The increasing challenges of urbanization and climate change have driven the need for innovative stormwater management solutions. Rain gardens, as a nature-based solution (NBS), have emerged as a critical component in urban water management, particularly in enhancing hydrological regulation, water quality, and ecosystem services. This bibliometric review examines the application of rain gardens in urban environments, focusing on their roles in stormwater management, pollutant removal, and ecological enhancement. Data from 728 academic papers published between 2000 and 2023 were analyzed using the Web of Science (WoS) Core Collection, employing bibliometric tools such as the “Bibliometrix” R package and CiteSpace. The analysis highlights the increasing global interest in rain gardens, particularly since 2015, with China and the United States leading research efforts. Key findings reveal that rain gardens significantly reduce runoff, improve water quality, and contribute to urban biodiversity. In addition, their integration into public spaces offers landscape esthetics and social benefits, enhancing the quality of life in urban areas. However, challenges remain in optimizing their design for diverse climates and long-term performance. The study underscores the need for further research on plant–soil interactions, pollutant removal mechanisms, and the broader ecological and social contributions of rain gardens. This review provides insights into the evolution of rain garden research and identifies future directions for advancing sustainable urban stormwater management.

Nature-based solutions (NbSs) are considered to form an innovative stormwater management approach that has living resolutions grounded in natural processes and structures. NbSs offer many other environmental benefits over traditional grey infrastructure, including reduced air pollution and climate change mitigation. This review predominantly centers on the hydrological aspect of NbSs and furnishes a condensed summary of the collective understanding about NbSs as an alternatives for stormwater management. In this study, which employed the CIMO (Context, Intervention, Mechanism, Outcome) framework, a corpus of 187 NbS-related publications (2000–2023) extracted from the Web of Science database were used, and we expounded upon the origins, objectives, and significance of NbSs in urban runoff and climate change, and the operational mechanisms of NbSs (including green roofs, permeable pavements, bioretention systems, and constructed wetlands), which are widely used in urban stormwater management, were also discussed. Additionally, the efficacy of NbSs in improving stormwater quality and quantity is discussed in depth in this study. In particular, the critical role of NbSs in reducing nutrients such as TSS, TN, TP, and COD and heavy metal pollutants such as Fe, Cu, Pb, and Zn is emphasized. Finally, the main barriers encountered in the promotion and application of NbSs in different countries and regions, including financial, technological and physical, regulatory, and public awareness, are listed, and future directions for improving and strategizing NbS implementation are proposed. This review gathered knowledge from diverse sources to provide an overview of NbSs, enhancing the comprehension of their mechanisms and applications. It underscores specific areas requiring future research attention.

This investigation delves into the waterfront plant landscapes of traditional villages in Western Hunan, China, aiming to bolster sustainable ecological resource management, amplify ecological culture, and ameliorate environmental standards. Furthermore, it endeavors to furnish a theoretical scaffold for the meticulous construction and assessment of these landscapes. This study has illustrated the waterfront botanical landscapes of 32 traditional hamlets within the Xiangxi region, integrating prior research on the waterfront botanical regression model based on the Scenic Beauty Estimation (SBE) method. It established and investigated fifteen landscape factors pivotal to the aesthetic valorization of these village waterfronts. The study concocted a beauty quality evaluation model, unearthing a significant correlation (p < 0.01) across evaluations by students majoring in landscape architecture, expert landscape architects, and laypersons, thus underscoring a consensus in aesthetic judgments. A noteworthy correlation between the beauty value (Z-value) and the entropy weight value was elucidated through the equation EWM = −0.106 + 0.425ZSBE, showcasing the landscape quality’s variance among the studied villages. The formulated evaluation model accentuates the significance of seasonal variation, scale affinity, and a rich hierarchical structure.

As economic growth and societal shifts reshape urban environments, cultural and creative industrial parks are emerging as vital contributors to sustainable urban development. The design of these landscapes plays a pivotal role in enhancing user satisfaction, increasing spatial attractiveness, and promoting eco-friendly urban practices. This study examines visitor landscape perception preferences in the Textile and Garment Cultural and Creative Industrial Park, located in Haizhu District, Guangzhou, through a novel methodology combining user-generated content (UGC), deep learning models, outdoor electrodermal activity (EDA) measurements, and questionnaire surveys. The UGC-based landscape recognition model achieved an accuracy of 86.8% and was validated against user preferences captured through questionnaires. Results demonstrate that visitors prefer areas featuring cultural landmarks and natural elements, while spaces dominated by human activity and transportation infrastructure are less favored. Key landscape elements, such as signage, thematic sculptures, brand logos, and trees, were identified as highly preferred features within the park. While EDA experiments revealed significant variations in physiological responses across different spatial settings, no strong correlation was observed between EDA indicators and subjective questionnaire scores. This integrative approach enables a comprehensive, objective assessment of landscape perception, providing a data-driven, user-centered framework for improving landscape design in cultural and creative industrial parks.