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Water Quality Simulation Of Lakes: Coupling Artificial Intelligence Techniques And Remote Sensing Data, Farkhondeh Khorashadi Zadeh, Albert Nkwasa, Saeed Khorashadizadeh, Ann Van Griensven Jul 2022

Water Quality Simulation Of Lakes: Coupling Artificial Intelligence Techniques And Remote Sensing Data, Farkhondeh Khorashadi Zadeh, Albert Nkwasa, Saeed Khorashadizadeh, Ann Van Griensven

International Congress on Environmental Modelling and Software

Freshwater lakes are a major resource for human populations. To support water quality (WQ) management for lakes, both WQ monitoring and WQ modeling are essential. WQ variables are traditionally determined by in-situ measurements. Although this method offers high accuracy, it is a costly and time consuming process. Moreover, the sampling method is not easily able to identify the special and temporal WQ variations in lakes. To overcome this limitations, the use of remote sensing (RS), as a promising tool for large-scale inland WQ monitoring, can be adopted. To simulate WQ variables in lakes, several types of models have been developed, …

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Introducing Pybyste: A Python Package For Source Term Estimation Using Bayesian Inference, Piotr Kopka, Anna Wawrzyńczak-Szaban, Sławomir Potempski Jul 2022

Introducing Pybyste: A Python Package For Source Term Estimation Using Bayesian Inference, Piotr Kopka, Anna Wawrzyńczak-Szaban, Sławomir Potempski

International Congress on Environmental Modelling and Software

Accidental and intentional releases of hazardous substances in populated areas are a significant concern for all people responsible for public security. The source term estimation (STE) problem of determining the gas emission origin from the limited information provided by a set of released substance concentration measurements from sensors network is an ill-posed inverse problem. This paper describes the PyBySTE package's details, which is a convenient and efficient tool able to reconstruct the parameters of the source of gas releases in various domains. Bayesian source reconstruction module combines sensor measurements with advanced models to determine the posterior probabilistic distribution of unknown …

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Centrality And City Size Effects On No2 Ground And Tropospheric Concentrations Within European Cities, Yufei Wei, Geoffrey Caruso, Rémi Lemoy Jul 2022

Centrality And City Size Effects On No2 Ground And Tropospheric Concentrations Within European Cities, Yufei Wei, Geoffrey Caruso, Rémi Lemoy

International Congress on Environmental Modelling and Software

Nitrogen dioxide (NO2) has been one of the constant health threats of urban citizens. But how the NO2 levels change across European cities, relate to urban population size is still unclear. Meanwhile, a theory shows that traffic-induced air pollution (e.g. NO2) decreases with the distance to the city center. But among empirical studies, whether this centrality effect is prevalent in NO2 pollution in European cities is still unknown. We therefore investigate 378 European cities to quantify the effects of centrality and population size using NO2 data from monitoring stations and the satellite Sentinel-5P. We confirm the centrality effect proposed by …

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Combining Filter And Embedded Approaches To Improve Variable Selection In Land Use Change Cellular Automata Models Using Random Forests., Benjamin Black, Adrienne Grêt-Regamey Jul 2022

Combining Filter And Embedded Approaches To Improve Variable Selection In Land Use Change Cellular Automata Models Using Random Forests., Benjamin Black, Adrienne Grêt-Regamey

International Congress on Environmental Modelling and Software

Cellular Automata (CA) are a commonly used type of model to simulate future land use/cover (LULC) change by treating the landscape as a pixelated abstraction of cells of different LULC classes. These models predict the potential for change at a cellular level based upon statistically modelled relationships between historically observed class-class transitions and environmental, socio-economic and neighbourhood predictor variables. Over the last two decades the diversity and complexity of the techniques used for this transition modelling within CAs has grown considerably. However, regardless of the technique chosen, an area that is still given insufficient attention is the process of variable …

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Evaluating The Suitability Of Remote Sensing Lake Turbidity In Validating Model Sediment Loadings: An Application In Lake Tana Basin, Albert Nkwasa, Rediet Esayas Getachew, Ann Van Griensven Jul 2022

Evaluating The Suitability Of Remote Sensing Lake Turbidity In Validating Model Sediment Loadings: An Application In Lake Tana Basin, Albert Nkwasa, Rediet Esayas Getachew, Ann Van Griensven

International Congress on Environmental Modelling and Software

Validating water quality model applications is challenging due to data gaps in in-situ observations, especially in developing regions. To such a challenge, remote sensing (RS) has provided an alternative to monitor the water quality of inland waters due to its low cost, spatial continuity and temporal consistency. However, limited studies have exploited the option of validating water quality model outputs with RS water quality data. With sediment loadings regarded as a threat to the turbidity and trophic status of Lake Tana in Ethiopia, this study aims at using existing RS lake turbidity data to validate the seasonal and long-term trends …

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Enabling Efficient Use Of Earth Observations For Hydrologic Model Evaluation, Adnan Rajib, Linji Wang, Venkatesh Merwade Jul 2022

Enabling Efficient Use Of Earth Observations For Hydrologic Model Evaluation, Adnan Rajib, Linji Wang, Venkatesh Merwade

International Congress on Environmental Modelling and Software

Modelers often create multiple scenarios of a hydrologic model to evaluate the effects of climate change and watershed management decisions on model outputs, test a hypothesis, understand the implications of an improved input parameter or source code, and above all, validate the accuracy of model calibrations. Spatially distributed Earth Observations (EO) offer opportunities for evaluating watershed processes at different spatial scales as opposed to evaluating only streamflow at a few locations. Yet, making EO data ready for model evaluation remains challenging due the difficulty of getting these data to interoperate with the model structure. This becomes even more labor and …

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Geomorphic Approach To Fill Existing Gaps In Remote Sensing Surface Water Extent Mapping, Maria Julieta Rossi, Willem Vervoort Jul 2022

Geomorphic Approach To Fill Existing Gaps In Remote Sensing Surface Water Extent Mapping, Maria Julieta Rossi, Willem Vervoort

International Congress on Environmental Modelling and Software

Optical-based remote sensing techniques can be an effective means to monitor surface water extent (SWE) in wetlands. However, these techniques have limitations which arise due to omission errors caused by cloud coverage, shadows, vegetation canopy above the water and the presence of water and vegetation within the pixel (mixed pixels). Moreover, regardless of the water index being used, images with small water bodies, or water bodies that have long perimeters compared to their area will have more mixed pixels and greater omission errors, leading to a failure to identify SWE. Geomorphic approaches have been recognised as a potential strategy to …

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Developing Containerised Automated Workflows For Large Scale Parallel Execution Of Netlogo Models, Douglas Salt, Gary Polhill, Alessandro Gimona, Jonathan Ball Jul 2022

Developing Containerised Automated Workflows For Large Scale Parallel Execution Of Netlogo Models, Douglas Salt, Gary Polhill, Alessandro Gimona, Jonathan Ball

International Congress on Environmental Modelling and Software

It appears that little work has been done on the usage of containers for the large scale parallel execution of NetLogo models. That said, there are generalised frameworks for the running of NetLogo models such as Jansssen et al. (2008) and Janssen et al. (2014), and in addition frameworks for the analysis of data produced from such large scale execution, such as Jin et al. (2017). Containers are ideally suited to the running of NetLogo models for several reasons. First, the large scale parallel execution of NetLogo models is a classic ‘embarrassingly parallel’ problem. Each NetLogo instance of execution is …

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Visualizing Abm Submodels To Promote Stakeholder Participation: A Look Into Sustainable Forest Operations, Zenith Arnejo, Benoit Gaudou, Nathaniel Bantayan, Leonardo Barua Jul 2022

Visualizing Abm Submodels To Promote Stakeholder Participation: A Look Into Sustainable Forest Operations, Zenith Arnejo, Benoit Gaudou, Nathaniel Bantayan, Leonardo Barua

International Congress on Environmental Modelling and Software

Over the years, there has been an accumulation of different agent-based models (ABM) dedicated to forest resource management. However, only a few have been used in the implementation of real-world decision-making applications. One reason for this is the low level of stakeholder engagement in model development. There is still a significant gap between the stakeholders' understanding of the socioecological system and its corresponding representation as a process in a simulation model. In order to bridge this gap, it is necessary to communicate to the stakeholders the actual processes taking place in the simulation model. In this study, we developed an …

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Convergent Anthropocene Systems – A System Of Systems Approach, John Little, Amro Farid Jul 2022

Convergent Anthropocene Systems – A System Of Systems Approach, John Little, Amro Farid

International Congress on Environmental Modelling and Software

The greatest societal challenges of the Anthropocene are numerous and daunting, collectively spanning almost every discipline of science and engineering. Societies confronted with these challenges need to manage synergies and trade-offs across multiple systems, scales and levels of analysis. Unfortunately, most researchers tend to begin with their own subsystem and incrementally add a few interactions to a few other subsystems. Such incremental approaches ignore the dynamics of the larger systems and entirely overlook the fact that the societal challenges are interdependent. This fragmented approach is paralleled in policy circles. To overcome these challenges, we are inspired by system-of-systems approaches to …

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Reconstruction Of 20th Century Burned Area Through Recurrent Neural Networks, Seppe Lampe, Bertrand Le Saux, Inne Vanderkelen, Wim Thiery Jul 2022

Reconstruction Of 20th Century Burned Area Through Recurrent Neural Networks, Seppe Lampe, Bertrand Le Saux, Inne Vanderkelen, Wim Thiery

International Congress on Environmental Modelling and Software

The absence of a global long-term burned area dataset significantly hampers analyses of longterm trends in wildfire impacts. This prevents conclusive statements on the role of anthropogenic activity on wildfire impacts over the last century. Here, we construct a 1901-2014 data-driven reanalysis of monthly global burned area at a 0.5° by 0.5° scale. A recurrent neural network is trained with weather-related, vegetational, societal and economic input parameters, and burned area as output label for the 1982-2014 time period. This model is then applied to the whole 1901-2014 time period to create a data-driven, longterm burned area reanalysis. This reconstruction allows …

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What Family Of Radial Basis Functions To Use In Direct Policy Search? A Comparative Analysis, Jazmin Zatarain Salazar, Jan Kwakkel Jul 2022

What Family Of Radial Basis Functions To Use In Direct Policy Search? A Comparative Analysis, Jazmin Zatarain Salazar, Jan Kwakkel

International Congress on Environmental Modelling and Software

Direct policy search (DPS) is increasingly being used to design adaptive policies for multi-objective state-based control policies. DPS is a promising approach that can easily find policies for many heterogenous objective functions, particularly when coupling global approximators (i.e., radial basis functions) with evolutionary algorithms. Nonetheless, specifying the topology and the family of radial basis functions is usually done by trial and error for practical applications and is often not reported in the literature. How does the selected family of radial basis functions affect the quality of the resulting control policies? Does the chosen family influence the search behavior of the …

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The Development Of Oobn Pattern Language: Design Approach And Case Study In Sdg Modelling, Ebrahim Aly, Sondoss Elsawah, Michael J. Ryan Jul 2022

The Development Of Oobn Pattern Language: Design Approach And Case Study In Sdg Modelling, Ebrahim Aly, Sondoss Elsawah, Michael J. Ryan

International Congress on Environmental Modelling and Software

Bayesian Networks (BN) are graph models that have been widely used in modeling applications where uncertainty treatment is a key consideration. When such applications strive to depict complex systems, an extension to the BN that utilizes the concepts of Object-Oriented programming (OOP) paradigm is adopted to reduce the model’s complexity and increase its understandability and modularity, namely Object-Oriented Bayesian Networks (OOBN). Although OOBN serve as a versatile framework that is apt for addressing a wide range of the challenges pertinent to developing complex interdisciplinary models, the development of OOBN can be a challenging task that comprises multiple critical design choices …

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Scaling Up A Watershed Model For Large Basins, Allen Brookes Jul 2022

Scaling Up A Watershed Model For Large Basins, Allen Brookes

International Congress on Environmental Modelling and Software

This talk describes changes to the VELMA model that allow the model to scale up to allow simulation of much larger watersheds than the original model version allowed. The U.S. EPA’s Visualizing Ecosystems for Land Management Assessment (VELMA) is a spatially-distributed (grid-based) ecohydrological model. Users specify the grid size based on land cover complexity and computational considerations, e.g., a 30m is often used for mixed use watersheds under 3,000 km2. Simulating moderately large watersheds at this scale was challenging with the original formulation of VELMA due to the amount of computing resources needed and processing time. There was a need …

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Integrating Equity Considerations Into Agent-Based Modeling: A Conceptual Framework And Practical Guidance, Tim G. Williams, Daniel G. Brown, Seth G. Guikema, Tom M. Logan Jul 2022

Integrating Equity Considerations Into Agent-Based Modeling: A Conceptual Framework And Practical Guidance, Tim G. Williams, Daniel G. Brown, Seth G. Guikema, Tom M. Logan

International Congress on Environmental Modelling and Software

Advancing equity is a multi-dimensional challenge for society, science, and policy. Agent-based models are increasingly used as scientific tools to advance system understanding, inform decision-making, and share knowledge. Yet, equity has not received due attention within the agent-based modeling (ABM) literature. In this work, we develop a conceptual framework and provide guidance for integrating equity considerations into ABM research and good modeling practice. The framework describes ABM as interfacing with equity outcomes at two levels: the science-society interface and within the model itself. The framework identifies the modeler as a filter and lens that projects knowledge between the target system …

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Horizontal And Vertical Model Reuse In Mathematical Programmingbased Farm Agent Simulation, Christian Troost, Thomas Berger Jul 2022

Horizontal And Vertical Model Reuse In Mathematical Programmingbased Farm Agent Simulation, Christian Troost, Thomas Berger

International Congress on Environmental Modelling and Software

A well-established strand of agricultural economic agent-based modeling employs mathematical programming (MP) to simulate farming decisions (Berger Troost 2012; Kremmydas et al. 2018). More specifically, in the sense of the MoHuB framework’s conceptualization of human behavior (Schlüter et al. 2017), MP is used to implement the Selection component in these models. It can be combined with perception, knowledge, learning and value-oriented components to reflect different theories of decisionmaking and is often coupled to biophysical process models to evaluate human-environment feedback. We conceptualize different levels of component reuse in MP-based farm agent simulation (i.a. technical basis, coupling interfaces, components for between-decision …

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Understanding Usa Power Plants Renewable Behaviours With Data Science, Ignacio Peñafiel, Karina Gibert Jul 2022

Understanding Usa Power Plants Renewable Behaviours With Data Science, Ignacio Peñafiel, Karina Gibert

International Congress on Environmental Modelling and Software

Article Understanding USA Power Plants renewable behaviours with data science Ignacio Peñafiel (1), Karina Gibert (2) (1) Knowledge Engineering and Machine Learning group at Intelligent Data Science and Artificial Intelligence Research Center; Research Institute of Science and Technology for Sustainability; Universitat Politècnica de Catalunya-BarcelonaTech, Spain), [email protected] (2) Knowledge Engineering and Machine Learning group at Intelligent Data Science and Artificial Intelligence Research Center; Research Institute of Science and Technology for Sustainability; Universitat Politècnica de Catalunya-BarcelonaTech, Spain), [email protected] 1. Abstract: Background: Decarbonization, renewable energy and sustainability awareness are growing. Society and Governments target a share of power plants from renewable energy sources …

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Multi-Criteria Decision Analysis Under Uncertainty: A Geometrically Inspired Approach, Matthias Grajewski, Imke Rhoden, Stefan Vögele Jul 2022

Multi-Criteria Decision Analysis Under Uncertainty: A Geometrically Inspired Approach, Matthias Grajewski, Imke Rhoden, Stefan Vögele

International Congress on Environmental Modelling and Software

ti-Criteria Decision Analysis (MCDA), originally a tool for decision making, is nowadays employed as a common tool for analyzing preferences and likely actions of stakeholders in many different contexts (e.g., attitudes of people towards changes in the transport sector or energy transformation scenarios). However, MCDA models rely on numerous parameters which are often hard to determine, subject to uncertainty, or are even unknown. In some cases, the actions or (partial) preferences of stakeholders under certain circumstances are known. We present a novel method for a class of popular MCDA approaches to obtain quantitative information on parameters of MCDA models, in …

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A Reusable, Extensible Netlogo Building Block Of Land And Housing Markets In A Touristic Region, Dawn Parker, Claudio Detotto, Eric Innocenti, Yuheng Ling Jul 2022

A Reusable, Extensible Netlogo Building Block Of Land And Housing Markets In A Touristic Region, Dawn Parker, Claudio Detotto, Eric Innocenti, Yuheng Ling

International Congress on Environmental Modelling and Software

In this paper, we present an Agent-Based Land Market Model (ABM/LMM) to simulate the complex system of land and property markets, motivated by the recognized suitability of ABMs for modelling these markets. Our ABM/LMM is based on the precepts, concepts and techniques from computer simulation science and economics. It was developed using a collectively designed template for agent-based models of land and housing markets, “MR POTATOHEAD: Property Market Edition,” co-developed by six international teams of complex systems economists. Thus this model can form the kernel for a reusable and flexible code for ABM/LMM land and housing market simulations, as it …

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A Weakly Supervised Framework For High-Resolution Crop Yield Forecasts, Dilli R. Paudel, Diego M. Gonzalez, Athanasiadis N. Ioannis, Allard De Wit Jul 2022

A Weakly Supervised Framework For High-Resolution Crop Yield Forecasts, Dilli R. Paudel, Diego M. Gonzalez, Athanasiadis N. Ioannis, Allard De Wit

International Congress on Environmental Modelling and Software

Predictor inputs and label data for crop yield forecasting are not always available at the same spatial resolution. We propose a deep learning framework that uses high resolution inputs (e.g. weather and soil) and low resolution labels (e.g. yield and crop area statistics) to produce crop yield forecasts for both spatial levels. The forecasting model is calibrated by weak supervision from low resolution crop area and yield statistics. We evaluated the framework by disaggregating regional yields in Europe from parent statistical regions to sub-regions for five countries (Germany, Spain, France, Hungary, Italy) and two crops (soft wheat and potatoes). Performance …

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Real-Time Monitoring Data Quality Assurance For Participatory Realtime Salinity Management, Nigel W.T. Quinn Jul 2022

Real-Time Monitoring Data Quality Assurance For Participatory Realtime Salinity Management, Nigel W.T. Quinn

International Congress on Environmental Modelling and Software

Real-time monitoring data quality assurance for participatory real-time salinity management Nigel W.T. Quinn Berkeley National Laboratory Climate and Ecosystem Sciences, Bld 64-209 Berkeley, CA 94720 Improvements in the accuracy and reliability of environmental sensors and cellular telemetry and falling costs have increased their deployment for hydrologic and water quality monitoring. These deployments support the continuous operation of water quality simulation and forecasting models that provide decision support to stakeholders engaged in a program to manage salinity in real-time a major river basin in California. Real-time quality assurance of data assimilated from monitoring stations in the river basin is key for …

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A Stepwise Reduction Of Model Complexity And Block-Specific Benchmarks Are The Key To Effective And Reliable Testing Of Complex Simulation Models That Consist Of Conceptually Differing Building Blocks, Marie-Christin Wimmler, Jasper Bathmann, Uta Berger Jul 2022

A Stepwise Reduction Of Model Complexity And Block-Specific Benchmarks Are The Key To Effective And Reliable Testing Of Complex Simulation Models That Consist Of Conceptually Differing Building Blocks, Marie-Christin Wimmler, Jasper Bathmann, Uta Berger

International Congress on Environmental Modelling and Software

Model reusability and reliable benchmarking strategies are of major concern in ecological modelling. Here, the object-oriented programming (OOP) paradigm provides new pathways. We demonstrate possible advantages of OOP using the process- and individual based mangrove model MANGA (mangrove groundwater salinity feedback model). MANGA is modular and comprises various modelling concepts to simulate the growth of (mangrove) trees in response to environmental conditions, competition or facilitation among neighboring trees. MANGA provides several tested and well documented building blocks among which a modeler can select the most suitable for a given research question. For example, below-ground competition can be described using the …

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Learning Latent Representations For Operational Nitrogen Response Rate Prediction, Pylianidis Christos, Athanasiadis N. Ioannis Jul 2022

Learning Latent Representations For Operational Nitrogen Response Rate Prediction, Pylianidis Christos, Athanasiadis N. Ioannis

International Congress on Environmental Modelling and Software

Learning latent representations has aided operational decision-making in several disciplines. Its advantages include uncovering hidden interactions in data and automating procedures which were performed manually in the past. Representation learning is also being adopted by the environmental sciences. However, there are still subfields that depend on manual feature engineering based on expert knowledge and the use of algorithms which do not utilize the latent space. Relying on those techniques can inhibit operational decision-making since they impose data constraints and inhibit automation. In this work, we adopt a case study for nitrogen response rate prediction and examine if representation learning can …

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Reusable Building Blocks For Agent-Based Modelling: Benefits, Challenges, And A Template For Their Release, Volker Grimm, Uta Berger, Tatiana Filatova Jul 2022

Reusable Building Blocks For Agent-Based Modelling: Benefits, Challenges, And A Template For Their Release, Volker Grimm, Uta Berger, Tatiana Filatova

International Congress on Environmental Modelling and Software

At its dawn, agent-based modelling (ABM) has been characterized by ad hoc model designs and poor model analysis. The development and increasing use of standards for documenting and testing models (e.g., ODD, ODD+D, TRACE) contributed significantly to an increase of transparency and reproducibility. Software environments specifically designed for ABMs (e.g. NetLogo, GAMA, MESA) facilitate both model development and implementation, while diffusion of Python and R-packages facilitate a thorough simulation experiments’ design and output analysis. Still, despite a massive progress on levering practice of micro-foundations of ABM design, most ABMs are developed from scratch over and over again. This is not …

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Classification Model For Selecting Appropriate Sanitation Technology Compatible With The Community Capacity, Jawad Hasan Shoqeir, Ibrahim Tomizeh Jul 2022

Classification Model For Selecting Appropriate Sanitation Technology Compatible With The Community Capacity, Jawad Hasan Shoqeir, Ibrahim Tomizeh

International Congress on Environmental Modelling and Software

Wastewater treatment and sanitation is a major issue in saving lives in many countries in the world especially in the developing arid and semi-arid countries where water sources are rare and considered as a source of conflict if not managed properly. Sustainable wastewater treatment systems may provide sustainable none conventional water sources where we can generate energy and food if monitored and managed properly. There are national and local organizations that work on monitoring water services regularly, assignee indicators to measure the effectiveness of the service, other organizations that follow up the service after implementation "post-implementation monitoring". This paper aims …

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Data-Intensive Discoveries For Feeding The World In A Changing Climate - An Artificial Intelligence Roadmap, Loannis Athanasiadis Jul 2022

Data-Intensive Discoveries For Feeding The World In A Changing Climate - An Artificial Intelligence Roadmap, Loannis Athanasiadis

International Congress on Environmental Modelling and Software

Artificial Intelligence offers new avenues for harnessing the power of big data. AI has accelerated research in several application domains, with agriculture not being an exception. This talk offers a bird's eye view of agricultural AI: It summarises current research, and presents challenges and opportunities for future research. What makes agriculture an interesting application for AI? Which are research challenges ahead? By sketching answers to the previous questions, I will attempt a research agenda of methodological challenges for addressing food security problems in a changing climate. Can AI help us respectfully produce food for the world in the years to …

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Governance Of A Watershed Model With An Evolving Purpose: Negotiating Adaptation, Stability, And Power, Theodore Lim, Patrick Bitterman, Pierre Glynn, Joseph Guillaume Jul 2022

Governance Of A Watershed Model With An Evolving Purpose: Negotiating Adaptation, Stability, And Power, Theodore Lim, Patrick Bitterman, Pierre Glynn, Joseph Guillaume

International Congress on Environmental Modelling and Software

Computer models play increasingly central roles in environmental management, however, the role of the modeling process within environmental governance contexts and specifically, the governance of computer models are understudied. In this research, we apply existing theories of network and hierarchical governance, adaptive management and governance, and participatory modeling to analyze a key historical period of the Chesapeake Bay Program, 2008 - 2012. During this period, the purpose of the program shifted substantially, challenges to the legitimacy of the model itself were made, and the model was exposed to potential capture by stakeholders who stood to directly benefit from its outputs. …

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Approaches To Reaching Critical (Self-Sustaining) Mass For Rbb Sharing, Andrew Bell Jul 2022

Approaches To Reaching Critical (Self-Sustaining) Mass For Rbb Sharing, Andrew Bell

International Congress on Environmental Modelling and Software

The development of reusable building blocks (RBB) for agent-based modeling toolkits offers benefits across multiple scales – to the modelers, by streamlining the model-building task, and to the research field, by (possibly) enabling convergence upon shared and standard approaches to common modeling tasks. However, the challenge of reaching a self-sustaining system of RBB sharing and use is not trivial. On the one hand, we have yet to identify what exactly constitutes a building block, and what is the most usable package to be shared. On the other hand, informing these questions is made more difficult by the relatively low frequency …

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Impacts Of Climate Change And Land-Use Change On Water Resources In Africa, Celray James Chawanda, Wim Thiery, Ann Van Griensven Jul 2022

Impacts Of Climate Change And Land-Use Change On Water Resources In Africa, Celray James Chawanda, Wim Thiery, Ann Van Griensven

International Congress on Environmental Modelling and Software

Like many continents, Africa depends on its water resources for hydroelectricity, inland fisheries, and water supply for domestic, industrial, and agricultural operations. Anthropogenic climate change (CC) has changed the state of these water resources. Land use and land cover has also undergone significant changes due to the need to provide resources to a growing population. Yet, the impact of the Land Use and Land Cover Change (LULCC) in addition to CC on the water resources of Africa is underexplored. This study investigates how precipitation, evapotranspiration (ET), and streamflow respond to CC and LULCC scenarios. We set up a SWAT+ model …

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Change Dynamics Of Agricultural Land Systems In Europe: An Innovative Approach Based On An Unsupervised Clustering Technique, Marj Tonini, Rabelo Marya, Silvestri Nicola Jul 2022

Change Dynamics Of Agricultural Land Systems In Europe: An Innovative Approach Based On An Unsupervised Clustering Technique, Marj Tonini, Rabelo Marya, Silvestri Nicola

International Congress on Environmental Modelling and Software

Spatial and temporal changes in Agricultural Land Systems (ALS) are often interlinked and coexist within quite large areas determining a complex set of structures and transitions. To detect these changes is necessary to reduce the complexity of the input information to few typologies which can be easier managed and interpreted. In the recent period, the development of data driven methods based on machine learning enlarged the availability of sophisticated techniques that allow researchers to discover pattern in environmental dataset. Among them, Self-Organizing Map (SOM), an unsupervised competitive learning neural network, performs particularly well to identify clusters from a multivariate dataset. …

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