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  • 1.
    Broekhuizen, Ico
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Uncertainties in rainfall-runoff modelling of green urban drainage systems: Measurements, data selection and model structure2019Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Green urban drainage systems are used to avoid flooding and damages to people and property, while limiting the downstream flooding and water quality problems caused by pipe-based drainage systems. Computer models are used to analyse and predict the performance of such systems for design and operation purposes. Such models are simplifications of reality and based on uncertain measured data, so uncertainties will be involved in the modelling process and its outcomes, which can affect the design and operation of these systems. These uncertainties have been investigated extensively for traditional pipe-based urban drainage systems, but not yet for green alternatives. Therefore, the overall objective of this thesis is to contribute to improved applicability and reliability of computer models of green urban drainage systems. Specifically, the thesis aims to (1) improve understanding of the uncertainties arising from (a) model structure and (b) calibration data selection, (2) evaluate two alternative calibration methods for green urban drainage models, (3) discuss desirable structural features in urban drainage models, and (4) evaluate several sensors for hydrometeorological measurements in urban catchments.

    The effects of model structure uncertainty were investigated using long-term simulations of synthetic catchments with varying soil types and depths for three different models. First, it was found that surface runoff could be a significant part of the annual water balance in all three models, depending on the soil type and depth considered. Second, differences were found in how sensitive the different models were to changes in soil type and depth. Third, the variation between different models was often large compared to the variation between different soil types. Fourth, the magnitude of inter-annual and inter-event variation varied between the models. Overall, the findings indicate that significant differences may occur in urban drainage modelling studies, depending on which model is used, and this may affect the design or operation of such systems.

    The uncertainty from calibration data selection was investigated primarily by calibrating both a low- and high-resolution stormwater model using different sets of events. These event sets used different rainfall-runoff statistics to rank all observed events before selecting the top six for use in calibration. In addition, they varied by either calibrating all parameters simultaneously, or by calibrating parameters for impervious and pervious surfaces separately. This last approach sped up the calibration process. In the validation period the high-resolution models performed better than their low-resolution counterparts and the two-stage calibrations matched runoff volume and peak flows better than single-stage calibrations. Overall, the way in which the calibration events are selected was shown to have a major impact on the performance of the calibrated model.

    Calibration data selection was also investigated by examining different ways of including soil water content (SWC) observations in the calibration process of a model of a swale. Some model parameters could be identified from SWC, but not from outflow observations. Including SWC in the model evaluation affected the precision of swale outflow predictions. Different ways of setting initial conditions in the model (observations or an equilibrium condition) affected both of these findings.

    The precipitation sensors used in this thesis showed generally satisfactory performance in field calibration checks. Different types of precipitation sensors were associated with different requirements for maintenance and data acquisition. Sensors for sewer pipe flow rates showed good agreement with a reference instrument in the laboratory, as long as installation conditions were good. Higher pipe slopes and upstream obstacles lead to larger measurement errors, but this last effect was reduced by increasing water levels in the pipe. Sensor fouling was a source of errors and gaps in field measurements, showing that regular maintenance is required. The findings show that the evaluated flow sensors can perform satisfactorily, if measurement sites are carefully selected.

  • 2.
    Broekhuizen, Ico
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Leonhardt, Günther
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Marsalek, Jiri
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Viklander, Maria
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Calibration event selection for green urban drainage modelling2019Manuscript (preprint) (Other (popular science, discussion, etc.))
    Abstract [en]

    Calibration of urban drainage models is typically performed based on a limited number of observed rainfall-runoff events, which may be selected from a longer time-series of measurements in different ways. In this study, 14 single- and two-stage strategies for selecting these events were tested for calibration of a SWMM model of a predominantly green urban area. The event selection was considered in relation to other sources of uncertainty such as measurement uncertainties, objective functions, and catchment discretization. Even though all 14 strategies resulted in successful model calibration, the difference between the best and worst strategies reached 0.2 in Nash–Sutcliffe Efficiency (NSE) and the calibrated parameter values notably varied. Most, but not all, calibration strategies were robust to changes in objective function, perturbations in calibration data and the use of a low spatial resolution model in the calibration phase. The various calibration strategies satisfactorily predicted 7 to 13 out of 19 validation events. The two-stage strategies performed better than the single-stage strategies when measuring performance using the Root Mean Square Error, flow volume error or peak flow error (but not using NSE); when flow data in the calibration period had been perturbed by ±40 %; and when using a lower model resolution. The two calibration strategies that performed best in the validation period were two-stage strategies. The findings in this paper show that different strategies for selecting calibration events may lead in some cases to different results for the validation period, and that calibrating impermeable and green area parameters in two separate steps may improve model performance in the validation period, while also reducing the computational demand in the calibration phase.

  • 3.
    Broekhuizen, Ico
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Leonhardt, Günther
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Marsalek, Jiri
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Viklander, Maria
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Event selection and two-stage approach for calibrating models of green urban drainage systems2020In: Hydrology and Earth System Sciences, ISSN 1027-5606, E-ISSN 1607-7938, Vol. 24, p. 869-885Article in journal (Refereed)
    Abstract [en]

    The calibration of urban drainage models is typically performed based on a limited number of observed rainfall–runoff events, which may be selected from a larger dataset in different ways. In this study, 14 single- and two-stage strategies for selecting the calibration events were tested in calibration of a high- and low-resolution Storm Water Management Model (SWMM) of a predominantly green urban area. The two-stage strategies used events with runoff only from impervious areas to calibrate the associated parameters, prior to using larger events to calibrate the parameters relating to green areas. Even though all 14 strategies resulted in successful model calibration (Nash–Sutcliffe efficiency; NSE >0.5), the difference between the best and worst strategies reached 0.2 in the NSE, and the calibrated parameter values notably varied. The various calibration strategies satisfactorily predicted 7 to 13 out of 19 validation events. The two-stage strategies reproduced more validation events poorly (NSE <0) than the single-stage strategies, but they also reproduced more events well (NSE >0.5) and performed better than the single-stage strategies in terms of total runoff volume and peak flow rates, particularly when using a low spatial model resolution. The results show that various strategies for selecting calibration events may lead in some cases to different results in the validation phase and that calibrating impervious and green-area parameters in two separate steps in two-stage strategies may increase the effectiveness of model calibration and validation by reducing the computational demand in the calibration phase and improving model performance in the validation phase.

  • 4.
    Broekhuizen, Ico
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Leonhardt, Günther
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Marsalek, Jiri
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Viklander, Maria
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Selection of Calibration Events for Modelling Green Urban Drainage2019In: New Trends in Urban Drainage Modelling: UDM 2018 / [ed] Giorgio Mannina, Cham: Springer, 2019, p. 608-613Conference paper (Refereed)
    Abstract [en]

    Urban drainage models are often calibrated using a limited number of rainfall-runoff events, which may be selected in different ways from a longer observation series. This paper compares 13 different single- and two-stage strategies for selecting events used to calibrate a SWMM model of a predominantly green urban area. Most led to successful calibration, but performance varied for various validation events. Most selection strategies were insensitive to the choice of Nash-Sutcliffe Model Efficiency or Root Mean Squared Error as the objective function. Calibrating impervious and green area parameters separately in two-stage strategies can help improve prediction of low-flow events in validation.

  • 5.
    Broekhuizen, Ico
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Muthanna, Tone M.
    Norwegian University of Science and Technology, Trondheim, Norway.
    Leonhardt, Günther
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Viklander, Maria
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Urban drainage models for green areas: Structural differences and their effects on simulated runoff2019In: Journal of Hydrology X, ISSN 2589-9155, Vol. 5, article id 100044Article in journal (Refereed)
    Abstract [en]

    Mathematical stormwater models are often used as tools for planning and analysing urban drainage systems. However, the inherent uncertainties of the models must be properly understood in order to make optimal use of them. One source of uncertainty that has received relatively little attention, particularly for increasingly popular green areas as part of urban drainage systems, is the mathematical model structure. This paper analyses the differences between three different widely-used models (SWMM, MOUSE and Mike SHE) when simulating rainfall runoff from green areas over a 26-year period. Eleven different soil types and six different soil depths were used to investigate the sensitivity of the models to changes in both. Important hydrological factors such as seasonal runoff and evapotranspiration, the number of events that generated runoff, and the initial conditions for rainfall events, varied significantly between the three models. MOUSE generated the highest runoff volumes, while it was rather insensitive to changes in soil type and depth. Mike SHE was mainly sensitive to changes in soil type. SWMM, which generated the least runoff, was sensitive to changes in both soil type and depth. Explanations for the observed differences were found in the descriptions of the mathematical models. The differences in model outputs could significantly impact the conclusions from studies on the design or analysis of urban drainage systems. The amount and frequency of runoff from green areas in all three models indicates that green areas cannot be simply ignored in urban drainage modelling studies.

  • 6.
    Broekhuizen, Ico
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water. Luleå Tekniska Universitet.
    Muthanna, Tone Merete
    Norwegian University of Science and Technology.
    Leonhardt, Günther
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Viklander, Maria
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Model structure uncertainty in green urban drainage modelsManuscript (preprint) (Other academic)
    Abstract [en]

    Mathematical storm water models are often used as tools for planning and analysis of urban drainage systems, but the models’ inherent uncertainties need to be understood to make optimal use of them. One source of uncertainty that has received relatively little attention, especially for the increasingly popular green areas as part of urban drainage systems, is the choice of the mathematical model structure. This paper analyses the differences between three different widely-used models (SWMM, MIKE MOUSE and MIKE SHE) when simulating green areas over a 26 year period. A wide range of eleven different soil types and six different soil depths was used to investigate sensitivity of the models to changes in both. Important hydrological factors such as seasonal runoff and evapotranspiration, the number of events that generated runoff, and the initial conditions for rainfall events, varied strongly between the three models. MOUSE generated the highest runoff and was insensitive to changes in soil type and depth, while SHE was sensitive mainly to changes in soil type, and SWMM, which generated the least runoff, was sensitive to changes in both soil type and depth. Explanations for the observed differences were found in the descriptions of the mathematical models. The differences in model outputs could significantly impact the conclusions from design or analysis studies of urban drainage systems. The amount and frequency of runoff from green areas in all three models indicates that green areas cannot be simply ignored in urban drainage modelling studies.

  • 7.
    Broekhuizen, Ico
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Muthanna, Tone Murete
    Norwegian University of Science and Technology.
    Leonhardt, Günther
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Viklander, Maria
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Model structure uncertainty in urban drainage models for green areas2017In: 14th IWA/IAHR International Conference on Urban Drainage: Conference Proceedings, 2017, Prague, 2017, p. 1490-1494Conference paper (Refereed)
    Abstract [en]

    Two urban drainage models (SWMM and MOUSE) were used to study the impact of model structureuncertainty on long-term simulation of green areas. Depending on the soil profile being consideredsignificant differences were observed between the models, both on an annual and event basedscale. In general MOUSE generates more runoff and is more sensitive to changing soil depth. Thedifferences can be explained by the conceptual approaches used to model infiltration, which alsoaffects how much water is apportioned to evapotranspiration, surface runoff, and baseflow.

  • 8.
    Broekhuizen, Ico
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Rujner, Hendrik
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Roldin, Maria
    DHI Sweden.
    Leonhardt, Günther
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Viklander, Maria
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Towards using soil water content observations for calibration of distributed urban drainage models2019Conference paper (Refereed)
    Abstract [en]

    Fully distributed urban drainage models can be used to analyse and predict the behaviour of green urban drainage infrastructure such as swales, but they need to be calibrated for specific study sites. Using only drainage outflow measurements may not provide enough information to do this in an optimal way, so additional types of measurements have to be considered. This study identifies different approaches to including soil water content (SWC) observations in the calibration process and investigates how they affect parameter identifiability and the predictive uncertainty of the calibrated model. This is done using the Generalized Likelihood Uncertainty Estimation methodology applied to a model of a large urban swale. It was found that setting initial conditions based on the SWC measurements improved the fit between observed and simulated SWC, but also reduced the accuracy of the simulated amount of infiltration. Including SWC observations allowed to identify one parameter (saturated moisture content of the swale bottom) that was not identifiable from outflow measurements alone. Including SWC observations in the derivation of predictive uncertainty bounds made those bounds narrower (more precise), but where SWC had been used to set initial conditions the uncertainty bound failed to capture the observations. It is concluded that SWC observations can provide useful information for the calibration of distributed urban drainage models.

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