Urban Trees and Hydrological Ecosystem Service: A Novel Approach to Analyzing the Relationship Between Landscape Structure and Runoff Reduction DOI Creative Commons
Vahid Amini Parsa, Mustafa Nur Istanbuly, Jakub Kronenberg

et al.

Environmental Management, Journal Year: 2023, Volume and Issue: 73(1), P. 243 - 258

Published: Aug. 26, 2023

Abstract Urban stormwater runoff has posed significant challenges in the face of urbanization and climate change, emphasizing importance trees providing reduction ecosystem services (RRES). However, sustainability RRES can be disturbed by urban landscape modification. Understanding impact structure on is crucial to manage landscapes effectively sustain supply RRES. So, this study developed a new approach that analyzes relationship between structural pattern Tabriz, Iran. The provision was estimated using i-Tree Eco model. Landscape structure-related metrics land use cover (LULC) were derived FRAGSTATS quantify structure. Stepwise regression analysis used assess results indicated throughout city, prevented 196854.15 m 3 annually. Regression models ( p ≤ 0.05) suggested could predicted measures related circumscribing circle metric (0.889 r 2 0.954) shape index = 0.983) LULC patches. findings also revealed regularity or given patches’ functions, which, turn, affects serve as proxies predict capacity for potential obtained models. This helps allocate suitable through optimizing management guidance

Language: Английский

Evaluating the association between morphological characteristics of urban land and pluvial floods using machine learning methods DOI
Jinyao Lin, Wenli Zhang, Youyue Wen

et al.

Sustainable Cities and Society, Journal Year: 2023, Volume and Issue: 99, P. 104891 - 104891

Published: Aug. 22, 2023

Language: Английский

Citations

50
Flood risk evaluation of the coastal city by the EWM-TOPSIS and machine learning hybrid method DOI
Ziyuan Luo, Jian Tian, Jian Zeng

et al.

International Journal of Disaster Risk Reduction, Journal Year: 2024, Volume and Issue: 106, P. 104435 - 104435

Published: March 28, 2024

Language: Английский

Citations

19
Can flood resilience of green-grey-blue system cope with future uncertainty? DOI
Dingkun Yin, Xiaoyue Zhang, Yihua Cheng

et al.

Water Research, Journal Year: 2023, Volume and Issue: 242, P. 120315 - 120315

Published: July 5, 2023

Language: Английский

Citations

27
Application and exploration of artificial intelligence technology in urban ecosystem-based disaster risk reduction: A scoping review DOI Creative Commons
Daixin Dai, Mingyang Bo,

Xiaosong Ren

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 158, P. 111565 - 111565

Published: Jan. 1, 2024

The impacts of natural hazards on urban areas are becoming more severe and frequent. As a leading theory resilient cities an international level, ecosystem-based disaster risk reduction (Eco-DRR) is crucial approach for (DRR) resilience. reasonable use artificial intelligence (AI) technology can effectively address the uncertainty problem faced in ecosystems hazard impacts. However, current research applying AI Eco-DRR still limited, evidence concepts interplay between not clear. We utilized PRISMA-ScR framework to survey analyze studies that apply Eco-DRR, ultimately selecting 76 scoping review. qualitatively analyzed case from 3 perspectives: risk, technology, identified spatiotemporal characteristics, objectives, algorithms, data source selected cases. Based findings, we conducted theoretical applied by organizing out logical relationship among perspectives. proposed discussed key points application practice: (1) scales types point aims Eco-DRR. (2) selection algorithms should align with objectives achieve (3) Data sources elements support Finally, summarized 4 approaches integrating traditional Disaster Risk Reduction using technology: ecosystem service, indicators, dynamic change prediction, green infrastructure (GI) construction. framework, progress, trend this field study provide basis reference which beneficial security

Language: Английский

Citations

12
A comprehensive framework for assessing the spatial drivers of flood disasters using an optimal Parameter-based geographical Detector–machine learning coupled model DOI Creative Commons

Luyi Yang,

Xuan Ji, Meng Li

et al.

Geoscience Frontiers, Journal Year: 2024, Volume and Issue: 15(6), P. 101889 - 101889

Published: July 11, 2024

Flood disasters pose serious threats to human life and property worldwide. Exploring the spatial drivers of flood on a macroscopic scale is great significance for mitigating their impacts. This study proposes comprehensive framework integrating driving-factor optimization interpretability, while considering heterogeneity. In this framework, Optimal Parameter-based Geographic Detector (OPGD), Recursive Feature Estimation (RFE), Light Gradient Boosting Machine (LGBM) models were utilized construct OPGD–RFE–LGBM coupled model identify essential driving factors simulate distribution disasters. The SHapley Additive ExPlanation (SHAP) interpreter was employed quantitatively explain mechanisms behind Yunnan Province, typical mountainous plateau area in Southwest China, selected implement proposed conduct case study. For purpose, disaster inventory 7332 historical events prepared, 22 potential related precipitation, surface environment, activity initially selected. Results revealed that Province exhibit high heterogeneity, with geomorphic zoning accounting 66.1% variation offers clear advantages over single LGBM identifying analyzing Moreover, simulation performance shows slight improvement (a 6% average decrease RMSE an increase 1% R2) even reduced factor data. Factor explanatory analysis indicated combination sets varied across different subregions; nevertheless, precipitation-related factors, such as precipitation intensity index (SDII), wet days (R10MM), 5-day maximum (RX5day), main controlling provides quantitative analytical at large scales significant offering reference management authorities developing macro-strategies prevention.

Language: Английский

Citations

9
A Bibliometric Review of Nature-Based Solutions on Urban Stormwater Management DOI Open Access
Jin Su, Mo Wang, Mohd Adib Mohammad Razi

et al.

Sustainability, Journal Year: 2023, Volume and Issue: 15(9), P. 7281 - 7281

Published: April 27, 2023

Urban stormwater management is a critical challenge facing cities globally, with natural-based solutions (NBS) emerging as promising approach for mitigating the impacts of urban runoff. This bibliometric review examined research trends and hot topics related to NBS management. The study utilized combination qualitative quantitative methods analyze 176 articles from Web Science database, covering period 2016 2022. Results showed that widely researched topic growing trend in publications recent years, led by United States, China, several European countries. majority were papers (82%) focus on environmental performance rather than social economic dimensions. Quantitative more frequently used articles, particularly statistical analysis/modeling. Interviews discussions most common method used. identified relevant countries, affiliations, authors, journals field. Furthermore, highlighted, including ecosystem services, climate change, sustainability. also emphasized future perspective should interdisciplinary collaborative research, scaling up mainstreaming NBS, exploring new ways integrating different disciplines stakeholders process. findings this provided insights into current state offer valuable information researchers, policymakers, practitioners field

Language: Английский

Citations

20
Modeling urban rail transit system resilience under natural disasters: A two-layer network framework based on link flow DOI
Ying Wang, Ou Zhao, Limao Zhang

et al.

Reliability Engineering & System Safety, Journal Year: 2023, Volume and Issue: 241, P. 109619 - 109619

Published: Aug. 31, 2023

Language: Английский

Citations

20
Future sea level rise exacerbates compound floods induced by rainstorm and storm tide during super typhoon events: A case study from Zhuhai, China DOI
Zhaoyang Zeng, Chengguang Lai,

Zhaoli Wang

et al.

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 911, P. 168799 - 168799

Published: Nov. 22, 2023

Language: Английский

Citations

20
The impact of connectivity in natural protected areas on the resilience of urban ecological networks: A research framework based on hierarchical disturbance scenario simulation DOI Creative Commons

Zhang Mengxian,

Jiaxin Li, Lina Wang

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 164, P. 112144 - 112144

Published: May 23, 2024

In the context of accelerating ecological fragmentation, it is urgent to enhance interconnectivity urban patches form a resilient network (EN). The construction Natural Protected Area (NPA) system proposed in 2019 latest strategy implemented by China protecting spaces. However, effectiveness this has not been adequately demonstrated. This study specifically analyzes concrete impacts natural protected area on resilience networks (ENs). economically developed Urban Agglomeration around Hangzhou Bay (UAHB) was chosen as an example for argumentation. Firstly, we utilized circuit theory construct EN consisting 173 sources and 401 corridors. Secondly, were categorized into three levels based their connectivity values. Finally, dynamic disturbance scenario simulation framework constructed evaluate impact NPA EN. results indicated that: (1) preceding 47% are crucial maintaining EN; (2) Compared with other spaces, NPAs have 38% 1100% greater effect first second-level sources, respectively, while its third-level 118% lower. innovatively investigates differential hierarchical areas unprotected environment.

Language: Английский

Citations

8
Assessing the influence of simulated environmental gradients on the spatial heterogeneity of landscape patterns in the Tibetan Plateau DOI
Jiamin Liu,

Xiutong Pei,

Wanyang Zhu

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 359, P. 120957 - 120957

Published: May 1, 2024

Language: Английский

Citations

6