Environmental Modelling & Software最新文献_第5页

DEM-based pluvial flood inundation modeling at a metropolitan scale 基于 DEM 的大都市尺度冲积洪水淹没模型

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-09-23 DOI: 10.1016/j.envsoft.2024.106226

Aylar Samadi, Keighobad Jafarzadegan, Hamid Moradkhani

{"title":"DEM-based pluvial flood inundation modeling at a metropolitan scale","authors":"Aylar Samadi, Keighobad Jafarzadegan, Hamid Moradkhani","doi":"10.1016/j.envsoft.2024.106226","DOIUrl":"10.1016/j.envsoft.2024.106226","url":null,"abstract":"<div><div>The global increase in urban flooding presents a substantial challenge that affects communities across the globe. This study introduces a post-flood inundation modeling framework tailored to pluvial floods on a metropolitan scale. We employ a dual drainage modeling approach for enhanced accuracy. The framework comprises two primary components: a Storm Water Management Model (<em>SWMM</em>) for simulating water movement within the storm drain system, and an advanced DEM-based flood inundation module that leverages <em>SWMM</em> results to predict flood inundation areas. Compared to the conventional flood spreading models commonly used in dual drainage modeling, this module incorporates high-resolution DEM cells into the surface flow routing processes, allowing to capture intricate surface terrain complexities. Additionally, the proposed module considers direct rainfall impacts on pluvial flood inundation mapping, resulting in enhanced accuracy. To evaluate the proposed model's accuracy, a two-step validation approach has been implemented. This includes comparing the proposed model results with both the high water marks measured in the aftermath of Hurricane Harvey and the flood depth map generated by a hydrodynamic model. The findings affirm the effectiveness of our proposed framework for post-flood inundation mapping within metropolitan settings. This method provides a dependable approach to urban flood modeling and represents an advancement in addressing the challenges associated with urban flooding.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"183 ","pages":"Article 106226"},"PeriodicalIF":4.8,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142322981","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

Advancing estuarine box modeling: A novel hybrid machine learning and physics-based approach 推进河口箱建模：新颖的机器学习和物理混合方法

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-09-23 DOI: 10.1016/j.envsoft.2024.106223

Rosalia Maglietta , Giorgia Verri , Leonardo Saccotelli , Alessandro De Lorenzis , Carla Cherubini , Rocco Caccioppoli , Giovanni Dimauro , Giovanni Coppini

{"title":"Advancing estuarine box modeling: A novel hybrid machine learning and physics-based approach","authors":"Rosalia Maglietta , Giorgia Verri , Leonardo Saccotelli , Alessandro De Lorenzis , Carla Cherubini , Rocco Caccioppoli , Giovanni Dimauro , Giovanni Coppini","doi":"10.1016/j.envsoft.2024.106223","DOIUrl":"10.1016/j.envsoft.2024.106223","url":null,"abstract":"<div><div>Estuaries play a crucial role in the maintenance of the ecological balance of coastal ecosystems. Salinity intrusion can disrupt these fragile ecosystems, impacting aquatic life and human activities in coastal regions. An accurate prediction of salinity intrusion is essential for managing water resources and preserving ecosystems. This paper introduces a novel hybrid tool, called Hybrid-EBM model, designed to predict the salt-wedge intrusion length and the salinity at river mouth of an estuary. Combining the state-of-the-art Estuary Box Model (EBM) with machine learning algorithms, the new Hybrid-EBM model provides an accurate forecast of the salinity intrusion events. Experimental results highlight the effectiveness of Hybrid-EBM in salinity prediction with an RMSE of 3.41 psu against the 4.22 obtained by EBM. The outputs of this paper represent a significant advancement in the understanding of the impacts of salinity intrusion along the estuarine ecosystems, contributing to the sustainability of the coastal regions worldwide.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"183 ","pages":"Article 106223"},"PeriodicalIF":4.8,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142322982","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

Predicting beach profiles with machine learning from offshore wave reflection spectra 利用离岸波浪反射光谱的机器学习预测海滩剖面

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-09-23 DOI: 10.1016/j.envsoft.2024.106221

Elsa Disdier , Rafael Almar , Rachid Benshila , Mahmoud Al Najar , Romain Chassagne , Debajoy Mukherjee , Dennis G. Wilson

引用次数: 0

Bridging existing energy and chemical transport models to enhance air quality policy assessment 衔接现有能源和化学传输模型，加强空气质量政策评估

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-09-21 DOI: 10.1016/j.envsoft.2024.106218

Stanley Ngo , Benjamin N. Murphy , Christopher G. Nolte , Kristen E. Brown

引用次数: 0

Robust and computationally efficient design for run-of-river hydropower 稳健且计算效率高的径流式水电设计

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-09-19 DOI: 10.1016/j.envsoft.2024.106220

Veysel Yildiz , Solomon Brown , Charles Rougé

{"title":"Robust and computationally efficient design for run-of-river hydropower","authors":"Veysel Yildiz , Solomon Brown , Charles Rougé","doi":"10.1016/j.envsoft.2024.106220","DOIUrl":"10.1016/j.envsoft.2024.106220","url":null,"abstract":"<div><p>This paper introduces innovative approaches for robust and computationally efficient optimal design of run-of-river hydropower plants. Compared with existing design software, it (1) integrates optimized turbine operations into design optimization instead of following predefined operational rules, and (2) combines this with a regular sampling of the flow duration curve to significantly reduce data inputs. Our rigorous benchmarking demonstrates that (1) operation optimization improves design performance at low computational cost, whilst (2) data input reduction slashes computational costs by over 92% with minimal impact on design recommendations and key robustness analysis insights. Taken together, these innovations make integrated design and operation optimization, complete with in-depth robustness analysis, laptop-accessible. They also reinforce sustainability efforts by minimizing the need for high-performance computing and large associated embodied greenhouse gas emissions.</p></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"183 ","pages":"Article 106220"},"PeriodicalIF":4.8,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1364815224002810/pdfft?md5=544fea23df3157353df3d4066dd3e760&pid=1-s2.0-S1364815224002810-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274352","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

River morphology information system: A web cyberinfrastructure for advancing river morphology research 河流形态信息系统：推进河流形态研究的网络基础设施

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-09-19 DOI: 10.1016/j.envsoft.2024.106222

Yusuf Sermet , Chung-Yuan Liang , Sayan Dey , Marian Muste , Venkatesh Merwade , Amanda L. Cox , J. Toby Minear , Ibrahim Demir

{"title":"River morphology information system: A web cyberinfrastructure for advancing river morphology research","authors":"Yusuf Sermet , Chung-Yuan Liang , Sayan Dey , Marian Muste , Venkatesh Merwade , Amanda L. Cox , J. Toby Minear , Ibrahim Demir","doi":"10.1016/j.envsoft.2024.106222","DOIUrl":"10.1016/j.envsoft.2024.106222","url":null,"abstract":"<div><div>The study of river systems is challenged by the complexity and volume of data required to understand and predict river morphology changes. The River Morphology Information System (RIMORPHIS) addresses these challenges with an open-access web-based cyberinfrastructure for advanced river morphology research. Built on the National Hydrography Dataset Plus High Resolution, RIMORPHIS integrates publicly available bathymetry data and third-party resources into a cohesive database architecture for real-time use and analysis. The platform, structured around a PostgreSQL database with PostGIS extension, offers tools for geospatial visualization using Deck.GL, data analytics with Python-based geospatial processing, and eHydro Cross Section Surveys integration via API. By providing on-demand access to relevant datasets and tools for data analytics and geospatial visualization, RIMORPHIS enhances data accessibility and interoperability, supporting informed decision-making in river basin management. This paper presents the development and functionalities of RIMORPHIS and its contributions to hydrological information systems as a self-sustained community platform.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"183 ","pages":"Article 106222"},"PeriodicalIF":4.8,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142319190","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

FastFuels: Advancing wildland fire modeling with high-resolution 3D fuel data and data assimilation 快速燃料：利用高分辨率三维燃料数据和数据同化推进野地火灾建模

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-09-18 DOI: 10.1016/j.envsoft.2024.106214

Anthony Marcozzi , Lucas Wells , Russell Parsons , Eric Mueller , Rodman Linn , J. Kevin Hiers

{"title":"FastFuels: Advancing wildland fire modeling with high-resolution 3D fuel data and data assimilation","authors":"Anthony Marcozzi , Lucas Wells , Russell Parsons , Eric Mueller , Rodman Linn , J. Kevin Hiers","doi":"10.1016/j.envsoft.2024.106214","DOIUrl":"10.1016/j.envsoft.2024.106214","url":null,"abstract":"<div><div>Acquiring detailed 3D fuel data for advanced fire models remains challenging, particularly at large scales. To address this need, we present FastFuels, a novel platform designed to generate detailed 3D fuel data and accelerate the use of advanced fire models. FastFuels integrates existing fuel and spatial data with innovative modeling techniques to represent complex 3D fuel arrangements across landscapes. It leverages data sources including the Forest Inventory and Analysis (FIA) database and plot imputation maps, and incorporates advanced features such as data assimilation from LiDAR. This research demonstrates FastFuels’ capabilities through two applications: evaluating fuel treatment effectiveness with the Fire Dynamics Simulator and simulating a prescribed fire operation using QUIC-Fire. FastFuels provides previously unavailable 3D fuel data at landscape scales, empowering informed decision-making, detailed investigations of fuel treatment impacts, and higher-resolution risk assessments. Its flexible data assimilation and model-agnostic outputs accelerate advanced fire science and support fire management decisions.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"183 ","pages":"Article 106214"},"PeriodicalIF":4.8,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142326875","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 Python toolkit for integrating geographic information system into regulatory dispersion models for refined pollution modeling 将地理信息系统整合到监管分散模型中的 Python 工具包，用于精细化污染建模

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-09-18 DOI: 10.1016/j.envsoft.2024.106219

Haobing Liu , Pengfei Gao , Sheng Xiang , Hong Zhu , Jia Chen , Qingyan Fu

{"title":"A Python toolkit for integrating geographic information system into regulatory dispersion models for refined pollution modeling","authors":"Haobing Liu , Pengfei Gao , Sheng Xiang , Hong Zhu , Jia Chen , Qingyan Fu","doi":"10.1016/j.envsoft.2024.106219","DOIUrl":"10.1016/j.envsoft.2024.106219","url":null,"abstract":"<div><div>AERMOD is designated as U.S. Environmental Protection Agency (EPA)'s preferred air dispersion model for refined transportation project hot-spot analyses beginning in 2020. One of the key challenges in its modeling process is spatially encoding roadway geometry, especially when simulating highways with complex geometric designs. This research proposed an open-source Python package, <em>GTA</em>, which enables conversion of publicly available roadway Geographic Information System (GIS) layers into defined sources, and source-based emission rates from MOtor Vehicle Emissions Simulator (MOVES) output for AERMOD modeling. The research selected a suburban area in Atlanta, and conducted a comprehensive analysis in terms of annual PM<sub>2.5</sub> concentration results and the speed of preparing AERMOD input files for highway network modeling both manually and using software developed based on the proposed methodology. The results prove that the proposed methodology significantly expedites the AERMOD input preparation process, and facilitates convenient testing of multiple modeling configurations for multi-scenario or sensitivity analysis.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"183 ","pages":"Article 106219"},"PeriodicalIF":4.8,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142322980","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

Assessing the influence of temperature on slope stability in a temperate climate: A nationwide spatial probability analysis in Italy 评估温度对温带气候下斜坡稳定性的影响：意大利全国范围的空间概率分析

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-09-13 DOI: 10.1016/j.envsoft.2024.106217

Marco Loche , Gianvito Scaringi

{"title":"Assessing the influence of temperature on slope stability in a temperate climate: A nationwide spatial probability analysis in Italy","authors":"Marco Loche , Gianvito Scaringi","doi":"10.1016/j.envsoft.2024.106217","DOIUrl":"10.1016/j.envsoft.2024.106217","url":null,"abstract":"<div><p>Among landslide controls, the role of temperature in temperate regions remains poorly understood. Experiments revealed thermo-hydro-mechanical effects in geomaterials; however, field evidence of temperature-controlled landsliding is scarce. This complexity hinders the formulation of a temperature-related variable, useable in modelling across scales. Here, we identified spatial correlations between temperature and shallow landslides in gentle clay slopes. Notably, the temperature in the shallow underground is controlled by that of the atmosphere, and clays are the most sensitive to temperature among all geomaterials. Exploiting the Italian Landslide Inventory, we constructed a slope unit-based Generalised Additive Model and utilised Land Surface Temperature (LST) data from MODIS, accessible in Google Earth Engine. Interestingly, we observed a stronger positive correlation between landslides and LST, particularly in southern Italy, where categorised widespread shallow instabilities are common. Although more experiments and site-specific studies are warranted, the observed pattern appears consistent with thermal soil weakening, which may enhance landslide mobility.</p></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"183 ","pages":"Article 106217"},"PeriodicalIF":4.8,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1364815224002780/pdfft?md5=e2de8363b881e91a2f746fb372fa3b6a&pid=1-s2.0-S1364815224002780-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239907","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

Research progress and prospects of urban flooding simulation: From traditional numerical models to deep learning approaches 城市洪水模拟的研究进展与展望：从传统数值模型到深度学习方法

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-09-12 DOI: 10.1016/j.envsoft.2024.106213

Bowei Zeng , Guoru Huang , Wenjie Chen

引用次数: 0