Developing Efficient Strategies for Automatic Calibration of Computationally Intensive Environmental Models

Environmental simulation models have been playing a key role in civil and environmental engineering decision making processes for decades. The utility of an environmental model depends on how well the model is structured and calibrated. Model calibration is typically in an automated form where the simulation model is linked to a search mechanism (e.g., an optimization algorithm) such that the search mechanism iteratively generates many parameter sets (e.g., thousands of parameter sets) and evaluates them through running the model in an attempt to minimize differences between observed data and corresponding model outputs. The challenge rises when the environmental model is computationally intensive to run (with run-times of minutes to hours, for example) as then any automatic calibration attempt would impose a large computational burden. Such a challenge may make the model users accept sub-optimal solutions and not achieve the best model performance. The objective of this thesis is to develop innovative strategies to circumvent the computational burden associated with automatic calibration of computationally intensive environmental models. The first main contribution of this thesis is developing a strategy called “deterministic model preemption” which opportunistically evades unnecessary model evaluations in the course of a calibration experiment and can save a significant portion of the computational budget (even as much as 90% in some cases). Model preemption monitors the intermediate simulation results while the model is running and terminates (i.e., pre-empts) the simulation early if it recognizes that further running the model would not guide the search mechanism. This strategy is applicable to a range of automatic calibration algorithms (i.e., search mechanisms) and is deterministic in that it leads to exactly the same calibration results as when preemption is not applied. One other main contribution of this thesis is developing and utilizing the concept of “surrogate data” which is basically a reasonably small but representative proportion of a full set of calibration data. This concept is inspired by the existing surrogate modelling strategies where a surrogate model (also called a metamodel) is developed and utilized as a fast-to-run substitute of an original computationally intensive model. A framework is developed to efficiently calibrate hydrologic models to the full set of calibration data while running the original model only on surrogate data for the majority of candidate parameter sets, a strategy which leads to considerable computational saving. To this end, mapping relationships are developed to approximate the model performance on the full data based on the model performance on surrogate data. This framework can be applicable to the calibration of any environmental model where appropriate surrogate data and mapping relationships can be identified. As another main contribution, this thesis critically reviews and evaluates the large body of literature on surrogate modelling strategies from various disciplines as they are the most commonly used methods to relieve the computational burden associated with computationally intensive simulation models. To reliably evaluate these strategies, a comparative assessment and benchmarking framework is developed which presents a clear computational budget dependent definition for the success/failure of surrogate modelling strategies. Two large families of surrogate modelling strategies are critically scrutinized and evaluated: “response surface surrogate” modelling which involves statistical or data–driven function approximation techniques (e.g., kriging, radial basis functions, and neural networks) and “lower-fidelity physically-based surrogate” modelling strategies which develop and utilize simplified models of the original system (e.g., a groundwater model with a coarse mesh). This thesis raises fundamental concerns about response surface surrogate modelling and demonstrates that, although they might be less efficient, lower-fidelity physically-based surrogates are generally more reliable as they to-some-extent preserve the physics involved in the original model. Five different surface water and groundwater models are used across this thesis to test the performance of the developed strategies and elaborate the discussions. However, the strategies developed are typically simulation-model-independent and can be applied to the calibration of any computationally intensive simulation model that has the required characteristics. This thesis leaves the reader with a suite of strategies for efficient calibration of computationally intensive environmental models while providing some guidance on how to select, implement, and evaluate the appropriate strategy for a given environmental model calibration problem

Unifying multilevel modelling through ontologies

In the last decades, the multilevel problem has received increasing attention in the conceptual modelling and semantic web communities. Recently, we proposed a solution to this problem in the context of ontological modelling which consists in extending the Web Ontology Language OWL with a new multilevel constructor that equates instances to classes. In this work we highlight the advantages of exploiting the reasoning capabilities of OWL ontologies with the proposed multilevel constructor by analizing requirements from a real-world application on the accounting domain

Scientific History of Incipit in the period 2010-2016

Historial de la actividad científica y técnica del Instituto de Ciencias del Patrimonio (Incipit) del CSIC, basado en Santiago de Compostela, desde su fecha de creación (2010) hasta el año 2016. Se presentan la misión y las líneas de investigación del Incipit, centradas principalmente en el estudio de los procesos de patrimonialización y de valorización social del patrimonio cultural realizadas con una perspectiva transdisciplinar. Se relacionan las publicaciones, proyectos de investigación, actividades de ciencia pública, eventos de comunicación y productos de divulgación que su personal investigador ha producido a lo largo de estos años.General introduction to the Incipit. Presentation of the Research Line: Cultural Heritage Studies: Sub-Theme: Landscape Archaeology and Cultural Landscapes, Sub-theme: Heritagization Processes: Memory, Power and Ethnicity, Sub-theme: Socioeconomics of Cultural Heritage, Sub-theme: Archaeology of the Contemporary Past, Sub-theme: Material culture and formalization processes of cultural heritage. Scientific Contributions. Transfer of Knowledge. International Activities. Other Activities and Results. Scientific DisseminationN

Ways of Following

In Ways of Following, Katve-Kaisa Kontturi offers rare, intimate access to artists’ studios and exhibitions, where art processes thrive in their material-relational becoming. The book argues for an ethical and affirmative mode of engaging with contemporary art that replaces critical distance with sensuous and transformative proximity. From writing-with to dancing and breathing, from conversations to modelling, it maps ways of following that make the moving materiality of art intensively felt. Drawing on long-term engagements with selected contemporary artists and their art-in-process, Kontturi expands the concept and practice of collaboration from human interactions to working with, and between, materials. With this shift, Ways of Following radically rethinks such core tenets of art theory as intention, artistic influences and the autonomy of art, bringing new urgency to the work of art and its political capacity to propose new ways of being and thinking

Investigations Into Web Science and the Concept of Web Life

Our increasing ability to construct large and complex computer and information systems suggests that the classical manner in which such systems are understood and architected is inappropriate for the open and unstructured manner in which they are often used. With the appearance of mathematically complex and, more importantly, high scale, non-deterministic systems, such as the World Wide Web, there is a need to understand, construct and maintain systems in a world where their assembly and use may not be precisely predicted. In Addition, few have thus far attempted to study such Web-scale systems holistically so as to understand the implications of non-programmable characteristics, like emergence and evolution – a matter of particular relevance in the new field of Web Science. This collection of prior published works and their associated commentary hence brings together a number of themes focused on Web Science and its broader application in systems and software engineering. It primarily rests on materials presented in the book The Web’s Awake, first published in April 2007