Environmental Modelling & Software最新文献_第6页

A numerical modelling-supported digital twin for urban floods monitoring in typhoon or storm scenario 台风或风暴情景下城市洪水监测的数值模拟支持的数字孪生

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.2026.106870

Tangyao Ai , Liang Gao , Xianfei Yin , Haoxuan Du , Qingbiao Li , Hongcai Zhang

{"title":"A numerical modelling-supported digital twin for urban floods monitoring in typhoon or storm scenario","authors":"Tangyao Ai , Liang Gao , Xianfei Yin , Haoxuan Du , Qingbiao Li , Hongcai Zhang","doi":"10.1016/j.envsoft.2026.106870","DOIUrl":"10.1016/j.envsoft.2026.106870","url":null,"abstract":"<div><div>Digital twin enables participatory system assessment and decision-making, establishing bidirectional connections between virtual system and real-world urban operations. Nevertheless, its widespread implementation in the urban flood faces persistent barriers to incorporate physics-guided urban flooding prediction with a scalable visualization platform. This study proposes a high-fidelity hydrodynamic digital twin framework that combines real-time forecasting data visualization platform with a numerical urban flood model by proposing an interactive interface. The framework consists of (1) a data acquisition layer that consolidates various inputs into specialized databases, (2) a modeling layer that employs numerical simulations for high-resolution flood predictions, and (3) a visualization layer that transforms outputs into interpretable web formats. The framework enables users to upload rainfall and storm data through a web interface and initiate urban flooding simulation. It allows real-time prediction of urban floods under a designed storm or a tropical scenario. The feasibility of the framework is tested by applying it to the Macao Peninsula during typhoon Hato (2017). The integration of a numerical model into a digital twin creates an intelligent decision-support framework, enabling real-time hydrodynamic forecasting, and dynamic scenario visualization for urban floods.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106870"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145956762","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

Towards democratized flood risk management: An advanced AI assistant enabled by GPT-4 for enhanced interpretability and public engagement 走向民主化的洪水风险管理：由GPT-4支持的高级人工智能助手，以增强可解释性和公众参与

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2025-12-12 DOI: 10.1016/j.envsoft.2025.106821

Rafaela Martelo , Kimia Ahmadiyehyazdi , Ruo-Qian Wang

{"title":"Towards democratized flood risk management: An advanced AI assistant enabled by GPT-4 for enhanced interpretability and public engagement","authors":"Rafaela Martelo , Kimia Ahmadiyehyazdi , Ruo-Qian Wang","doi":"10.1016/j.envsoft.2025.106821","DOIUrl":"10.1016/j.envsoft.2025.106821","url":null,"abstract":"<div><div>Traditional flood risk communication fails to bridge the gap between complex technical data and the needs of the public, hindering effective response. This research addresses this gap by developing and validating a novel AI-powered assistant that uses GPT-4 to democratize flood risk information. Our core methodology includes a Retrieval-Augmented Generation (RAG) framework that synthesizes real-time flood warnings, geospatial data, and social vulnerability indices into clear, conversational responses. To validate its effectiveness, we conducted a mixed-methods evaluation, including a comparison across different GPT models. Key quantitative findings reveal that the assistant achieved high performance scores in general flood knowledge (5/5) and handling flash flood alerts (4.3/5). Response times averaged a rapid 12 s for non-function-calling queries, though more complex data retrieval tasks averaged 36 s, highlighting areas for optimization. Our comparison identified GPT-4o as the optimal model for balancing accuracy with response time. The broader implications of this work demonstrate that large language models can serve as powerful tools to translate complex environmental data for non-experts, paving the way for more equitable, engaging, and effective public participation in disaster risk management.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106821"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145732498","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

On generalization, language, interpretability and the future of geo-scientific machine learning 论地球科学机器学习的泛化、语言、可解释性和未来

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2025-12-12 DOI: 10.1016/j.envsoft.2025.106834

Hoshin V. Gupta

{"title":"On generalization, language, interpretability and the future of geo-scientific machine learning","authors":"Hoshin V. Gupta","doi":"10.1016/j.envsoft.2025.106834","DOIUrl":"10.1016/j.envsoft.2025.106834","url":null,"abstract":"<div><div>There are several types of generalization ability that we may wish our models to be capable of. All but the most basic of these require the representation to be suitably interpretable so that it can provide meaningful support for scenario analysis, scientific reasoning, and decision making under system non-stationarity and model transfer. However interpretability of a model can only be meaningfully understood in the context of the ‘<em>language’</em> used for its construction. In this regard it is important to recognize that, while machine-learning-based (MLB) models tend to prioritize accuracy and precision (in service of predictive performance) and physics-based (PB) models tend to emphasize physical/geo-scientific interpretability (in service of understanding), their learned representations are actually based in related but somewhat different languages, levels of linguistic abstraction, and grammatical rules.</div><div>Importantly, these differences are not fundamentally necessary. It is my opinion that the future of geo-scientific ML need not compromise accuracy and precision to achieve improved understanding. Instead, we must develop “<em>telescopic</em>” hierarchical representations that prioritize “<em>learning from data</em>” at their fundamental levels, while simultaneously enabling “<em>geo-scientific abstraction</em>” so that higher-level interpretable and understandable representations can be extracted by directed compression. Ultimately, the geosciences will benefit from a specific kind of “<em>interpretable generative modeling</em>” that can learn how to construct causal and/or understandable representations of the underlying physical data generating processes from data, and that can facilitate the kind of hierarchical, multi-level abstraction processes alluded to above.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106834"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145732499","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

Integrating field surveys and visual interpretation to enhance CSLE model of soil erosion response to LUCC in Southwest China 结合野外调查和目视解译改进西南地区土地利用变化对土壤侵蚀响应的CSLE模型

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2025-12-11 DOI: 10.1016/j.envsoft.2025.106831

Rui Tan , Geng Guo , Kaiwen Huang , Zicheng Liu , Chaorui Wang , Jie Lin , Yizhong Huang

{"title":"Integrating field surveys and visual interpretation to enhance CSLE model of soil erosion response to LUCC in Southwest China","authors":"Rui Tan , Geng Guo , Kaiwen Huang , Zicheng Liu , Chaorui Wang , Jie Lin , Yizhong Huang","doi":"10.1016/j.envsoft.2025.106831","DOIUrl":"10.1016/j.envsoft.2025.106831","url":null,"abstract":"<div><div>Absence of high-resolution spatial data on Soil and water conservation measures (SWCM) hampers the accuracy of erosion modeling, particularly in regions with complex terrain and frequent land use/cover changes (LUCC). This study integrated multi-source remote sensing (RS), field surveys, and visual interpretation to map SWCM distribution and estimate soil erosion. It further quantified the response of erosion to LUCC. Soil erosion conditions have improved, with an average annual decrease in erosion modulus of 0.51 % and a total reduction of approximately 9.5 × 10<sup>5</sup> t. LUCC was characterized by cropland reduction, expansion of garden, and increasing landscape fragmentation. Garden development enhances economic returns but may exacerbate erosion when vegetation cover is insufficient. Nonetheless, under similar conservation intensity, slope, and elevation, conversion of cropland or bare land to woodland or garden effectively reduces erosion. The findings provide a new perspective for evaluating soil erosion in fragmented mountainous landscapes with complex management measures.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106831"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145732500","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

Origin–destination specific traffic emissions and data-driven NO2 pollution-optimal routing in urban environments 城市环境下交通排放与数据驱动的NO2污染优化路径

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2025-12-29 DOI: 10.1016/j.envsoft.2025.106813

Samantha Ivings , James A. King , Alexander Roocroft , Patricio Ortiz , Toby Willis , Maria Val Martin , Hadi Arbabi , Giuliano Punzo

{"title":"Origin–destination specific traffic emissions and data-driven NO2 pollution-optimal routing in urban environments","authors":"Samantha Ivings , James A. King , Alexander Roocroft , Patricio Ortiz , Toby Willis , Maria Val Martin , Hadi Arbabi , Giuliano Punzo","doi":"10.1016/j.envsoft.2025.106813","DOIUrl":"10.1016/j.envsoft.2025.106813","url":null,"abstract":"<div><div>Urban air pollution from traffic poses serious public health risks. Pollution exposure can be minimised through traffic routing systems; these currently rely on detailed local environmental information, which is often difficult to collect or generalise within and across cities. Here, we introduce a new data-driven approach for ready application to different urban road networks by directly relating NO<sub>2</sub> to traffic density in a time-dependent and weather-corrected manner. We demonstrate this application by comparing pollution-optimal routings, using our novel direct NO<sub>2</sub>/density approach, to the conventional traffic assignment minimising user travel time, in a case study of Sheffield, UK. There, we find user-optimal traffic flows result in 21% higher total NO<sub>2</sub> concentrations than pollution-optimal routings, while saving only 9% in total travel time: an average of 0.3 min per road. Our generalisable framework offers a practical alternative to current emissions-based models for air-quality-aware traffic control and environmental zone planning.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106813"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145894782","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

Effects of rising CO2 concentrations on water dynamics and yields for C3 and C4 crops under both irrigated and dryland conditions in the Texas High Plains 德州高平原灌溉和旱地条件下CO2浓度上升对C3和C4作物水分动态和产量的影响

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2026-01-06 DOI: 10.1016/j.envsoft.2026.106859

Na Wen , Junyu Qi , Yue Wang , Gary W. Marek , Srinivasulu Ale , Puyu Feng , De Li Liu , Raghavan Srinivasan , Yong Chen

{"title":"Effects of rising CO2 concentrations on water dynamics and yields for C3 and C4 crops under both irrigated and dryland conditions in the Texas High Plains","authors":"Na Wen , Junyu Qi , Yue Wang , Gary W. Marek , Srinivasulu Ale , Puyu Feng , De Li Liu , Raghavan Srinivasan , Yong Chen","doi":"10.1016/j.envsoft.2026.106859","DOIUrl":"10.1016/j.envsoft.2026.106859","url":null,"abstract":"<div><div>Elevated CO<sub>2</sub> affect crop growth and water dynamics by altering stomatal conductance (g<sub>s</sub>, m s<sup>−1</sup>) and leaf area index (LAI). However, the effects on C3 and C4 crops under different water conditions remain unclear. This study employed a modified SWAT model, incorporating a nonlinear g<sub>s</sub> equation and a LAI function, to evaluate elevated CO<sub>2</sub> impacts on actual evapotranspiration (ET), irrigation, and crop yields. Results indicated that solely elevated CO<sub>2</sub> reduced ET by 6.8%–20.7% under irrigated conditions, but had no apparent effect on ET under dryland conditions. Elevated CO<sub>2</sub> enhanced crop yields, with its effect more pronounced under dryland conditions. Under future climate scenarios (2041–2100), ET increased by 6.7%–9.4% for dryland crops, while irrigated winter wheat ET declined by 0.6%–8.6%. Future crop yields generally increased, except for irrigated sorghum, which declined by up to 11.9% under high emission scenario. C3 crops were more positive response to future climate than C4 crops.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106859"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145903155","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

Meteorological observation research based on an improved EfficientNetV2 model 基于改进的EfficientNetV2模型的气象观测研究

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2025-12-16 DOI: 10.1016/j.envsoft.2025.106835

Haozheng Yin , Yu Cao , Linlin Liu , Dan Chen , Qiong Zhang

{"title":"Meteorological observation research based on an improved EfficientNetV2 model","authors":"Haozheng Yin , Yu Cao , Linlin Liu , Dan Chen , Qiong Zhang","doi":"10.1016/j.envsoft.2025.106835","DOIUrl":"10.1016/j.envsoft.2025.106835","url":null,"abstract":"<div><div>Meteorological observation plays a critical role in ensuring safety, promoting agricultural development, optimizing energy management, and achieving sustainable development. Although image recognition methods based on deep learning have made notable progress, existing models still face challenges in complex weather scenarios, such as insufficient feature extraction, inadequate utilization of scale information, and poor robustness to interference. To address these issues, this study proposes a novel deep learning model based on EfficientNetV2-CBAM-PANet. By leveraging transfer learning, the training efficiency and accuracy of the EfficientNetV2 pretrained model are enhanced. The integration of the CBAM attention mechanism improves the perception of meteorological features, while the PANet structure enables multi-level feature fusion. Experimental results demonstrate that the proposed model achieves a recognition accuracy of 97.6% on a self-constructed dataset, indicating strong classification capability across various weather conditions and providing useful insights for future research in weather image classification and forecasting.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106835"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785086","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

From vegetation classification to vegetation zonation: a multi-source modelling framework for evergreen broad-leaved forests in complex terrain 从植被分类到植被区带：复杂地形常绿阔叶林多源建模框架

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2025-11-22 DOI: 10.1016/j.envsoft.2025.106780

Shiqi Zhang , Peihao Peng , Ning Li , Juan Wang , Xuefeng Peng , Zhaozhi Luo

{"title":"From vegetation classification to vegetation zonation: a multi-source modelling framework for evergreen broad-leaved forests in complex terrain","authors":"Shiqi Zhang , Peihao Peng , Ning Li , Juan Wang , Xuefeng Peng , Zhaozhi Luo","doi":"10.1016/j.envsoft.2025.106780","DOIUrl":"10.1016/j.envsoft.2025.106780","url":null,"abstract":"<div><div>Fine-scale vegetation zoning of evergreen broad-leaved forests (EBFs) is essential for ecological understanding and forest management, yet expert-led schemes often under-represent environmental complexity. This study proposes a multi-source modelling framework that bridges vegetation classification and zonation, demonstrated in Sichuan Province, China. Vegetation classification data for primary units were derived from Landsat-8 and Sentinel-1 imagery using a hierarchical multi-label network, and for secondary units from kernel density estimation of constructive species. A vegetation–environment relationship model then quantifies the influence of climate, topography and soil, converting discrete classes into the continuous indicators required for zoning. Finally, zoning thresholds were defined using confidence interval and Jenks natural breaks, and boundaries refined through upscaling and Gaussian filtering. The resulting map delineates three vegetation areas and fifteen vegetation districts, capturing spatial heterogeneity across the Sichuan Basin-Tibetan Plateau ecotone. The framework provides a replicable tool for vegetation zoning in complex mountain systems.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106780"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145575240","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

HR-MM Segformer: Enhancing land use and land cover semantic segmentation through transformer-based multisource remote sensing feature fusion HR-MM分割器：基于变压器的多源遥感特征融合增强土地利用和土地覆盖语义分割

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.2025.106848

Junfu Fan , Zongwen Shi , Yujie Du , Can Zhuang

{"title":"HR-MM Segformer: Enhancing land use and land cover semantic segmentation through transformer-based multisource remote sensing feature fusion","authors":"Junfu Fan , Zongwen Shi , Yujie Du , Can Zhuang","doi":"10.1016/j.envsoft.2025.106848","DOIUrl":"10.1016/j.envsoft.2025.106848","url":null,"abstract":"<div><div>Automatic land use and land cover (LULC) semantic segmentation is constrained by spectral confusion and the semantic gap inherent in independent-branch multisource and multisensor (MM) data fusion architectures. To address these limitations, this study proposes HR-MM SegFormer, a framework incorporating a unified transformer encoder. Unlike conventional dual-stream approaches, the architecture projects heterogeneous high-resolution (HR) optical imagery and MM auxiliary data (multispectral/DSM) into a shared semantic manifold via a feature correction (FC) layer. Additionally, a multimodal cross-attention fusion (MCAF) module dynamically retrieves complementary spectral and geometric contexts guided by HR spatial structures. Experimental evaluations of the HR-MS LULC and HR-DSM Potsdam datasets yield mean intersection over union (mIoU) scores of 88.50 % and 87.84 %, respectively. These results correspond to improvements of 8.89 % and 12.67 % over single-modal baselines, accompanied by a 6.3 % increase in computational overhead. This study substantiates that the unified full-attention paradigm bridges cross-modal disparities, providing an effective solution for fine-grained Earth observations.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106848"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145845131","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

Re-Emission: A free open-source software for estimating, reporting, and visualizing greenhouse gas emissions from reservoirs 重新排放：一个免费的开源软件，用于估计、报告和可视化水库的温室气体排放

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.2025.106850

Tomasz Janus , Christopher Barry , Xingxing Zhang , Jaise Kuriakose

引用次数: 0