Environmental Modelling & Software最新文献_第3页

Advancing timely satellite precipitation for IMERG-ER using GOES-16 data and a U-net convolutional neural network modelling approach 利用GOES-16数据和U-net卷积神经网络建模方法推进imerger的及时卫星降水

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-04-04 DOI: 10.1016/j.envsoft.2025.106457

Mateo Vélez-Hernández , Paul Muñoz , Esteban Samaniego , María José Merizalde , Rolando Célleri

{"title":"Advancing timely satellite precipitation for IMERG-ER using GOES-16 data and a U-net convolutional neural network modelling approach","authors":"Mateo Vélez-Hernández , Paul Muñoz , Esteban Samaniego , María José Merizalde , Rolando Célleri","doi":"10.1016/j.envsoft.2025.106457","DOIUrl":"10.1016/j.envsoft.2025.106457","url":null,"abstract":"<div><div>Timely precipitation information is essential for water resources management and hazard monitoring. In regions with limited ground-based measurements, satellite precipitation products (SPPs) provide a valuable alternative, though data latency often creates an information gap for real-time applications. This study addresses the latency gap of IMERG-ER using a U-Net-based Convolutional Neural Network (CNN) model, trained with near-instantaneous GOES-16 satellite data. The optimal combination of GOES-16 infrared bands (6.2, 6.9, 7.3, 8.4, and 11.2 μm) was determined to enhance IMERG-ER predictions. The CNN model's performance, evaluated with both quantitative and qualitative metrics, showed an RMSE of 0.46 mm/h, a Pearson's correlation coefficient of 0.60, and a Critical Success Index of 0.53. The model performed well in predicting low-intensity precipitation (<3 mm/h), which occurs 97 % of the time, but faced challenges with high-intensity events due to data imbalance. These findings advance the use of SPPs and deep learning for operational hydrology.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"189 ","pages":"Article 106457"},"PeriodicalIF":4.8,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143807739","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

SENTINEL: A Shiny App for Processing and Analysis of Fenceline Sensor Data SENTINEL：用于处理和分析围栏传感器数据的闪亮应用程序

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-04-03 DOI: 10.1016/j.envsoft.2025.106462

MacDonald M.K., Champion W.M., Thoma E.D.

{"title":"SENTINEL: A Shiny App for Processing and Analysis of Fenceline Sensor Data","authors":"MacDonald M.K., Champion W.M., Thoma E.D.","doi":"10.1016/j.envsoft.2025.106462","DOIUrl":"10.1016/j.envsoft.2025.106462","url":null,"abstract":"<div><div>SENTINEL (<strong>SE</strong>nsor <strong>N</strong>e<strong>T</strong>work <strong>IN</strong>telligent <strong>E</strong>missions <strong>L</strong>ocator) is an application developed in R Shiny to support emerging user groups of lower cost fenceline sensors, such as those monitoring volatile organic compound or methane concentrations inside and near industrial facilities or for emergency response applications. During deployment, sensors collect a large quantity of high-frequency pollutant concentration data, time-aligned meteorological information, and sensor performance indicators. These sensors can collect a quantity of data that is overwhelming for users to process and understand without designated software. The SENTINEL application provides users with a consistent framework for processing, analyzing, and visualizing fenceline sensor data. SENTINEL temporally aggregates data for synthesized analysis and interpretation. Quality assurance screening automatically removes anomalous datapoints and a baseline correction algorithm reduces background drift in pollutant concentration data. SENTINEL offers streamlined sensor data analysis through a user-friendly graphical user interface that supports interpretation of source emission data and sensor-triggered field samples.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"189 ","pages":"Article 106462"},"PeriodicalIF":4.8,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143807738","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 prototype adaptive mesh generator for enhancing computational efficiency and accuracy in physically-based modeling of flood-landslide hazards 一种用于提高洪水滑坡灾害物理建模计算效率和准确性的自适应网格生成器原型

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-04-03 DOI: 10.1016/j.envsoft.2025.106458

Guoding Chen , Ke Zhang , Sheng Wang , Lijun Chao

{"title":"A prototype adaptive mesh generator for enhancing computational efficiency and accuracy in physically-based modeling of flood-landslide hazards","authors":"Guoding Chen , Ke Zhang , Sheng Wang , Lijun Chao","doi":"10.1016/j.envsoft.2025.106458","DOIUrl":"10.1016/j.envsoft.2025.106458","url":null,"abstract":"<div><div>Predicting landslides across large regions using physically-based models requires balancing computational accuracy and efficiency. Current methods often use limited resolutions, underutilizing available data. We present a prototype mesh generator that manages multiple resolutions in grid-based modeling frameworks, focusing on identifying likely landslide initiation points and conditionally stable pixels as meshing criteria. The generator refines critical locations using finer grids based on set parameters and is integrated into a coupled hydrological-geotechnical framework that combines one-dimensional (1D) and three-dimensional (3D) slope stability models. This framework operates on non-uniform grids and adaptively applies 1D or 3D models according to local accuracy requirements. Testing in the upper Han River basin, China (∼ <span><math><mrow><msup><mn>10</mn><mn>5</mn></msup></mrow></math></span> <span><math><mrow><msup><mtext>km</mtext><mn>2</mn></msup></mrow></math></span>), during the July 2010 floods and landslides demonstrated that the mesh generator enhances landslide prediction, and the combined 1D-3D approach outperforms the standalone 1D model. This prototype shows promise for large-scale flood-landslide forecast systems.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"189 ","pages":"Article 106458"},"PeriodicalIF":4.8,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816402","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

Landscape-level assessment of spray drift – A virtual experiment using the Droplet and Atmospheric Dispersion drift (DAD-drift) model 喷雾漂移的景观级评估-使用液滴和大气弥散漂移（DAD-drift）模型的虚拟实验

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-04-02 DOI: 10.1016/j.envsoft.2025.106455

Mike Devin Fuchs , Sebastian Gebler , Andreas Lorke

{"title":"Landscape-level assessment of spray drift – A virtual experiment using the Droplet and Atmospheric Dispersion drift (DAD-drift) model","authors":"Mike Devin Fuchs , Sebastian Gebler , Andreas Lorke","doi":"10.1016/j.envsoft.2025.106455","DOIUrl":"10.1016/j.envsoft.2025.106455","url":null,"abstract":"<div><div>Spray drift significantly contributes to the off-target movement of pesticides. While factors influencing spray drift at the field scale, such as environmental conditions, equipment, and buffer zones, are well understood, deposition at landscape scale, is influenced by additional factors including landscape characteristics and the proximity of non-target areas. The DAD-drift model accounts for the physical basis of spray drift, application location, wind direction, and deposition at the landscape scale. In a virtual experiment we compared DAD-drift with simplified spatial representations of application areas, commonly used in other modelling approaches, the results showed large differences in spray drift predictions. In a second virtual experiment, results from DAD-drift were analyzed using multiple linear regressions to identify spray drift drivers at the landscape scale. Results showed that the droplet size distribution, determined by nozzle type, closely followed by proximity to non-target area, are the two most influential factors determining deposition in non-target areas.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"189 ","pages":"Article 106455"},"PeriodicalIF":4.8,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143786233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Spatial-temporal monitoring of compound droughts over global land areas 全球陆地复合干旱时空监测

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-04-02 DOI: 10.1016/j.envsoft.2025.106463

Zengchao Hao , Xuan Zhang , Yuting Pang , Boying Lv , Vijay P. Singh

引用次数: 0

Subgrid correction of storm surge modeling in orthogonal curvilinear coordinates 正交曲线坐标下风暴潮模拟的子网格校正

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-04-02 DOI: 10.1016/j.envsoft.2025.106435

Haoran Sun , Damrongsak Wirasaet , Andrew B. Kennedy , Yuepeng Li , Amirhosein Begmohammadi , Diogo Bolster

{"title":"Subgrid correction of storm surge modeling in orthogonal curvilinear coordinates","authors":"Haoran Sun , Damrongsak Wirasaet , Andrew B. Kennedy , Yuepeng Li , Amirhosein Begmohammadi , Diogo Bolster","doi":"10.1016/j.envsoft.2025.106435","DOIUrl":"10.1016/j.envsoft.2025.106435","url":null,"abstract":"<div><div>Ensemble forecasts of storm surge require rapid computations of storm surge models over a fixed cycle, usually with relatively coarse-grid models. This work describes numerical extensions to include subgrid approaches accounting for the bulk effect of high-resolution bathymetry and bottom roughness to increase the accuracy of these coarse-grid setups. In particular, the subgrid corrections are developed in a semi-implicit staggered-grid finite difference formulation for the 2D non-linear Shallow Water Equations expressed in an orthogonal curvilinear coordinate system. This general framework is implemented for the Coastal and Estuarine Storm Tide (CEST) model. Verification and validation using a number of test cases, ranging from an idealized test case with analytical solutions to real-world storm surge problems, are conducted in order to assess the performance of the subgrid features. Comparisons of solution accuracy and speed show the subgrid implementation consistently improves cost versus accuracy performance.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"189 ","pages":"Article 106435"},"PeriodicalIF":4.8,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143767503","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 global ocean circulation-tide-sea ice model using unstructured grid: Development, validation, and applications 使用非结构化网格的全球海洋环流-潮汐-海冰模型：开发、验证和应用

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-04-02 DOI: 10.1016/j.envsoft.2025.106456

Chunxiao Wang , Huaming Yu , Xin Qi , Yuchen Sun , Liansong Liang , Yang Ding

引用次数: 0

Navigating the space between empirics and theory – Empirically stylized modelling for theorising social-ecological phenomena 导航经验和理论之间的空间-经验风格化建模的理论社会生态现象

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-03-27 DOI: 10.1016/j.envsoft.2025.106444

Maja Schlüter , Nanda Wijermans , Blanca González-Mon , Emilie Lindkvist , Kirill Orach , Hannah Prawitz , Romina Martin , Rodrigo Martínez-Peña , Kara E. Pellowe , Udita Sanga

{"title":"Navigating the space between empirics and theory – Empirically stylized modelling for theorising social-ecological phenomena","authors":"Maja Schlüter , Nanda Wijermans , Blanca González-Mon , Emilie Lindkvist , Kirill Orach , Hannah Prawitz , Romina Martin , Rodrigo Martínez-Peña , Kara E. Pellowe , Udita Sanga","doi":"10.1016/j.envsoft.2025.106444","DOIUrl":"10.1016/j.envsoft.2025.106444","url":null,"abstract":"<div><div>The potential of agent-based modelling (ABM) for developing theory has been recognized, yet methodologies are lacking. Building theories of social-ecological systems is challenging because of complex causality, context-dependence, and social-ecological interdependencies. We propose an approach that addresses these challenges through combining case-based empirical research with ABM in a collaborative modelling process. In-depth empirical research is essential for identifying a puzzle and potential explanations thereof, and for recognizing context and social-ecological interdependencies. Collaborative model building and analysis enables careful abstraction and reflection, and allows further exploring and testing the emerging theory in dynamic contexts, leading to better-grounded and transparent assumptions and theories. We call this approach BIM (Being In the Middle) and articulate it through three features: contextually embedded, collaboratively abductive and empirically stylized. We highlight how BIM facilitates new interdisciplinary avenues for discovering social-ecological interdependencies, discuss how it can be applied and what challenges and frontiers lie ahead.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"189 ","pages":"Article 106444"},"PeriodicalIF":4.8,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An urban flood inundation model accelerated by the parallel acceleration technology 基于并行加速技术的城市洪水淹没模型

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-03-24 DOI: 10.1016/j.envsoft.2025.106441

Wei Zhu , Zhe Cao , Pingping Luo , Shuangtao Wang , Chengyi Xv , Yongxing Ji

{"title":"An urban flood inundation model accelerated by the parallel acceleration technology","authors":"Wei Zhu , Zhe Cao , Pingping Luo , Shuangtao Wang , Chengyi Xv , Yongxing Ji","doi":"10.1016/j.envsoft.2025.106441","DOIUrl":"10.1016/j.envsoft.2025.106441","url":null,"abstract":"<div><div>Due to factors such as changes in land use and climate change, floods are increasingly occurring worldwide, resulting in excessive property damage and casualties in urban areas. Numerical simulation techniques can provide valuable support in mitigating urban flood risks. This study developed a coupled flood inundation model for one-dimensional sewer and two-dimensional surface based on parallel acceleration technology. The main findings include: 1. The model was validated in Omihachiman City and Shanghai City, demonstrating satisfactory results in flood inundation simulations and confirming the model's reliability in simulating flood processes. 2. A comparison of simulation times between the surface inundation model's serial version, CPU-accelerated version, and GPU-accelerated version was conducted. The GPU-accelerated version showed significant speed-up compared to the CPU model using the same numerical algorithms, with better performance as computational units increased. 3. The performance of the model is significantly influenced by the underground sewer model.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"189 ","pages":"Article 106441"},"PeriodicalIF":4.8,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143746779","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 surrogate machine learning model using random forests for real-time flood inundation simulations 使用随机森林进行实时洪水模拟的代理机器学习模型

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-03-21 DOI: 10.1016/j.envsoft.2025.106439

Santosh Kumar Sasanapuri, C.T. Dhanya, A.K. Gosain

{"title":"A surrogate machine learning model using random forests for real-time flood inundation simulations","authors":"Santosh Kumar Sasanapuri, C.T. Dhanya, A.K. Gosain","doi":"10.1016/j.envsoft.2025.106439","DOIUrl":"10.1016/j.envsoft.2025.106439","url":null,"abstract":"<div><div>Real-time simulation of flood inundation helps to mitigate the catastrophic effects on human lives by facilitating emergency evacuations. Traditional two-dimensional (2D) physics-based hydrodynamic models, though accurate, require significant computational time, thereby rendering them unsuitable for such real-time applications. To address this limitation, we developed Random Forest (RF) models as surrogate hydrodynamic models for predicting maximum flood depth and velocity under complex fluvial conditions with backwater effects. These models integrate hydrological parameters, such as upstream discharge, physical catchment characteristics, to enhance predictive accuracy and generalizability. A comprehensive assessment revealed that the inclusion of physical characteristics increased the prediction accuracy of RF models by 1.72 times and 2.60 times for depth and velocity models with root mean square error of 0.494 m and 0.148 m/s respectively, compared to baseline models. Furthermore, the RF models required only 1.5 %–4 % (for minor flood event and major flood event respectively) of the computational time needed by hydrodynamic models. With its ability to understand complex flooding scenarios with high prediction accuracy and computing efficiency, the proposed RF models have demonstrated great potential for real-time flood inundation modelling. Efforts in this direction to improve the real-time flood inundation predictions may greatly aid the decision makers for undertaking emergency evacuations during catastrophic flood events.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"188 ","pages":"Article 106439"},"PeriodicalIF":4.8,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705312","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