{"title":"智能监测和人工神经网络建模揭示了孔隙水压力、降雨量和风速对树木稳定性的综合影响","authors":"Nisa Leksungnoen , Apiniti Jotisankasa , Ponthep Meunpong , Washirawat Praphatsorn , Korakot Tanyacharoen , Podpakhon Toikaew","doi":"10.1016/j.ufug.2025.129072","DOIUrl":null,"url":null,"abstract":"<div><div>Tree stability in tropical urban environments is significantly influenced by heavy rainfall, strong winds, and soil conditions. However, the role of pore-water pressure (PWP) in the root zone is often overlooked in monitoring efforts. This study investigates the stability of a leaning tree subjected to heavy rain and strong winds, using smart sensors to measure tilt, tilt rate (hourly), root-zone PWP, rainfall, and wind speed. Results revealed a notable correlation between tilt and PWP (r = 0.75), emphasizing the role of soil saturation in weakening root anchorage. Tilt rate showed a moderate correlation with rainfall (r = 0.49) and a weaker correlation with wind speed (r = 0.25) and the combined effect of rainfall and PWP (r = 0.30). An artificial neural network (ANN) model, trained with rainfall, wind speed, pore-water pressure (PWP), and rainfall × PWP as inputs to predict tilt and tilt rate, achieved a mean squared error (MSE) of 0.0020 and an R² of 0.526. These results highlight the critical role of root-zone PWP in tree stability and demonstrate the potential of predictive models based on widely available environmental data and tensiometer measurement for early warning of tree instability in urban environments.</div></div>","PeriodicalId":49394,"journal":{"name":"Urban Forestry & Urban Greening","volume":"113 ","pages":"Article 129072"},"PeriodicalIF":6.7000,"publicationDate":"2025-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Smart monitoring and ANN modeling reveal the combined influence of pore-water pressure, rainfall, and wind speed on tree stability\",\"authors\":\"Nisa Leksungnoen , Apiniti Jotisankasa , Ponthep Meunpong , Washirawat Praphatsorn , Korakot Tanyacharoen , Podpakhon Toikaew\",\"doi\":\"10.1016/j.ufug.2025.129072\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Tree stability in tropical urban environments is significantly influenced by heavy rainfall, strong winds, and soil conditions. However, the role of pore-water pressure (PWP) in the root zone is often overlooked in monitoring efforts. This study investigates the stability of a leaning tree subjected to heavy rain and strong winds, using smart sensors to measure tilt, tilt rate (hourly), root-zone PWP, rainfall, and wind speed. Results revealed a notable correlation between tilt and PWP (r = 0.75), emphasizing the role of soil saturation in weakening root anchorage. Tilt rate showed a moderate correlation with rainfall (r = 0.49) and a weaker correlation with wind speed (r = 0.25) and the combined effect of rainfall and PWP (r = 0.30). An artificial neural network (ANN) model, trained with rainfall, wind speed, pore-water pressure (PWP), and rainfall × PWP as inputs to predict tilt and tilt rate, achieved a mean squared error (MSE) of 0.0020 and an R² of 0.526. These results highlight the critical role of root-zone PWP in tree stability and demonstrate the potential of predictive models based on widely available environmental data and tensiometer measurement for early warning of tree instability in urban environments.</div></div>\",\"PeriodicalId\":49394,\"journal\":{\"name\":\"Urban Forestry & Urban Greening\",\"volume\":\"113 \",\"pages\":\"Article 129072\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2025-09-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Urban Forestry & Urban Greening\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1618866725004066\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL STUDIES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Urban Forestry & Urban Greening","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1618866725004066","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
Smart monitoring and ANN modeling reveal the combined influence of pore-water pressure, rainfall, and wind speed on tree stability
Tree stability in tropical urban environments is significantly influenced by heavy rainfall, strong winds, and soil conditions. However, the role of pore-water pressure (PWP) in the root zone is often overlooked in monitoring efforts. This study investigates the stability of a leaning tree subjected to heavy rain and strong winds, using smart sensors to measure tilt, tilt rate (hourly), root-zone PWP, rainfall, and wind speed. Results revealed a notable correlation between tilt and PWP (r = 0.75), emphasizing the role of soil saturation in weakening root anchorage. Tilt rate showed a moderate correlation with rainfall (r = 0.49) and a weaker correlation with wind speed (r = 0.25) and the combined effect of rainfall and PWP (r = 0.30). An artificial neural network (ANN) model, trained with rainfall, wind speed, pore-water pressure (PWP), and rainfall × PWP as inputs to predict tilt and tilt rate, achieved a mean squared error (MSE) of 0.0020 and an R² of 0.526. These results highlight the critical role of root-zone PWP in tree stability and demonstrate the potential of predictive models based on widely available environmental data and tensiometer measurement for early warning of tree instability in urban environments.
期刊介绍:
Urban Forestry and Urban Greening is a refereed, international journal aimed at presenting high-quality research with urban and peri-urban woody and non-woody vegetation and its use, planning, design, establishment and management as its main topics. Urban Forestry and Urban Greening concentrates on all tree-dominated (as joint together in the urban forest) as well as other green resources in and around urban areas, such as woodlands, public and private urban parks and gardens, urban nature areas, street tree and square plantations, botanical gardens and cemeteries.
The journal welcomes basic and applied research papers, as well as review papers and short communications. Contributions should focus on one or more of the following aspects:
-Form and functions of urban forests and other vegetation, including aspects of urban ecology.
-Policy-making, planning and design related to urban forests and other vegetation.
-Selection and establishment of tree resources and other vegetation for urban environments.
-Management of urban forests and other vegetation.
Original contributions of a high academic standard are invited from a wide range of disciplines and fields, including forestry, biology, horticulture, arboriculture, landscape ecology, pathology, soil science, hydrology, landscape architecture, landscape planning, urban planning and design, economics, sociology, environmental psychology, public health, and education.