MODSIM2023, 25th International Congress on Modelling and Simulation.最新文献_第9页

Limited impacts of a permanent inland lake in central Australia on local-to-regional precipitation 澳大利亚中部一个永久性内陆湖对局地降水的有限影响

MODSIM2023, 25th International Congress on Modelling and Simulation. Pub Date : 2023-08-01 DOI: 10.36334/modsim.2023.yang280

Z. Yang, D. Ryu, M. Lo, S. Narsey, M. Peel, K. McColl

{"title":"Limited impacts of a permanent inland lake in central Australia on local-to-regional precipitation","authors":"Z. Yang, D. Ryu, M. Lo, S. Narsey, M. Peel, K. McColl","doi":"10.36334/modsim.2023.yang280","DOIUrl":"https://doi.org/10.36334/modsim.2023.yang280","url":null,"abstract":": This research was inspired by a potential geo-engineering project, commonly referred to as the Bradfield Scheme, proposed decades ago aiming at irrigating semi-arid regions of central Australia for agriculture and gradually changing the rainfall regime over the region. The initial conceptual appeal of the proposal was to introduce a large water expanse into the middle of an arid region lacking water resources, which was suggested would induce hydroclimatic changes favourable toward increased agricultural productivity. However, there is a lack of research into the impact of newly established inland water bodies on local-to-regional hydroclimate and detailed land-atmosphere interactions involved in the potential changes. We will present the impact of a permanent inland lake in central Australia on local-to-regional precipitation based on a numerical experiment using a coupled land-atmosphere model with numerical water tracers (WVTs). Kati Thanda–Lake Eyre is an ephemeral saline lake in central Australia and when full, is the largest inland water expanse in Australia. By emulating an idealised permanent Kati Thanda in the community earth system model (CESM) coupling land and atmosphere, we investigated how precipitation responded to that land surface perturbation from local to regional scales. At the local scale, the permanent lake strengthened the rainfall recycling process but failed to cause significant changes in total precipitation. The permanent lake was found to influence the local thermodynamics and dynamics. Specifically, the lake increased the latent heat flux through changes in the surfaceenergy budget, which corresponded to a significantly enhanced moisture flux into the overlying atmosphere. However, it also led to significant evaporative cooling, creating strong divergence in the lower atmosphere and suppressing precipitation formation. At the regional scale, the impacts of the permanent lake were negligible as well even though additional moisture originating from the lake spread over the continent as shown by the built-in WVTs of CESM. To compensate for a relatively small sample size, instead of simply depending on significant tests, our study employed an isotope-enabled version of CESM with internal WVTs and showed that the precipitation of water vapor originating from the lake region trivially contributed to total precipitation. Based on the results, we conclude that a large permanent lake in the Kati Thanda–Lake Eyre region in central Australia may have limited impacts on local-to-regional precipitation. For a better understanding of the underlying mechanisms of land-atmosphere interactions, our study also shows that coupled climate models together with moisture-tracking tools have important potentials in the assessment and mitigation of extremes (e.g., floods) or perturbed land surface (driven by either natural or anthropogenic factors). Future works will continue to investigate the variability of local and regional hydroclimate","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131520160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluating multiobjective evolutionary algorithms: A real-world benchmarking framework 评估多目标进化算法:一个真实世界的基准框架

MODSIM2023, 25th International Congress on Modelling and Simulation. Pub Date : 2023-08-01 DOI: 10.36334/modsim.2023.salazar

J. Z. Salazar, D. Hadka, P. Reed, H. Seada, K. Deb

{"title":"Evaluating multiobjective evolutionary algorithms: A real-world benchmarking framework","authors":"J. Z. Salazar, D. Hadka, P. Reed, H. Seada, K. Deb","doi":"10.36334/modsim.2023.salazar","DOIUrl":"https://doi.org/10.36334/modsim.2023.salazar","url":null,"abstract":": Multiobjective evolutionary algorithms (MOEAs) have shown significant progress in addressing well-defined test problems, but their effectiveness in real-world applications remains uncertain. To bridge this gap, we provide a comprehensive benchmarking framework designed to rigorously evaluate state-of-the-art MOEAs in real-world scenarios. Our framework comprises a suite of statistical evaluation metrics, for a collection of diverse real-world benchmark applications representing various mathematical problem difficulties. In this study, we carefully selected four benchmark applications with 3 to 10 objectives, capturing challenging characteristics such as stochastic objectives, severe constraints, strong nonlinearity, and complex Pareto frontiers. We evaluated the performance of five popular MOEAs, including NSGA-II, NSGA-III, RVEA, MOEA/D, and the Borg MOEA, using our benchmarking framework. Multiobjective evolutionary algorithms (MOEAs) have shown significant progress in addressing well-defined test problems, but their effectiveness in real-world applications remains uncertain. To bridge this gap, we provide a comprehensive benchmarking framework designed to rigorously evaluate state-of-the-art MOEAs in real-world scenarios. Our framework comprises a suite of statistical evaluation metrics, for a collection of diverse real-world benchmark applications representing various mathematical problem difficulties. The results revealed distinct differences in the performance of the evaluated MOEAs across the real-world applications. Surprisingly, MOEAs that excelled on standard test problems struggled when confronted with the complexities inherent in real-world applications. These findings underscore the need to enhance the adaptability and ease-of-use of MOEAs, considering the often ill-defined nature of real-world problem solving. Furthermore, our study provides insights into successful algorithmic design choices for MOEAs. Optimal selection strategies and archive mechanisms are crucial to prevent deterioration, maintain diversity, and provide adequate selection pressure throughout the optimization process. Additionally, the choice of stable and flexible operators plays a vital role in reliably driving the search towards the Pareto front. Recent advancements in hyper-heuristics and multi-operator MOEAs offer promising automated approaches for tackling these challenges. We found that epsilon non-dominated sorting effectively maintains diversity and selection pressure for problems with up to ten objectives when the entire Pareto front is desired. Moreover, auto-adaptive search operators demonstrate their efficacy in adapting to the search landscape of diverse real-world applications. However, the performance of reference point/vector methods deteriorated at higher dimensions, indicating the need for further investigation. Our study highlights the inadequacy of existing test benchmarks in differentiating MOEAs based on real-world performance. While consi","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127575504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Estimation of the water balance and water yield in the Lagan River catchment, Sweden, using the Australian Water Resources Assessment Landscape Model 利用澳大利亚水资源评价景观模型估算瑞典拉干河流域的水平衡和水量

MODSIM2023, 25th International Congress on Modelling and Simulation. Pub Date : 2023-08-01 DOI: 10.36334/modsim.2023.bjerken

引用次数: 0

A hybrid approach to mountain forest management using Earth observing system and machine learning 利用地球观测系统和机器学习进行山地森林管理的混合方法

MODSIM2023, 25th International Congress on Modelling and Simulation. Pub Date : 2023-08-01 DOI: 10.36334/modsim.2023.sysoeva

引用次数: 0

Comparing and ranking the global cost of green industrial electricity 全球绿色工业用电成本比较与排名

MODSIM2023, 25th International Congress on Modelling and Simulation. Pub Date : 2023-08-01 DOI: 10.36334/modsim.2023.graham125

引用次数: 0

Integrating field observations and mapping with model outputs (pesticides) to help identify ecologically vulnerable areas and determine suitable field site locations in the Great Barrier Reef 将实地观察和绘图与模型输出(农药)结合起来，帮助确定生态脆弱的地区，并确定大堡礁合适的实地地点

MODSIM2023, 25th International Congress on Modelling and Simulation. Pub Date : 2023-08-01 DOI: 10.36334/modsim.2023.skerratt

引用次数: 0

Estimates of recharge for current and future climate scenarios in Victoria using SoilFlux 使用SoilFlux估算维多利亚州当前和未来气候情景的补给

MODSIM2023, 25th International Congress on Modelling and Simulation. Pub Date : 2023-08-01 DOI: 10.36334/modsim.2023.jordan

引用次数: 0

Decoding soil-plant-atmosphere processes by extending in-situ monitoring and experimental data with numerical modelling 利用数值模拟扩展原位监测和实验数据，解码土壤-植物-大气过程

MODSIM2023, 25th International Congress on Modelling and Simulation. Pub Date : 2023-08-01 DOI: 10.36334/modsim.2023.filipovic

V. Filipović, V. Krevh, T. Baumgartl

{"title":"Decoding soil-plant-atmosphere processes by extending in-situ monitoring and experimental data with numerical modelling","authors":"V. Filipović, V. Krevh, T. Baumgartl","doi":"10.36334/modsim.2023.filipovic","DOIUrl":"https://doi.org/10.36334/modsim.2023.filipovic","url":null,"abstract":": The soil-plant-atmosphere nexus is a complex and interconnected system that is essential for the functioning of ecosystems. Understanding the dynamics and processes occurring in this system is crucial for addressing issues related to soil degradation, climate change, and food security. The experimental data collection from displacement soil cores or monoliths (soil columns) and in-situ monitoring of the soil processes can be further enhanced by applying models of various complexity to quantify different fluxes. Numerical modelling can be used as a predictive tool for estimation of various transport processes in unsaturated soil within agricultural, environmental and geotechnical applications. The approach of combining numerical simulations with laboratory analytics and extensive field observations has been proven to be very efficient. In homogeneous soil, vadose zone modelling is commonly based on Richards equation for describing water flow, and advection-dispersion equations for solute transport; which usually works quite well in describing physical processes. However, there is still difficulty in estimation and modelling of preferential flow and nonuniform solute transport in structured soils. The presentation aims at discussing vadose zone processes and modelling capabilities and restraints by presenting various examples of modelling with HYDRUS suite. The examples illustrate the use of various models like single porosity, dual-porosity and dual permeability and their ability to account for various soil structure properties but also properties of other porous materials, like coal, which is a relevant issue in mine rehabilitation. The modelling was performed on various scales, from column, profile, plot to hillslope using one-dimensional and two-dimensional model domains. In-situ examples and soil column observations include data from soil moisture and matric potential sensors, lysimeter fluxes and outflows and collection of water samples from surface or subsurface runoff instruments. The collected water samples i.e., leachate includes analytical determination of various contaminants like nitrates, pesticides, pharmaceuticals and trace elements. The ability of models to represent solute transport parameters and processes like leaching, sorption and degradation will be presented briefly. The complexity of solute transport processes and the ability of modelling them is additionally enhanced by the difficulty of modelling non-uniform water flow which is the governing process underlying the solute transport in structured soils. The issue of non-linearity in vadose zone is mainly connected to heterogeneity in soil properties (chemical, physical, biological) which can be difficult to quantify or integrate into numerical models. Modelling capabilities are now on high level, while meanwhile we still have issues of incorporation and proper quantification of soil structure formation or how to link soil hydraulic properties to vegetation metrics like bi","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133830022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Using deep learning methods to create translators between biogeochemical models, improving regional ocean model global integration 利用深度学习方法创建生物地球化学模型之间的翻译，提高区域海洋模型的全球整合

MODSIM2023, 25th International Congress on Modelling and Simulation. Pub Date : 2023-08-01 DOI: 10.36334/modsim.2023.mongin

M. Mongin, Lachlan R. Phillips, S. Frydman, E. Jones

{"title":"Using deep learning methods to create translators between biogeochemical models, improving regional ocean model global integration","authors":"M. Mongin, Lachlan R. Phillips, S. Frydman, E. Jones","doi":"10.36334/modsim.2023.mongin","DOIUrl":"https://doi.org/10.36334/modsim.2023.mongin","url":null,"abstract":": The marine ecosystem is driven by a complex set of processes spanning a wide range of temporal and spatial scales. Processes-based modelling is one of the key elements in our understanding of the marine biogeochemical status of the ocean and the prediction of its future. With the increasing complexity and specific application of biogeochemical (BGC) models, comes the difficulty to cross over between the variety of models and being able to leverage from one model simulation to another. Most BGC models have a different size class arrangement for plankton species meaning it is challenging to initialize/nest a BGC model using another one. Regional applications of a biogeochemical model usually use climatology or statistical relationship to initialise and set ocean boundary conditions for the BGC tracers. By setting the offshore boundary far enough from the area of interest the errors due to the poorly constrained boundary usually dissipate before impacting the model result in the region of interest. Improving interoperability across different BGC models could alleviate this problem and allow for the complete integration of regional models within global models. Here we show that machine learning algorithms (generative adversarial network (GAN)) can be used to create a translator between different BGC models. The neural network learns the specifics of the complex BGC regional model from variables common across all BGC models (total chlorophyll, nitrate, temperature, salinity). The GAN can then be used to regenerate the specific variables of the regional model from the global model. We applied this translator to the eReefs biogeochemical model and performed a set of twin experiments to quantify the errors and behaviour of the model when using the translator.","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125667144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predicting impact of fires on water quality 预测火灾对水质的影响

MODSIM2023, 25th International Congress on Modelling and Simulation. Pub Date : 2023-08-01 DOI: 10.36334/modsim.2023.miotlinski

K. Miotlinski, P. Horwitz, J. Bellhouse, D. Blake, R. Silberstein, A. Bath, A. Mitchell, A. Carvalho, K. Tshering

{"title":"Predicting impact of fires on water quality","authors":"K. Miotlinski, P. Horwitz, J. Bellhouse, D. Blake, R. Silberstein, A. Bath, A. Mitchell, A. Carvalho, K. Tshering","doi":"10.36334/modsim.2023.miotlinski","DOIUrl":"https://doi.org/10.36334/modsim.2023.miotlinski","url":null,"abstract":": Wildfires and prescribed burns are becoming more common in a warming world potentially affecting drinking water resources. User-friendly tools are needed to evaluate potential post-fire responses and mitigation strategies. Although simple models to predict soil erosion following fires are available, they (1) often require a specialised software; and (2) may be too generic for certain regions. One of these regions is the northern jarrah forest near Perth, in which soil erosion occurs in very limited circumstances due to an advanced stage of landscape evolution and highly permeable lateritic cover limiting the occurrence of overland flow. To address the needs, we developed a cloud-based tool to be used in decision making. The tool informs short-term erosion effects and long-term hydrological risks. The tool utilises cloud-based satellite imagery and weather predictions to generate maps of both erosion rates and hydrological risks. The erosion calculation is similar to RUSLE used for post-wildfire environs by incorporating the rainfall, soil properties, topography, and the land use from satellites. The major differences from the classic RUSLE are governed by greater data availability and how rainfall erosivity and post-wildfire debris mass are calculated. The rainfall erosivity rate takes into account weather predictions as opposed to the historical rainfall, although its spatial distribution may be calculated from historical datasets. The post-wildfire debris mass, which in jarrah forest is chiefly derived from vegetation, is a proxy for a land use change and is derived from ten-metre-resolution Sentinel-2 images. The hydrological risks are based on numerical modelling which assume that preferential flow paths, low regolith depth and high-conductivity soils predominantly affect contaminant transport rates from the burnt areas to creeks and, consequently, to drinking water reservoirs. The tool allows for a quick and easy evaluation of post-fire conditions by managers and rangers without the need for an expert knowledge or specialised software. The short-term predictions of erosion rates immediately following a fire facilitate on-site evaluation and potential responses as next step actions. The long-term predictions of hydrological hotspots are helpful to manage the use of land and to develop post-fire mitigation strategies. Although the short-term erosion rates are consistent with field observations, there is a need to develop new monitoring strategies and a water quality database of long-term observations following wildfires and prescribed burns.","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125707901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0