Nature Based Solutions for Sustainable Urban Storm Water Management in Global South: A Short Review

Rapid urbanization in the Global South exacerbates urban water management challenges such as urban flooding and water pollution, rendering many areas water-insecure. Our reliance on grey infrastructures to combat these water management challenges is not sustainable in the long run, due to which a better alternative must be sought. Nature-based Solution (NBS) promote ecosystem services and enhance climate resiliency along with flood control and improvement of water quality by utilizing natural elements including green spaces and water bodies within the urban environment. In the past few decades, NBS have been adapted for urban drainage in Global North and evolved by means of various terms based on geographic location, practices and applications. Some of these well-known terms include Low Impact Development (LIDs), Sustainable Urban Drainage Systems (SUDS), Water Sensitive Urban Design (WSUD) and Best Management Practices (BMPs). The transition towards a resilient and sustainable environment has been made possible through the application of NBS. Recently, countries in the Global South such as Singapore, Malaysia, Vietnam, and Thailand are trying to alter urban storm water management strategies through conversion of grey infrastructure to green infrastructure by employing various NBS techniques. The findings of this study show how NBS has influenced the Global South’s urban water management.

Evaluating different machine learning methods to simulate runoff from extensive green roofs

Green roofs are increasingly popular measures to permanently reduce or delay storm-water runoff. The main objective of the study was to examine the potential of using machine learning (ML) to simulate runoff from green roofs to estimate their hydrological performance. Four machine learning methods, artificial neural network (ANN), M5 model tree, long short-term memory (LSTM) and k nearest neighbour (kNN), were applied to simulate storm-water runoff from 16 extensive green roofs located in four Norwegian cities across different climatic zones. The potential of these ML methods for estimating green roof retention was assessed by comparing their simulations with a proven conceptual retention model. Furthermore, the transferability of ML models between the different green roofs in the study was tested to investigate the potential of using ML models as a tool for planning and design purposes. The ML models yielded low volumetric errors that were comparable with the conceptual retention models, which indicates good performance in estimating annual retention. The ML models yielded satisfactory modelling results (NSE >0.5) in most of the roofs, which indicates an ability to estimate green roof detention. The variations in ML models' performance between the cities was larger than between the different configurations, which was attributed to the different climatic characteristics between the four cities. Transferred ML models between cities with similar rainfall events characteristics (Bergen–Sandnes, Trondheim–Oslo) could yield satisfactory modelling performance (Nash–Sutcliffe efficiency NSE >0.5 and percentage bias |PBIAS| <25 %) in most cases. However, we recommend the use of the conceptual retention model over the transferred ML models, to estimate the retention of new green roofs, as it gives more accurate volume estimates. Follow-up studies are needed to explore the potential of ML models in estimating detention from higher temporal resolution datasets.

Opportunities and challenges for implementing managed aquifer recharge models in drought-prone Barind tract, Bangladesh

This study focuses on the Barind tract, a drought prone area situated in the north-west region of Bangladesh where inadequate rainfall and limited surface water have created high dependence on groundwater for irrigation and other purposes, leading to significant declines in groundwater level. Managed aquifer recharge (MAR) offers a potential solution to restore groundwater levels. This study sets out to identify the opportunities and challenges for implementing MAR in the Barind tract. To accomplish this aim, different data sets including bore log lithology, rainfall, groundwater levels, information about re-excavated ponds, dighis, kharies, beels, check dams, rubber dams, dug wells and other necessary information were collected from the Barind Multipurpose Development Authority (BMDA) and other sources and analyzed. Major opportunities for MAR are identified for about 2000 km of re-excavated kharies (canals) containing about 750 check dams, more than 3000 re-excavated ponds, a number of beels (comparatively large marshes) and other water bodies which are used to conserve runoff storm water for supplementary irrigation. The conserved water can be used for groundwater recharge and subsequently abstracted for irrigation. Furthermore, roof-top rain water from buildings can also be used for groundwater recharge purposes. In contrast, the major challenges include the high turbidity of storm water runoff leading to clogging of MAR structures, inadequacy of conventional direct surface methods of recharge due to the presence of a 15 m or more thick upper clay layer with limited percolation capacity, and lack of practical knowledge on MAR. Therefore, overcoming the challenges for MAR application is a prerequisite to maximize the opportunities from MAR that can support the sustainable use of groundwater resources.

Concentrations and Risk Assessment of Metals, Antifouling Paint Particles and Microplastics in Coastal Sediment of a Marina in Simon’s Town, South Africa

Maintenance of maritime vessels includes the removal of paint from hulls that ultimately ends up the aquatic environment. Coastal maritime vessel maintenance is a source of metals, antifouling paint particles (APPs) and microplastics (MPs) that ends up in the coastal environment. Simon’s Town is a small urban town in False Bay, Cape Town, South Africa, where maritime activities take place (there is a naval harbour, marina and boat maintenance facility). The aim of this study was to measure metals, APPs and MPs in Simon’s Town, to assess the impact of maritime activities and a storm water pipe in a protected marina. Sediment samples were collected from 6 sites during winter 2018. Sediment and extracted APPs were analysed for metal content and MPs characterised based on type (visual and polymer), colour and size. Metal and MP fragment concentrations were highest at the slipway of a boatyard / maintenance facility, decreasing with increased distance from the slipway. MP filaments were highest close to the storm water outfall pipe. Our results suggest that boating maintenance facilities are potential sources metals and MP APP fragments, with storm water pipes potential sources of MP filaments. Various indices applied to assessed the potential impacts of metals and MPs, suggests that these contaminants have the potential to severely adversely impact the intertidal ecosystem investigated.