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Temporal Uncertainty Propagation Analysis: A Contribution Towards Sustainable Urban Water Management.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Temporal Uncertainty Propagation Analysis: A Contribution Towards Sustainable Urban Water Management./
作者:	Torres-Matallana, Jairo Arturo.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	289 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-05, Section: B.
Contained By:	Dissertations Abstracts International83-05B.
標題:	Computer science. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28760908
ISBN:	9798494449733

Temporal Uncertainty Propagation Analysis: A Contribution Towards Sustainable Urban Water Management.
Torres-Matallana, Jairo Arturo.

Temporal Uncertainty Propagation Analysis: A Contribution Towards Sustainable Urban Water Management. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 289 p.

Source: Dissertations Abstracts International, Volume: 83-05, Section: B.

Thesis (Ph.D.)--Wageningen University and Research, 2021.

This item must not be sold to any third party vendors.

Sustainable urban water management (SUWM) is becoming a global priority due to the impact of urbanisation on natural and urban ecosystems. The global population in 2018 was equivalent to 55 per cent of the world's population residing in urban areas. By 2050, the global population will reach 9.7 billion, with 68 per cent of the world's population (i.e., 6.6 billion people) projected to be urban. With the increase of urbanisation development the lack of basic urban infrastructure (i.e., water and energy supplies, sanitation, education, and green space or parks) could become more acute for the sustainability of cities in the future, especially in developing countries.Urbanisation not only impacts the hydrological cycle, but also has an interlinked impact on the urban landscape ecosystem and its evolution. This has been recognised in the last two decades by governments, especially in more economically developed countries, with the advent of concepts such as "Sustainable Development", and "Nature-Based Solutions", which focus primarily on what nature can provide to humans. This is a response to the urgency of solving urban water problems and integrating solutions with new urban water management strategies and practices.SUWM is a key tool contributing to several of the United Nations' Sustainable Development Goals. Integrated urban drainage models are primary components of monitoring systems and essential decision-making tools for SUWM. However, it is paramount to recognise that in environmental modelling, and hence also in SUWM, every model contains uncertainties to some degree. This is because any model makes simplifications and assumptions about the real-world processes involved, while model inputs are rarely if ever known without error. Quantification of model input and output uncertainty is essential for characterising inputs and choosing objectively the suitable configuration of the model for addressing a specific task related to integrated urban drainage modelling (IUDM).Uncertainty quantification in integrated environmental models with emphasis in SUWM, specifically urban stormwater system models (USSM's) used in decision-making for environmental protection, require that the accuracy of model outputs is known and meets predefined standards. Uncertainty propagation in SUWM is yet not well understood.Four important problems are identified:1. Full hydrodynamic USSM's are complex and require a highly intense computational budget, which constitutes a constraint when long-term simulations or uncertainty propagation analysis are required.2. Although catchment average precipitation is a key component of USSM's, catchment average precipitation is not always accurately known when derived from measurements at point support, i.e. by rain gauges. To estimate the precipitation in a catchment given a known precipitation time series at a location outside of the catchment is often needed, while also quantify the uncertainty associated with the estimated catchment average precipitation.3. Software tools for temporal uncertainty propagation for USSM's are not generally available.4. Many studies in USSM's do not pay attention to uncertainty and uncertainty propagation. Statistical uncertainty analysis of USSM's is a relatively new subject that largely needs to be developed while very few solid applications have been done.

ISBN: 9798494449733Subjects--Topical Terms:

523869
Computer science.

Temporal Uncertainty Propagation Analysis: A Contribution Towards Sustainable Urban Water Management.
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500 $a Source: Dissertations Abstracts International, Volume: 83-05, Section: B.
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506 $a This item must not be sold to any third party vendors.
520 $a Sustainable urban water management (SUWM) is becoming a global priority due to the impact of urbanisation on natural and urban ecosystems. The global population in 2018 was equivalent to 55 per cent of the world's population residing in urban areas. By 2050, the global population will reach 9.7 billion, with 68 per cent of the world's population (i.e., 6.6 billion people) projected to be urban. With the increase of urbanisation development the lack of basic urban infrastructure (i.e., water and energy supplies, sanitation, education, and green space or parks) could become more acute for the sustainability of cities in the future, especially in developing countries.Urbanisation not only impacts the hydrological cycle, but also has an interlinked impact on the urban landscape ecosystem and its evolution. This has been recognised in the last two decades by governments, especially in more economically developed countries, with the advent of concepts such as "Sustainable Development", and "Nature-Based Solutions", which focus primarily on what nature can provide to humans. This is a response to the urgency of solving urban water problems and integrating solutions with new urban water management strategies and practices.SUWM is a key tool contributing to several of the United Nations' Sustainable Development Goals. Integrated urban drainage models are primary components of monitoring systems and essential decision-making tools for SUWM. However, it is paramount to recognise that in environmental modelling, and hence also in SUWM, every model contains uncertainties to some degree. This is because any model makes simplifications and assumptions about the real-world processes involved, while model inputs are rarely if ever known without error. Quantification of model input and output uncertainty is essential for characterising inputs and choosing objectively the suitable configuration of the model for addressing a specific task related to integrated urban drainage modelling (IUDM).Uncertainty quantification in integrated environmental models with emphasis in SUWM, specifically urban stormwater system models (USSM's) used in decision-making for environmental protection, require that the accuracy of model outputs is known and meets predefined standards. Uncertainty propagation in SUWM is yet not well understood.Four important problems are identified:1. Full hydrodynamic USSM's are complex and require a highly intense computational budget, which constitutes a constraint when long-term simulations or uncertainty propagation analysis are required.2. Although catchment average precipitation is a key component of USSM's, catchment average precipitation is not always accurately known when derived from measurements at point support, i.e. by rain gauges. To estimate the precipitation in a catchment given a known precipitation time series at a location outside of the catchment is often needed, while also quantify the uncertainty associated with the estimated catchment average precipitation.3. Software tools for temporal uncertainty propagation for USSM's are not generally available.4. Many studies in USSM's do not pay attention to uncertainty and uncertainty propagation. Statistical uncertainty analysis of USSM's is a relatively new subject that largely needs to be developed while very few solid applications have been done.
520 $a La gesti´on sostenible del agua urbana (SUWM, del ingl´es sustainable urban water management) se est´a convirtiendo en una prioridad mundial debido al impacto de la urbanizaci´on en los ecosistemas naturales y urbanos. En 2018, la poblaci´on mundial equival´ia al 55% de la poblaci´on mundial que resid´ia en zonas urbanas. En 2050, la poblaci´on mundial alcanzar´a los 9.700 millones, y se prev´e que el 68% de la poblaci´on mundial (es decir, 6.600 millones de personas) sea urbana. Con el aumento del desarrollo de la urbanizaci´on, la falta de infraestructura urbana b´asica (es decir, suministros de agua y energ´ia, saneamiento, educaci´on y espacios verdes o parques) podr´ia agudizarse para la sostenibilidad de las ciudades en el futuro, especialmente en los pa´ises en desarrollo.La urbanizaci´on no s´olo repercute en el ciclo hidrol´ogico, sino que tambi´en tiene un impacto interrelacionado en el ecosistema del paisaje urbano y su evoluci´on. Esto ha sido reconocido en las dos ´ultimas d´ecadas por los gobiernos, especialmente en los pa´ises econ´omicamente m´as desarrollados, con la aparici´on de conceptos como "Desarrollo Sostenible", y "Soluciones basadas en la naturaleza", que se centran principalmente en lo que la naturaleza puede proporcionar a los humanos. Se trata de una respuesta a la urgencia de resolver los problemas del agua urbana y de integrar las soluciones con nuevas estrategias y pr´acticas de gesti´on del agua urbana.La SUWM es una herramienta clave que contribuye a varios de los Objetivos de Desarrollo Sostenible de las Naciones Unidas. Los modelos integrados de drenaje urbano son componentes primarios de los sistemas de control y herramientas esenciales para la toma de decisiones en la SUWM. Sin embargo, es primordial reconocer que en la modelaci´on medioambiental, y por tanto tambi´en en la SUWM, todo modelo tiene incertidumbre en cierta medida. Esto se debe a que cada modelo hace simplificaciones y suposiciones sobre los procesos del mundo real, mientras que las entradas del modelo rara vez se conocen sin errores. La cuantificaci´on de la incertidumbre de las entradas y salidas del modelo es esencial para caracterizar las entradas y elegir objetivamente la configuraci´on adecuada del modelo para abordar una tarea espec´ifica relacionada con la modelaci´on del drenaje urbano integrado (IUDM, del ingl´es integrated urban drainage modelling).La cuantificaci´on de la incertidumbre en los modelos ambientales integrados, con ´enfasis en la SUWM, espec´ificamente en los modelos de sistemas urbanos de aguas pluviales (USSM's, del ingl´es urban stormwater system models) utilizados en la toma de decisiones para la protecci´on del medio ambiente, requieren que la precisi´on de los resultados del modelo sea conocida y cumpla con est´andares predefinidos.
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