Standard

Uncertainty analysis in integrated catchment modelling. / Moreno Rodenas, Antonio.

2019. 150 p.

Research output: ThesisDissertation (TU Delft)

Harvard

APA

Vancouver

Author

Moreno Rodenas, Antonio. / Uncertainty analysis in integrated catchment modelling. 2019. 150 p.

BibTeX

@phdthesis{a8577854a25444a4bdb2b63218454828,
title = "Uncertainty analysis in integrated catchment modelling",
abstract = "The adoption of increasingly restrictive water quality standards is directed to maintain natural ecosystems in a good status. Complying with such standards requires significant investments in water infrastructure and operations. Consequently, mathematical simulation is usually applied to assist in the decision-making process for such large-scale actuations. In particular, environmental models are proposed to represent the wastewater cycle in natural water bodies, such that the effect of different pollution mitigation alternatives can be estimated. Integrated catchment models (ICM) aim at simulating water quality dynamics by representing the link between urban drainage networks, wastewater treatment operations, rural hydrology and river physical-biochemical processes. However, these subsystems present dynamics acrossmultiple spatiotemporal scales and many relevant processes are still not fully understood. System observations are scarce and often insufficient to identify most model representations. As a result, ICM studies often produce significant output uncertainties.",
author = "{Moreno Rodenas}, Antonio",
year = "2019",
month = jul,
day = "8",
doi = "10.4233/uuid:a8577854-a254-44a4-bdb2-b63218454828",
language = "English",
isbn = "978-94-92801-89-0",
school = "Delft University of Technology",

}

RIS

TY - THES

T1 - Uncertainty analysis in integrated catchment modelling

AU - Moreno Rodenas, Antonio

PY - 2019/7/8

Y1 - 2019/7/8

N2 - The adoption of increasingly restrictive water quality standards is directed to maintain natural ecosystems in a good status. Complying with such standards requires significant investments in water infrastructure and operations. Consequently, mathematical simulation is usually applied to assist in the decision-making process for such large-scale actuations. In particular, environmental models are proposed to represent the wastewater cycle in natural water bodies, such that the effect of different pollution mitigation alternatives can be estimated. Integrated catchment models (ICM) aim at simulating water quality dynamics by representing the link between urban drainage networks, wastewater treatment operations, rural hydrology and river physical-biochemical processes. However, these subsystems present dynamics acrossmultiple spatiotemporal scales and many relevant processes are still not fully understood. System observations are scarce and often insufficient to identify most model representations. As a result, ICM studies often produce significant output uncertainties.

AB - The adoption of increasingly restrictive water quality standards is directed to maintain natural ecosystems in a good status. Complying with such standards requires significant investments in water infrastructure and operations. Consequently, mathematical simulation is usually applied to assist in the decision-making process for such large-scale actuations. In particular, environmental models are proposed to represent the wastewater cycle in natural water bodies, such that the effect of different pollution mitigation alternatives can be estimated. Integrated catchment models (ICM) aim at simulating water quality dynamics by representing the link between urban drainage networks, wastewater treatment operations, rural hydrology and river physical-biochemical processes. However, these subsystems present dynamics acrossmultiple spatiotemporal scales and many relevant processes are still not fully understood. System observations are scarce and often insufficient to identify most model representations. As a result, ICM studies often produce significant output uncertainties.

U2 - 10.4233/uuid:a8577854-a254-44a4-bdb2-b63218454828

DO - 10.4233/uuid:a8577854-a254-44a4-bdb2-b63218454828

M3 - Dissertation (TU Delft)

SN - 978-94-92801-89-0

ER -

ID: 54811639