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Do LSTM memory states reflect the relationships in reduced-complexity sandy shoreline models LSTM 记忆状态是否反映了复杂度降低的沙质海岸线模型中的关系
IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-09-30 DOI: 10.1016/j.envsoft.2024.106236
Kit Calcraft , Kristen D. Splinter , Joshua A. Simmons , Lucy A. Marshall
Equilibrium-based models are a transparent method of modelling shoreline change, though often too simplistic to capture complex dynamics. Conversely, deep learning methodologies offer greater predictive power at the expense of transparency. In this research we scrutinize the internal workings of an LSTM shoreline model. A regression-based probe is used to show that cell state vectors, responsible for past-to-future information flow, autonomously generate equilibrium-like information akin to the physics-based equilibrium term of the ShoreFor model, Ωeq. The variation in probe skill throughout training is tracked to show that at 5 of 6 transects, the LSTM was able to meaningfully acquire equilibrium information (ΣΔR2 = 0.3–0.6). The results of this work offer evidence that an LSTM may model shoreline change with internal methods that are consistent with the current understanding of coastal shoreline dynamics. These physically meaningful representations emphasize the importance of co-evolution between machine learning and physics-based approaches moving forward.
基于平衡的模型是模拟海岸线变化的一种透明方法,但往往过于简单,无法捕捉复杂的动态变化。与此相反,深度学习方法以牺牲透明度为代价,却能提供更强的预测能力。在这项研究中,我们仔细研究了 LSTM 海岸线模型的内部运作。我们使用基于回归的探针来证明,负责过去到未来信息流的细胞状态向量会自主生成类似于 ShoreFor 模型中基于物理学的平衡项 Ωeq 的平衡信息。对整个训练过程中探测技能的变化进行了跟踪,结果表明,在 6 个横断面中的 5 个横断面,LSTM 能够有意义地获取平衡信息(ΣΔR2 = 0.3-0.6)。这项工作的结果证明,LSTM 可以用内部方法模拟海岸线变化,这与目前对海岸线动态的理解是一致的。这些具有物理意义的表征强调了机器学习与基于物理的方法共同进化的重要性。
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引用次数: 0
Modelling and validating soil carbon dynamics at the long-term plot scale using the rCTOOL R package 利用 rCTOOL R 软件包建立和验证长期地块尺度的土壤碳动态模型
IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-09-27 DOI: 10.1016/j.envsoft.2024.106229
Franca Giannini-Kurina , João Serra , Bent Tolstrup Christensen , Jørgen Eriksen , Nicholas John Hutchings , Jørgen Eivind Olesen , Johannes Lund Jensen
We introduce rCTOOL, an open-source R package for carbon (C) turnover modelling, featuring comprehensive documentation and a user-friendly interface. As an enhanced version of the widely used Danish C-TOOL model, rCTOOL maintains minimal input data requirements and reliable performance, while addressing the original model's limitations in openness and documentation. To validate rCTOOL, we analysed topsoil Soil Organic Carbon (SOC) dynamics using data from the long-term Askov straw disposal experiment (1981–2019), which quantifies the impact of varying annual straw C inputs on SOC storage. Our validation shows an unbiased global prediction error of less than 10%, with a mean error of 1.1 Mg C/ha (CI -0.7–3.0 Mg C/ha). The discrepancies between observed and predicted values were primarily due to spatiotemporal variability represented by the block and year in the long-term field experiment. We demonstrate how rCTOOL is a reliable asset for diverse applications in SOC management and research.
我们介绍的 rCTOOL 是一个用于碳(C)周转建模的开源 R 软件包,具有全面的文档和友好的用户界面。作为广泛使用的丹麦 C-TOOL 模型的增强版,rCTOOL 保持了最低的输入数据要求和可靠的性能,同时解决了原始模型在开放性和文档方面的局限性。为了验证 rCTOOL,我们利用长期阿斯科夫秸秆处理实验(1981-2019 年)的数据分析了表土土壤有机碳(SOC)动态,该实验量化了每年不同的秸秆 C 输入对 SOC 储存的影响。我们的验证结果表明,全球预测误差小于 10%,平均误差为 1.1 毫克碳/公顷(CI -0.7-3.0 毫克碳/公顷)。观测值和预测值之间的差异主要是由于长期田间试验中以区块和年份为代表的时空变异造成的。我们展示了 rCTOOL 如何成为 SOC 管理和研究领域各种应用的可靠资产。
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引用次数: 0
Using national hydrologic models to obtain regional climate change impacts on streamflow basins with unrepresented processes 利用国家水文模型获取区域气候变化对未体现过程的河川流域的影响
IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-09-27 DOI: 10.1016/j.envsoft.2024.106234
Patience Bosompemaa , Andrea Brookfield , Sam Zipper , Mary C. Hill
Climate change is increasingly impacting water availability. National-scale hydrologic models simulate streamflow resulting from many important processes, but often without processes such as human water use and management activities. This work explores and tests methods to account for such omitted processes using one national-scale hydrologic model. Two bias correction methods, Flow Duration Curve (FDC) and Auto-Regressive Integrated Moving Average (ARIMA), are tested on streamflow simulated by the US Geological Survey National Hydrologic Model (NHM-PRMS), which omits irrigation pumping. A semi-arid agricultural case study is used. FDC and ARIMA perform better for correcting low and high flows, respectively. A hybrid method performs well at both low and high flows; typical Nash-Sutcliffe values increased from <-1.00 to about 0.75. Results suggest methods with which national-scale hydrologic models can be bias-corrected for omitted processes to improve regional streamflow estimates. Utility of these correction methods in simulation of future projections is discussed.
气候变化对水资源供应的影响越来越大。国家尺度水文模型模拟了许多重要过程所产生的河水流量,但往往忽略了人类用水和管理活动等过程。这项工作利用一个国家尺度的水文模型,探索并测试了考虑此类遗漏过程的方法。在美国地质调查局国家水文模型(NHM-PRMS)模拟的溪流上测试了流量持续时间曲线(FDC)和自回归综合移动平均(ARIMA)这两种偏差校正方法,该模型忽略了灌溉抽水。采用的是半干旱农业案例研究。FDC 和 ARIMA 分别在修正低流量和高流量方面表现较好。一种混合方法在低流量和高流量时均表现良好;典型的 Nash-Sutcliffe 值从 <-1.00 增加到约 0.75。研究结果表明,全国尺度的水文模型可以根据遗漏过程进行偏差校正,以改进区域性的流量估算。讨论了这些校正方法在模拟未来预测中的实用性。
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引用次数: 0
Historical simulation performance evaluation and monthly flow duration curve quantile-mapping (MFDC-QM) of the GEOGLOWS ECMWF streamflow hydrologic model GEOGLOWS ECMWF 溪流水文模型的历史模拟性能评估和月流量持续时间曲线量化绘图 (MFDC-QM)
IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-09-27 DOI: 10.1016/j.envsoft.2024.106235
J.L. Sanchez Lozano , D.J. Rojas Lesmes , E.G. Romero Bustamante , R.C. Hales , E.J. Nelson , G.P. Williams , D.P. Ames , N.L. Jones , A.L. Gutierrez , C. Cardona Almeida
Global hydrological models are essential for managing water resources and predicting hydrological events. However, the local-scale usability of global models challenges big-data management, communication, adoption, and validation. Validation is the biggest challenge bercause of the need for large-scale data management and model calibration, which requires extensive and often inaccessible observed data. This study assesses the GEOGLOWS-ECMWF Global Hydrologic Model, revealing systematic biases that impact its accuracy. We propose a bias-correction methodology using flow duration curves to align non-exceedance probabilities of simulated and observed streamflow, significantly improving the GEOGLOWS model. Unfortunately, this approach does not inherently improve simulations in ungauged locations. The methodology not only enhances the GEOGLOWS model's accuracy but also stands as a versatile solution applicable across various hydrological models. This bias correction approach provides a tool for improving hydrological predictions and gives users the confidence to use global models for local water resource management and decision-making processes.
全球水文模型对于管理水资源和预测水文事件至关重要。然而,全球模型在地方范围内的可用性对大数据管理、交流、采用和验证提出了挑战。验证是最大的挑战,因为需要大规模的数据管理和模型校准,而这需要大量且通常无法获取的观测数据。本研究对 GEOGLOWS-ECMWF 全球水文模型进行了评估,揭示了影响其准确性的系统性偏差。我们提出了一种偏差校正方法,利用水流持续时间曲线来调整模拟和观测水流的非超标概率,从而显著改善 GEOGLOWS 模型。遗憾的是,这种方法并不能从本质上改善无测站地点的模拟。该方法不仅提高了 GEOGLOWS 模型的准确性,也是适用于各种水文模型的通用解决方案。这种偏差修正方法提供了一种改进水文预测的工具,使用户有信心将全球模型用于当地水资源管理和决策过程。
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引用次数: 0
Evaluation of the SpatioTemporal Asset Catalog for management and discovery of FAIR flood hazard models 评估用于管理和发现 FAIR 洪水灾害模型的时空资产目录
IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-09-26 DOI: 10.1016/j.envsoft.2024.106230
Seth Lawler , Thomas Williams , William Lehman , Christina Lindemer , David Rosa , Celso Ferreira , Chen Zhang
Approaches for performing flood hazards modeling and risk assessment at federal, state, and local agencies are undergoing emergent challenge for consistent metadata and cataloging systems to ensure the sharing of flood risk data in a Findable, Accessible, Interoperable, and Reusable (FAIR) manner. This paper explores the suitability of a suite of software and specifications developed by the Earth observation community for environmental modeling, which adhere to the FAIR principles not only for managing published or authoritative data but throughout the model development and flood hazard analysis phases. Specifically, we evaluate the SpatioTemporal Asset Catalog (STAC) in a pilot study undertaken as part of the Future of Flood Risk Data (FFRD) initiative of FEMA. The experimental results indicate the STAC ecosystem offers a flexible cloud native approach for linking data, managing metadata, and cataloging collections of models. Further, the STAC framework shows favorable results in a probabilistic and other use cases.
联邦、州和地方机构进行洪水灾害建模和风险评估的方法正面临着新的挑战,即需要一致的元数据和编目系统,以确保以可查找、可访问、可互操作和可重用(FAIR)的方式共享洪水风险数据。本文探讨了地球观测界为环境建模开发的一套软件和规范的适用性,这些软件和规范不仅在管理已发布或权威数据方面遵循 FAIR 原则,而且在整个模型开发和洪水灾害分析阶段都遵循该原则。具体而言,我们在一项试点研究中对时空资产目录(STAC)进行了评估,该研究是联邦紧急事务管理局未来洪水风险数据(FFRD)计划的一部分。实验结果表明,STAC 生态系统为连接数据、管理元数据和编目模型集合提供了灵活的云本地方法。此外,STAC 框架在概率和其他用例中也显示出良好的效果。
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引用次数: 0
CataEx: A multi-task export tool for the Google Earth Engine data catalog CataEx:谷歌地球引擎数据目录的多任务导出工具
IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-09-26 DOI: 10.1016/j.envsoft.2024.106227
Gisela Domej , Kacper Pluta , Marek Ewertowski
Satellite imagery is provided by different missions such as ASTER, MODIS, Sentinel, Landsat, IKONOS, GeoEye, SPOT, WorldView, Pléaides, or RapidEye. One of the major encumbrances is the digital volume that satellite imagery claims during download, storage, and processing. This inconvenience has been overcome since 2010 by the Google Earth Engine, a cloud-based platform for global geospatial analysis dedicated to users who are not necessarily remote sensing specialists.
However, compatibility with traditional desktop or web-based GIS software remains tricky as bringing satellite imagery from the Google Earth Engine to another software requires a coded export via JavaScript or Python.
We present the multi-functional code tool CataEx in JavaScript to exemplify several essential types of computations (i.e., filtering of image collections, cloud masking, index and histogram generation, and layer creation) before exporting images as GeoTIFFs. CataEx is kept deliberately simple without much "sophisticated" code language to allow JavaScript beginners to get familiar with basic coding concepts and develop their own scripts.
卫星图像由不同的任务提供,如 ASTER、MODIS、Sentinel、Landsat、IKONOS、GeoEye、SPOT、WorldView、Pléaides 或 RapidEye。其中一个主要障碍是卫星图像在下载、存储和处理过程中产生的数字体积。自 2010 年以来,谷歌地球引擎(Google Earth Engine)克服了这一不便,它是一个基于云的全球地理空间分析平台,专门面向不一定是遥感专家的用户。然而,与传统桌面或基于网络的 GIS 软件的兼容性仍然很棘手,因为将卫星图像从谷歌地球引擎导出到其他软件需要通过 JavaScript 或 Python 进行编码导出、在将图像导出为 GeoTIFFs 之前,我们介绍了 JavaScript 中的多功能代码工具 CataEx,它演示了几种基本计算类型(即图像集合过滤、云遮蔽、索引和直方图生成以及图层创建)。CataEx 特意保持简单,没有太多 "复杂 "的代码语言,以便 JavaScript 初学者熟悉基本编码概念并开发自己的脚本。
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引用次数: 0
A web-based tool for watershed delineation considering lakes and reservoirs 基于网络的湖泊和水库流域划分工具
IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-09-26 DOI: 10.1016/j.envsoft.2024.106232
Beichen Zhang , Junzhi Liu , Bin Zhang , Dawei Xiao , Min Chen
Lakes have significant impacts on watershed hydrology. However, until now, no web-based tool has been available for watershed delineation considering lakes. In this study, we developed a tool to address this, enabling non-exports to delineate watersheds. First, a conceptual data model was proposed to represent related spatial units and their flow relationships, including rivers, lakes, river sub-basins, lake hillslopes, and flow paths. Subsequently, a web-based tool was designed and implemented, which enables users to select an area of interest and obtain watershed delineation results without the need for software installation or data preparation. This tool also supports for the customization of data and parameters. Two case studies, conducted at the Fushi Reservoir and Mahu Lake, demonstrated the system's usability. To our knowledge, this study presents the first web-based tool for watershed delineation that considers lakes, and it has great potential for applications in watershed modeling and management.
湖泊对流域水文有重大影响。然而,到目前为止,还没有基于网络的工具可用于考虑湖泊因素的流域划分。在本研究中,我们开发了一种工具来解决这一问题,使非出口商能够划定流域。首先,我们提出了一个概念数据模型,用于表示相关的空间单元及其流动关系,包括河流、湖泊、河流子流域、湖泊山坡和流动路径。随后,设计并实施了一个基于网络的工具,用户可以选择感兴趣的区域,无需安装软件或准备数据即可获得流域划分结果。该工具还支持数据和参数的定制。在 Fushi 水库和 Mahu 湖进行的两个案例研究证明了该系统的可用性。据我们所知,这项研究提出了第一个考虑湖泊的基于网络的流域划分工具,它在流域建模和管理方面具有巨大的应用潜力。
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引用次数: 0
Development of an inclusive, scalable, and flexible hydrologic modeling system: Establishing integrated flood simulation system at agricultural watersheds 开发具有包容性、可扩展性和灵活性的水文建模系统:建立农业流域综合洪水模拟系统
IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-09-24 DOI: 10.1016/j.envsoft.2024.106225
Jihye Kwak , Junhyuk Lee , Jihye Kim , Hyunji Lee , Seokhyeon Kim , Sinae Kim , Moon Seong Kang
In this study, we developed a comprehensive hydrological modeling system to address the diverse needs of hydrologists and researchers. The system comprised nine modules, each serving a specific purpose. These modules include a multiplicative random cascade model, frequency analysis, inflow simulation, Hydrologic Engineering Center – 5, Hydrologic Engineering Center – River Analysis System, and farmland drainage simulations. The system follows a structured sequence within a large framework, beginning with user inputs for the initial condition information and period specifications for frequency analysis. It then calculates the time-disaggregated precipitation data utilizing the Dask distributed server for efficient computation. Subsequent module computations were conducted on dedicated mask workers. The Integrated Database serves as a comprehensive repository for simulation studies, encompassing historical precipitation data, shared socioeconomic pathways, climate change scenario data, and reservoir and farmland survey data. This system has been used in several studies and has provided cohesive and reliable results for flood simulations.
在这项研究中,我们开发了一个综合水文建模系统,以满足水文学家和研究人员的不同需求。该系统由九个模块组成,每个模块都有特定用途。这些模块包括乘法随机级联模型、频率分析、流入模拟、水文工程中心 - 5、水文工程中心 - 河流分析系统和农田排水模拟。该系统在一个大框架内按结构顺序运行,首先由用户输入初始条件信息和频率分析的周期规格。然后,系统利用 Dask 分布式服务器计算按时间分列的降水数据,以提高计算效率。随后的模块计算由专门的掩码工作者进行。综合数据库是模拟研究的综合资料库,包括历史降水数据、共享的社会经济路径、气候变化情景数据以及水库和农田调查数据。该系统已在多项研究中使用,并为洪水模拟提供了连贯可靠的结果。
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引用次数: 0
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 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-09-23 DOI: 10.1016/j.envsoft.2024.106226
Aylar Samadi, Keighobad Jafarzadegan, Hamid Moradkhani
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 (SWMM) for simulating water movement within the storm drain system, and an advanced DEM-based flood inundation module that leverages SWMM 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.
全球城市洪水的增加带来了巨大的挑战,影响着全球各地的社区。本研究针对大都市规模的冲积洪水引入了洪水后淹没建模框架。我们采用了双重排水建模方法,以提高准确性。该框架由两个主要部分组成:一个是用于模拟雨水排放系统内水流运动的雨水管理模型(SWMM),另一个是基于 DEM 的先进洪水淹没模块,该模块利用雨水管理模型的结果来预测洪水淹没区域。与双排水系统建模中常用的传统洪水蔓延模型相比,该模块将高分辨率 DEM 单元纳入地表水流路由过程,从而捕捉到错综复杂的地表地形。此外,该模块还考虑了降雨对冲积洪水淹没区绘图的直接影响,从而提高了精度。为了评估拟议模型的准确性,采用了两步验证方法。其中包括将提议的模型结果与哈维飓风后测量到的高水位线以及水动力模型生成的洪水深度图进行比较。研究结果肯定了我们提出的框架在大都市环境中绘制洪水后淹没图的有效性。这种方法为城市洪水建模提供了一种可靠的方法,是应对城市洪水相关挑战的一个进步。
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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 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 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
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.
河口在维持沿岸生态系统的生态平衡方面发挥着至关重要的作用。盐度入侵会破坏这些脆弱的生态系统,影响沿海地区的水生生物和人类活动。准确预测盐度入侵对管理水资源和保护生态系统至关重要。本文介绍了一种新颖的混合工具,即 Hybrid-EBM 模型,用于预测盐边入侵长度和河口盐度。新的 Hybrid-EBM 模型将最先进的河口箱模型(EBM)与机器学习算法相结合,可准确预测盐度入侵事件。实验结果凸显了混合-EBM 在盐度预测方面的有效性,与 EBM 得出的 4.22 psu 相比,混合-EBM 的均方根误差为 3.41 psu。本文的研究成果极大地促进了人们对河口生态系统盐度入侵影响的认识,有助于全球沿海地区的可持续发展。
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引用次数: 0
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Environmental Modelling & Software
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