Urban green infrastructure (UGI) can be used as a sustainable stormwater management approach. UGI can bring numerous ecological benefits to cities, including increased urban resilience, increased availability of water resources, and optimization of habitats. This paper used empirical research methods to describe an Internet of things (IoT)-based UGI monitoring and control system for stormwater management (MCSSWM). Using a Xuzhou-based practical project in China as a case study, we introduce the construction process, method, and monitoring results of the system. The results showed that the MCSSWM could be beneficial for UGI ecological performance evaluation and management.

Urban block-scale sponge system design needs address how to specify the optimal approach to combine the number of areas and types of sponge facilities for diverse land conditions and sponge system design objectives, while ensuring sponge performance and economic efficiency. With the gradual application of multi-objective optimization algorithms in the design of sponge cities, multi-objective combinatorial problem solving for sponge facilities based on optimization algorithms is more accurate and efficient than traditional design methods based on the designer’s experience. This study utilizes a residential complex in Nanjing as a practical example, selects six types of typical sponge facilities to construct a multi-objective optimization combination model for sponge facilities, and employs the SPEA-2 algorithm to determine the optimal combination of sponge facility types and quantities. Finally, 186,754 combinations of sponge facilities were calculated. For the three sponge objectives of optimal performance and economy for stormwater infiltration and storage, optimal performance and economy for runoff pollution control, and optimal average overall performance for stormwater infiltration, runoff pollution control, and economy, a number of combinations of sponge types and numbers were obtained.

A sponge city is an established urban stormwater management approach that effectively reduces urban runoff and pollutant discharges. In order to plan and design, estimate costs, and evaluate the performance of urban sponge city systems, it is essential to calculate the storage scale. In this context, a sponge city storage scale and calculation method based on a multifactor spatial overlay was designed, utilising the starting area of the Dafeng Hi-tech Development Zone in Yancheng City, China, as an illustrative example. The indicators for assessing the impact of sponge city systems on river plain networks are constructed based on four aspects: land planning, building density, water surface rate and green space rate. The relative importance of each indicator was determined based on the necessity of controlling runoff from land parcels and the appropriateness of facility construction. The annual runoff control rate of the 39 low-impact development control units in the study area was calculated using ArcGIS through multifactor spatial overlay mapping and weighting. The results showed that (1) the Geographic Information System (GIS)overlay technology can effectively assist in the decomposition of LID scales; (2) data can be derived, including the design storage volume and other basic control scale indicators for each unit. The study results are expected to serve as a reference for the preparation of special low-impact development plans in the river plain network area of China and the promotion of the construction of a sustainable blue–green system in the city.

Advancing intelligent water conservancy construction through the integration of next-generation technologies has become a crucial direction for the current development of water conservancy informatization in China. This paper introduces a smart management system for national water park that utilizes a 3D IVR model as its foundational data. Specifically, the system comprises: (i) Constructing a 3D IVR model using data from unmanned aerial vehicle (UAV) oblique photography; (ii) Establishing a smart management system that integrates the 3D IVR model and geographic information data; and (iii) Developing and implementing customized functional modules for managing national water park.