Pub Date : 2023-08-01DOI: 10.36334/modsim.2023.bhosale
B. Bhosale
: Remote sensing applications such as change detection, multispectral classification, environment monitoring, image mosaicking, weather forecasting, super resolution images and integrating information into geographic information system (GIS), image registration is a required process. Such natural images contain intrinsic geometrical structures that form the key features in visual information. Satellite data thus delivered/received in the form signals/images have a wide coverage with multi-temporal and multispectral capabilities. In such problems, a prime objective is to improve the quality of transmitted signals/images composed of desired signal plus additive random/Gaussian noise, by employing efficient feature extraction and denoising techniques with efficient representation of visual information. The experimental results and performance factor analysis based on of each of the multiresolution transforms show that contourlet transform produces relatively better result in terms of capturing directional information, reconstruction, noise restraints. The modelling and simulation: The feature extraction and denoising process is aimed at removing the noise with the help of a matched filter (either using wavelet, curvelet or contourlet), and is composed of three major steps viz. Decomposition of the transmitted signal, Thresholding to demise noisy elements, and Reconstruction of the processed signal. Signal is represented as
{"title":"Wavelet-curvelet-contourlet based remote sensing data mining model","authors":"B. Bhosale","doi":"10.36334/modsim.2023.bhosale","DOIUrl":"https://doi.org/10.36334/modsim.2023.bhosale","url":null,"abstract":": Remote sensing applications such as change detection, multispectral classification, environment monitoring, image mosaicking, weather forecasting, super resolution images and integrating information into geographic information system (GIS), image registration is a required process. Such natural images contain intrinsic geometrical structures that form the key features in visual information. Satellite data thus delivered/received in the form signals/images have a wide coverage with multi-temporal and multispectral capabilities. In such problems, a prime objective is to improve the quality of transmitted signals/images composed of desired signal plus additive random/Gaussian noise, by employing efficient feature extraction and denoising techniques with efficient representation of visual information. The experimental results and performance factor analysis based on of each of the multiresolution transforms show that contourlet transform produces relatively better result in terms of capturing directional information, reconstruction, noise restraints. The modelling and simulation: The feature extraction and denoising process is aimed at removing the noise with the help of a matched filter (either using wavelet, curvelet or contourlet), and is composed of three major steps viz. Decomposition of the transmitted signal, Thresholding to demise noisy elements, and Reconstruction of the processed signal. Signal is represented as","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"78 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":"129271443","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}
Pub Date : 2023-08-01DOI: 10.36334/modsim.2023.lowchoy656
S. Low-Choy, T. J. McKinley, L. Pulscher, A. Peel
.
．
{"title":"Bayesian decision-theoretic analysis of thresholds in Gompertz-mixture models, for robust detection of corona-like viruses in wildlife","authors":"S. Low-Choy, T. J. McKinley, L. Pulscher, A. Peel","doi":"10.36334/modsim.2023.lowchoy656","DOIUrl":"https://doi.org/10.36334/modsim.2023.lowchoy656","url":null,"abstract":".","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"16 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":"125398595","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}
Pub Date : 2023-08-01DOI: 10.36334/modsim.2023.goswami501
Pallavi Goswami, T. Peterson, A. Mondal, C. Rüdiger
: Hydrological variables of a catchment and their corresponding extreme characteristics have a possibility of switching regimes, particularly when a catchment undergoes protracted dry periods. This can result in a catchment experiencing a flow anomaly that is even more extreme than what was historically considered an extreme low flow event for the catchment. Existing studies suggest that extreme events may be changing with time; it is thus important to understand whether extremes in flows also have the potential to exist in multiple states. Goswami et al. (2022) established that low flows exhibit non-stationarity induced by climate modes (i.e., covariate-based non-stationarity in low flows). Our present work investigates if low flows exhibit a more complex form of non-stationarity, in the form of state (or regime) changes beyond the routine covariate-based non-stationarity as explored in Goswami et al. (2022). This work is also an extension of the study by Peterson et al. (2021), which showed complex dynamics for flows in catchments in southeast Australia. Peterson et al. (2021) established that a catchment's annual and seasonal mean flows can switch into alternative stable states, resulting in a catchment producing less streamflow than normal for a given precipitation. The term ‘switching of states’ or ‘regime-switching’ relates to a shift in the underlying probability distribution of a variable. Our study looks specifically at extreme (low) flows to investigate if they undergo regime changes, and at a much finer temporal resolution. We studied intensity, duration, and frequency (IDF) of low flows for 161 unregulated catchments in southeast Australia. A Hidden Markov Model-based approach was used to examine shifts in the low flow characteristics. The key findings are:
{"title":"Can drought regimes undergo shifts?","authors":"Pallavi Goswami, T. Peterson, A. Mondal, C. Rüdiger","doi":"10.36334/modsim.2023.goswami501","DOIUrl":"https://doi.org/10.36334/modsim.2023.goswami501","url":null,"abstract":": Hydrological variables of a catchment and their corresponding extreme characteristics have a possibility of switching regimes, particularly when a catchment undergoes protracted dry periods. This can result in a catchment experiencing a flow anomaly that is even more extreme than what was historically considered an extreme low flow event for the catchment. Existing studies suggest that extreme events may be changing with time; it is thus important to understand whether extremes in flows also have the potential to exist in multiple states. Goswami et al. (2022) established that low flows exhibit non-stationarity induced by climate modes (i.e., covariate-based non-stationarity in low flows). Our present work investigates if low flows exhibit a more complex form of non-stationarity, in the form of state (or regime) changes beyond the routine covariate-based non-stationarity as explored in Goswami et al. (2022). This work is also an extension of the study by Peterson et al. (2021), which showed complex dynamics for flows in catchments in southeast Australia. Peterson et al. (2021) established that a catchment's annual and seasonal mean flows can switch into alternative stable states, resulting in a catchment producing less streamflow than normal for a given precipitation. The term ‘switching of states’ or ‘regime-switching’ relates to a shift in the underlying probability distribution of a variable. Our study looks specifically at extreme (low) flows to investigate if they undergo regime changes, and at a much finer temporal resolution. We studied intensity, duration, and frequency (IDF) of low flows for 161 unregulated catchments in southeast Australia. A Hidden Markov Model-based approach was used to examine shifts in the low flow characteristics. The key findings are:","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"32 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":"126855062","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}
Pub Date : 2023-08-01DOI: 10.36334/modsim.2023.kapsis100
M. Kapsis, Peter Pudney, W. Miller, G. Freebairn
: This paper describes an optimal strategy for defending against an attacking missile with a team of cooperating defending missiles. The motivation is to allow us to compare a single high-cost defending missile to a team of low-cost defending missiles. The strategy predicts the possible paths of the attacking missile from a known initial state to a known target, then determines two regions: the region the attacking missile will be in when the defending missiles start seeking the attacking missile, and the region the attacking missile will be in when it can be intercepted. The selection of aim points that maximise the defending missile team’s coverage of these two regions can be formulated as a multi-dimensional unconstrained non-linear optimisation problem. The optimisation determines whether it is better to have thin coverage of the entire seek and intercept regions or concentrated coverage on parts of the seek and intercept regions to maximise the probability of stopping the attacking missile. In general, the more paths that each defending missile can see and hit, the greater the probability of stopping the attacking missile. The optimisation problem is solved using the Nelder-Mead method and an example is given to demonstrate the effectiveness of the method.
{"title":"An optimised strategy for using cooperating missiles for missile defence","authors":"M. Kapsis, Peter Pudney, W. Miller, G. Freebairn","doi":"10.36334/modsim.2023.kapsis100","DOIUrl":"https://doi.org/10.36334/modsim.2023.kapsis100","url":null,"abstract":": This paper describes an optimal strategy for defending against an attacking missile with a team of cooperating defending missiles. The motivation is to allow us to compare a single high-cost defending missile to a team of low-cost defending missiles. The strategy predicts the possible paths of the attacking missile from a known initial state to a known target, then determines two regions: the region the attacking missile will be in when the defending missiles start seeking the attacking missile, and the region the attacking missile will be in when it can be intercepted. The selection of aim points that maximise the defending missile team’s coverage of these two regions can be formulated as a multi-dimensional unconstrained non-linear optimisation problem. The optimisation determines whether it is better to have thin coverage of the entire seek and intercept regions or concentrated coverage on parts of the seek and intercept regions to maximise the probability of stopping the attacking missile. In general, the more paths that each defending missile can see and hit, the greater the probability of stopping the attacking missile. The optimisation problem is solved using the Nelder-Mead method and an example is given to demonstrate the effectiveness of the method.","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"7 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":"126858562","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}
Pub Date : 2023-08-01DOI: 10.36334/modsim.2023.davis
K. Davis, P. L. Bodic, Andreas T. Ernst, R. Kapoor, R. Garc´ıa-Flores
: This paper introduces a simplified deterministic model for plant breeding and an efficient algorithm to solve it. The model abstracts away much of the complexity of plant breeding to a version that can be solved in polynomial time. While this model only considers single-point recombinations and assumes all desired crossings are successful, it provides a lower bound on the number of generations required to achieve the target. The algorithm presented exploits runs of favourable alleles on producible gametes to guide its decision-making, which highlights the importance of considering segments rather than individual alleles. This paper suggests that seg-ments will be instrumental in the development of efficient algorithms for more comprehensive plant breeding models. However, future research should explore extending the model to account for factors such as polyploid plants and resource constraints that breeders face in reality. Overall, this paper serves as the first in a series of models exploring dedicated solving techniques applicable to plant breeding problems.
{"title":"A simplified model for plant breeding","authors":"K. Davis, P. L. Bodic, Andreas T. Ernst, R. Kapoor, R. Garc´ıa-Flores","doi":"10.36334/modsim.2023.davis","DOIUrl":"https://doi.org/10.36334/modsim.2023.davis","url":null,"abstract":": This paper introduces a simplified deterministic model for plant breeding and an efficient algorithm to solve it. The model abstracts away much of the complexity of plant breeding to a version that can be solved in polynomial time. While this model only considers single-point recombinations and assumes all desired crossings are successful, it provides a lower bound on the number of generations required to achieve the target. The algorithm presented exploits runs of favourable alleles on producible gametes to guide its decision-making, which highlights the importance of considering segments rather than individual alleles. This paper suggests that seg-ments will be instrumental in the development of efficient algorithms for more comprehensive plant breeding models. However, future research should explore extending the model to account for factors such as polyploid plants and resource constraints that breeders face in reality. Overall, this paper serves as the first in a series of models exploring dedicated solving techniques applicable to plant breeding problems.","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"94 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":"126895731","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}
Pub Date : 2023-08-01DOI: 10.36334/modsim.2023.longmuir
Daniel N. R. Longmuir, A. Hoskins, R. Hickson
: The Little Red Flying Fox ( Pteropus scapulatus ) is native to large coastal areas of northern and eastern Australia. A primary food source for this species is the nectar from Eucalyptus and Corymbia blossoms. There is only partial understanding of their roosting locations (known as “camps”) and movement, being semi-nomadic in nature to move between flowering events and camps. This creates a complexity in modelling the Little Red Flying Fox population. However, through stacked data including monthly spatial estimates of nectar availability, we can begin to understand how the bats move with these events. To investigate the population dynamics, we use a metapopulation model, coupling the spatial data of average monthly nectar availability through a radiation model for movement between camps. We couple the approximately 1 × 1km spatial nectar data using Voronoi diagrams based on known camp locations. The radiation model then considers a combination of camp distance and nectar availability to determine which patch leaving bats move to. We use a combination of density and caloric needs approach to limit the population in a patch. We compare our modelled population with historic camp survey data of population estimates. We show this relatively simple metapopulation model results in emergent behaviour aligned with the observation of ecologists, particularly to do with movement and patch numbers around pupping season. We showcase two areas of interest, regions across Cape Yorke and around Brisbane, where seasonal trends are expected to be substantially different. This metapopulation model based on nectar availability will form the basis of further work exploring infectious diseases risks, such as Hendra or Leptospirosis. Our model can be extended to consider the spatio-temporal availability of other resources, such as fresh water, vegetation coverage, and other environmental factors (temperature, humidity, aridity, etc.).
{"title":"A metapopulation model of Little Red Flying Fox population dynamics across Queensland","authors":"Daniel N. R. Longmuir, A. Hoskins, R. Hickson","doi":"10.36334/modsim.2023.longmuir","DOIUrl":"https://doi.org/10.36334/modsim.2023.longmuir","url":null,"abstract":": The Little Red Flying Fox ( Pteropus scapulatus ) is native to large coastal areas of northern and eastern Australia. A primary food source for this species is the nectar from Eucalyptus and Corymbia blossoms. There is only partial understanding of their roosting locations (known as “camps”) and movement, being semi-nomadic in nature to move between flowering events and camps. This creates a complexity in modelling the Little Red Flying Fox population. However, through stacked data including monthly spatial estimates of nectar availability, we can begin to understand how the bats move with these events. To investigate the population dynamics, we use a metapopulation model, coupling the spatial data of average monthly nectar availability through a radiation model for movement between camps. We couple the approximately 1 × 1km spatial nectar data using Voronoi diagrams based on known camp locations. The radiation model then considers a combination of camp distance and nectar availability to determine which patch leaving bats move to. We use a combination of density and caloric needs approach to limit the population in a patch. We compare our modelled population with historic camp survey data of population estimates. We show this relatively simple metapopulation model results in emergent behaviour aligned with the observation of ecologists, particularly to do with movement and patch numbers around pupping season. We showcase two areas of interest, regions across Cape Yorke and around Brisbane, where seasonal trends are expected to be substantially different. This metapopulation model based on nectar availability will form the basis of further work exploring infectious diseases risks, such as Hendra or Leptospirosis. Our model can be extended to consider the spatio-temporal availability of other resources, such as fresh water, vegetation coverage, and other environmental factors (temperature, humidity, aridity, etc.).","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"33 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":"126419841","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}
Pub Date : 2023-08-01DOI: 10.36334/modsim.2023.liu519
Yangyang Liu
: In recent years, the vegetation cover has been significantly improved, and the water and soil loss have been effectively controlled due to the carried out of the Grain for Green project in the Yellow River Basin (YRB) of China (Cao et al. 2022). However, the improper selection of restoration species in large-scale vegetation restoration and reconstruction also caused new ecological problems. For example, introducing high water-consuming species for high-density planting neglects the balance between vegetation growth and the hydrological cycle, thus increasing soil water consumption (Shao et al. 2019; Liang et al. 2020; Yang et al. 2022). Obviously, in arid areas such as the YRB, in order to maintain the sustainability of vegetation restoration and ensure the stability of available water resources, it is necessary to fully comprehend the impact of regional vegetation evolution on the evapotranspiration process, and then construct vegetation restoration strategies with the goal of sustainable water resources. Meanwhile, the YRB has shown a significant warming trend in recent years. Under the influence of climate change, changes in vegetation patterns will lead to significant uncertainty in the regional evapotranspiration process, as there is a synergistic effect between climate change and vegetation evolution on the evapotranspiration process. Ignoring the synergistic effects of climate and vegetation evolution will increase the uncertainty in understanding the response relationship between vegetation evolution and regional evapotranspiration processes. In order to quantify the relative impact of climate change and vegetation restoration on regional evapotranspiration processes, we used an optimized Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model to simulate evapotranspiration (ET), transpiration (T) and transpiration fractions (T/ET). Partial correlation analysis, multiple regression analysis, and structural equation modelling were used to elucidate the response mechanism of evapotranspiration processes to climate change and vegetation greening. Model evaluation showed that the PT-JPL model performs well in the simulation of ET and T. During the study period of 1982 to 2015, the average annual ET, T, and TF increased at a rate of 3.20 mm/a, 0.77 mm/a and 0.003/a, respectively. Vegetation greening was proved to be the primary driver for the increase of ET, T and TF, which enhanced ET, T, and TF at a rate of 0.81 mm/a, 0.26 mm/a and 0.54/a, respectively. Radiation and temperature jointly dominated ET changes in the upper reaches of the YRB, as well as the T and TF changes in the southern part of the basin, while the relative humidity and temperature jointly dominated the T change in the upper reaches of the basin. The findings were helpful for regional water resources management and formulating water resources-sustainable vegetation restoration strategies.
:近年来，由于中国黄河流域退耕还林工程的实施，植被覆盖明显改善，水土流失得到有效控制(Cao et al. 2022)。然而，在大规模植被恢复重建中，恢复物种的选择不当也造成了新的生态问题。例如，为高密度种植引入高耗水物种，忽视了植被生长与水循环之间的平衡，从而增加了土壤水分消耗(Shao et al. 2019;Liang et al. 2020;Yang et al. 2022)。显然，在干旱区如长江干旱区，为了保持植被恢复的可持续性，确保有效水资源的稳定性，有必要充分了解区域植被演化对蒸散过程的影响，进而构建以可持续水资源为目标的植被恢复策略。同时，长江三角洲近年来呈现明显的增温趋势。在气候变化的影响下，植被格局的变化将导致区域蒸散发过程的显著不确定性，因为气候变化和植被演化对蒸散发过程存在协同效应。忽视气候与植被演化的协同效应，将增加对植被演化与区域蒸散响应关系认识的不确定性。为了量化气候变化和植被恢复对区域蒸散发过程的相对影响，采用优化的Priestley-Taylor喷气推进实验室(PT-JPL)模型对蒸散发(ET)、蒸腾(T)和蒸腾分数(T/ET)进行了模拟。采用偏相关分析、多元回归分析和结构方程建模等方法，阐明了蒸散过程对气候变化和植被绿化的响应机制。模式评价结果表明，PT-JPL模式对ET和T的模拟效果较好。1982 ~ 2015年研究期间，年平均ET、T和TF分别以3.20 mm/a、0.77 mm/a和0.003 mm/a的速率增加。植被绿化是增加ET、T和TF的主要驱动因素，分别以0.81 mm/a、0.26 mm/a和0.54 mm/a的速率增加ET、T和TF。辐射和温度共同主导YRB上游ET变化，以及盆地南部T和TF变化，而相对湿度和温度共同主导盆地上游T变化。研究结果可为区域水资源管理和制定水资源可持续植被恢复策略提供参考。
{"title":"Greening of vegetation and climate change promote an increase in evapotranspiration and transpiration fraction in the Yellow River Basin, China","authors":"Yangyang Liu","doi":"10.36334/modsim.2023.liu519","DOIUrl":"https://doi.org/10.36334/modsim.2023.liu519","url":null,"abstract":": In recent years, the vegetation cover has been significantly improved, and the water and soil loss have been effectively controlled due to the carried out of the Grain for Green project in the Yellow River Basin (YRB) of China (Cao et al. 2022). However, the improper selection of restoration species in large-scale vegetation restoration and reconstruction also caused new ecological problems. For example, introducing high water-consuming species for high-density planting neglects the balance between vegetation growth and the hydrological cycle, thus increasing soil water consumption (Shao et al. 2019; Liang et al. 2020; Yang et al. 2022). Obviously, in arid areas such as the YRB, in order to maintain the sustainability of vegetation restoration and ensure the stability of available water resources, it is necessary to fully comprehend the impact of regional vegetation evolution on the evapotranspiration process, and then construct vegetation restoration strategies with the goal of sustainable water resources. Meanwhile, the YRB has shown a significant warming trend in recent years. Under the influence of climate change, changes in vegetation patterns will lead to significant uncertainty in the regional evapotranspiration process, as there is a synergistic effect between climate change and vegetation evolution on the evapotranspiration process. Ignoring the synergistic effects of climate and vegetation evolution will increase the uncertainty in understanding the response relationship between vegetation evolution and regional evapotranspiration processes. In order to quantify the relative impact of climate change and vegetation restoration on regional evapotranspiration processes, we used an optimized Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model to simulate evapotranspiration (ET), transpiration (T) and transpiration fractions (T/ET). Partial correlation analysis, multiple regression analysis, and structural equation modelling were used to elucidate the response mechanism of evapotranspiration processes to climate change and vegetation greening. Model evaluation showed that the PT-JPL model performs well in the simulation of ET and T. During the study period of 1982 to 2015, the average annual ET, T, and TF increased at a rate of 3.20 mm/a, 0.77 mm/a and 0.003/a, respectively. Vegetation greening was proved to be the primary driver for the increase of ET, T and TF, which enhanced ET, T, and TF at a rate of 0.81 mm/a, 0.26 mm/a and 0.54/a, respectively. Radiation and temperature jointly dominated ET changes in the upper reaches of the YRB, as well as the T and TF changes in the southern part of the basin, while the relative humidity and temperature jointly dominated the T change in the upper reaches of the basin. The findings were helpful for regional water resources management and formulating water resources-sustainable vegetation restoration strategies.","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"13 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":"121522320","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}
Pub Date : 2023-08-01DOI: 10.36334/modsim.2023.stratford
D. Stratford, S. Linke, L. Merrin, S. Lachish, F. Karim, S. K. Csiro, Australia
: River flows are important for driving the condition and persistence of many aquatic dependent species, to support habitats, and to facilitate ecosystem function. In the tropics of northern Australia, flow regimes are highly dynamic with strong seasonal trends. Within these seasonal regimes, species seek and use habitats across river channels and floodplains that best suit their needs. The habitat that is deemed suitable for species varies in location and extent across time, depending on interactions between flow regimes and landscape features. Changes in flow associated with water resource development and climate change threaten to change the quality, extent and/or location of suitable habitat for a range of flow dependent species. Despite the ecological importance of flow, quantifying the relationships between hydrological change and ecological outcomes remains a challenge. Species interact with their physical environment differently and have diverse preferences and requirements across ranges of habitat attributes that include inundation, depth, velocity and connectivity. Species, including fish, waterbirds and other biota are recognised to form spatial relationships based upon these physical conditions. Complex landscapes and highly variable flow regimes mean that interactions between flow and geomorphology result in different hydrological and hydraulic characteristics across different settings, often making discharge alone a poor proxy for ecological outcomes in many novel settings. Improvement in our conceptual understanding indicates that ecological flow requirements have a complex relationship with geomorphology and flow dynamics through the landscape, with responses often being non-linear in relation to discharge (Theodoropoulos, 2020; Whipple, 2018). Hydrodynamic modelling provides a mechanism to explore changes in these attributes and their ecological relationships through space and time, and to enable analysis to compare differences between scenarios while considering these complex geomorphological settings. Here we model flow habitat suitability using depth and velocity outputs from hydrodynamic (HD) models. We use species or functional groups specific habitat preference relationships informed by field data and/or literature to provide mechanistic links between hydraulic variables from HD modelling to predict habitat suitability. The form of these relationships can be used for a range of biota such as fish and waterbirds where depth and velocity are important determinants of habitat preference and suitability. Flow habitat suitability is rated on a scale of 0 (not suitable) to 1 (preferred) for each species given their specific hydraulic preferences at each grid cell, and compared between scenarios to identify the loss or gain of weighted habitat suitability between scenarios. Model results are expressed as spatial representations of suitable habitat across time at daily timesteps. The spatial resolution and domain are defined by the
{"title":"Modelling habitat suitability under hydrological change in aquatic habitats of northern Australia","authors":"D. Stratford, S. Linke, L. Merrin, S. Lachish, F. Karim, S. K. Csiro, Australia","doi":"10.36334/modsim.2023.stratford","DOIUrl":"https://doi.org/10.36334/modsim.2023.stratford","url":null,"abstract":": River flows are important for driving the condition and persistence of many aquatic dependent species, to support habitats, and to facilitate ecosystem function. In the tropics of northern Australia, flow regimes are highly dynamic with strong seasonal trends. Within these seasonal regimes, species seek and use habitats across river channels and floodplains that best suit their needs. The habitat that is deemed suitable for species varies in location and extent across time, depending on interactions between flow regimes and landscape features. Changes in flow associated with water resource development and climate change threaten to change the quality, extent and/or location of suitable habitat for a range of flow dependent species. Despite the ecological importance of flow, quantifying the relationships between hydrological change and ecological outcomes remains a challenge. Species interact with their physical environment differently and have diverse preferences and requirements across ranges of habitat attributes that include inundation, depth, velocity and connectivity. Species, including fish, waterbirds and other biota are recognised to form spatial relationships based upon these physical conditions. Complex landscapes and highly variable flow regimes mean that interactions between flow and geomorphology result in different hydrological and hydraulic characteristics across different settings, often making discharge alone a poor proxy for ecological outcomes in many novel settings. Improvement in our conceptual understanding indicates that ecological flow requirements have a complex relationship with geomorphology and flow dynamics through the landscape, with responses often being non-linear in relation to discharge (Theodoropoulos, 2020; Whipple, 2018). Hydrodynamic modelling provides a mechanism to explore changes in these attributes and their ecological relationships through space and time, and to enable analysis to compare differences between scenarios while considering these complex geomorphological settings. Here we model flow habitat suitability using depth and velocity outputs from hydrodynamic (HD) models. We use species or functional groups specific habitat preference relationships informed by field data and/or literature to provide mechanistic links between hydraulic variables from HD modelling to predict habitat suitability. The form of these relationships can be used for a range of biota such as fish and waterbirds where depth and velocity are important determinants of habitat preference and suitability. Flow habitat suitability is rated on a scale of 0 (not suitable) to 1 (preferred) for each species given their specific hydraulic preferences at each grid cell, and compared between scenarios to identify the loss or gain of weighted habitat suitability between scenarios. Model results are expressed as spatial representations of suitable habitat across time at daily timesteps. The spatial resolution and domain are defined by the","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"155 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":"121524001","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}
Pub Date : 2023-08-01DOI: 10.36334/modsim.2023.rosello103
C. Rosello, Joseph Guillaume, C. Pollino, A. Jakeman
,
，
{"title":"Identifying factors influencing water planning: Benefits of a capability approach?","authors":"C. Rosello, Joseph Guillaume, C. Pollino, A. Jakeman","doi":"10.36334/modsim.2023.rosello103","DOIUrl":"https://doi.org/10.36334/modsim.2023.rosello103","url":null,"abstract":",","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"70 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":"123111244","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}
Pub Date : 2023-08-01DOI: 10.36334/modsim.2023.saco
P. Saco, José Raúl Rodríguez Rodríguez, A. Breda, S. Sandi
: Predictions of the fate of coastal wetlands under the effects of sea-level rise (SLR) vary widely due to uncertainties on environmental variables, but also due to unavoidable simplifications in the models. Assessment of coastal wetland resilience under rising sea levels using models is challenging due to uncertainties in processes and external drivers. In addition, a number of assumptions and simplifications are required in order to be able to carry out long-term complex simulations that include processes over a wide range of time and spatial scales. Some of those simplifications can have important implications for the assessment of wetland resilience. In this contribution we look at a number of simplifications typically used in coastal wetland evolution models, and we try to quantify their effects on the results. We include simplifications related to hydrodynamics, sediment transport and vegetation dynamics focusing on issues of process description, process interactions and spatial and temporal discretisation. We pay special attention to the identification of methods that include a level of simplification that allows for efficient computation with acceptable margins of error. Finally, we present a simplified domain model that includes all relevant hydrodynamic, sedimentation and vegetation dynamics mechanisms that affect wetland evolution, it does not require detailed information and it is efficient enough computationally to allow the simulation of long time periods. We test this framework and apply it in different settings typically found in coastal wetlands around the world, comprising different geomorphic configurations, vegetation types, sediment characteristics and tidal regimes (see figure below). Most of the wetland settings analysed are unable to cope with the high SLR rates expected by the end of the century, in agreement with results using paleo-records during periods of high SLR rates.
{"title":"Ecohydrological interactions in coastal wetlands and their resilience to future sea-level rise","authors":"P. Saco, José Raúl Rodríguez Rodríguez, A. Breda, S. Sandi","doi":"10.36334/modsim.2023.saco","DOIUrl":"https://doi.org/10.36334/modsim.2023.saco","url":null,"abstract":": Predictions of the fate of coastal wetlands under the effects of sea-level rise (SLR) vary widely due to uncertainties on environmental variables, but also due to unavoidable simplifications in the models. Assessment of coastal wetland resilience under rising sea levels using models is challenging due to uncertainties in processes and external drivers. In addition, a number of assumptions and simplifications are required in order to be able to carry out long-term complex simulations that include processes over a wide range of time and spatial scales. Some of those simplifications can have important implications for the assessment of wetland resilience. In this contribution we look at a number of simplifications typically used in coastal wetland evolution models, and we try to quantify their effects on the results. We include simplifications related to hydrodynamics, sediment transport and vegetation dynamics focusing on issues of process description, process interactions and spatial and temporal discretisation. We pay special attention to the identification of methods that include a level of simplification that allows for efficient computation with acceptable margins of error. Finally, we present a simplified domain model that includes all relevant hydrodynamic, sedimentation and vegetation dynamics mechanisms that affect wetland evolution, it does not require detailed information and it is efficient enough computationally to allow the simulation of long time periods. We test this framework and apply it in different settings typically found in coastal wetlands around the world, comprising different geomorphic configurations, vegetation types, sediment characteristics and tidal regimes (see figure below). Most of the wetland settings analysed are unable to cope with the high SLR rates expected by the end of the century, in agreement with results using paleo-records during periods of high SLR rates.","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"61 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":"126587525","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：