Environmental Modelling & Software最新文献

英文中文

Advancing timely satellite precipitation for IMERG-ER using GOES-16 data and a U-net convolutional neural network modelling approach

IF 4.8 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

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

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.

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引用次数: 0

SENTINEL: A Shiny App for Processing and Analysis of Fenceline Sensor Data

IF 4.8 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Environmental Modelling & Software

Pub Date : 2025-04-03 DOI: 10.1016/j.envsoft.2025.106462

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

SENTINEL (SEnsor NeTwork INtelligent Emissions Locator) 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.

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引用次数: 0

Landscape-level assessment of spray drift – A virtual experiment using the Droplet and Atmospheric Dispersion drift (DAD-drift) model

IF 4.8 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Environmental Modelling & Software

Pub Date : 2025-04-02 DOI: 10.1016/j.envsoft.2025.106455

Mike Devin Fuchs , Sebastian Gebler , Andreas Lorke

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.

喷洒漂移在很大程度上造成了农药的非目标移动。虽然影响田间喷洒漂移的因素（如环境条件、设备和缓冲区）已广为人知，但景观尺度上的沉积却受到其他因素的影响，包括景观特征和非目标区域的邻近性。DAD 漂移模型考虑了喷洒漂移的物理基础、施药位置、风向和景观尺度的沉积。在一次虚拟实验中，我们将 DAD 漂移与其他建模方法常用的施药区域简化空间表示法进行了比较，结果表明两者在喷洒漂移预测方面存在很大差异。在第二个虚拟实验中，我们使用多元线性回归分析了 DAD 漂移的结果，以确定景观尺度上的喷雾漂移驱动因素。结果表明，由喷嘴类型决定的液滴大小分布是决定非目标区域沉积的两个最有影响的因素，紧随其后的是与非目标区域的距离。

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引用次数: 0

Spatial-temporal monitoring of compound droughts over global land areas

IF 4.8 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

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

Recent decades have witnessed frequent droughts across spatial-temporal scales (or compound droughts), which challenges current drought monitoring systems that are usually designed based on drought information at a specific period or location. To address the challenge, this study proposed monitoring approaches for compound droughts, including preconditioned droughts, multivariate droughts, temporally compounding droughts, and spatially compounding droughts. Based on the designed indicator for each type of droughts, the performance of the compound drought monitoring approach was evaluated based on case studies, including the preconditioned droughts and multivariate droughts during 2022, temporally compounding drought during 2012–2015 in California, and spatially compounding drought during 1983 across eastern United States, northeastern Brazil, and southern Africa. Overall, the proposed drought monitoring approach performs well in capturing compound droughts and provides a useful tool for drought planning and management across different regions.

引用次数: 0

Subgrid correction of storm surge modeling in orthogonal curvilinear coordinates

IF 4.8 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

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

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.

{"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

IF 4.8 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

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

Recent advances in computing have transformed ocean modeling from single-process simulations—such as circulation, tides, and sea ice—into integrated models that couple multiple dynamic processes. This study introduces an innovative global ocean model using an unstructured mesh to enable precise, multi-scale simulations across complex terrains. We conducted a ten-year, global ocean circulation to assess the model's accuracy, comparing simulated circulation, tide, and sea ice characteristics with observational data across key regions. The model effectively captures meso-scale dynamics, including boundary current separation, meso-scale eddy formation, and internal tides in the Luzon Strait, along with accurate global water mass distributions. Completing this extensive simulation within a month demonstrates the model's capability for efficient, high-resolution, long-term studies, paving the way for future ultra-high-resolution atmosphere-ocean coupling.

引用次数: 0

Navigating the space between empirics and theory – Empirically stylized modelling for theorising social-ecological phenomena

IF 4.8 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

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

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.

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引用次数: 0

An urban flood inundation model accelerated by the parallel acceleration technology

IF 4.8 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

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

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.

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引用次数: 0

A surrogate machine learning model using random forests for real-time flood inundation simulations

IF 4.8 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Environmental Modelling & Software

Pub Date : 2025-03-21 DOI: 10.1016/j.envsoft.2025.106439

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

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.

{"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

ZHPO-LightXBoost an integrated prediction model based on small samples for pesticide residues in crops

IF 4.8 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Environmental Modelling & Software

Pub Date : 2025-03-21 DOI: 10.1016/j.envsoft.2025.106440

Xiaopeng Sha , Yuejie Zhu , Xiaoying Sha , Zheng Guan , Shuyu Wang

Excessive dependence on and unreasonable use of pesticides in actual crop growth will lead to excessive pesticide residues and exacerbate environmental pollution. Therefore, the prediction of pesticide residues in crops is particularly important. In order to ensure the accuracy and generalization of the pesticide residue prediction model, a ZHPO-LightXBoost pesticide residue prediction model based on small sample datasets was proposed. The ZHPO algorithm was used to solve the problem of determining hyperparameters in the LightXBoost model. Comparative experiments conducted on four independently constructed datasets have shown that the proposed model achieves an increase in R² of 0.004–0.042, and achieves a reduction in MSE ranging from 0.0002 to 0.276 mg/kg, as well as a reduction in MAE ranging from 0.0005 to 0.181 mg/kg.

引用次数: 0

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Environmental Modelling & Software

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