Sensitivity of Model-Based Water Balance to Low Impact Development Parameters

Leimgruber, Johannes; Krebs, Gerald; Camhy, David; Muschalla, Dirk

doi:10.3390/w10121838

Cited by 36 publications

(36 citation statements)

References 26 publications

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“…For the uncalibrated model, the default parameter values from the literature review were applied [21,29]. Simulation and observation show similar patterns in terms of timing and variability of the time series, but the simulation overestimates the runoff.…”

Section: Model Run With Default Parametersmentioning

confidence: 99%

“…Niazi et al [20] conclude that, overall, EPA SWMM can be used as a flexible tool for simulating urban hydrology, but special attention should be paid to the current gaps within the model, for instance, the lack of guidance on parameter estimation, sensitivity analysis and calibration, especially while considering LID structures for water-quality simulations. Moreover, storm event-based simulations on green roofs show that water availability in the soil becomes the most important aspect for ET processes and, thus, a good estimate on the antecedent dry period should be calculated [21].…”

Section: Introductionmentioning

confidence: 99%

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Robust Vegetation Parameterization for Green Roofs in the EPA Stormwater Management Model (SWMM)

et al. 2021

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In increasingly expanding cities, roofs are still largely unused areas to counteract the negative impacts of urbanization on the water balance and to reduce flooding. To estimate the effect of green roofs as a sustainable low impact development (LID) technique on the building scale, different approaches to predict the runoff are carried out. In hydrological modelling, representing vegetation feedback on evapotranspiration (ET) is still considered challenging. In this research article, the focus is on improving the representation of the coupled soil–vegetation system of green roofs. Relevant data to calibrate and validate model representations were obtained from an existing field campaign comprising several green roof test plots with different characteristics. A coupled model, utilizing both the Penman–Monteith equation to estimate ET and the software EPA stormwater management model (SWMM) to calculate the runoff, was set up. Through the application of an automatic calibration procedure, we demonstrate that this coupled modelling approach (Kling–Gupta efficiency KGE = 0.88) outperforms the standard ET representation in EPA SWMM (KGE = −0.35), whilst providing a consistent and robust parameter set across all green roof configurations. Moreover, through a global sensitivity analysis, the impact of changes in model parameters was quantified in order to aid modelers in simplifying their parameterization of EPA SWMM. Finally, an improved model using the Penman–Monteith equation and various recommendations are presented.

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Section: Model Run With Default Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust Vegetation Parameterization for Green Roofs in the EPA Stormwater Management Model (SWMM)

et al. 2021

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“…However, nowadays, the design consideration of the SWMFs has shifted towards the water balance and stream health. The primary purpose of the SWMF is to maintain the streams of a watershed to its predevelopment condition (Damodaram et al 2010;Krebs 2017;Leimgruber et al 2018;Li et al 2017). Since the early 1990s, the treatment train approach has been suggested, which combines lot level, conveyance, and end of pipe SWMFs as a line of the last defence.…”

Section: Stormwater Management Facilities (Swmf)mentioning

confidence: 99%

Development of a Multi-Scale Stormwater Management Modelling Methodology

Haque¹

2021

Preprint

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The evaluation process of the land development project becomes complicated, as the simulation results of Fine-Scale Models (FCM) of lands proposed for development cannot be easily transferred to the watershed Coarse-Scale Models (CSM) due to parameterization problem. In this research study, a Multi-Scale Modelling (MSM) methodology was developed to minimize the difficulty in transferring the result into the different spatial scales of the models. The developed MSM methodology was tested on Ganatsekiagon Creek’s sub-watershed, simulating several scenarios. The analyses of model results show that the CSM is generating a lower Peak Flow Rate (PFR) and Flow Volume (FV) than the MSM, while the increasing level of development with BMPs leads to a rise in FV and a decrease in PFR. The comparison results of with and without BMPs show that the stormwater management ponds are effective in PFR reduction and the implementation of LID practices can be effective in FV reduction.

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“…The earliest water quality reduces pavement performance, but permeable asphalt implementation provides better results. Leimgruber et al [20] studied the impact of the installation of 3 LIDs on the water balance using long-term simulation. They wanted to provide the influential parameters list to practitioners.…”

Section: Introductionmentioning

confidence: 99%

Urban Drainage Networks Rehabilitation Using Multi-Objective Model and Search Space Reduction Methodology

2019

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The drainage network always needs to adapt to environmental and climatic conditions to provide best quality services. Rehabilitation combining pipes substitution and storm tanks installation appears to be a good solution to overcome this problem. Unfortunately, the calculation time of such a rehabilitation scenario is too elevated for single-objective and multi-objective optimization. In this study, a methodology composed by search space reduction methodology whose purpose is to decrease the number of decision variables of the problem to solve and a multi-objective optimization whose purpose is to optimize the rehabilitation process and represent Pareto fronts as the result of urban drainage networks optimization is proposed. A comparison between different model results for multi-objective optimization is made. To obtain these results, Storm Water Management Model (SWMM) is first connected to a Pseudo Genetic Algorithm (PGA) for the search space reduction and then to a Non-Dominated Sorting Genetic Algorithm II (NSGA-II) for multi-objective optimization. Pareto fronts are designed for investment costs instead of flood damage costs. The methodology is applied to a real network in the city of Medellin in Colombia. The results show that search space reduction methodology provides models with a considerably reduced number of decision variables. The multi-objective optimization shows that the models’ results used after the search space reduction obtain better outcomes than in the complete model in terms of calculation time and optimality of the solutions.

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Sensitivity of Model-Based Water Balance to Low Impact Development Parameters

Cited by 36 publications

References 26 publications

Robust Vegetation Parameterization for Green Roofs in the EPA Stormwater Management Model (SWMM)

Robust Vegetation Parameterization for Green Roofs in the EPA Stormwater Management Model (SWMM)

Development of a Multi-Scale Stormwater Management Modelling Methodology

Urban Drainage Networks Rehabilitation Using Multi-Objective Model and Search Space Reduction Methodology

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