Environmental Modelling & Software最新文献_第6页

Integrated models of nutrient dynamics in lake and reservoir watersheds: A systematic review and integrated modelling decision pathway 湖泊与水库流域营养动态综合模型：系统综述与综合建模决策途径

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-02-01 DOI: 10.1016/j.envsoft.2025.106321

Floran Clopin , Ilaria Micella , Jorrit P. Mesman , Ma Cristina Paule-Mercado , Marina Amadori , Shuqi Lin , Lisette N. de Senerpont Domis , Jeroen J.M. de Klein

{"title":"Integrated models of nutrient dynamics in lake and reservoir watersheds: A systematic review and integrated modelling decision pathway","authors":"Floran Clopin , Ilaria Micella , Jorrit P. Mesman , Ma Cristina Paule-Mercado , Marina Amadori , Shuqi Lin , Lisette N. de Senerpont Domis , Jeroen J.M. de Klein","doi":"10.1016/j.envsoft.2025.106321","DOIUrl":"10.1016/j.envsoft.2025.106321","url":null,"abstract":"<div><div>Eutrophication of inland water bodies is a serious environmental threat. This review explores current integrated models for lake and reservoir ecosystems that focus on nutrient dynamics at a catchment scale. Many studies applied either watershed or lake/reservoir models, however, 49 studies were finally selected that combined both. We derived a list of 21 watershed models, 23 lake/reservoir models, and 6 hybrid models in different sets of combinations, with a range of objectives (e.g. understanding the natural processes, predicting, and analysing climate change and land-use scenarios, or evaluating the different management options). Some integrated models had multiple applications whereas others were only applied once, with an uneven global geographical distribution.</div><div>To aid model selection by future users, we present a support tool discriminating the models by their features and application fields. This study encourages the development of open-source tools aiding interdisciplinary collaborations and further research in the field of integrated modelling.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"185 ","pages":"Article 106321"},"PeriodicalIF":4.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143020243","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

Geo-WC: Custom web components for earth science organizations and agencies Geo-WC：为地球科学组织和机构定制的web组件

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-02-01 DOI: 10.1016/j.envsoft.2025.106328

Sümeyye Kaynak , Baran Kaynak , Carlos Erazo Ramirez , Ibrahim Demir

{"title":"Geo-WC: Custom web components for earth science organizations and agencies","authors":"Sümeyye Kaynak , Baran Kaynak , Carlos Erazo Ramirez , Ibrahim Demir","doi":"10.1016/j.envsoft.2025.106328","DOIUrl":"10.1016/j.envsoft.2025.106328","url":null,"abstract":"<div><div>The development of web technologies and their integration into various fields has allowed a new era in data-driven decision-making and public data accessibility, especially through their adoption of monitoring and quantification environmental resources provided by governmental institutions. The use of web technologies has made it possible to create applications that can be accessed and used by a wide user base. However, dealing with the complexity of environmental data and non-standard data formats remains a hindering issue. To overcome these challenges and obtain up-to-date information from different institutions, we present Geo-WC: a web component framework specifically designed for earth and environmental sciences, serving as a bridge across various scientific domains. The Geo-WC utilizes a developer-friendly approach through simple HTML declarative syntax to bring together data in a single interface that is easy for developers to work with, making it accessible to users of varying skill levels. The framework integrates widely used web technologies, facilitating client-side data analysis, visualization, and accessibility within web browsers.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"185 ","pages":"Article 106328"},"PeriodicalIF":4.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142990594","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 optimal parameter determination algorithm for two-dimensional flow analysis model 二维流动分析模型最优参数确定算法的发展

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-02-01 DOI: 10.1016/j.envsoft.2025.106331

Eun Taek Shin , Se Hyuck An , Sung Won Park , Seung Oh Lee , Chang Geun Song

引用次数: 0

Automating physics-based models to estimate thermoelectric-power water use

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-02-01 DOI: 10.1016/j.envsoft.2024.106265

M.A. Harris , T.H. Diehl , L.E. Gorman Sanisaca , A.E. Galanter , M.A. Lombard , K.D. Skinner , C. Chamberlin , B.A. McCarthy , R. Niswonger , J.S. Stewart , K.J. Valseth

{"title":"Automating physics-based models to estimate thermoelectric-power water use","authors":"M.A. Harris , T.H. Diehl , L.E. Gorman Sanisaca , A.E. Galanter , M.A. Lombard , K.D. Skinner , C. Chamberlin , B.A. McCarthy , R. Niswonger , J.S. Stewart , K.J. Valseth","doi":"10.1016/j.envsoft.2024.106265","DOIUrl":"10.1016/j.envsoft.2024.106265","url":null,"abstract":"<div><div>Thermoelectric (TE) power plants withdraw more water than any other sector of water use in the United States and consume water at rates that can be significant especially in water-stressed regions. Historical TE water-use data have been inconsistent, incomplete, or discrepant, resulting in an increased research focus on improving the accuracy and availability of TE water-use data using modeling approaches. This paper describes and benchmarks new code that was developed to automate and update a physics-based TE water use model that was previously published. Utilizing the automated physics-based model, monthly TE-power water withdrawal and consumption were calculated for a total of 1341 TE power plants for the 2008–2020 historical reanalysis. The updated and automated physics-based thermoelectric-power water-use model provides spatially and temporally relevant TE water-use estimates that are consistent, reproducible, transparent, and can be generated efficiently for water-using, utility-scale TE-power plants across conterminous United States (CONUS).</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"185 ","pages":"Article 106265"},"PeriodicalIF":4.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143128135","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

A coupled multiscale description of seasonal Physical–BioGeoChemical dynamics in Southern Ocean Marginal Ice Zone 南大洋边缘冰带季节物理-生物地球化学动力学的多尺度耦合描述

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-02-01 DOI: 10.1016/j.envsoft.2024.106270

Raghav Pathak , Seyed Morteza Seyedpour , Bernd Kutschan , Silke Thoms , Tim Ricken

{"title":"A coupled multiscale description of seasonal Physical–BioGeoChemical dynamics in Southern Ocean Marginal Ice Zone","authors":"Raghav Pathak , Seyed Morteza Seyedpour , Bernd Kutschan , Silke Thoms , Tim Ricken","doi":"10.1016/j.envsoft.2024.106270","DOIUrl":"10.1016/j.envsoft.2024.106270","url":null,"abstract":"<div><div>Sea ice in the polar oceans plays a significant role in regulating global climate and biological ecosystems. During the winter months, seawater freezes to form porous ice, which also serves as a habitat for sea ice algae to survive in harsh winter conditions. However, accurate description of mechanisms and interactions associated with formation of ice, and its interaction with photosynthesis and carbon assimilation have not been well understood. This paper presents a modeling framework to describe coupled small scale Physical (P) and BioGeoChemical (BGC) processes associated with sea ice. Critical processes associated with photosynthesis along with growth and loss of algal carbon are considered. Appropriate parametrization for environmental factors such as temperature, light, salinity, and nutrients are employed to model the photosynthetic rate. Summer and winter environmental conditions are presented and discussed in detail. Finally, monthly data is taken from literature to simulate a typical year in the Southern Ocean.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"185 ","pages":"Article 106270"},"PeriodicalIF":4.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142874847","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

VERE Py-framework: Dual environment for physically-informed machine learning in seismic landslide hazard mapping driven by InSAR VERE Py-框架：InSAR 驱动的地震滑坡灾害绘图中物理信息机器学习的双重环境

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-02-01 DOI: 10.1016/j.envsoft.2024.106287

Gerardo Grelle , Luigi Guerriero , Domenico Calcaterra , Diego Di Martire , Chiara Di Muro , Enza Vitale , Giuseppe Sappa

{"title":"VERE Py-framework: Dual environment for physically-informed machine learning in seismic landslide hazard mapping driven by InSAR","authors":"Gerardo Grelle , Luigi Guerriero , Domenico Calcaterra , Diego Di Martire , Chiara Di Muro , Enza Vitale , Giuseppe Sappa","doi":"10.1016/j.envsoft.2024.106287","DOIUrl":"10.1016/j.envsoft.2024.106287","url":null,"abstract":"<div><div>The VERE framework was designed and developed in Python to generate hazard confidence maps for seismic-induced landslides, leveraging advanced data analysis and machine learning capabilities. A Virtual Environment (VE) and a Real Environment (RE) containing, respectively, datasets and map sets, are the core of the framework. The Virtual Environment (VE) comprises datasets including morphometric, geotechnical, and hydrological metadata, which are generated assuming a normal distribution, based on representative recurrent values of these parameters in the study area. The Real Environment (RE) includes grid datasets with a common resolution, obtained through analytical preprocessing of various spatial data distributions, including InSAR (Interferometric Synthetic Aperture Radar) data. This data is processed to detect ongoing slope instability and the activity state of surveyed landslides. The framework employs numerical machine learning, trained on meta-solutions derived from an advanced simplified physical model. The model accounts for viscoplastic behavior as well as the reduction of shear strengths toward the residual state during seismic-induced sliding. Hazard confidence maps are produced through an ML-based prediction, considering co-seismic displacements and post-seismic mobility under different initial porewater pressures and seismicity scenarios. The test-site region is the Sele River valley located in an inter-Apennine sector of southern Italy, a seismic-prone area known for its recent seismic activity.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"185 ","pages":"Article 106287"},"PeriodicalIF":4.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825339","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

Amadeus: Accessing and analyzing large scale environmental data in R

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-01-31 DOI: 10.1016/j.envsoft.2025.106352

Mitchell Manware , Insang Song , Eva S. Marques , Mariana Alifa Kassien , Lara P. Clark , Kyle P. Messier

{"title":"Amadeus: Accessing and analyzing large scale environmental data in R","authors":"Mitchell Manware , Insang Song , Eva S. Marques , Mariana Alifa Kassien , Lara P. Clark , Kyle P. Messier","doi":"10.1016/j.envsoft.2025.106352","DOIUrl":"10.1016/j.envsoft.2025.106352","url":null,"abstract":"<div><div>Environmental health research increasingly uses large scale spatial data to understand relationships between environmental factors and health outcomes. Data access and analysis tools which improve the timeliness and reproducibility of environmental health research are crucial for advancing the field. We present the <em>amadeus</em> package for R, a tool to improve access to and utility with large scale environmental data, primarily covering the United States. <em>amadeus</em> aims to reduce the learning curve for conducting spatial data analyses in R by providing functions which download, process, and calculate covariates from various publicly available environmental data sources. The functions promote interoperability with popular spatial data R packages and integration across other programming languages. Created and maintained with test-driven development, <em>amadeus</em> supports the reproducibility of environmental data acquisition and preparation. The <em>amadeus</em> package has diverse data access and integration applications, ranging from health-oriented studies in environmental epidemiology to ecology and climatology.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"186 ","pages":"Article 106352"},"PeriodicalIF":4.8,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377302","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

Adaptive Surrogate Model Assisted Swarm Intelligence for Parameter Inversion of complex hydrological models

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-01-30 DOI: 10.1016/j.envsoft.2025.106353

Guhan Li , Peng Shi , Simin Qu , Lingzhong Kong , Xiaohua Xiang , Qian Yang , Yu Qiao , Shiyu Lu

{"title":"Adaptive Surrogate Model Assisted Swarm Intelligence for Parameter Inversion of complex hydrological models","authors":"Guhan Li , Peng Shi , Simin Qu , Lingzhong Kong , Xiaohua Xiang , Qian Yang , Yu Qiao , Shiyu Lu","doi":"10.1016/j.envsoft.2025.106353","DOIUrl":"10.1016/j.envsoft.2025.106353","url":null,"abstract":"<div><div>Parameter inversion in hydrological models aims to estimate parameters from observed data, improving accuracy and understanding of the system. This process typically involves optimization algorithms to identify optimal parameter combinations, often resulting in significant computational costs due to the necessity for numerous model runs, particularly in complex hydrological models. To address this challenge, this study introduces the Adaptive Surrogate Model Assisted Swarm Intelligence (ASMA-SI) framework. ASMA-SI uses the iterative traces of swarm intelligence (SI) as a training sample set, fostering a tightly coupling between SI and the surrogate model while minimizing computational demands and enhancing search efficiency. The framework was applied to enhance three prominent SI algorithms: Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA). Synthetic experiments and a case study were conducted to evaluate the inversion efficacy of ASMA-SI. In the synthetic experiments, ASMA-SI demonstrated faster convergence to the ‘true value’, while in the real-world case study, it outperformed in nearly all of the nine test groups, achieving better average performance metrics.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"186 ","pages":"Article 106353"},"PeriodicalIF":4.8,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388453","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

MANG@COAST: A spatio-temporal modeling approach of muddy shoreline mobility based on mangrove monitoring

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-01-30 DOI: 10.1016/j.envsoft.2025.106345

P.E. Augusseau , C. Proisy , A. Gardel , G. Brunier , L. Granjon , T. Maury , A. Mury , A. Staquet , V.F. Santos , R. Walcker , P. Degenne , D. Lo Seen , E.J. Anthony

{"title":"MANG@COAST: A spatio-temporal modeling approach of muddy shoreline mobility based on mangrove monitoring","authors":"P.E. Augusseau , C. Proisy , A. Gardel , G. Brunier , L. Granjon , T. Maury , A. Mury , A. Staquet , V.F. Santos , R. Walcker , P. Degenne , D. Lo Seen , E.J. Anthony","doi":"10.1016/j.envsoft.2025.106345","DOIUrl":"10.1016/j.envsoft.2025.106345","url":null,"abstract":"<div><div>Highly dynamic wave-exposed muddy coasts harbouring mangrove ecosystems can be subject to both marked accretion and erosion depending on the complex interactions between mud and waves. We propose a multiscale modelling approach and empirical equations calibrated and integrated into a landscape dynamics model implemented on a mud-bank coast using the Ocelet language to simplify the complex processes driving sea-mangrove coastline dynamics and quantity them with 10 years of satellite observations of mangrove shoreline fluctuations.</div><div>We find that fluctuations in seafront mangroves can be simulated with acceptable accuracy along 200 km of coastline. In the absence of mud banks, seasonal wave forcing resulted in erosion rates reaching 1100 m/y. Our findings indicate that wave energy can be reduced by 90% at all locations when the width of mud banks exceeds 2000 m in front of the mangroves. Finally, we discuss the potential of this modeling approach for anticipating coastal changes.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"186 ","pages":"Article 106345"},"PeriodicalIF":4.8,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077716","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

Derivation of characteristic physioclimatic regions through density-based spatial clustering of high-dimensional data

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-01-28 DOI: 10.1016/j.envsoft.2025.106324

Sebastian Lehner , Katharina Enigl , Matthias Schlögl

{"title":"Derivation of characteristic physioclimatic regions through density-based spatial clustering of high-dimensional data","authors":"Sebastian Lehner , Katharina Enigl , Matthias Schlögl","doi":"10.1016/j.envsoft.2025.106324","DOIUrl":"10.1016/j.envsoft.2025.106324","url":null,"abstract":"<div><div>Physioclimatic regions are homogeneous geospatial entities that exhibit similar characteristics in both climatic conditions and the physiographic environment. They provide a foundation for a broad range of analyses in earth system sciences that are conditional on the prevailing climatological properties shaping geographical areas. However, delineating such regions is challenging due to high-dimensional input data and nonlinear processes in nature. We introduce a nonparametric clustering methodology to derive geospatial clusters with similar physioclimatic attributes, using a comprehensive dataset of climatological and geomorphometric indices from Austria. Our analysis workflow includes (1) Principal Component Analysis (PCA) for linear dimension reduction, (2) Uniform Manifold Approximation and Projection (UMAP) for nonlinear dimension reduction, (3) Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) for clustering and (4) random forest for feature importance assessment. Results show both agreement and differences compared to reference classification, thereby highlighting the need for quantitative performance evaluation and synoptic plausibility assessment. Findings include the identification of two characteristic clusters for inneralpine valleys in Western Austria and interfluves in the Styrian basin. This workflow offers a blueprint for delineating consistent geospatial regions for various applications. Clusters obtained with this approach may assist in unearthing new perspectives on regionalisation, provide new insights in the underlying characteristics determining these regions, and thus aid in the understanding of complex environmental patterns.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"186 ","pages":"Article 106324"},"PeriodicalIF":4.8,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077717","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