Environmental Modelling & Software最新文献_第3页

Development of a web-based tool for rapid flood inundation modeling 开发基于网络的快速洪水淹没建模工具

IF 4.6 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Environmental Modelling & Software

Pub Date : 2026-01-13 DOI: 10.1016/j.envsoft.2026.106876

Dawei Xiao , Binjie Yuan , Zhengxu Guo , Wanhong Yang , Jingchao Jiang , Min Chen , Guonian Lv , Junzhi Liu

To address the growing risk of floods under global climate change, management agencies need flood inundation modeling to support decision-making and emergency response. However, traditional desktop-based modeling remains a complex and time-consuming process, making it difficult for users to perform rapid flood simulations. To overcome this limitation, this study developed a web-based rapid flood modeling tool based on the LISFLOOD-FP model. Each key step involved in the modeling process—such as data preparation, preprocessing, model run and calibration, and postprocessing— was encapsulated into an automated executable workflow. These workflows were deployed on servers, published as web services, and invoked from a web-based interface, significantly streamlining and simplifying the modeling process. Four flood events in the upper Missouri River Basin were successfully simulated to showcase the tool's capability. This user-friendly web-based tool enables users to conduct flood inundation modeling quickly, thereby lowering user barriers and facilitating timely flood risk mitigation.

为了应对全球气候变化下日益增长的洪水风险，管理机构需要洪水淹没建模来支持决策和应急响应。然而，传统的基于桌面的建模仍然是一个复杂且耗时的过程，使得用户难以执行快速的洪水模拟。为了克服这一局限性，本研究基于LISFLOOD-FP模型开发了基于web的快速洪水建模工具。建模过程中涉及的每个关键步骤（如数据准备、预处理、模型运行和校准以及后处理）都被封装到一个自动化的可执行工作流中。这些工作流部署在服务器上，作为web服务发布，并从基于web的接口调用，显著地简化了建模过程。成功地模拟了密苏里河上游流域的四次洪水事件，以展示该工具的能力。这个用户友好的基于web的工具使用户能够快速进行洪水淹没建模，从而降低用户的障碍，并促进及时减轻洪水风险。

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引用次数: 0

Towards an improved language for river data analysis: Demonstration for the highly-regulated Ohio River basin 迈向河流数据分析的改进语言：高度管制的俄亥俄河流域示范

IF 4.6 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Environmental Modelling & Software

Pub Date : 2026-01-13 DOI: 10.1016/j.envsoft.2026.106866

Gaurav Atreya , Todd Steissberg , Drew McAvoy , Xi Chen , Patrick Ray

We present the Network Analysis and Data Integration (NADI) System for extracting, organizing, analyzing, and visualizing river data with upstream/downstream relationships. The NADI System consists of a Geographical Information System (GIS) tool that uses spatial methods to generate the network, and a Domain Specific Language (DSL) that provides a concise and intuitive syntax for data analysis and is extensible through a plugin system. We demonstrate the capabilities of NADI using a case study of the Ohio River basin, showing it to be well-suited for large-scale metadata analysis based on river connections. The result of the case study shows that approximately half of the USGS streamflow gages in the Ohio Basin were constructed after dam(s) upstream, and only 35% of the gages remain without any dams upstream. These unaffected gages only account for 1.2% of the measured streamflow, showing the scarcity of natural streamflow data.

我们提出了网络分析和数据集成（NADI）系统，用于提取、组织、分析和可视化具有上游/下游关系的河流数据。NADI系统由地理信息系统（GIS）工具和领域特定语言（DSL）组成，后者使用空间方法生成网络，为数据分析提供简洁直观的语法，并可通过插件系统进行扩展。我们使用俄亥俄河流域的一个案例研究来展示NADI的功能，表明它非常适合基于河流连接的大规模元数据分析。案例研究的结果表明，在俄亥俄盆地，大约一半的USGS流量测量仪是在上游建坝之后建造的，只有35%的测量仪在上游没有建坝的情况下仍然存在。这些未受影响的仪表仅占测量流量的1.2%，显示了自然流量数据的稀缺性。

引用次数: 0

Compact bioretention cell for urban stormwater management: Assessment of hydrologic, hydraulic, and water quality performance via laboratory and SWMM modelling 城市雨水管理的紧凑型生物滞留电池：通过实验室和SWMM模型评估水文、水力和水质性能

IF 4.6 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Environmental Modelling & Software

Pub Date : 2026-01-13 DOI: 10.1016/j.envsoft.2026.106877

Shaahin Nazarpour Tameh , Jennifer Drake , Anna Palla , Ilaria Gnecco

Bioretention cells (BRCs) are widely implemented to restore undeveloped hydrologic cycle; however, conventional BRCs need considerable surface area, limiting their applicability in densely populated areas. Compact BRCs like Filterra® have been designed to provide comparable hydrologic and pollutant removal effectiveness with a smaller footprint. The hydraulic characteristics of Filterra's engineered media were assessed through laboratory testing using KSAT and HYPROP devices and these results were integrated with field monitoring to implement a field-validated storm water management model (SWMM). Laboratory results showed a hydraulic conductivity of 1750 mm/h. The validated SWMM model replicated the outflow dynamics with satisfactory accuracy (KGE >0.35, R² > 0.47), and the total suspended solids (TSS) removal was suitably predicted (R² = 0.83). Results demonstrate that the field-validated SWMM model can be used to evaluate both hydrologic performance and pollutant TSS removal efficiency of compact BRCs, while noting its limitations in representing complex TSS dynamics.

生物滞留细胞（BRCs）被广泛应用于恢复未开发的水文循环；然而，传统的BRCs需要相当大的表面积，限制了它们在人口稠密地区的适用性。像Filterra®这样的紧凑型brc设计用于提供类似的水文和污染物去除效果，占地面积更小。通过KSAT和HYPROP设备对Filterra工程介质的水力特性进行了实验室测试，并将这些结果与现场监测相结合，实现了现场验证的雨水管理模型（SWMM）。实验室结果显示其水力传导率为1750 mm/h。经过验证的SWMM模型以令人满意的精度（KGE >0.35, R2 > 0.47）复制了流出动态，并且预测了总悬浮物（TSS）去除（R2 = 0.83）。结果表明，现场验证的SWMM模型可用于评估致密BRCs的水文性能和污染物TSS去除效率，同时指出其在表示复杂TSS动态方面的局限性。

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引用次数: 0

SPAR-TC: A framework for accounting spatial representativeness in triple collocation SPAR-TC：三重搭配中空间代表性的核算框架

IF 4.6 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Environmental Modelling & Software

Pub Date : 2026-01-12 DOI: 10.1016/j.envsoft.2026.106874

Diksha Gupta, C.T. Dhanya

Triple collocation (TC) has been widely used to overcome the rarity of “ground truth” in geophysical measurements. While TC assumes all systems observe the same underlying geophysical variable, it does not inherently correct for spatial representativeness errors due to different spatial measurement systems. To address this, we propose the Spatially Representative Triple Collocation (SPAR-TC), which accounts for the spatial variability of the “ground truth” across different spatial scales. A synthetic soil moisture experiment assessed SPAR-TC sensitivity to spatial heterogeneity and sample size, followed by a real-world application with remotely sensed precipitation data. Results showed that SPAR-TC provides more reliable estimates of “true” error variance compared with traditional TC, especially in spatially heterogeneous regions. Both methods yield comparable dataset rankings; however, SPAR-TC provides error variance estimates more consistent with ground-based observations. Hence, SPAR-TC offers robust framework for addressing spatial representativeness errors and improves error quantification for datasets with differing spatial support.

为了克服地球物理测量中“地面真值”的稀缺性，三重配置（TC）被广泛应用。虽然TC假设所有系统都观测到相同的潜在地球物理变量，但它并不能固有地纠正由于不同空间测量系统而导致的空间代表性误差。为了解决这个问题，我们提出了空间代表性三重搭配（SPAR-TC），它解释了“地面真值”在不同空间尺度上的空间变异性。综合土壤湿度试验评估了SPAR-TC对空间异质性和样本量的敏感性，随后进行了遥感降水数据的实际应用。结果表明，SPAR-TC比传统TC提供了更可靠的“真实”误差方差估计，特别是在空间异质性区域。两种方法都会产生可比较的数据集排名；然而，SPAR-TC提供的误差方差估计值与地面观测值更为一致。因此，SPAR-TC为解决空间代表性误差提供了强大的框架，并改进了具有不同空间支持的数据集的误差量化。

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引用次数: 0

Model support tools for Informed Decision Making - MIDAS and sensitivity analysis 模型支持工具的知情决策MIDAS和敏感性分析

IF 4.6 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Environmental Modelling & Software

Pub Date : 2026-01-12 DOI: 10.1016/j.envsoft.2026.106873

Matthew Hardy, Elena Bastianon, d'Artis Kancs, Enrico Pisoni, Rossana Rosati

Models play a key role in informing evidence-based policymaking, particularly in addressing complex societal-economic-environmental issues. By promoting informed decision-making and responsible use of models, the European Commission (EC) has developed tools and procedures for a trustworthy modelling workflow. Two complementary good modelling practice tools of the EC are presented, and their crucial role in enhancing modelling transparency is detailed. MIDAS – a publicly accessible meta-database that consolidates a standardised information on models and provides real-time information to modelling-supported EU legislative documents – ensures FAIR principles in model use. Uncertainty and Sensitivity Analysis methods allows us to identify and prioritise sources of uncertainty, and visualise how model uncertainties affect decision-making. To illustrate the role of sensitivity analysis for policymaking an application on the Screening for High Emission Reduction Potential on Air (SHERPA) model is presented. The SIML@B tool for global sensitivity analysis developed by European Commission has been employed.

模型在为基于证据的决策提供信息方面发挥着关键作用，特别是在解决复杂的社会、经济和环境问题方面。通过促进知情决策和负责任地使用模型，欧洲委员会（EC）开发了可信赖的建模工作流程的工具和程序。介绍了欧共体的两个互补的良好建模实践工具，并详细介绍了它们在提高建模透明度方面的关键作用。MIDAS是一个可公开访问的元数据库，它整合了关于模型的标准化信息，并为支持建模的欧盟立法文件提供实时信息，它确保了模型使用中的公平原则。不确定性和敏感性分析方法使我们能够识别和优先考虑不确定性的来源，并可视化模型的不确定性如何影响决策。为了说明敏感性分析在政策制定中的作用，本文介绍了空气高减排潜力筛选（SHERPA）模型的应用。采用了欧盟委员会开发的SIML@B全球敏感性分析工具。

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引用次数: 0

Coupling a micro-genetic algorithm with RegCM5 for improving extreme precipitation simulations over Southeast Asia 微遗传算法与RegCM5耦合改进东南亚极端降水模拟

IF 4.6 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Environmental Modelling & Software

Pub Date : 2026-01-10 DOI: 10.1016/j.envsoft.2026.106871

Zixuan Zhou , Ji Won Yoon , Thanh Nguyen-Xuan , Jina Hur , Seon Ki Park , Eun-Soon Im

Regional climate models (RCMs) are essential for producing fine-scale climate information, but their effectiveness is highly sensitive to the combination of physical parameterizations and optimal settings of key parameters. To tackle this problem, this study develops a coupled modeling system that integrates a micro-genetic algorithm (μGA) with the Regional Climate Model version 5 (RegCM5), focusing on optimizing parameters in the Tiedtke convection scheme, crucial for precipitation simulations. Using the benchmarking version of RegCM5 for Southeast Asia, we aim to identify the optimal parameter set that enhances performance for three extreme precipitation events. The evaluation of this parameter set is then conducted by simulating six additional extreme events. Results show that simulations with optimized parameters improve both precipitation and temperature compared to the default model, significantly reducing biases, particularly over ocean regions. Our coupled RegCM5-μGA system will aid the broader RegCM5 community in enhancing model performance in their target regions.

区域气候模式是产生精细尺度气候信息的关键，但其有效性对物理参数化和关键参数的最佳设置的组合高度敏感。为了解决这一问题，本研究开发了一个将微遗传算法（μGA）与区域气候模式第5版（RegCM5）相结合的耦合建模系统，重点优化了降水模拟中关键的Tiedtke对流方案的参数。使用RegCM5东南亚基准版本，我们的目标是确定提高三种极端降水事件性能的最佳参数集。然后通过模拟另外六个极端事件对该参数集进行评估。结果表明，与默认模式相比，使用优化参数的模拟改善了降水和温度，显著减少了偏差，特别是在海洋区域。我们的耦合RegCM5-μGA系统将帮助更广泛的RegCM5社区提高模型在目标区域的性能。

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引用次数: 0

A numerical modelling-supported digital twin for urban floods monitoring in typhoon or storm scenario 台风或风暴情景下城市洪水监测的数值模拟支持的数字孪生

IF 4.6 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Environmental Modelling & Software

Pub Date : 2026-01-09 DOI: 10.1016/j.envsoft.2026.106870

Tangyao Ai , Liang Gao , Xianfei Yin , Haoxuan Du , Qingbiao Li , Hongcai Zhang

Digital twin enables participatory system assessment and decision-making, establishing bidirectional connections between virtual system and real-world urban operations. Nevertheless, its widespread implementation in the urban flood faces persistent barriers to incorporate physics-guided urban flooding prediction with a scalable visualization platform. This study proposes a high-fidelity hydrodynamic digital twin framework that combines real-time forecasting data visualization platform with a numerical urban flood model by proposing an interactive interface. The framework consists of (1) a data acquisition layer that consolidates various inputs into specialized databases, (2) a modeling layer that employs numerical simulations for high-resolution flood predictions, and (3) a visualization layer that transforms outputs into interpretable web formats. The framework enables users to upload rainfall and storm data through a web interface and initiate urban flooding simulation. It allows real-time prediction of urban floods under a designed storm or a tropical scenario. The feasibility of the framework is tested by applying it to the Macao Peninsula during typhoon Hato (2017). The integration of a numerical model into a digital twin creates an intelligent decision-support framework, enabling real-time hydrodynamic forecasting, and dynamic scenario visualization for urban floods.

数字孪生使参与式系统评估和决策成为可能，在虚拟系统和现实城市运行之间建立双向联系。然而，它在城市洪水中的广泛实施面临着将物理指导的城市洪水预测与可扩展的可视化平台相结合的持续障碍。本研究提出了一种高保真水动力数字孪生框架，通过交互界面将实时预测数据可视化平台与城市洪水数值模型相结合。该框架包括(1)一个数据采集层，它将各种输入整合到专门的数据库中；(2)一个建模层，它采用数值模拟进行高分辨率洪水预测；(3)一个可视化层，它将输出转换为可解释的网络格式。该框架使用户可以通过网络界面上传降雨和风暴数据，并启动城市洪水模拟。它可以在设计的风暴或热带情景下实时预测城市洪水。将该框架应用于台风天鸽（2017）期间的澳门半岛，验证了该框架的可行性。将数值模型集成到数字孪生体中创建了一个智能决策支持框架，实现了城市洪水的实时水动力预测和动态场景可视化。

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引用次数: 0

Development of an interactive web-based tool for flood risk analysis and climate–resilient road drainage design: RiskDRAIN 开发用于洪水风险分析和气候适应性道路排水设计的交互式网络工具：RiskDRAIN

IF 4.6 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Environmental Modelling & Software

Pub Date : 2026-01-09 DOI: 10.1016/j.envsoft.2026.106867

Mohammad Fereshtehpour , Rashid Bashir , Neil F. Tandon

As climate change intensifies extreme rainfall, traditional design storm methods based on stationary assumptions are increasingly inadequate, often leading to misdesigned drainage infrastructure. To address this and manage projection uncertainties, we developed RiskDRAIN, a web-based application designed for the risk-based adjustment of projected design storms. RiskDRAIN, which stands for Risk-based Design for Resilient Adaptation to Infrastructure Needs, integrates risk analysis with Canadian downscaled CMIP6 projections (CanDCS-M6). The framework incorporates Intensity-Duration-Frequency (IDF) curves derived from the IDF-CC tool, considering two projection techniques (Clausius-Clapeyron scaling and Equidistance Quantile Matching) with GEV and Gumbel distributions, covering a range of emission pathways (SSP2-4.5, SSP5-8.5) and future horizons. Through an interactive interface, users refine design storms by evaluating provincial and site-specific risks derived from hazard exposure and multi-dimensional vulnerability (socio-economic, transportation, and environmental). Validated through a highway drainage case study, RiskDRAIN empowers practitioners with a data-driven platform for cost-effective, climate-resilient infrastructure planning.

随着气候变化加剧极端降雨，基于固定假设的传统设计风暴方法越来越不充分，往往导致排水基础设施设计不当。为了解决这个问题并管理预测的不确定性，我们开发了RiskDRAIN，这是一个基于网络的应用程序，旨在根据预测设计风暴的风险进行调整。RiskDRAIN是基于风险的基础设施需求弹性适应设计，将风险分析与加拿大缩小版CMIP6预测（CanDCS-M6）相结合。该框架结合了来自IDF- cc工具的强度-持续时间-频率（IDF）曲线，考虑了GEV和Gumbel分布的两种投影技术（Clausius-Clapeyron缩放和等距离分位数匹配），涵盖了一系列发射路径（SSP2-4.5, SSP5-8.5）和未来视野。通过交互界面，用户通过评估来自危害暴露和多维脆弱性（社会经济、交通和环境）的省级和场地特定风险来完善设计风暴。通过高速公路排水案例研究，RiskDRAIN为从业者提供了一个数据驱动的平台，以实现成本效益高、适应气候变化的基础设施规划。

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引用次数: 0

Comment on Williams (2025): “Friends don't let friends use NSE or KGE for hydrologic model accuracy evaluation: A rant with data and suggestions for better practice” 评论：“朋友不让朋友使用NSE或KGE来评估水文模型的精度：一篇关于数据和更好实践建议的评论”

IF 4.6 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Environmental Modelling & Software

Pub Date : 2026-01-09 DOI: 10.1016/j.envsoft.2026.106869

Martyn P. Clark , Wouter J.M. Knoben , Diana Spieler , Gaby J. Gründemann , Cyril Thébault , Nicolás A. Vásquez , Andrew W. Wood , Yalan Song , Chaopeng Shen , Shaun Carney , Katie van Werkhoven

Williams (2025), hereafter W25, raises valid concerns about the widespread use of the Nash–Sutcliffe Efficiency (NSE) and Kling–Gupta Efficiency (KGE) metrics in hydrologic model evaluation, arguing that these skill scores confound model accuracy with flow variability and should be replaced by error-based metrics such as the Root Mean Squared Error (RMSE) and the Mean Absolute Error (MAE). While we agree that model evaluation often lacks critical interpretation, we disagree that abandoning skill scores offers a constructive path forward. In this commentary, we discuss three main limitations in the W25 paper. First, we contend that W25 gives little attention to the broader literature on hydrologic model evaluation, leaving its recommendations weakly grounded in existing research. Second, we note that W25's recommendation to replace skill scores with error-based metrics such as RMSE does not resolve the underlying issue: both skill scores and error-based metrics conflate spatial variations in model accuracy with variations in flow variability. Third, we suggest that W25 overlooks the value of NSE and KGE in supporting standardized test environments that enable consistent model comparison. More generally, we argue that the W25 paper points the field in less productive directions for future research – simply replacing NSE and KGE with error-based metrics does not help the community address the core challenges in hydrologic model evaluation.

Williams(2025)（以下简称W25）对纳什-苏特克利夫效率（NSE）和克林-古普塔效率（KGE）指标在水文模型评估中的广泛使用提出了合理的担忧，认为这些技能分数混淆了模型准确性和流量可变性，应该被基于误差的指标（如均方根误差（RMSE）和平均绝对误差（MAE））所取代。虽然我们同意模型评估经常缺乏批判性的解释，但我们不同意放弃技能分数提供了一条建设性的前进道路。在这篇评论中，我们讨论了W25论文的三个主要局限性。首先，我们认为W25很少关注关于水文模型评估的更广泛的文献，使其建议在现有研究中缺乏基础。其次，我们注意到W25建议用基于误差的指标（如RMSE）代替技能分数并不能解决潜在的问题：技能分数和基于误差的指标都将模型精度的空间变化与流可变性的变化相混淆。第三，我们建议W25忽略了NSE和KGE在支持标准化测试环境中的价值，从而实现一致的模型比较。更一般地说，我们认为W25论文指出了该领域未来研究的低生产力方向——简单地用基于误差的指标取代NSE和KGE并不能帮助社区解决水文模型评估中的核心挑战。

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引用次数: 0

A LLM-based agent for the construction of typhoon knowledge graphs 基于llm的台风知识图谱构建代理

IF 4.6 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Environmental Modelling & Software

Pub Date : 2026-01-08 DOI: 10.1016/j.envsoft.2026.106856

Yi Huang , Yongqi Xia , Ran Tao , Donglai Jiao , Xiangqiang Min , Jieying Zheng , Yuting Jiang , Wenjun Wu , Peijun Du

Conventional knowledge graphs (KGs) struggle to integrate fragmented typhoon disaster data due to error accumulation and inadequate modeling of complex spatiotemporal relationships. To overcome this, we propose TyphoonKGent, an agent driven by large language models (LLMs), which employs hierarchical knowledge representation to structurally encode typhoon evolution and impacts. It decomposes KG construction into specialized tasks (role-playing, spatiotemporal completion, entity alignment, lifecycle determination, event identification) with domain-optimized Chain-of-Thought (CoT) generation to enhance LLM reasoning for geospatial tasks. Built via efficient LoRA-based fine-tuning of distilled LLaMA/Qwen models, TyphoonKGent improves accuracy by 30 % over non-finetuned baseline models and outperforms DeepSeek-R1 under 3-shot inference by 2 %–5 %. Furthermore, visualization applications confirm its effectiveness in trajectory analysis, impact mapping, and real-time decision support. The proposed TyphoonKGent enables end-to-end KG construction, cross-domain adaptability via customizable CoTs, task-specific fine-tuning, and scalable dynamic updates for disaster management.

传统的知识图（knowledge graph, KGs）由于误差积累和对复杂时空关系建模不足，难以整合碎片化的台风灾害数据。为了克服这个问题，我们提出了一个由大型语言模型（llm）驱动的智能体TyphoonKGent，它采用分层知识表示对台风的演变和影响进行结构化编码。它将KG构建分解为专门的任务（角色扮演、时空完成、实体对齐、生命周期确定、事件识别），并生成领域优化的思维链（CoT），以增强LLM对地理空间任务的推理能力。通过高效的基于lora的精炼LLaMA/Qwen模型微调，TyphoonKGent比未经微调的基线模型提高了30%的精度，在3次推理下比DeepSeek-R1高出2% - 5%。此外，可视化应用证实了其在轨迹分析、影响映射和实时决策支持方面的有效性。拟议的台风kgent支持端到端KG构建，通过可定制的CoTs实现跨域适应性，特定于任务的微调和可扩展的灾害管理动态更新。

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引用次数: 0