The expansion of cities and land use changes have led to the emergence of peri-urban areas representing a transition between fully urbanized and agricultural regions in Southeast Asia. Peri-urban communities provide essential ecosystem services but are vulnerable to climate-related disruptions and socioeconomic challenges. Utilizing their unique characteristics, peri-urban communities can contribute to sustainable development and resilience. This study assesses the potential of peri-urban areas to meet future challenges for sustainable development in a changing world, focusing on the local pandan farming community of Pathum Thani, approximately 53 km north of Bangkok, using the Community-Based Resilience Analysis (CoBRA) approach. A formally established group of peri-urban farming households identified COVID-19, water quality, and solid waste as their primary disruptive challenges. The community identified economic stability and resources (land ownership, financial security, and government support), community and social support (collaborative community, and healthcare facilities), an environmental dimension (sufficient food and clean water), and an information dimension (news and knowledge update) as key community resilience characteristics, which highlight their comprehensive approach to hazard resilience. The study concludes that the community was moderately resilient to hazards and COVID-19 was the primary disrupting event over the past 10 years. To address future challenges in peri-urban agriculture, it is suggested to focus on enhancing economic diversification, strengthening social networks and support systems, implementing sustainable land management practices, and promoting access to timely and accurate information. Additionally, investing in infrastructure for water management and waste recycling, supporting small-scale farming initiatives, and fostering collaboration between farmers and local authorities can contribute to building resilience in peri-urban agricultural communities.

Rapid suburbanization can alter catchment flow regime and increase stormwater runoff, posing threats to sensitive ecosystems. Applications of Nature-based Solutions (NbS) have increasingly been adopted as part of integrated water management efforts to tackle the hydrological impact of urbanization with co-benefits for improved urban resilience, sustainability, and community well-being. However, the implementation of NbS can be hindered by gaps in performance assessment. This paper introduces a physically based dynamic modeling approach to assess the performance of a nature-based storage facility designed to capture excess runoff from an urbanizing catchment (Armstrong Creek catchment) in Geelong, Australia. The study adopts a numerical modelling approach, supported by extensive field monitoring of water levels over a 2.5-year period. The model provides a decision support tool for Geelong local government in managing stormwater runoff to protect Lake Connewarre, a Ramsar-listed wetland under the Port Phillip Bay (Western Shoreline) and Bellarine Peninsula. Runoff is currently managed via a set of operating rules governing gate operations that prevents flows into the ecological sensitive downstream waterbody from December to April (drier periods in summer and most of autumn). Comparison with observed water level data at three monitoring stations for a continuous simulation period of May 2022 to October 2024 demonstrates satisfactory to excellent model performance (NSE: 0.55–0.79, R²: 0.80–0.89, ISE rating: excellent). Between 1670 × 10³ m³ and 2770 × 10³ m³ of runoff was intercepted by the nature-based storage facility, representing a 56–70% reduction in stormwater discharge into Lake Connewarre. Our model development underscores the importance of understanding and incorporating user interventions (gate operations and emergency pumping) from the standard operation plan to better manage catchment runoff. As revealed by the seasonal flow analysis for consecutive years, adaptive runoff management practices, capable of responding to rainfall variability, should be incorporated.

This study employs HYDRUS-1D for modelling the vadose zone processes in a shallow groundwater wetland. HYDRUS-1D is based on Richards equation whose numerical solution heavily relies on reliable data derived from soil water retention curves. This modelling was supported by extensive field and laboratory measurements. Both disturbed and undisturbed soil samples were collected at the four depths for determination of particle size distribution, bulk density, saturated hydraulic conductivity, and saturated water content. The van Genuchten retention curves were used to describe the relationship between pressure head and water content; model parameters were optimized through inverse modelling with initial estimates of residual water content, shape parameters (α and n) obtained from ROSETTA model 3 (provided in HYDRUS-1D) and saturated water content and saturated hydraulic conductivity, determined from laboratory tests. Independent measurements of soil moisture and soil tension measured both in the field and laboratory fit well with the water retention curve obtained from the optimized ROSETTA parameters. Model performance in simulating measured water contents was good (average RMSE = 0.02 m³/m³) during calibration and validation (0.01 m³/m³ and 0.03 m³/m³ for two independent periods). Water content in upper soil layers was strongly influenced by atmospheric conditions, while groundwater level has the most influence in the bottom layers. Evapotranspiration was found out to be the dominant process in summer with total flux higher than that of infiltration while in winter evapotranspiration was relatively lower, even though still higher than infiltration.

The impacts of land use on stormwater runoff quality and Best Management Practices to mitigate these impacts have been investigated since the 1970s, yet challenges remain in providing a modeling approach that concomitantly considers contributions from different land use types. In densely developed urban areas, a buildup/washoff approach is often applied, while in rural areas, some type of erosion modeling is employed, as the processes of detachment, entrainment, and transport are fundamentally different. This study presents a coupled modeling approach within PCSWMM, integrating exponential buildup/washoff for impervious surfaces with the Modified Universal Soil Loss Equation (MUSLE) for pervious areas, including construction sites, to characterize water quality in the large mixed urban–rural Sparrovale catchment in Geelong, Australia. The watershed includes an innovative cascading system of 12 online NbS wetlands along one of the main tributaries, Armstrong Creek, to manage runoff quantity and quality, as well as 16 offline NbS wetlands that are tributary to the online system. A total of 78 samples for Total Suspended Solids (TSS), Total Phosphorus (TP), and Total Nitrogen (TN) were collected from six monitoring sites along Armstrong Creek during wet- and dry-weather events between May and July 2024 for model validation. The data were supplemented with six other catchment stormwater quality datasets collected during earlier studies, which provided an understanding of water quality status for the broader Geelong region. Results showed that average nutrient concentrations across all the sites ranged from 0.44 to 2.66 mg/L for TP and 0.69 to 5.7 mg/L for TN, spanning from within to above the ecological threshold ranges for eutrophication risk (TP: 0.042 to 1 mg/L, TN: 0.3 to 1.5 mg/L). In the study catchment, upstream wetlands reduced pollutant levels; however, downstream wetlands that received runoff from agriculture, residential areas, and, importantly, construction sites, showed a substantial increase in sediment and nutrient concentration. Water quality modeling revealed washoff parameters primarily influenced concentrations from established urban neighborhoods, whereas erosion parameters substantially impacted total pollutant loads for the larger system, demonstrating the importance of integrated modeling for capturing pollutant dynamics in heterogeneous, urbanizing catchments. The study results emphasize the need for spatially targeted management strategies to improve stormwater runoff quality and also show the potential for cascading wetlands to be an important element of the Nature-based Solution (NbS) runoff management system.

Urban flooding represents a growing concern on a global scale, particularly in regions characterized by rapid urbanization and increased climate variability. This study concentrates on the Rangsit area in Pathum Thani Province, Thailand, an urbanizing peri-urban area north of Bangkok and within the Chao Phraya River Basin where transitions in land use and the intensification of rainfall induced by climate change are elevating flood risks. A physically based hydrodynamic model was developed utilizing PCSWMM to assess current and future flood scenarios that considered future build-out plans and climate change scenarios. The model underwent calibration and validation using a continuous modeling approach that conservatively focused on wet year conditions, based on available rainfall and water level data. In assessing future scenarios, we considered land use projections based on regional development plans and climate projections downscaled under RCP4.5 and RCP8.5 pathways. Results indicate that both urban expansion and intensifying rainfall are likely to increase flood magnitudes, durations, and impacted areas, although in this rapidly developing peri-urban area, land use change was the most important driver. The findings suggest that a physically based modeling approach could support a smart-control framework that could effectively inform evidence-based urban planning and infrastructure investments. These insights are of paramount importance for flood-prone regions in Thailand and Southeast Asia, where dynamic modeling tools must underpin governance, climate adaptation, and risk communication. Furthermore, given the greater impact of future build-out on flood risk, as compared to climate change, there is an opportunity to effectively and proactively improve flood resilience through the implementation of integrated Nature-based Solution and hard engineering approaches, in combination with effective flood management policy.