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

Framework for interpretable Bayesian soil moisture modelling 可解释贝叶斯土壤湿度模型的框架

MODSIM2023, 25th International Congress on Modelling and Simulation. Pub Date : 2023-08-01 DOI: 10.36334/modsim.2023.simmons461

J. Simmons, V. Pino, A. Graaf, R. Vervoort

{"title":"Framework for interpretable Bayesian soil moisture modelling","authors":"J. Simmons, V. Pino, A. Graaf, R. Vervoort","doi":"10.36334/modsim.2023.simmons461","DOIUrl":"https://doi.org/10.36334/modsim.2023.simmons461","url":null,"abstract":": Soil moisture is a key driver of hydrological processes such as flooding during wet periods and vegetation growth in dry periods, but is highly variable in time and space. Soil moisture varies due to landcover, soil type, landscape position, and rainfall input. Disentangling the different drivers and spatial relationships in soil moisture are important to deliver forecasts. To facilitate this, the most widely-used approach to simulating soil moisture is numerical modelling. More recent approaches using neural networks display good predictive performance, but lose interpretability. In contrast, numerical models are often too rigid, and quantifying uncertainty can be difficult and computationally expensive. The objective of this paper is to demonstrate a Bayesian modelling framework that is flexible, quantifies uncertainties, disentangles the relative importance of different drivers, and is able to make forecasts. The data are derived from a dense soil moisture observation network at Llara farm in Narrabri (NSW), installed as part of a landscape rehydration project. This project consists of two 40 ha sites, each with control areas and treatment areas. The treatment involves the installation of contour banks with 1 m elevation to reduce over-land flow velocities and increase infiltration. Given their spatial distribution, each of the gauges has varying topological features and soil characteristics that may also influence the relationship of soil moisture to forcing variables (e.g., rainfall and evaptranspiration). For this modelling, we focused on 16 months of 10 minute interval data across 32 gauges at a common depth below the surface (200 mm). These data were aggregated to a daily mean to align with rainfall data from a nearby rain gauge at Llara farm and evapotranspiration data downloaded from SILO. The model is a Hierarchical Linear Model (HLM) fit using a Bayesian approach leveraging the No-U-Turn MCMC sampler implemented in NumPyro. HLMs are well suited to modelling nested data, such as in this case where gauges can be grouped by site and treatment, alongside gauge specific factors. Soil moisture at time t ( SM t ) is modelled at each gauge as a simple linear regression of the rainfall ( R ), evapotranspiration ( E ), and an autoregressive term (the soil moisture from the previous timestep, SM t − 1 ). The corresponding coefficients of the linear regression are β R , β E and β AR , respectively, along with an intercept term ( β 0 ). By introducing group level parameters via hierarchical priors on our β terms, we can explore the effects of site and treatment on the dynamics of soil moisture over time.","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"20 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":"115613754","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

Can we use state and transition models to add dynamism to fire risk and behaviour models? 我们可以使用状态和转换模型来增加火灾风险和行为模型的动态性吗?

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

J. Furlaud, K. Szetey, S. Luxton, G. Newnham, K. Williams, S. Prober, A. Richards

{"title":"Can we use state and transition models to add dynamism to fire risk and behaviour models?","authors":"J. Furlaud, K. Szetey, S. Luxton, G. Newnham, K. Williams, S. Prober, A. Richards","doi":"10.36334/modsim.2023.furlaud","DOIUrl":"https://doi.org/10.36334/modsim.2023.furlaud","url":null,"abstract":": Fire risk and fire behaviour models have long assumed static fuel profiles: fuels reaccumulate post-disturbance to an equilibrium value following the Olson curve (Olson, 1963). However, fuel load is not the only vegetation-related predictor of fire behaviour and does not always follow Olsen accumulation patterns, and, perhaps more importantly such static models are unable to represent the dynamic changes to ecosystems that are likely under climate change. One approach for modelling and mapping ecosystems dynamically is using State and Transition Simulation Models (STSMs; Daniel et al., 2016), a spatially-explicit parameterisation of state and transition conceptual models (S&TMs; Westoby et al., 1989), that has been widely applied in the United States . S&TMs, or similar models with the same underpinning theory, have been utilised by Australian ecologists and practitioners for over 50 years. Many such models exist but few have been parameterised to make spatially explicit predictions of the extent and change of different vegetation types in Australia. We outline an approach for using STSMs to model fuels and fire risk at both landscape and continental scales. This involves (a) identifying important expressions of ecosystem dynamics (e.g. frequently burnt savanna or structurally mature forest) and pathways between them (e.g. succession), (b) identifying anthropogenic drivers of change (e.g. reference or altered fuel structure) and drivers of transitions between states (e.g. fire exclusion) for an ecosystem type, (c) locating existing states and expressions in the landscape using remote sensing variables, and (d) using existing abiotic and biophysical models (e.g., fire behaviour, climate change, and plant growth) to understand how rates of change along these pathways might be altered by climate change interacting with land management. We then discuss two case studies of the landscape-scale approach: one in Tasmanian wet eucalypt forest, and one in tropical savanna in central Arnhem Land, providing preliminary results and indicating how this approach fits into a national state and transition modelling framework. We examine how this approach could create ecologically meaningful, dynamic maps of fuels that will be compatible with modern fire risk and behaviour modelling efforts , contributing to a nationally consistent map of fuels and fire risk through inclusion in the Australian Fire Danger Rating System (AFDRS) and inform natural asset protection.","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"2 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":"114389067","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