant transport from the catchment to outlet. Considering strong correlation between contributing impervious area and runoff pollutant generation, the study raised the concern that in lieu of following the policy of infill development, there can be potential increase in pollutant concentration in runoff outflows from Australian residential catchments. It is recommended to monitor stormwater quality from more residential catchments in their present conditions. This will assist in informed decision-making regarding adopting mitigations measures before considering developments.

Stormwater managers use hydrological models to understand the runoff management performance of stormwater systems in urban catchments. However, few published studies attempted to evaluate the performance of hydrological models to represent water sensitive urban design (WSUD) elements at a catchment scale. This study reported on an evaluation of the Storm Water Management Model (SWMM) to represent a study catchment before installing leaky well systems in the catchment (preinstallation) and after introducing leaky wells (postinstallation). The process of representing individual leaky well systems using the user-defined hydraulic storage node or the built-in infiltration trench tools was also compared. The modeling approaches were evaluated against observed flow and infiltration data based on goodness-of-fit statistics, including the Nash-Sutcliffe Efficiency (NSE) and Kolmogorov-Smirnov (K-S) test for the catchment model. The results of goodness-of-fit tests and a K-S test indicated that SWMM can simulate a statistically similar runoff series to the observed series before and after the installation of leaky wells in the catchment. The ability of SWMM to model a leaky well performance using the storage or a built-in infiltration node was also evaluated using goodness-of-fit statistics against adopted criteria for good models. The results of model calibration and validations demonstrated that SWMM was able to simulate the performance of leaky well systems at the catchment scale, and the best performance was achieved by adopting a storage node to represent leaky wells. The model evaluation as per the adopted criteria indicated that the storage node model is suitable for assessing the impacts of leaky wells on stormwater runoff volume and peak flow rates.