Environmental Modelling & Software最新文献_第7页

Increasing parameter identifiability through clustered time-varying sensitivity analysis 通过聚类时变敏感性分析提高参数可识别性

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-08-19 DOI: 10.1016/j.envsoft.2024.106189

Lu Wang , Yue-Ping Xu , Jiliang Xu , Haiting Gu , Zhixu Bai , Peng Zhou , Hongjie Yu , Yuxue Guo

{"title":"Increasing parameter identifiability through clustered time-varying sensitivity analysis","authors":"Lu Wang , Yue-Ping Xu , Jiliang Xu , Haiting Gu , Zhixu Bai , Peng Zhou , Hongjie Yu , Yuxue Guo","doi":"10.1016/j.envsoft.2024.106189","DOIUrl":"10.1016/j.envsoft.2024.106189","url":null,"abstract":"<div><p>Hydrological models are becoming progressively complex, leading to unclear internal model behavior, increasing uncertainty, and the risk of equifinality. Accordingly, our study provided a research framework based on global sensitivity analysis, aiming at unraveling the process-level behavior of high-complexity models, teasing out the main information, and ultimately exploiting its usage for model parameterization. The Distributed Hydrology-Soil-Vegetation Model implemented in a mountainous watershed was used. Results indicated that 5 soil parameters and 5 vegetation parameters were most important to control the streamflow responses, while their importance varied greatly throughout the simulation period. Four typical patterns of parameter importance corresponding to different watershed conditions (i.e., flood, short dry-to-wet, fast recession, and continuous dry periods) were successfully distinguished. Using this clustered information, parameters with short dominance times were more identifiable over the clusters (time periods) in which they were most important. The reduced posterior parameter space also slightly improved the model performance.</p></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"181 ","pages":"Article 106189"},"PeriodicalIF":4.8,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142047903","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

How to assess conditions for the acceptance of climate change adaptation measures by applying implementation probability Bayesian Networks in participatory processes 如何通过在参与式进程中应用实施概率贝叶斯网络来评估接受气候变化适应措施的条件

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-08-14 DOI: 10.1016/j.envsoft.2024.106188

Laura Müller , Max Czymai , Birgit Blättel-Mink , Petra Döll

{"title":"How to assess conditions for the acceptance of climate change adaptation measures by applying implementation probability Bayesian Networks in participatory processes","authors":"Laura Müller , Max Czymai , Birgit Blättel-Mink , Petra Döll","doi":"10.1016/j.envsoft.2024.106188","DOIUrl":"10.1016/j.envsoft.2024.106188","url":null,"abstract":"<div><p>Climate change adaptation measures are best identified participatorily, yet their implementation poses challenges. While Bayesian Network (BN) modeling has been widely used to assess how adaptation measures mitigate risks, we present how to develop, in a participatory process, an innovative BN type that quantifies the implementation probability of adaptation measures by considering conditions for actors’ acceptance as well as cultural worldviews. The BN structure was derived from participatorily identified causal networks, while the conditional probability tables were straightforwardly developed with stakeholder-assigned weights. Sensitivity analysis shows how BN structure and parameters influence the BN results. We found that our approach achieves knowledge integration and learning without overwhelming stakeholders with technical details. As BNs enable exploring scenarios, stakeholders learn that many plausible futures exist. Integrating our approach in participatory adaptation processes contributes to identifying the best combinations of implementation actions, reducing the “know-do gap” in local adaptation challenges.</p></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"181 ","pages":"Article 106188"},"PeriodicalIF":4.8,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1364815224002494/pdfft?md5=dea53c061631a1c69c03572d58c0e5a2&pid=1-s2.0-S1364815224002494-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142088855","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

PyCHAMP: A crop-hydrological-agent modeling platform for groundwater management PyCHAMP：用于地下水管理的作物-水文-代理建模平台

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-08-13 DOI: 10.1016/j.envsoft.2024.106187

Chung-Yi Lin , Maria Elena Orduna Alegria , Sameer Dhakal , Sam Zipper , Landon Marston

{"title":"PyCHAMP: A crop-hydrological-agent modeling platform for groundwater management","authors":"Chung-Yi Lin , Maria Elena Orduna Alegria , Sameer Dhakal , Sam Zipper , Landon Marston","doi":"10.1016/j.envsoft.2024.106187","DOIUrl":"10.1016/j.envsoft.2024.106187","url":null,"abstract":"<div><p>The Crop-Hydrological-Agent Modeling Platform (PyCHAMP) is a Python-based open-source package designed for modeling agro-hydrological systems. The modular design, incorporating aquifer, crop field, groundwater well, finance, and behavior components, enables users to simulate and analyze the interactions between human and natural systems, considering both environmental and socio-economic factors. This study demonstrates PyCHAMP's capabilities by simulating the dynamics in the Sheridan 6 Local Enhanced Management Area, a groundwater conservation program in the High Plains Aquifer in Kansas. We highlight how a model, empowered by PyCHAMP, accurately captures human-water dynamics, including groundwater level, water withdrawal, and the fraction of cropland dedicated to each crop. We also show how farmer behavior, and its representation, drives system outcomes more strongly than environmental conditions. The results indicate PyCHAMP's potential as a useful tool for human-water research and sustainable groundwater management, offering prospects for future integration with detailed sub-models and systematic evaluation of model structural uncertainty.</p></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"181 ","pages":"Article 106187"},"PeriodicalIF":4.8,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141985253","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

Modernizing the US National Fire Danger Rating System (version 4): Simplified fuel models and improved live and dead fuel moisture calculations 更新美国国家火灾危险分级系统（第 4 版）：简化燃料模型，改进活燃料和死燃料湿度计算

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-08-13 DOI: 10.1016/j.envsoft.2024.106181

W. Matt Jolly , Patrick H. Freeborn , Larry S. Bradshaw , Jon Wallace , Stuart Brittain

{"title":"Modernizing the US National Fire Danger Rating System (version 4): Simplified fuel models and improved live and dead fuel moisture calculations","authors":"W. Matt Jolly , Patrick H. Freeborn , Larry S. Bradshaw , Jon Wallace , Stuart Brittain","doi":"10.1016/j.envsoft.2024.106181","DOIUrl":"10.1016/j.envsoft.2024.106181","url":null,"abstract":"<div><p>The US National Fire Danger Rating System (USNFDRS) supports wildfire management decisions nationwide, but it has not been updated since 1988. Here we implement new fuel moisture models, and we simplify the fuel models while maintaining the overall USNFDRS structure. Modeled and measured live fuel moisture content values were highly correlated (<span><math><mrow><msup><mrow><mi>r</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>=</mo><mn>0</mn><mo>.</mo><mn>629</mn></mrow></math></span> with defaults and <span><math><mrow><msup><mrow><mi>r</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>=</mo><mn>0</mn><mo>.</mo><mn>693</mn></mrow></math></span> when species and location optimized). We also consolidated fuel models to five fuel types that eliminated significant index cross-correlation. Index seasonality compared between old (V2) and new USNFDRS models (v4) across six US National Forests was very similar (<span><math><mrow><mi>ρ</mi><mo>=</mo></mrow></math></span> 0.97). V4 was as good or better than V2 at predicting fire days in 92% of the cases tested and V4 effectively predicted wildfire days and large fire ignition days (AUCs 0.647 to 0.915). USNFDRS V4 can adequately depict spatial and temporal wildland fire potential and it can be adapted for worldwide use.</p></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"181 ","pages":"Article 106181"},"PeriodicalIF":4.8,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1364815224002421/pdfft?md5=0bad9d72fff3df2a680583db6650ac7a&pid=1-s2.0-S1364815224002421-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142047904","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

Modelling vegetation dynamics for future climates in Australian catchments: Comparison of a conceptual eco-hydrological modelling approach with a deep learning alternative 澳大利亚流域未来气候的植被动态建模：概念生态水文建模方法与深度学习替代方法的比较

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-08-12 DOI: 10.1016/j.envsoft.2024.106179

Hui Zou , Lucy Marshall , Ashish Sharma , Jie Jian , Clare Stephens , Philippa Higgins

{"title":"Modelling vegetation dynamics for future climates in Australian catchments: Comparison of a conceptual eco-hydrological modelling approach with a deep learning alternative","authors":"Hui Zou , Lucy Marshall , Ashish Sharma , Jie Jian , Clare Stephens , Philippa Higgins","doi":"10.1016/j.envsoft.2024.106179","DOIUrl":"10.1016/j.envsoft.2024.106179","url":null,"abstract":"<div><p>Dynamically simulating leaf area index assists in modelling the feedbacks between eco-hydrologic and climatic processes. The particular challenge for Australia is the prevalence of arid and semi-arid ecosystems where water availability plays a crucial role in vegetation productivity. To understand whether existing LAI models can capture plant dynamics under changing climates, we tested two competing models across Australia's different climate zones: a conceptual eco-hydrologic model that applies water use efficiency term to relate LAI to water uptake, and a deep learning approach. An initial virtual catchment experiment with deep learning showed that it only uses information from potential evapotranspiration. For future climates, the conceptual model captured a negative trend and increasing variance in LAI, which is plausible given projected rainfall changes, while deep learning did not. Our study demonstrated an example of ‘right answer for the wrong reasons’, and the importance of incorporating knowledge of water-carbon coupling for appropriate scenarios.</p></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"181 ","pages":"Article 106179"},"PeriodicalIF":4.8,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1364815224002408/pdfft?md5=a17aa7bf042ec562a0e4f5935767b5b9&pid=1-s2.0-S1364815224002408-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142043584","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

Web application of an integrated simulation for aquatic environment assessment in coastal and estuarine areas 沿海和河口地区水环境评估综合模拟的网络应用

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-08-12 DOI: 10.1016/j.envsoft.2024.106184

Yoshitaka Matsuzaki , Tetsunori Inoue , Masaya Kubota , Hiroki Matsumoto , Tomoyuki Sato , Hikari Sakamoto , Daisuke Naito

{"title":"Web application of an integrated simulation for aquatic environment assessment in coastal and estuarine areas","authors":"Yoshitaka Matsuzaki , Tetsunori Inoue , Masaya Kubota , Hiroki Matsumoto , Tomoyuki Sato , Hikari Sakamoto , Daisuke Naito","doi":"10.1016/j.envsoft.2024.106184","DOIUrl":"10.1016/j.envsoft.2024.106184","url":null,"abstract":"<div><p>This paper introduces the web application-type Graphical User Interface that has been developed and also presents an application example. The introduced simulator conducts hydrodynamics and ecosystems in coastal and estuarine areas. It consists of (1) a hydrodynamic model that can simulate the current velocity, water temperature, salinity, and water level; (2) an ecosystem model that can simulate dissolved oxygen, phytoplankton, zooplankton, nutrients, fish, and bivalves; and (3) a benthic ecosystem model that can simulate elution. Web GUI is the first web system of aquatic environment simulation system that can both prepare calculation conditions and visualize them. Another significant feature is that it requires no installation and can be easily used by anyone to perform calculations. Thus, the proposed system helps fill the expertise gap experienced by potential users of the model. The use of standard systems, such as those discussed in this study, will facilitate evidence-based policymaking (EBPM).</p></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"181 ","pages":"Article 106184"},"PeriodicalIF":4.8,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1364815224002457/pdfft?md5=50affda9fd41d1b57556dae1043a0eff&pid=1-s2.0-S1364815224002457-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142077005","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

An explainable MHSA enabled deep architecture with dual-scale convolutions for methane source classification using remote sensing 利用遥感技术对甲烷源进行分类的可解释 MHSA 双尺度卷积深度架构

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-08-12 DOI: 10.1016/j.envsoft.2024.106178

Kamakhya Bansal, Ashish Kumar Tripathi

{"title":"An explainable MHSA enabled deep architecture with dual-scale convolutions for methane source classification using remote sensing","authors":"Kamakhya Bansal, Ashish Kumar Tripathi","doi":"10.1016/j.envsoft.2024.106178","DOIUrl":"10.1016/j.envsoft.2024.106178","url":null,"abstract":"<div><p>Methane is the second most abundant greenhouse gas after carbon dioxide. Anthropogenic sources are the dominant emitters of methane. The poor spatial resolution of satellite imagery, high interclass similarity, the multi-scalar nature of features, and the dominance of background limit the performance of the previous approaches. Further, the reliance on high-resolution imagery limits the cost-effective global application of the works introduced in the literature. To resolve this, the present work proposes a novel method for methane source classification based on open-source multi-spectral satellite imagery of Sentinel-1 and 2. The work utilizes deep dual-scale convolutions with scaled dot product self-attention calculated across the 15 composite bands of Sentinel-1 and 2 data. The incorporation of non-RGB bands along with the RGB bands further enables the model to learn the spectral differences essential for the classification. The experimental results witness the superior performance of the developed method against other considered state-of-the-art methods.</p></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"181 ","pages":"Article 106178"},"PeriodicalIF":4.8,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141998605","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

Cloud-based system for monitoring event-based hydrological processes based on dense sensor network and NB-IoT connectivity 基于密集传感器网络和 NB-IoT 连接的基于事件的水文过程监测云系统

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-08-11 DOI: 10.1016/j.envsoft.2024.106186

Ernesto Sanz , Jorge Trincado , Jorge Martínez , Jorge Payno , Omer Morante , Andrés F. Almeida-Ñaulay , Antonio Berlanga , José M. Molina , Sergio Zubelzu , Miguel A. Patricio

{"title":"Cloud-based system for monitoring event-based hydrological processes based on dense sensor network and NB-IoT connectivity","authors":"Ernesto Sanz , Jorge Trincado , Jorge Martínez , Jorge Payno , Omer Morante , Andrés F. Almeida-Ñaulay , Antonio Berlanga , José M. Molina , Sergio Zubelzu , Miguel A. Patricio","doi":"10.1016/j.envsoft.2024.106186","DOIUrl":"10.1016/j.envsoft.2024.106186","url":null,"abstract":"<div><p>Hydrologists claim high-quality experimental data are required to improve the understanding of hydrological processes. Though accurate devices for measuring hydrological processes are available, the on-site deployment and operation of effective monitoring networks face many relevant issues caused by the peculiar characteristics of hydrological systems. In this manuscript, we present a self-developed system for monitoring events-based hydrological processes comprising a dense network with both soil moisture and water level gauges connected by NB-IoT technology integrated into a cloud system for near real-time gathering of information. We designed, built and calibrated the sensors and integrated them into a cloud system. We deployed them in two monitoring networks and gathered the data from several experimental runs (battery lifecycles). Results showed the suitability of the sensors and the network to properly monitor the processes solving the initial relevant issues mainly derived from connectivity issues and battery duration.</p></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"182 ","pages":"Article 106186"},"PeriodicalIF":4.8,"publicationDate":"2024-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1364815224002470/pdfft?md5=13f29f5b5e5bc51e3c80cb4402b5983a&pid=1-s2.0-S1364815224002470-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142135738","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

Pywr-DRB: An open-source Python model for water availability and drought risk assessment in the Delaware River Basin Pywr-DRB：特拉华河流域水资源可用性和干旱风险评估的开源 Python 模型

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-08-10 DOI: 10.1016/j.envsoft.2024.106185

Andrew L. Hamilton , Trevor J. Amestoy, Patrick M. Reed

{"title":"Pywr-DRB: An open-source Python model for water availability and drought risk assessment in the Delaware River Basin","authors":"Andrew L. Hamilton , Trevor J. Amestoy, Patrick M. Reed","doi":"10.1016/j.envsoft.2024.106185","DOIUrl":"10.1016/j.envsoft.2024.106185","url":null,"abstract":"<div><p>The Delaware River Basin (DRB) in the Mid-Atlantic region of the United States is an institutionally complex water resources system that provides drinking water for 13.5 million people, plus water for energy, industry, recreation, and ecosystems. This paper introduces Pywr-DRB, an open-source Python model exploring the impacts of reservoir operations, transbasin diversions, and minimum flow targets on water availability and drought risk in the DRB. Pywr-DRB draws on streamflow estimates from emerging data resources, bridging advances in large-scale hydrologic modeling with an improved representation of the basin's evolving water infrastructure and management institutions. Our detailed model diagnostic assessment demonstrates that Pywr-DRB provides substantial improvements over sole use of hydrologic models in capturing the DRB's dynamics. We also explore how water management alters model-derived risk estimates for low flows and water demand shortfalls. Our approach to diagnostic benchmarking and water systems modeling is broadly applicable to other major basins.</p></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"181 ","pages":"Article 106185"},"PeriodicalIF":4.8,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1364815224002469/pdfft?md5=91c5b1e93b9f2f09503b058effe2fca6&pid=1-s2.0-S1364815224002469-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141991093","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

An introduction to data-driven modelling of the water-energy-food-ecosystem nexus 水-能源-粮食-生态系统关系数据驱动建模简介

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2024-08-10 DOI: 10.1016/j.envsoft.2024.106182

Elise Jonsson , Andrijana Todorović , Malgorzata Blicharska , Andreina Francisco , Thomas Grabs , Janez Sušnik , Claudia Teutschbein

{"title":"An introduction to data-driven modelling of the water-energy-food-ecosystem nexus","authors":"Elise Jonsson , Andrijana Todorović , Malgorzata Blicharska , Andreina Francisco , Thomas Grabs , Janez Sušnik , Claudia Teutschbein","doi":"10.1016/j.envsoft.2024.106182","DOIUrl":"10.1016/j.envsoft.2024.106182","url":null,"abstract":"<div><p>Attaining resource security in the <strong>w</strong>ater, <strong>e</strong>nergy, <strong>f</strong>ood, and <strong>e</strong>cosystem (WEFE) sectors, the WEFE nexus, is paramount. This necessitates the use of quantitative modelling, which presents many challenges, as this is a complex system acting at the intersection of the physical- and social sciences. However, as WEFE data is becoming more widely available, data-driven methods of modelling this system are becoming increasingly viable. Here, we discuss two main problems in WEFE nexus modelling: system identification and control. System identification uses Machine Learning algorithms to obtain dynamical models from data and have shown promise in many disciplines with similar characteristics as the nexus. Meanwhile, control algorithms manipulate a system to achieve objectives and are becoming instrumental in shaping nexus policy. Despite the promise of these algorithms, data-driven modelling is a vast and daunting field, and so here we provide an introductory overview of this field, with emphasis on nexus applications.</p></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"181 ","pages":"Article 106182"},"PeriodicalIF":4.8,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1364815224002433/pdfft?md5=5cfc6d90e65be6d19815e087d8b6f5c8&pid=1-s2.0-S1364815224002433-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142012956","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