Calibration Criteria Research Articles

Modelling an urban wastewater system via a space–time multivariate calibration to understand and improve water bodies quality

ABSTRACT The European Water Framework Directive requires good quality status for water bodies remaining solely attainable through a global approach. Urban wastewater integrated modelling is a promising tool for this purpose. However, certain barriers still hinder its application, such as the significant amount of data required and specifically in the sewer system, the issues with data quality or the monitoring and maintenance costs. This study develops an integrated model for Dijon Metropole in France using multiple hydraulic and quality data sources (e.g. sensors, analysers, laboratory measurements) and calibration criteria. The results show that long-term trends can be predicted for hydraulic and quality variables. The scenarios demonstrate that combined sewer overflows are responsible for most of the anoxic and ammonium high concentration periods in the rivers during rain events compared to the Water Resources Recovery Facility (WRRF). Therefore, adding storm tanks in the wastewater system will reduce stress on aquatic organisms during rainfall events. Reducing WRRF discharge during wet weather can also reduce the average and percentile of ammonium in the river. These results indicate that strategies should be adapted depending on the water quality objective (biological and/or physico-chemical) and the sensitivity of the organisms present in the river.

Dos & Don’ts in Measuring Illuminance With Smartphones

We explored the reliability of smartphones for measuring illuminance and discussed their use on occupational lighting assessments. In a 20–1000 lux range, we compared the illuminance readings from three Android applications on two smartphones versus a calibrated illuminance meter, and proposed seven calibration criteria. Mean non-calibrated smartphone measurements ranged between 28.36% and 37.58% above the reference illuminance. Two calibration criteria stood out: (i) single correction factor at the mean illuminance level (relative difference = 0.84%); (ii) power function (relative difference = −0.17%). We can state that properly calibrated smartphones might replace a low-end illuminance meter, and provide practical tips for measuring illuminance with smartphones.

Caries experience in children with molar-incisor hypomineralisation in Fujairah, United Arab Emirates and its association with hypomineralised teeth number.

Molar-incisor hypomineralisation (MIH) has been found associated with an increase in dental caries. Studies utilising the recent MIH diagnosis and calibration criteria recommended by the EAPD in 2021 are very scarce. Additionally, the available data in literature about the relationship between the hypomineralised teeth number (HTN) and caries come from only one study. To assess the relationship between MIH and caries experience among children in the city of Fujairah, UAE, utilising the recent criteria recommended by the European Academy of Paediatric Dentistry (EAPD) in 2021, and to assess the relationship between the number of teeth affected with MIH, and dental caries. One hundred and sixty-two children were included in this cross-sectional study, aged 7-9years old. Children were examined for MIH according to Ghanim et al. (Eur Arch Paediatr Dent 16:235-246, 2015. 10.1007/s40368-015-0178-8) criteria and Ghanim et al. (Eur Arch Paediatr Dent 18:225-242. 10.1007/s40368-017-0293-92017) training manual. Caries experience was assessed with decayed, missing, filled (dmft, DMFT) scoring system. dmft mean was 6.56 (SD ± 3.78) and DMFT mean was 0.91 (SD ± 1.23). Children with MIH had significantly higher dmft (p = 0.003) scores. Children with higher HTN had significantly higher dmft (p = 0.008) scores. Children in Fujairah have extremely high caries scores. Children with MIH have more decayed, missing and filled teeth. Hypomineralised teeth number was positively associated with caries experience.

Improving glacio-hydrological model calibration and model performance in cold regions using satellite snow cover data

Hydrological modeling realism is a central research question in hydrological studies. However, it is still a common practice to calibrate hydrological models using streamflow as a single hydrological variable, which can lead to large parameter uncertainty in hydrological simulations. To address this issue, this study employed a multi-variable calibration framework to reduce parameter uncertainty in a glacierized catchment. The current study employed multi-variable calibration using three different calibration schemes to calibrate a glacio-hydrological model (namely the FLEXG) in northern Sweden. The schemes included using only gauged streamflow data (scheme 1), using satellite snow cover area (SCA) derived from MODIS data (scheme 2), and using both gauged streamflow data and satellite SCA data as references for calibration (scheme 3) of the FLEXG model. This study integrated the objective functions of satellite-derived SCA and gauged streamflow into one criterion for the FLEXG model calibration using a weight-based approach. Our results showed that calibrating the FLEXG model based on solely satellite SCA data (from MODIS) produced an accurate simulation of SCA but poor simulation of streamflow. In contrast, calibrating the FLEXG model based on the measured streamflow data resulted in minimum error for streamflow simulation but high error for SCA simulation. The promising results were achieved for glacio-hydrological simulation with acceptable accuracy for simulation of both streamflow and SCA, when both streamflow and SCA data were used for calibration of FLEXG. Therefore, multi-variable calibration in a glacierized basin could provide more realistic hydrological modeling in terms of multiple glacio-hydrological variables.

In-situ empirical validation of common indoor climate parameters in an inhabited multizone dwelling

Combined building indoor climate and energy simulation models only recently gained vast popularity and their application has been moving from the research community to a broader audience. Yet, in-situ empirical validation of this new generation of complex multi-purpose dynamic simulation models has lagged behind. Using a dynamic multizone building indoor climate and energy simulation model in Modelica with the IDEAS library and buoyancy driven airflow components (validated with CONTAM), this research presents model validation results and lessons learned from an in-situ empirical validation study of common indoor climate parameters (i.e., indoor air temperature (), relative humidity (RH) and CO2 concentration (CO2)) for an inhabited and mechanically ventilated case study dwelling in The Netherlands. The simulation results show that the latest generation of building indoor climate and energy models in Modelica have great ability to accurately predict common indoor climate parameters in multizone inhabited dwellings (provided that user behavior info is available). Evaluation metrics for the three studied parameters show excellent calibration criteria (i.e., MAE between 0.60–0.78 °C (), 3.5–4.6% (RH) and 88–181 ppm (CO2)) and the accompanying graphs corroborate the findings. In the event that no motion sensor data is available, statistically generated occupancy profiles prove good representative alternatives on the condition that basic info is available about the number of inhabitants and the inhabitants’ lifestyle. In-situ monitoring for empirical model validation proves to be a real challenge full of (un)foreseen obstacles.

Exploring parameter (dis)agreement due to calibration metric selection in conceptual rainfall–runoff models

ABSTRACT We examine the extent to which the parameters of different types of catchments are sensitive to calibration criteria selection (i.e. parameter agreement), and explore possible connections with overall model performance and model complexity. To this end, we calibrate the lumped GR4J, GR5J and GR6J hydrological models – coupled with the CemaNeige snow module – in 95 catchments spanning a myriad of hydroclimatic and physiographic characteristics across Chile, using 12 streamflow-oriented objective functions. The results show that (i) the choice of objective function has smaller effects on parameter values in catchments with low aridity index and high mean annual runoff ratio, in contrast to drier climates; and (ii) catchments with better parameter agreement also provide better performance across model structures and simulation periods. More generally, this work provides insights on the type of catchments where it is more challenging to find sub-domains in the parameter space that satisfy multiple streamflow criteria.

Preliminary study of thermography applied to diagnosed faults in Diesel Engine and network rack

In this study, we applied thermographic analysis to gather data and establish decision criteria for the corrective maintenance of electrical and mechanical systems. Our main objective is to generate a thermographic database for systems such as combustion engines and network racks. To achieve this, we conducted preliminary experiments on electrical and mechanical systems with known faults. We also established calibration criteria for the thermal emissivity of the components. Subsequently, we analyzed a Diesel engine with induced faults, obtaining the maximum temperature threshold in malfunctioning components, as well as emissivity values. Additionally, we carried out an analysis on a network rack, specifically a 48-node Patch, with constant and intermittent connection faults. Our methodology included analyzing the transience of the mentioned systems to identify patterns indicating wear, malfunction, or damage. The collected data allowed us to create a database and perform calibration for effective emissivity

Research on Employee Voice Intention: Conceptualization, Scale Development, and Validation Among Enterprises in China.

Expressing opinions and ideas in the workplace is an important aspect of organizational development and employee well-being. However, employee voice intention, which refers to an employee's willingness to share their opinions or ideas, is an area that has received limited attention in research. Therefore, the aim of this study was to develop and validate a reliable measurement tool for employee voice intention. The study followed a three-stage process. First, in-depth interviews were conducted with managers and employees from Chinese companies, resulting in 38 qualitative data points. Second, the employee voice intention scale was developed and validated through two surveys. Exploratory factor analysis (N=264) and confirmatory factor analysis (N=260) were performed, respectively. Third, the predictive validity of the scale was assessed by collecting 366 valid responses across three rounds of questionnaires, using voice efficacy and employee voice behavior as correlational calibration criteria. The study employed grounded theory methodology to analyze the qualitative data collected, resulting in the development of a robust conceptual framework of employee voice intention. This framework is composed of two dimensions: perceived desirability and perceived feasibility, which together capture the key factors that influence whether an employee will express their opinions or ideas within an organizational context. A corresponding measurement scale was developed, consisting of nine measurement items that underwent rigorous testing to ensure their reliability and validity. Furthermore, the results of the empirical study showed that employee voice intention mediated the positive effect of voice efficacy on voice behavior, supporting the scale's predictive validity. This study provides valuable insights into the dimensions of employee voice intention and contributes significantly to the existing literature on this topic by introducing a reliable and valid measurement tool. Furthermore, it advances our understanding of the underlying dimensions associated with this construct.

Efficient Calibration of Groundwater Contaminant Transport Models Using Bayesian Optimization.

Numerical modeling is a significant tool to understand the dynamic characteristics of contaminants transport in groundwater. The automatic calibration of highly parametrized and computationally intensive numerical models for the simulation of contaminant transport in the groundwater flow system is a challenging task. While existing methods use general optimization techniques to achieve automatic calibration, the large numbers of numerical model evaluations required in the calibration process lead to high computing overhead and limit the efficiency of model calibration. This paper presents a Bayesian optimization (BO) method for efficient calibration of numerical models of groundwater contaminant transport. A Bayes model is built to fully represent calibration criteria and derive the objective function for model calibration. The efficiency of model calibration is made possible by the probabilistic surrogate model and the expected improvement acquisition function in BO. The probabilistic surrogate model approximates the computationally expensive objective function with a closed-form expression that can be computed efficiently, while the expected improvement acquisition function proposes the most promising model parameters to improve the fitness to the calibration criteria and reduce the uncertainty of the surrogate model. These schemes allow us to find the optimized model parameters effectively by using a small number of numerical model evaluations. Two case studies for the calibration of the Cr(VI) transport model demonstrate that the BO method is effective and efficient in the inversion of hypothetical model parameters, the minimization of the objective function, and the adaptation of different model calibration criteria. Specifically, this promising performance is achieved within 200 numerical model evaluations, which substantially reduces the computing budget for model calibration.

Groundwater Assessment using Numerical Flow Model: A Case Study in Gash Sub-Basin-Kassala State, Sudan

The main objective of groundwater modelling in Gash River Sub-basin, is to investigate the effect of hydrologic, hydrogeological parameters and stresses on hydrodynamic behaviour through the implementation of a realistic three-dimensional groundwater flow model. Severe decline of water level due to uncontrollable heavy abstraction, exposes a water scarcity problem especially in summer seasons. The model was developed for four geological layers encompassing two aquifer zones. The improved three-dimensional visual MODFLOW Code was selected, implemented and run using WHS method to solve the finite difference equation using trail-and-error calibration procedure at Kassala Area. The transient model was successfully calibrated with acceptable results of model calibration criteria. The contour maps of the simulated heads were performed as potentiometric surface. The general flow direction of the groundwater is from southeast towards northwest part of the area and from Gash River course towards the east and west directions as detected from gradual decreasing of potential line’s values in those directions, confirming the aquifer recharge from Gash River. The similarity of potentiometric surface contour maps of the two aquifers confirm the aquifers hydraulic interactions. It is found that the increasing pumping rate caused considerable increase in drawdown as detected from pumping rate incremental scenarios. Moreover, incremental pumping rate scenarios also reflected increasing river leakage into the aquifer system due to disturbance of water balance due to water level decline. The components of water budgets were calculated and its percentage was performed for the hydrologic balance. The difference between inflow and outflow of the water balance shows a deficit in most stress periods of the model simulations. Calibration fitness was accomplished at most of the observation wells suggesting that the groundwater model is an accurate representation of the actual historic groundwater system and confirm the validity of the model to forecasting purposes. It was found that the model is more sensitive to hydraulic conductivity and least sensitive to specific yield (Sy). Hence, precaution should be revealed for hydraulic conductivity in forecasting model usage.

Generation Mechanism and Decoupling Strategy of Coupling Effect in Maglev Planar Motor

Magnetically levitated (maglev) planar motor is a promising precision motion system in industry. In order to address the issue of coupling effect in maglev planar motor and achieve satisfying precision motion performance, a novel decoupling strategy based on generation mechanism of coupling effect is proposed in this article. Detailed modeling process is first provided including wrench modeling, coordinates transformation, and control allocation. Further theoretical analysis proves that coupling effect caused by certain factors can be observed by specific phenomena which can be utilized as a criterion for calibration. An effective synthesized decoupling strategy is then proposed. In comparative experimental investigation, the practical phenomena are consistent with the prediction by the proposed theoretical analysis. After applying the proposed decoupling strategy, the tracking errors in the affected axes are enormously reduced and the coupling effect is eliminated to a great extent. Achieved by simply observing specific phenomena, the proposed decoupling method for maglev planar motor is actually a meaningful supplement to existing baseline to further calibrate certain factors that are not considered in previous methods.

Impact of snow distribution modelling for runoff predictions

AbstractSnow in the mountains is essential for the water cycle in cold regions. The complexity of the snow processes in such an environment makes it challenging for accurate snow and runoff predictions. Various snow modelling approaches have been developed, especially to improve snow predictions. In this study, we compared the ability to improve runoff predictions in the Överuman Catchment, Northern Sweden, using different parametric representations of snow distribution. They included a temperature-based method, a snowfall distribution (SF) function based on wind characteristics and a snow depletion curve (DC). Moreover, we assessed the benefit of using distributed snow observations in addition to runoff in the hydrological model calibration. We found that models with the SF function based on wind characteristics better predicted the snow water equivalent (SWE) close to the peak of accumulation than models without this function. For runoff predictions, models with the SF function and the DC showed good performances (median Nash–Sutcliffe efficiency equal to 0.71). Despite differences among the calibration criteria for the different snow process representations, snow observations in model calibration added values for SWE and runoff predictions.

Whitecapping term analysis of extreme wind wave modelling considering spectral characteristics and water depth

The Simulating WAves Nearshore (SWAN) model can be used to simulate extreme wind waves such as tropical cyclone waves, which are of great significance for the study of coastal processes and the protection of coastal engineering. In this study, the basic setting and whitecapping term of the SWAN model are analysed to model tropical cyclone waves, with spectral characteristics and water depth taken into account. By investigating the temporal variation of bulk wave parameters and wave spectral characteristics of key nodes, the optimal values of 4 basic setting parameters are determined. By analysing the sensitivity of tuning effects of key coefficients in different whitecapping formulations, calibration criteria of these parameters are provided, and the coefficients Stpm and Powk in the Komen formulation are found to be most sensitive to the outputted significant wave height and mean wave period, respectively. To further study the sensitivity of these coefficients, especially their relationship with water depth, spatial analyses of sensitivity variations are performed in the coastal region, which show that the sensitivity of these coefficients increases first and then tends to be stable with the increase of water depth, indicating a critical water depth between 20 m and 50 m. This study provides insights for more effective and directional modelling of tropical cyclone waves in coastal and shelf seas.

Novel fluorescence spectroscopy coupled with PARAFAC modeling for major cannabinoids quantification and identification in cannabis extracts

Cannabinoids are commonly identified and quantified using chromatographic based methods. In the present study, fluorescence spectroscopic method coupled with Parallel Factor Analysis (PARAFAC) modeling was developed and validated as a simple and fast alternative technique for identification and quantification of major cannabinoids. A PARAFAC model was built on a set of excitation-emission matrices, yielding an optimal quantitative and qualitative performance using five components, which were identified as (-)-Δ9-trans-tetrahydrocannabinolic acid (THCA), cannabidiolic acid (CBDA), cannabigerolic acid (CBGA), cannabichromenic acid (CBCA) and (-)-Δ9-trans-tetrahydrocannabinol/cannabidiol/cannabigerol (THC/CBD/CBG). The identity of the major acidic components, THCA, CBDA and CBGA was verified by the correlation between PARAFAC model scores and their corresponding concentrations measured by HPLC as well as by the similarity between the excitation-emission spectral loadings of each PARAFAC component and the excitation-emission spectra of pure cannabinoids standards. Moreover, the PARAFAC model scores of each component were plotted against the cannabinoids actual concentrations in the extracts to evaluate the performance of the model for predicting the concentration of each compound. All three major acidic cannabinoids revealed good to excellent linear correlations (R2 > 0.7) between the model scores and measured concentrations according to the model calibration, cross-validation and prediction performance criteria. On the other hand, components 4 and 5 identified as CBCA and THC/CBD/CBG, respectively, revealed weaker linear correlation between the PARAFAC scores to the measured concentrations. These findings pave the way for a more comprehensive assessment of cannabis excitation-emission matrices (EEMs) as a cheaper and fast alternative for commonly used chromatographic-based quantification methods.

LBSUN214 Accuracy Of A Continuous Glucose Monitor In The Intensive Care Unit

Abstract Studies have shown that hyper/hypoglycemia and glycemic variation are associated with adverse outcomes in critically ill patients. Currently, frequent blood point-of-care (POC) glucose measurements from an arterial or capillary sample is the only technology available to minimize glycemic excursions in the ICU. Continuous glucose monitoring (CGM) is becoming the standard of care for outpatient diabetes care and has shown improved glycemic control in the non-ICU inpatient setting. The Dexcom G6 sensor (G6) is the first CGM device approved by Health Canada for outpatient diabetes management without the need for calibration, but it has not yet been approved for inpatient use. We collected data from 23 adults who were on an insulin infusion in a medical-surgical ICU in Vancouver, British Columbia to evaluate the accuracy of uncalibrated CGM in the ICU. A blinded G6 was attached to the patient's arm and collected glucose measurements every five minutes without calibration. Nursing staff continued POC arterial glucose measurements using the AccuChek Inform II machine per standard of care. Excluding four outliers (with mean absolute relative difference (MARD) ≥ 25%), the overall MARD was 13.24% (SE 0.43) over 649 matched CGM and arterial glucose values. A Clarke Error Grid demonstrated 99.1% of CGM measurements within zones A and B. The MARD using three-point rolling averages of CGM measurements in five-minute intervals was 13.49% (SE 0.68). There were 573 matched pairs between glucose ranges of 3.9-13.9 mmol/L with two pairs <3.9 and 74 pairs >13.9 mmol/L. Eleven patients had renal replacement therapy and twelve had vasopressor use. There was no significant difference in MARD with renal replacement or across glycemic ranges ≥3.9. The MARD for patients with vasopressors was lower than for patients without (13% vs 13.55%, p<0. 01), a finding of doubtful clinical relevance. There is no expert agreement yet about the acceptable accuracy for CGM use in hospital. Our overall MARD meets the 2013 Critical Care expert consensus recommendations for MARD <14%. The FDA guidance on standard of accuracy for conventional POC glucometers require 98% of values within 15% for BG ≥ 75mg/dL. Our data showed 65.18% of values were within 15%. Previous studies using CGM in the ICU, even those using G6, all used calibration. The majority were non-blinded, and none met FDA criteria for inpatient use. Our study is the first uncalibrated and blinded study that was able to demonstrate acceptable accuracy in a large sample size. Since CGM accuracy may be affected by various factors, our comprehensive data can potentially identify specific interferences and quantify a calibration or correction criteria to improve CGM accuracy in critically ill patients. Overall, our results show that CGM shows strong potential to be an accurate, resource-efficient, and intuitive alternative to POC glucose monitoring to meet glycemic targets in the ICU. Presentation: Sunday, June 12, 2022 12:30 p.m. - 2:30 p.m.

The effects of antecedent dry days and land use types on urban runoff quality in a semi-Arid region

ABSTRACT This study simulated the effects of land-use changes on runoff pollution in a catchment of Tehran, Iran. The catchment has a semi-arid climate, a relatively long period from dry summer to rainy autumn and highly varying precipitation levels. Urban runoff samples were collected from six stations including five different land-based activities and a mixed land-use, which supported all land-use types. Event Mean Concentration (EMC) was applied to determine the Nonpoint Source (NPS) pollution of urban runoff such as Total Suspended Solid (TSS), Total Nitrogen (TN), Total Phosphorus (TP) and heavy metals, including zinc (Zn), copper (Cu) and lead (Pb), in five land-uses. Sampling was performed during five events with different Antecedent Dry Days (ADDs) in time period 2019-2020. The Storm Water Management Model (SWMM) was employed to simulate the quality of urban runoff base on measured EMCs in each event for the different parameters under investigation and the average of measured EMCs. The results illustrated that that the maximum and minimum amount of EMCs were pertained to the events with 115 and 1 dry days respectively. While, daily simulation of runoff pollution based on measured amount of EMCs in the catchment indicated that the calibration criteria such as Root Mean Square Error (RMSE), Normalized Objective Function (NOF), Nash-Sutcliffe Efficiency (NSE) and R 2 were very good for the minimum amount of EMCs and satisfactory for the average of EMC`s calculated, NSE values was not satisfactory for the maximum amount of EMCs. Uncertainty of ADDs can significantly affect the results of the maximum EMC simulation. This study also found higher TSS and TP concentrations in runoff in open space land-use and significantly higher heavy metals and TN concentrations in runoff in the industrial land-use compared with other land-use types in the catchment.

A northeast United States Atlantis marine ecosystem model with ocean reanalysis and ocean color forcing

The northeast United States Atlantis model (NEUSv2) is an end-to-end ecosystem model that can simulate biogeochemical, ecological, fishery, management, and socio-economic processes within marine ecosystems. As a major update to the original model, NEUSv2 includes changes to the model's functional group definitions and forcing data. NEUSv2 is the first Atlantis model to use a satellite-ocean-color-derived phytoplankton size class model that was tuned specifically for the region to force marine primary production. Additionally, physical ocean variables (currents, temperature, and salinity) were updated using a high-resolution global ocean reanalysis. Despite its coarse resolution, NEUSv2 was capable of reproducing the broad spatial patterns seen in the physical and biological forcing sources, with the exception of some circulation features. NEUSv2 produced plausible zooplankton and planktivore biomass, a stable lower trophic food web, and recent trends in zooplankton biomass. NEUSv2 meets calibration criteria for the persistence and long-term stability of functional group biomass. Given the success of this new Atlantis forcing approach, we detail the observations and challenges regarding spatial scale-related processes, data assimilation, and biological calibration. We also discuss possible tradeoffs with model scope, calibration, and the availability of feedback mechanisms. This NEUSv2 hindcast is well suited for exploring ecosystem-level sensitivity to lower trophic processes and for testing alternative biogeochemical forcing. Further developments will improve model performance for higher trophic levels.

Implicitization of the Vegter Yield Criterion

An advanced yield criterion plays a central role in rate-independent plasticity modeling of sheet metals in automotive and other industrial applications. Different from many non-quadratic yield criteria based on implicit polynomials, Vegter yield criterion is piecewise and quadratic as it is originally constructed by interpolation of several biaxial stress states using multiple second-order Bézier curves. Additional efforts in recent years have made Vetger yield criterion more user-friendly, flexible and robust for sheet metal forming applications. Nevertheless, Vetger yield criterion has only been presented in its parametric formulation in the literature. This work describes a method of reformulating the existing Vetger Lite yield criterion into the implicit form that is more commonly used in the conventional sheet metal plasticity modeling. The potential benefits of using both the original parametric and the new implicit forms of Vegter yield criterion for material parameter calibration, convexity certification, and computational simulations are discussed.

Calibration problems with the ASTM E108 fire test

AbstractResults obtained from two accredited laboratories that regularly conduct ASTM E108 fire tests showed serious discrepancies. The source of the problem was identified to be errors in the ASTM E108 standard instructions for calibration of the fire test apparatus. The standard requires that the apparatus calibration achieve three criteria—two quantitative and one qualitative criteria. The quantitative calibration criteria include measurement of a specified wind speed across the calibration deck surface and measurement of a specified flame temperature at the leading edge of the calibration deck. The qualitative criterion is the specification of a required flame shape above the calibration deck surface that is determined by observation rather than measurement. From an engineering control standpoint, this problem has only two independent variables (air flow rate and fuel flow rate), so there can be no more than two control points, but the standard specifies three (air flow rate, flame temperature, and flame size). This is an example of an over‐constrained problem where a unique solution cannot be obtained, which satisfies all the constraints. It is suggested that the test standard be revised to eliminate this conflict. It is further suggested that the ASTM E108 calibration procedure be revised to control the burner heat release rate instead of controlling the flame temperature and flame size.

Urban Flood Modeling of a Partially Separated and Combined Drainage System in the Grefsen Basin in Oslo, Norway

The Storm Water Management Model (SWMM) has been globally used for stormwater management. However, the calibration and evaluation of SWMM for historical rainfall–runoff events in partially separated and combined drainage systems is rarely reported in Norway. In this study, we employed SWMM for the Grefsen catchment in Oslo, Norway. The main problem in the Grefsen basin is combined sewer overflow. We calibrated the model parameters based on 32 rainfall–runoff events and evaluated the calibrations using four indicators: Nash–Sutcliffe efficiency, percentage bias, and continuity errors for runoff and flow. There were 32 successful calibrations using Nash–Sutcliffe efficiency, 30 successful calibrations using percentage bias, 32 successful calibrations using continuity error runoff, and four successful calibrations using continuity error flow. SWMM can well simulate the dynamics of hydrological and hydraulic systems in this catchment. Among the 124 validations, there were 88 successful simulations using Nash–Sutcliffe efficiency, 35 successful simulations using percentage bias, 124 successful simulations using continuity error for runoff, and 62 successful simulations using continuity error for flow. The results show that percentage bias and continuity error flow are the critical indicators for model calibration. This study reveals the large uncertainty caused by calibration and validation criteria, and highlights the importance of considering model computation error.