Environmental Modelling & Software最新文献_第5页

evapoRe: An R-based application for exploratory data analysis of evapotranspiration 蒸散发：一个基于r的探索性数据分析应用程序

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-03-01 Epub Date: 2026-01-29 DOI: 10.1016/j.envsoft.2026.106884

Akbar Rahmati Ziveh , Mijael Rodrigo Vargas Godoy , Vishal Thakur , Johanna R. Thomson , Martin Hanel , Yannis Markonis

{"title":"evapoRe: An R-based application for exploratory data analysis of evapotranspiration","authors":"Akbar Rahmati Ziveh , Mijael Rodrigo Vargas Godoy , Vishal Thakur , Johanna R. Thomson , Martin Hanel , Yannis Markonis","doi":"10.1016/j.envsoft.2026.106884","DOIUrl":"10.1016/j.envsoft.2026.106884","url":null,"abstract":"<div><div>Evapotranspiration (ET) datasets derived from satellites, hydrological models, and reanalyses each have distinct strengths and limitations. Relying on a single source can bias interpretations. To address this, we present evapoRe, an R package for efficient access, visualization, and analysis of ET and potential evapotranspiration (PET) across spatial and temporal scales. evapoRe includes 22 homogenized datasets (18 ET, 4 PET) and six supporting datasets for PET estimations, covering 1948–2023 at 0.25° resolution and daily to annual scales. It also includes 12 PET estimation methods, from empirical to physically based. We demonstrate evapoRe’s capabilities through: (i) global evaluation with FLUXNET, (ii) regional analyses over the Mediterranean, (iii) case studies in Spain for drought and extremes, and (iv) an Iberian Peninsula assessment for ET product benchmarking. By unifying datasets and methods, evapoRe offers a flexible, accessible tool to support diverse research on land–atmosphere interactions and enable robust ET and PET analysis.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"198 ","pages":"Article 106884"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146072498","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

Operational digital twin for multi-hazard coastal flood prediction with adaptive learning: Real-time performance in the Chesapeake Bay 基于自适应学习的多灾种海岸洪水预报的可操作数字孪生：切萨皮克湾的实时性能

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-03-01 Epub Date: 2026-01-23 DOI: 10.1016/j.envsoft.2026.106891

Paul Magoulick

{"title":"Operational digital twin for multi-hazard coastal flood prediction with adaptive learning: Real-time performance in the Chesapeake Bay","authors":"Paul Magoulick","doi":"10.1016/j.envsoft.2026.106891","DOIUrl":"10.1016/j.envsoft.2026.106891","url":null,"abstract":"<div><div>Coastal flooding threatens growing populations where compound hazards amplify risks. This study presents a proof-of-concept operational digital twin for single-location flood prediction at Annapolis in the Chesapeake Bay, integrating real-time NOAA and USGS data. An ensemble of Random Forest, XGBoost, Gradient Boosting, and LSTM models achieves RMSE = 0.043 ft with R<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span> = 0.997 for short-term predictions, validated across 508,000 records and 369 extreme events over six years. Strong short-term accuracy largely reflects tidal autocorrelation in this semi-enclosed estuarine system. Feature importance shows 98.9% of predictive power derives from three water-level persistence variables, enabling efficient deployment. An empirical correction factor (0.87) calibrates predictions to local conditions. Key limitations include single-site validation without spatial inundation capability and no major hurricane landfall during the study period. The system complements physics-based models such as NOAA’s STOFS, which provide essential spatial detail and process understanding. The open-source implementation enables replication and community evaluation.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"198 ","pages":"Article 106891"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146033917","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

Multi-source uncertainty quantification of water quality index models based on two-dimensional Monte Carlo simulation 基于二维蒙特卡罗模拟的水质指标模型多源不确定性量化

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2026-01-05 DOI: 10.1016/j.envsoft.2026.106860

Xizhi Nong , Jiaojiao Tian , Lihua Chen , Jiahua Wei

引用次数: 0

Data-driven parameterization of SWAT+ reservoir module without access to operation rules 无操作规则的SWAT+油藏模块数据驱动参数化

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2025-12-25 DOI: 10.1016/j.envsoft.2025.106852

S. Sreeraj , P. Athira , Kristin Peters , Jens Kiesel

引用次数: 0

A coupled Darcy–Richards framework for hydrological modeling of permeable pavements, green roofs, and bioretention systems 一个耦合的达西-理查兹框架，用于透水路面，绿色屋顶和生物保持系统的水文建模

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2025-11-07 DOI: 10.1016/j.envsoft.2025.106766

Marcus Nóbrega Gomes Jr. , Jose Artur Teixeira Brasil , Drew Johnson , Athanassios T. Papagiannakis , Marcio Hofheinz Giacomoni

{"title":"A coupled Darcy–Richards framework for hydrological modeling of permeable pavements, green roofs, and bioretention systems","authors":"Marcus Nóbrega Gomes Jr. , Jose Artur Teixeira Brasil , Drew Johnson , Athanassios T. Papagiannakis , Marcio Hofheinz Giacomoni","doi":"10.1016/j.envsoft.2025.106766","DOIUrl":"10.1016/j.envsoft.2025.106766","url":null,"abstract":"<div><div>Urbanization and climate change decrease groundwater recharge while increasing rapid runoff. Low-Impact-Development (LID) practices — such as permeable pavements, green roofs, and bioretention — can mitigate these impacts, but many models oversimplify infiltration and lack long-term capabilities to simulate decades of continuous simulations usually required to capture hydrologic signatures. This study presents a physics-based, open-source framework coupling a one-dimensional mixed-form Richards equation solver with a conceptual rainfall–runoff model. Benchmarking against Hydrus-1D showed strong agreement across soil types (RMSE <span><math><mo>≤</mo></math></span> 0.020 m for pressure head; <span><math><mo>≤</mo></math></span> 0.003 for water content). Calibration/validation with 255-day field data from a permeable asphalt site yielded NSE = 0.93 and <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> = 0.94 for calibration, NSE = 0.729 and <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> = 0.80 for validation. A 30-year continuous simulation for four U.S. cities revealed distinct regional runoff retention, evaporation efficiency, and flow duration patterns, indicating differences in runoff partitioning among typical designs of bioretention systems, green roofs, and permeable pavements across climate gradients.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106766"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145461580","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

Modelling near-surface ice content and midwinter melt events in mineral soils 模拟矿物土壤近地表冰含量和冬至融化事件

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2025-12-05 DOI: 10.1016/j.envsoft.2025.106816

Élise G. Devoie , Renato Pardo Lara , Aaron Berg , William L. Quinton , James R. Craig

{"title":"Modelling near-surface ice content and midwinter melt events in mineral soils","authors":"Élise G. Devoie , Renato Pardo Lara , Aaron Berg , William L. Quinton , James R. Craig","doi":"10.1016/j.envsoft.2025.106816","DOIUrl":"10.1016/j.envsoft.2025.106816","url":null,"abstract":"<div><div>Over winter freeze–thaw events are notoriously difficult to represent in hydrologic models and have serious implications for the hydrologic function of intermittently freezing regions. Changing climate is leading to more frequent mid-winter thaw events. Midwinter thaw events are often the cause of flooding due to the combined impacts of snowmelt, precipitation, and limited soil infiltrability. A numerically efficient, semi-analytical coupled thermal and mass transport model is presented that represents the ice content of near-surface soil, and reports the depth of freezing/thawing. The model tracks pore ice formation and mean soil temperature in terms of enthalpy. It is tested against data collected in Southern Saskatchewan and is shown to capably reproduce field observations of frozen, thawed or transitioning soils. This numerically efficient model can be incorporated into regional hydrologic models where it is expected to improve predictions of soil ice content, leading to improved estimates of over-winter streamflow and flood potential.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106816"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145689377","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

Development of a web-based No coding machine learning platform for hydrology and environmental management - MoolML 开发基于web的水文和环境管理无编码机器学习平台- MoolML

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.2025.106830

Sangjoon Bak , Jeongho Han , Gwanjae Lee , Naehyeon Nam , Joo Hyun Bae , Yeonji Jeong , Hyungjin Shin , Kyoung Jae Lim , Seoro Lee

{"title":"Development of a web-based No coding machine learning platform for hydrology and environmental management - MoolML","authors":"Sangjoon Bak , Jeongho Han , Gwanjae Lee , Naehyeon Nam , Joo Hyun Bae , Yeonji Jeong , Hyungjin Shin , Kyoung Jae Lim , Seoro Lee","doi":"10.1016/j.envsoft.2025.106830","DOIUrl":"10.1016/j.envsoft.2025.106830","url":null,"abstract":"<div><div>Developing data-driven models for hydrology and environmental management is challenging for non-experts, such as field engineers and environmental practitioners, due to limited coding experience and the complexity of model training and validation. To address this, we developed <strong>MoolML</strong>, a free, web-based, no-coding machine learning platform for simplified regression and classification modeling. The name MoolML is derived from the Korean word “물” (mool), meaning “water,” combined with Machine Learning (ML). MoolML integrates key functions such as data preprocessing, model training and prediction, hyperparameter tuning, cross-validation, feature importance analysis, and weather data collection, along with visualization tools for intuitive result presentation. The platform enables users to manage the entire modeling process without coding expertise while supporting data sharing and collaboration. The applicability and efficiency of developing ML models through the platform were tested using hydrological and environmental datasets from South Korea, and it is expected to support comprehensive watershed management.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106830"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145732502","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

Freshwater modeling in Aotearoa New Zealand: Current practice and future directions 新西兰奥特罗阿淡水建模：当前实践和未来方向

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2025-12-05 DOI: 10.1016/j.envsoft.2025.106820

Katharina Dost , Kohji Muraoka , Anne-Gaelle Ausseil , Rubianca Benavidez , Brendon Blue , Nic Conland , Chris Daughney , Annette Semadeni-Davies , Linh Hoang , Anna Hooper , Theodore Alfred Kpodonu , Tapuwa Marapara , Richard McDowell , Trung Nguyen , Dang Anh Nguyet , Ned Norton , Deniz Özkundakci , Lisa Pearson , James Rolinson , Ra Smith , Jörg Wicker

{"title":"Freshwater modeling in Aotearoa New Zealand: Current practice and future directions","authors":"Katharina Dost , Kohji Muraoka , Anne-Gaelle Ausseil , Rubianca Benavidez , Brendon Blue , Nic Conland , Chris Daughney , Annette Semadeni-Davies , Linh Hoang , Anna Hooper , Theodore Alfred Kpodonu , Tapuwa Marapara , Richard McDowell , Trung Nguyen , Dang Anh Nguyet , Ned Norton , Deniz Özkundakci , Lisa Pearson , James Rolinson , Ra Smith , Jörg Wicker","doi":"10.1016/j.envsoft.2025.106820","DOIUrl":"10.1016/j.envsoft.2025.106820","url":null,"abstract":"<div><div>Freshwater modeling is vital for addressing environmental and societal challenges. In two workshops preceding this article, we revealed issues in current modeling practices in New Zealand, with a focus on catchment-level water quality modelling. Predominant were low trust in models, lack of transparency, and models unfit for purpose. This article uses a root-cause analysis to explore these issues, identify causes, and propose solutions. We find that current best practices and research are a good foundation but insufficient to fulfill our freshwater research and management needs. We advocate for long-term national strategies with centralized funding, standardized documentation, data, models, evaluation techniques, and communication methods, along with a centralized open-access platform for collaboration. Our vision is to streamline modeling projects, enhance the accessibility and reliability of models, and foster more effective decision-making processes for the sustainable management of freshwater ecosystems.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106820"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145689372","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

Hybrid high-dimensional vine copula–Bayesian network framework for flood risk analysis in reservoir–lake systems: Addressing multisource uncertainties 水库-湖泊系统洪水风险分析的混合高维藤copula -贝叶斯网络框架：处理多源不确定性

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2025-12-05 DOI: 10.1016/j.envsoft.2025.106818

Xuesong Yang , Bin Xu , Huili Wang , Xinman Qin , Xinrong Wang , Zichen Ren , Yao Yao , Siying Zhou , Yao Liu , Ping Chang

{"title":"Hybrid high-dimensional vine copula–Bayesian network framework for flood risk analysis in reservoir–lake systems: Addressing multisource uncertainties","authors":"Xuesong Yang , Bin Xu , Huili Wang , Xinman Qin , Xinrong Wang , Zichen Ren , Yao Yao , Siying Zhou , Yao Liu , Ping Chang","doi":"10.1016/j.envsoft.2025.106818","DOIUrl":"10.1016/j.envsoft.2025.106818","url":null,"abstract":"<div><div>Complex flood control systems which comprise reservoirs, lakes, and external rivers, frequently encounter multifaceted risk sources that are spatiotemporally interconnected, resulting in diverse flood risks. This study developed a comprehensive risk analysis framework integrating stochastic simulation and Bayesian networks to facilitate refined risk prediction and diagnosis. Vine copula and Monte Carlo methods were used for probabilistic modeling and simulation, while Bayesian network was used for bidirectional risk assessment. A case study of Chaohu Lake Basin (China) show that vine copula effectively elucidates both intervariable correlations and single variable characteristics. The lateral inflow volume of lake and the external river water levels are dominant risk sources. When the maximum water level of lake increases from 9.5 m to 11.5 m, the posterior probability of dominant risk sources exceeding the design value at 20 % increases by 46.12 % and 32.22 %. This study represents an innovative approach to risk analysis for complex reservoir-lake systems.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106818"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145689374","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

Improve the estimation of forest wind vulnerability through remote sensed data: a new methodology 利用遥感数据改进森林风脆弱性估算：一种新方法

IF 4.6 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2026-02-01 Epub Date: 2025-12-04 DOI: 10.1016/j.envsoft.2025.106825

Tommaso Baggio , Maximiliano Costa , Niccolò Marchi , Tommaso Locatelli , Emanuele Lingua

{"title":"Improve the estimation of forest wind vulnerability through remote sensed data: a new methodology","authors":"Tommaso Baggio , Maximiliano Costa , Niccolò Marchi , Tommaso Locatelli , Emanuele Lingua","doi":"10.1016/j.envsoft.2025.106825","DOIUrl":"10.1016/j.envsoft.2025.106825","url":null,"abstract":"<div><div>Windstorms are the primary cause of damage to European forests. Although different mechanistic and probabilistic models have been developed to estimate the vulnerability of forests to wind, their practical application remains limited. This study presents a new, semi-automated methodology for deriving tree and forest characteristics over large areas through the analysis of Canopy Height Model (CHM) data. By integrating the semi-mechanistic model ForestGALES, the developed algorithm uses these data to calculate spatially explicit maps of Critical Wind Speed (CWS). The presented methodology is applied to a real case study to calculate the CWS of forests in the Italian Eastern Alps. Results show that adding detailed and spatially distributed forest cover information improves the CWS calculations, thereby enhancing the reliability of models to assess forest wind vulnerability. Forest practitioners can take advantage of this new methodology to enhance the resistance and resilience of their forests through specific management techniques.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"197 ","pages":"Article 106825"},"PeriodicalIF":4.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145689375","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