Environmental Modelling & Software最新文献_第4页

Streamlining land surface model Initialization: Automated data retrieval for VELMA using HMS REST API and GDAL 简化地表模型初始化：使用HMS REST API和GDAL的VELMA自动数据检索

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-04-23 DOI: 10.1016/j.envsoft.2025.106492

Kar'retta Venable , John M. Johnston , Stephen D. LeDuc

{"title":"Streamlining land surface model Initialization: Automated data retrieval for VELMA using HMS REST API and GDAL","authors":"Kar'retta Venable , John M. Johnston , Stephen D. LeDuc","doi":"10.1016/j.envsoft.2025.106492","DOIUrl":"10.1016/j.envsoft.2025.106492","url":null,"abstract":"<div><div>Continuous monitoring data required for performing environmental model simulations using gridded land surface models (LSMs) are often difficult to obtain and manage, making the modeling process challenging and prone to error. In response, this study focuses on automated retrieval and processing of digital elevation models (DEMs from Google Earth Engine (GEE)), meteorologic drivers of hydrology, and surface runoff time series data, using the Visualizing Ecosystem and Land Management Assessment (VELMA) model as a case study. Our automation methodology is accomplished using the USEPA's Hydrologic Micro Services (HMS) Representation State Transfer (REST) application programming interface (API) and Geospatial Data Abstraction Library (GDAL) with Python. This workflow provides greater efficiency, minimizes data preparation time, reduces manual processing errors, and provides a reusable methodology for use in other modeling studies. With this innovation, users of VELMA and other gridded LSMs will be able to initialize simulations more efficiently, improving their operational capabilities.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"191 ","pages":"Article 106492"},"PeriodicalIF":4.8,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143916259","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

Accelerating large-scale hydrological modeling with stepwise spatial-temporal multimember parallelization 基于分步时空多元并行化的大尺度水文模拟

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-04-23 DOI: 10.1016/j.envsoft.2025.106495

Lulu Jiang , Huan Wu , Ting Yang , Lei Qu , Zhijun Huang

{"title":"Accelerating large-scale hydrological modeling with stepwise spatial-temporal multimember parallelization","authors":"Lulu Jiang , Huan Wu , Ting Yang , Lei Qu , Zhijun Huang","doi":"10.1016/j.envsoft.2025.106495","DOIUrl":"10.1016/j.envsoft.2025.106495","url":null,"abstract":"<div><div>Advancements in distributed hydrological modeling require higher temporal and spatial resolutions, increasing the demand for high-performance computing. Runoff-routing models face inefficiencies due to upstream–downstream dependencies. Increasing threads reduce computing time but lower efficiency due to task imbalances. We propose a stepwise spatial–temporal–multimember domain decomposition method with OpenMP. Applied to the Pearl River Basin at 90-m resolution, the method was tested at three stations: ZhaiGao (110,808 grids), ShiJiao (4.94 million grids), and Outlet0 (48.58 million grids). Results showed traditional serial computing took 172.18, 7726.94, and 79,470.21 seconds, respectively, for 10-year daily simulations (totaling 3653 time steps). With 13 threads, spatial layering parallelization reduced times to 21.86, 757.93, and 7262.06 seconds, achieving efficiencies of 0.61, 0.78, and 0.84. At ZhaiGao, 52 threads yielded efficiency of 0.06 with only spatial layering but increased to 0.55 and 0.80 upon adding temporal indexing and multimember parallelization. Overall, our approach significantly accelerates large-scale hydrodynamic flood modeling.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"191 ","pages":"Article 106495"},"PeriodicalIF":4.8,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143892192","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

Improving continental and global scale digital elevation models via estimation of a riverine topobathymetric surface 通过估算河流地形深度面改进大陆和全球尺度数字高程模型

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-04-22 DOI: 10.1016/j.envsoft.2025.106487

Joseph L. Gutenson , Michael L. Follum , Mark D. Wahl , Emily S. Ondich , Kathleen A. Staebell

{"title":"Improving continental and global scale digital elevation models via estimation of a riverine topobathymetric surface","authors":"Joseph L. Gutenson , Michael L. Follum , Mark D. Wahl , Emily S. Ondich , Kathleen A. Staebell","doi":"10.1016/j.envsoft.2025.106487","DOIUrl":"10.1016/j.envsoft.2025.106487","url":null,"abstract":"<div><div>Contemporary continental and global-scale digital elevation models (DEMs) are not a composite topobathymetric surface, as they tend to lack bathymetry. In this study, we analyzed if continental- and global-scale DEMs can be improved using a global hydrologic model and simple steady-state hydraulic techniques. We used two DEM datasets, globally available streamflow estimates, and simple hydraulic and mapping software to perform the analysis. We analyzed two distinct means by which to estimate bathymetry: the use of bank elevations and bankfull discharge estimates and the use of water surface elevation (WSE) and baseflow estimates to estimate bathymetry. We also introduced and investigated a new method for pre-cleaning the DEM prior to estimating a bathymetry. We found that the error and bias of a DEM can consistently be reduced using a global hydrologic model's streamflow and simple hydraulic analysis by using the DEMs WSE estimate and a baseflow to estimate the topobathymetric surface.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"191 ","pages":"Article 106487"},"PeriodicalIF":4.8,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143902450","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

Updated multi-layer perceptron algorithm for predicting solute transport parameters and processes in karst conduits with variable flow rates 基于多层感知器的变流量岩溶管道溶质输运参数与过程预测

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-04-22 DOI: 10.1016/j.envsoft.2025.106489

Xiaoer Zhao , Zhenxue Dai , Mohamad Reza Soltanian , Jichun Wu , Botao Ding , Yue Ma , Dayong Wang

{"title":"Updated multi-layer perceptron algorithm for predicting solute transport parameters and processes in karst conduits with variable flow rates","authors":"Xiaoer Zhao , Zhenxue Dai , Mohamad Reza Soltanian , Jichun Wu , Botao Ding , Yue Ma , Dayong Wang","doi":"10.1016/j.envsoft.2025.106489","DOIUrl":"10.1016/j.envsoft.2025.106489","url":null,"abstract":"<div><div>This study pioneers the application of a Bayesian-optimized multilayer perceptron (MLP) framework to predict the complete breakthrough curve (BTC) in two conduits under various flow conditions, unlike prior research that predicted only partial BTC. MLP shows significant advances in BTC prediction accuracy compared with Random Forest and Support Vector Regression. The transient storage model then simulates predicted BTCs to derive parameters: dispersion coefficient (<em>D</em>), cross-sectional area of main channel (<em>A</em>), cross-sectional area of storage zone (<em>A</em><sub>s</sub>), and exchange coefficient (<em>α</em>). Fifty-four MLP models are developed and trained, with an incremental increase in training data and input variables across scenarios S1-S3. S2 and S3 notably improve BTC prediction accuracy over S1, with <em>R</em><sup>2</sup> ≥ 0.9. S2 and S3 predict <em>A</em> with <6.6 % error, and <em>A</em><sub>s</sub> and <em>α</em> with <20 % and <50 % errors respectively. These results prove MLP's effectiveness in predicting solute transport parameters in karst conduits with variable discharges.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"191 ","pages":"Article 106489"},"PeriodicalIF":4.8,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143882663","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

STICr: An open-source package and workflow for stream temperature, intermittency, and conductivity (STIC) data STICr：用于流温度、间歇和电导率（STIC）数据的开源包和工作流程

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-04-20 DOI: 10.1016/j.envsoft.2025.106484

Sam Zipper , Christopher T. Wheeler , Delaney M. Peterson , Stephen C. Cook , Sarah E. Godsey , Ken Aho

{"title":"STICr: An open-source package and workflow for stream temperature, intermittency, and conductivity (STIC) data","authors":"Sam Zipper , Christopher T. Wheeler , Delaney M. Peterson , Stephen C. Cook , Sarah E. Godsey , Ken Aho","doi":"10.1016/j.envsoft.2025.106484","DOIUrl":"10.1016/j.envsoft.2025.106484","url":null,"abstract":"<div><div>Non-perennial streams constitute over half the world's stream miles but are not commonly included in streamflow monitoring networks. As a result, Stream Temperature, Intermittency, and Conductivity (STIC) loggers are widely used for characterizing flow presence or absence in non-perennial streams. To facilitate ‘FAIR’ (findable, accessible, interoperable, and reusable) stream intermittency science, we present an open-source R package, STICr, for processing STIC logger data. STICr includes functions to tidy data, calibrate sensors, classify data into wet/dry readings, and perform quality checks and validation. We also show a reproducible STICr-based workflow for an interdisciplinary project spanning multiple watersheds, years, and research groups. In South Fork Kings Creek (Konza Prairie, Kansas, USA), we show that stream intermittency is driven by the balance between monthly precipitation inputs, seasonal evapotranspiration fluxes, and underlying geology. Overall, STICr can be used to create FAIR stream intermittency data and enable advances in hydrologic and ecosystem science.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"190 ","pages":"Article 106484"},"PeriodicalIF":4.8,"publicationDate":"2025-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143859978","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

Enhancing rainfall frequency analysis through bivariate nonstationary modeling in South Korea 通过二元非平稳模型加强韩国降雨频率分析

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-04-17 DOI: 10.1016/j.envsoft.2025.106471

Heejin An , Hyun-Han Kwon , Moonyoung Lee , Inkyung Min , Kichul Jung , Daeryong Park

{"title":"Enhancing rainfall frequency analysis through bivariate nonstationary modeling in South Korea","authors":"Heejin An , Hyun-Han Kwon , Moonyoung Lee , Inkyung Min , Kichul Jung , Daeryong Park","doi":"10.1016/j.envsoft.2025.106471","DOIUrl":"10.1016/j.envsoft.2025.106471","url":null,"abstract":"<div><div>This study conducted a bivariate nonstationary frequency analysis utilizing rainfall events to capture the multidimensional nature of rainfall phenomena and rainfall pattern variability in South Korea. Extreme events were identified by the peaks over threshold (POT) method which enhanced the accuracy of estimation. The nonstationary model, incorporating a nonlinear regression using time as a covariate instead of the scale parameter in the generalized Pareto distribution (GPD), provided a more stable interannual variability of rainfall representation under a dynamic climate compared to stationary models. The ability of the bivariate POT method threshold <span><math><mrow><mo>(</mo><msub><mi>T</mi><mrow><mi>a</mi><mi>n</mi><mi>d</mi></mrow></msub><mo>)</mo></mrow></math></span> to enhance our understanding of climate change by extracting events with high values in both variables was confirmed. Furthermore, bivariate analysis and nonstationarity significantly influenced the estimation of the return period, indicating that the proposed framework facilitates robust adjustment to nonstationary rainfall patterns, ensuring the dependable utilization of current design frequencies in the context of climate change.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"190 ","pages":"Article 106471"},"PeriodicalIF":4.8,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143855798","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

Recommendations on benchmarks for the DeNitrification–DeComposition model application in China: Insights from literature analysis 反硝化分解模型在中国应用的基准建议：来自文献分析的见解

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-04-17 DOI: 10.1016/j.envsoft.2025.106485

Nanchi Shen , Jiani Tan , Qing Mu , Ling Huang , Wenbo Xue , Yangjun Wang , Maggie Chel Gee Ooi , Mohd Talib Latif , Gang Yan , Lam Yun Fat Nicky , Li Li

{"title":"Recommendations on benchmarks for the DeNitrification–DeComposition model application in China: Insights from literature analysis","authors":"Nanchi Shen , Jiani Tan , Qing Mu , Ling Huang , Wenbo Xue , Yangjun Wang , Maggie Chel Gee Ooi , Mohd Talib Latif , Gang Yan , Lam Yun Fat Nicky , Li Li","doi":"10.1016/j.envsoft.2025.106485","DOIUrl":"10.1016/j.envsoft.2025.106485","url":null,"abstract":"<div><div>This study addresses the lack of standardized evaluation criteria for the DeNitrification–DeComposition (DNDC) model, widely used to assess greenhouse gas emissions in agricultural systems. Based on a comprehensive analysis of literature data, we propose a set of benchmarks to improve the model's reliability, focusing on crop yield, soil organic carbon (SOC), nitrous oxide (N<sub>2</sub>O), and methane (CH<sub>4</sub>) emissions within the context of Chinese agriculture. Key performance indicators, including correlation coefficient (R), normalized root mean square error (nRMSE), and index of agreement (IOA), are defined to enhance model calibration and validation. The proposed benchmarks aim to provide a consistent reference for DNDC applications, facilitating accurate assessments of greenhouse gas emissions and supporting sustainable agricultural practices. By synthesizing existing research, this study contributes to improving model accuracy and enhancing agricultural management strategies, with implications for climate change mitigation.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"190 ","pages":"Article 106485"},"PeriodicalIF":4.8,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864133","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

NSVineCopula: R package for modeling non-stationary multivariate dependence NSVineCopula：非平稳多变量相关性建模的R包

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-04-17 DOI: 10.1016/j.envsoft.2025.106474

Q. Zhang , Y.P. Li , G.H. Huang , X.M. Huang , H. Wang , Z. Wang , Z.P. Xu , Y.Y. Wang , Z.Y. Shen

{"title":"NSVineCopula: R package for modeling non-stationary multivariate dependence","authors":"Q. Zhang , Y.P. Li , G.H. Huang , X.M. Huang , H. Wang , Z. Wang , Z.P. Xu , Y.Y. Wang , Z.Y. Shen","doi":"10.1016/j.envsoft.2025.106474","DOIUrl":"10.1016/j.envsoft.2025.106474","url":null,"abstract":"<div><div>A vine copula is a flexible method for multivariate dependence simulations that assumes stationarity. However, only a few studies have focused on non-stationarity and comprehensively developed nonstationary vine copula functions. In this study, a novel R package, NSVineCopula was developed and presented. Canonical-vine and Drawable-vine structure with 36 bivariate copula functions were considered in NSVineCopula. This package is capable of capturing non-stationary multivariate dependence, providing time-varying parameters for each bivariate copula, and quantifying the conditional probability. Notably, NSVineCopula provides a simple way for sampling non-stationary vine copulas. The capability of NSVineCopula was evaluated through two case studies: (1) agricultural drought risk assessment under compound dry-hot extreme conditions and water level prediction. The results demonstrate the advantages of NSVineCopula in non-stationary multivariate dependence analysis, and highlights the potential of NSVineCopula in many fields. Overall, NSVineCopula can provide valuable and robust functionalities for modeling nonstationary multivariate dependence.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"190 ","pages":"Article 106474"},"PeriodicalIF":4.8,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143851400","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

Automatic detection of in-stream river wood from random forest machine learning and exogenous indices using very high-resolution aerial imagery 基于随机森林机器学习和外生指数的河流木材自动检测

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-04-16 DOI: 10.1016/j.envsoft.2025.106460

Gauthier Grimmer , Romain Wenger , Germain Forestier , Valentin Chardon

引用次数: 0

An efficient data-driven method for isolating dry-weather flow from total combined sewer flow data 一种有效的数据驱动方法，用于从总组合下水道流量数据中分离干燥天气流量

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-04-15 DOI: 10.1016/j.envsoft.2025.106470

Katie Straus , John Barton , M. Sadegh Riasi , Lilit Yeghiazarian

{"title":"An efficient data-driven method for isolating dry-weather flow from total combined sewer flow data","authors":"Katie Straus , John Barton , M. Sadegh Riasi , Lilit Yeghiazarian","doi":"10.1016/j.envsoft.2025.106470","DOIUrl":"10.1016/j.envsoft.2025.106470","url":null,"abstract":"<div><div>Wastewater treatment plants in combined sewer systems are often required to accommodate the widely fluctuating flow due to the dynamic interactions between multiple water flow sources. A major challenge in wastewater management, and particularly in combined sewer overflow (CSO) mitigation, is decoupling the total sewer flow into its components: dry-weather flow (DWF) and rain-derived inflow and infiltration (RDII). While current approaches have been successful for dry climates, their requirement to filter out rainfall-affected data often leads to inaccurate estimates for flow components in wet and semi-wet climates or seasons. The twice-detrended residual method (TDRM) developed in this study is a data-driven model that seeks to alleviate this drawback while utilizing all available data. We implement TDRM with sewer flow data collected from three locations and time periods within the Greater Cincinnati, Ohio Metropolitan Sewer District, and demonstrate that it can successfully decouple rain-inclusive flow datasets into their weekly DWF and RDII components.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"190 ","pages":"Article 106470"},"PeriodicalIF":4.8,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864134","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