Environmental Modelling & Software最新文献_第8页

Digital-twin tool for a drinking water distribution system using augmented reality and EPANET 使用增强现实和EPANET的饮用水分配系统的数字孪生工具

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2025-12-10 DOI: 10.1016/j.envsoft.2025.106829

Ji-Ye Park , Kwang-Ju Kim , Minhyuk Jeung , In-Su Jang , Jung-Won Yu , Mi-Seon Kang , Hyun-Su Bae , Changyoon Jeong , Sang-Soo Baek

{"title":"Digital-twin tool for a drinking water distribution system using augmented reality and EPANET","authors":"Ji-Ye Park , Kwang-Ju Kim , Minhyuk Jeung , In-Su Jang , Jung-Won Yu , Mi-Seon Kang , Hyun-Su Bae , Changyoon Jeong , Sang-Soo Baek","doi":"10.1016/j.envsoft.2025.106829","DOIUrl":"10.1016/j.envsoft.2025.106829","url":null,"abstract":"<div><div>Urban water distribution networks are typically represented as 2D models using points and lines, which fail to capture spatial complexity and structural detail. To address these limitations, this study develops an augmented reality (AR) toolbox integrated with a digital twin (DT) framework. The motivation behind this research lies in the need for more intuitive, spatially aware visualization tools to support water infrastructure management and public understanding. AR enables the overlay of virtual content onto real environments, enhancing interpretation of pipe structures and simulation outcomes. A 3D water distribution system was generated from EPANET model data, and a mobile AR application was developed. The system visualizes pollutant dispersion and flow rates through spatially aligned 3D pipe objects. Simulation results are mapped to real-world coordinates, offering enhanced clarity and user engagement. The system is designed to be user-friendly and accessible to nontechnical stakeholders, enabling real-time, location-based interaction with complex water network data.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106829"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145732504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Artificial intelligence enhanced litter pollution mapping: Integrating citizen science with geospatial and social data 人工智能增强了垃圾污染制图：将公民科学与地理空间和社会数据相结合

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2025-12-09 DOI: 10.1016/j.envsoft.2025.106823

Hadiseh Rezaei , Keiron. P. Roberts , Farzad Arabikhan , Steve Fletcher , Antaya March , Fay Couceiro , David Bacon , David. J. Hutchinson , John. B. Williams

{"title":"Artificial intelligence enhanced litter pollution mapping: Integrating citizen science with geospatial and social data","authors":"Hadiseh Rezaei , Keiron. P. Roberts , Farzad Arabikhan , Steve Fletcher , Antaya March , Fay Couceiro , David Bacon , David. J. Hutchinson , John. B. Williams","doi":"10.1016/j.envsoft.2025.106823","DOIUrl":"10.1016/j.envsoft.2025.106823","url":null,"abstract":"<div><div>Citizen science provides extensive litter data, but inconsistent recording limits its use in environmental modelling and decision making. We present a scalable AI-assisted framework that harmonises two major UK datasets, Marine Debris Tracker and Litterati, into a unified, spatially detailed resource. Over 460,000 records (2015–2024) were standardised through a rules-to-embeddings-to-LLM cascade (schema-constrained Llama 3.1) for material classification. Items were clustered by material using K-means at a validated 200 m scale and linked to OpenStreetMap amenities within 500 m to identify accumulation hotspots and contextual features such as parks or transport hubs. Plastic dominated nationally, accounting for 71 percent of entries, while integration with UK Census 2021 data enabled demographic and health analyses where plastic remained highest (68.9 percent). This reproducible framework demonstrates how artificial intelligence can harmonise citizen-science data and enhance spatial modelling to inform targeted pollution prevention and sustainable waste-management strategies.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106823"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145732505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Coupling a micro-genetic algorithm with RegCM5 for improving extreme precipitation simulations over Southeast Asia 微遗传算法与RegCM5耦合改进东南亚极端降水模拟

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2026-01-10 DOI: 10.1016/j.envsoft.2026.106871

Zixuan Zhou , Ji Won Yoon , Thanh Nguyen-Xuan , Jina Hur , Seon Ki Park , Eun-Soon Im

{"title":"Coupling a micro-genetic algorithm with RegCM5 for improving extreme precipitation simulations over Southeast Asia","authors":"Zixuan Zhou , Ji Won Yoon , Thanh Nguyen-Xuan , Jina Hur , Seon Ki Park , Eun-Soon Im","doi":"10.1016/j.envsoft.2026.106871","DOIUrl":"10.1016/j.envsoft.2026.106871","url":null,"abstract":"<div><div>Regional climate models (RCMs) are essential for producing fine-scale climate information, but their effectiveness is highly sensitive to the combination of physical parameterizations and optimal settings of key parameters. To tackle this problem, this study develops a coupled modeling system that integrates a micro-genetic algorithm (μGA) with the Regional Climate Model version 5 (RegCM5), focusing on optimizing parameters in the Tiedtke convection scheme, crucial for precipitation simulations. Using the benchmarking version of RegCM5 for Southeast Asia, we aim to identify the optimal parameter set that enhances performance for three extreme precipitation events. The evaluation of this parameter set is then conducted by simulating six additional extreme events. Results show that simulations with optimized parameters improve both precipitation and temperature compared to the default model, significantly reducing biases, particularly over ocean regions. Our coupled RegCM5-μGA system will aid the broader RegCM5 community in enhancing model performance in their target regions.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106871"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145956763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An efficient multi-objective optimization method for inter-basin water diversion based on the rotation vector method for exploring the convex objective space 基于旋转矢量法探索凸目标空间的高效跨流域调水多目标优化方法

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2026-01-08 DOI: 10.1016/j.envsoft.2026.106858

Zekun Li , Bin Xu , Ping-an Zhong , Jiaying Tan , Ran Mo , Xinrong Wang , Zichen Ren , Guoqing Wang , Jianyun Zhang , Jiangyuan Li , Scott E. Boyce

{"title":"An efficient multi-objective optimization method for inter-basin water diversion based on the rotation vector method for exploring the convex objective space","authors":"Zekun Li , Bin Xu , Ping-an Zhong , Jiaying Tan , Ran Mo , Xinrong Wang , Zichen Ren , Guoqing Wang , Jianyun Zhang , Jiangyuan Li , Scott E. Boyce","doi":"10.1016/j.envsoft.2026.106858","DOIUrl":"10.1016/j.envsoft.2026.106858","url":null,"abstract":"<div><div>Inter-basin water diversion systems involve multiple sources, users, and objectives with complex interrelations and numerous decision variables. Classical <span><math><mrow><mi>ε</mi></mrow></math></span>-constraint method often produce infeasible or redundant solutions in multi-objective optimization. To address this, the limitations of the classical <span><math><mrow><mi>ε</mi></mrow></math></span>-constraint method are analyzed, and long-term water diversion models with convex objectives are reformulated as convex programming problems. Based on convex programming characteristics, a rotation vector method is proposed to explore the boundary range of the objective space and optimize <span><math><mrow><mi>ε</mi></mrow></math></span>-constraint threshold combinations, reducing infeasibility and redundancy. The method is applied to testing functions and the South-to-North Water Diversion Eastern Route Project in China, targeting minimization of water shortage, diversion volume, and ecological water supplementation. Results indicate that the main conflicts arise from competition between water supply and ecological demands. Compared with the classical <span><math><mrow><mi>ε</mi></mrow></math></span>-constraint method, the proposed algorithm increases the Pareto set hypervolume by 35 % and decreases spacing by 15 %, enhancing diversity and uniformity.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106858"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145956767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AI-driven knowledge synthesis for food web parameterisation 人工智能驱动的食物网参数化知识综合

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2026-01-07 DOI: 10.1016/j.envsoft.2026.106865

Scott Spillias , Elizabeth A. Fulton , Fabio Boschetti , Cathy Bulman , Joanna Strzelecki , Rowan Trebilco

{"title":"AI-driven knowledge synthesis for food web parameterisation","authors":"Scott Spillias , Elizabeth A. Fulton , Fabio Boschetti , Cathy Bulman , Joanna Strzelecki , Rowan Trebilco","doi":"10.1016/j.envsoft.2026.106865","DOIUrl":"10.1016/j.envsoft.2026.106865","url":null,"abstract":"<div><div>We introduce a proof-of-concept framework, Synthesizing Parameters for Ecosystem modelling with LLMs (SPELL), that automates species grouping and diet matrix generation to accelerate food web construction for ecosystem models. SPELL retrieves species lists, classifies them into functional groups, and synthesizes trophic interactions by integrating global biodiversity databases (e.g., FishBase, GLOBI), species interaction repositories, and optionally curated local knowledge using Large Language Models (LLMs). We validate the approach through a marine case study across four Australian regions, achieving high reproducibility in species grouping (<span><math><mo><</mo></math></span>99.7%) and moderate consistency in trophic interactions (51%–59%). Comparison with an expert-derived food web for the Great Australian Bight indicates strong but incomplete ecological accuracy: 92.6% of group assignments were at least partially correct and 82% of trophic links were identified. Specialized groups such as benthic organisms, parasites, and taxa with variable feeding strategies remain challenging. These findings highlight the importance of expert review for fine-scale accuracy and suggest SPELL is a generalizable tool for rapid prototyping of trophic structures in marine and potentially non-marine ecosystems.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106865"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145956829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

GeoClimate intelligence platform: A web-based framework for environmental data analysis 地理气候情报平台：一个基于网络的环境数据分析框架

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2025-12-13 DOI: 10.1016/j.envsoft.2025.106826

Saurav Bhattarai , Nawa Raj Pradhan , Rocky Talchabhadel

{"title":"GeoClimate intelligence platform: A web-based framework for environmental data analysis","authors":"Saurav Bhattarai , Nawa Raj Pradhan , Rocky Talchabhadel","doi":"10.1016/j.envsoft.2025.106826","DOIUrl":"10.1016/j.envsoft.2025.106826","url":null,"abstract":"<div><div>Environmental science education faces a critical barrier: programming requirements prevent students, novice researchers, and domain experts from accessing planetary-scale datasets. This study presents the GeoClimate Intelligence Platform, a web-based framework powered by Google Earth Engine (GEE) that eliminates programming barriers while maintaining research-grade analytical capabilities. The platform comprises five integrated modules: GeoData Explorer for climate dataset access, Climate Analytics implementing 20+ ETCCDI-compliant climate indices, Hydrology Analyzer for precipitation analysis and return periods, Product Selector for dataset validation, and Data Visualizer for interactive analysis. This modular design supports integrated workflows while maintaining analytical independence across specialized functions. Development was motivated by workshops where students found programming barriers insurmountable despite strong motivation. Educational validation through university coursework demonstrated effectiveness. Performance evaluation shows robust scalability from educational to research-scale applications. The platform requires only a GEE account and operates through web browsers, eliminating software installation. This accessibility transformation enables broader participation in data-driven environmental problem-solving with scientific rigor, democratizing sophisticated environmental analysis for educational and research communities.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106826"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145732496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PyDRGHT: A comprehensive python package for drought analysis pydright：用于干旱分析的全面Python包

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2025-12-24 DOI: 10.1016/j.envsoft.2025.106847

Tolga Barış Terzi

引用次数: 0

A distributed data-driven system for dynamic wildfire monitoring and forecasting 用于动态野火监测和预报的分布式数据驱动系统

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2026-01-01 DOI: 10.1016/j.envsoft.2026.106854

Mengxia Zha , Zheng Wang , Jie Ji , Jiping Zhu

引用次数: 0

Comment on Williams (2025): “Friends don't let friends use NSE or KGE for hydrologic model accuracy evaluation: A rant with data and suggestions for better practice” 评论：“朋友不让朋友使用NSE或KGE来评估水文模型的精度：一篇关于数据和更好实践建议的评论”

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2026-01-09 DOI: 10.1016/j.envsoft.2026.106869

Martyn P. Clark , Wouter J.M. Knoben , Diana Spieler , Gaby J. Gründemann , Cyril Thébault , Nicolás A. Vásquez , Andrew W. Wood , Yalan Song , Chaopeng Shen , Shaun Carney , Katie van Werkhoven

{"title":"Comment on Williams (2025): “Friends don't let friends use NSE or KGE for hydrologic model accuracy evaluation: A rant with data and suggestions for better practice”","authors":"Martyn P. Clark , Wouter J.M. Knoben , Diana Spieler , Gaby J. Gründemann , Cyril Thébault , Nicolás A. Vásquez , Andrew W. Wood , Yalan Song , Chaopeng Shen , Shaun Carney , Katie van Werkhoven","doi":"10.1016/j.envsoft.2026.106869","DOIUrl":"10.1016/j.envsoft.2026.106869","url":null,"abstract":"<div><div>Williams (2025), hereafter W25, raises valid concerns about the widespread use of the Nash–Sutcliffe Efficiency (NSE) and Kling–Gupta Efficiency (KGE) metrics in hydrologic model evaluation, arguing that these skill scores confound model accuracy with flow variability and should be replaced by error-based metrics such as the Root Mean Squared Error (RMSE) and the Mean Absolute Error (MAE). While we agree that model evaluation often lacks critical interpretation, we disagree that abandoning skill scores offers a constructive path forward. In this commentary, we discuss three main limitations in the W25 paper. First, we contend that W25 gives little attention to the broader literature on hydrologic model evaluation, leaving its recommendations weakly grounded in existing research. Second, we note that W25's recommendation to replace skill scores with error-based metrics such as RMSE does not resolve the underlying issue: both skill scores and error-based metrics conflate spatial variations in model accuracy with variations in flow variability. Third, we suggest that W25 overlooks the value of NSE and KGE in supporting standardized test environments that enable consistent model comparison. More generally, we argue that the W25 paper points the field in less productive directions for future research – simply replacing NSE and KGE with error-based metrics does not help the community address the core challenges in hydrologic model evaluation.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106869"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145956768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A coupled land use change-ecohydrological model for multi-seasonal arid agricultural systems: an Egyptian case study 多季节干旱农业系统的土地利用变化-生态水文耦合模型：埃及案例研究

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2025-12-26 DOI: 10.1016/j.envsoft.2025.106845

Aimen Sattar , Simon Moulds , Calum Brown , Mark Rounsevell , Peter Alexander

{"title":"A coupled land use change-ecohydrological model for multi-seasonal arid agricultural systems: an Egyptian case study","authors":"Aimen Sattar , Simon Moulds , Calum Brown , Mark Rounsevell , Peter Alexander","doi":"10.1016/j.envsoft.2025.106845","DOIUrl":"10.1016/j.envsoft.2025.106845","url":null,"abstract":"<div><div>Modelling interactions between climate, water, crops, and human decision-making requires coupling of biophysical and socioeconomic processes to model outcomes and explore potential futures. This study presents a novel coupled model of land-use change and ecohydrological processes in arid agricultural systems. The model links SWAT+, which simulates ecohydrological processes, including crop growth and irrigation water use, with CRAFTY, an agent-based framework that allocates land according to agent characteristics and resource conditions. Egypt is used as a case study where climate and socioeconomic stressors constrain agricultural production. The coupling captures how shifts in potential yields, driven by elevated CO<sub>2</sub> and warming, shape land-use change. Crop yields vary by crop and scenario, with the largest gains – and declines – under high-emission futures, while water use efficiency consistently improves, especially at higher CO<sub>2</sub> concentrations. Relying on open global datasets, the model provides a transferable approach for exploring climate adaptation in data-scarce, water-limited regions.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106845"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145845134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0