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RISS 인기검색어
- 검색키워드
- 저자 : Mallari, Kristine Joy B. (검색결과 10 건)
- 무료
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Mallari, K. J. B.,Kim, H.,Pak, G.,Aksoy, H.,Yoon, J. IWA Publishing 2015 Water Science & Technology Vol.71 No.9
<P>At the hillslope scale, where the rill-interrill configuration plays a significant role, infiltration is one of the major hydrologic processes affecting the generation of overland flow. As such, it is important to achieve a good understanding and accurate modelling of this process. Horton's infiltration has been widely used in many hydrologic models, though it has been occasionally found limited in handling adequately the antecedent moisture conditions (AMC) of soil. Holtan's model, conversely, is thought to be able to provide better estimation of infiltration rates as it can directly account for initial soil water content in its formulation. In this study, the Holtan model is coupled to an existing overland flow model, originally using Horton's model to account for infiltration, in an attempt to improve the prediction of runoff. For calibration and validation, experimental data from a two-dimensional flume which is incorporated with hillslope configuration have been used. Calibration and validation results showed that Holtan's model was able to improve the modelling results with better performance statistics than the Horton-coupled model. Holtan's infiltration equation, which allows accounting for AMC, provided an advantage and resulted in better runoff prediction of the model.</P>
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Considering the effect of groundwater on bioretention using the Storm Water Management Model
Kim, Hwansuk,Mallari, Kristine Joy B.,Baek, Jongrak,Pak, Gijung,Choi, Hyun Il,Yoon, Jaeyoung Elsevier 2019 Journal of environmental management Vol.231 No.-
<P><B>Abstract</B></P> <P>The Storm Water Management Model (SWMM), with its recently released low impact development (LID) module, is among several models used for the performance evaluation of LID facilities in reducing runoff and pollutants. Modeling is often difficult because of the variety of factors affecting the LID system. Among these factors, the effect of groundwater can be important in the LID modeling results due to the possibility of its interaction with LID. In this study, the performance of the SWMM-LID controls in predicting runoff from bioretention cells was evaluated for a site under groundwater influence. In addition, for considering the groundwater effect in the model, this study explores the utility of the SWMM groundwater model in predicting runoff under groundwater influence. Runoff from the considered watershed draining into the bioretention cells was well-simulated with very favorable performance statistic values (r<SUP>2</SUP> = 0.96, NSE = 0.94, % difference = 2.76). However, comparison of simulated with observed runoff from bioretention cells produced weaker statistical values (r<SUP>2</SUP> = 0.69, NSE = 0.65, % difference = 18.22), which is thought to be due to the presence of events affected by groundwater interference. Removal of these events and recalibration were able to improve the overall results, suggesting that the influence of groundwater should be taken into account for better LID modeling of the study site. In order to consider the groundwater influence, the SWMM groundwater model was used in tandem with LID controls to provide an additional influent source to bioretention cells. This resulted in a good fit for two events which were thought to be impacted by groundwater (events in which outflow exceeded inflow) and overall better performance (r<SUP>2</SUP> = 0.95, NSE = 0.95, % difference = 3.49) compared to the results obtained by using only LID controls. In conclusion, the SWMM groundwater model can help deal with groundwater-impacted events. However, for better representation of the phenomenon, the LID module itself needs to be improved to account for direct interaction with groundwater.</P> <P><B>Highlights</B></P> <P> <UL> <LI> We calibrated and validated a bioretention system under groundwater influence using SWMM LID control. </LI> <LI> Data used for calibration and validation was screened from International Stormwater BMP Database. </LI> <LI> The effect of groundwater was found to be negative on the outflow modeling results for the events with high antecedent moisture condition. </LI> <LI> The use of the SWMM's groundwater model was able to represent well the impact of groundwater on the outflow from bioretention. </LI> </UL> </P>
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Modelling of suspended sediment in a weir reach using EFDC model
Pak, Gijung,Mallari, Kristine Joy B.,Baek, Jongrak,Kim, Deokwoo,Kim, Hwansuk,Jung, Minjae,Kim, Young,Yoon, Jaeyoung IWA Publishing 2016 Water Science & Technology Vol.73 No.7
<P>Construction of hydraulic structures often leads to alteration of river dynamics and water quality. Suspended solids entering the upstream of the weir cause adverse effects to the hydroecological system and, therefore, it is necessary to build a modelling system to predict the changes in the river characteristics for proper water quality management. In this study, the discharges and total suspended solids upstream and downstream of the Baekje Weir installed in Geum River, Korea, was modelled using the environmental fluid dynamics code (EFDC) model. The resulting trend of four rainfall events shows that as rainfall increases, the total suspended solids (TSS) concentration increases as well. For the two larger events, at the upstream of the weir, TSS was observed to decrease or remain constant after the rainfall event depending on the lowering of the open gate. At the downstream, TSS supply was controlled by the weir during and after the rainfall event resulting in decline in the TSS concentration. The modelling produced good results for discharge based on % Diff. (4.37-6.35), Nash-Sutcliffe efficiency (NSE) (0.94-0.99) and correlation coefficient (r) (0.97-0.99) values as well as for TSS with acceptable values for % Diff. (12.08-14.11), NSE (0.75-0.81) and r (0.88-0.91), suggesting good applicability of the model for the weir reach of the river in the study site.</P>
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Assessing the significance of evapotranspiration in green roof modeling by SWMM
Limos, Aviva Gabriel,Mallari, Kristine Joy Bernardo,Baek, Jongrak,Kim, Hwansuk,Hong, Seungwan,Yoon, Jaeyoung IWA Publishing 2018 Journal of hydroinformatics Vol.20 No.3
<P>Green roof is a low impact development (LID) practice used to mitigate imperviousness in urban areas and to reduce flood risks. In order to have sufficient designs and accurate runoff predictions, computer models should be utilized with full understanding of green roofs' hydrologic processes. Evapotranspiration is usually considered important by researchers in the water balance modeling of a green roof. The Storm Water Management Model (SWMM) version 5.1 is widely utilized rainfall-runoff modeling software which has LID controls capable of modeling green roofs. A previous study has evaluated the performance of this model in green roof simulations for single events without considering evapotranspiration in its application, but attained negative outcomes. Thus, the objective of this study is to determine the significance of considering evapotranspiration in producing accurate runoff simulations specifically using SWMM 5.1. The results of this study have shown that when evapotranspiration was not considered, simulations failed to agree with observed values, whereas when evapotranspiration was considered, simulated runoff volumes attained a very good fit with the observed runoff volumes proving the significance of evapotranspiration as an important parameter in green roof modeling.</P>
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Performance Assessment of SWMM 5.1 Green Roof LID Control in Modeling Runoff
Aviva G. Limos,Kristine Joy B. Mallari,Jong-Rak Baek(백종락),Jae-Young Yoon(윤재영) 한국산학기술학회 2014 한국산학기술학회 학술대회 Vol.- No.-
Green roof is one of the emerging Low Impact Development (LID) technologies highly applicable in urban areas used to temporarily retain storm water. However, there are limited data available on their field performance. Thus, development of effective mathematical models is important to predict the runoff and evaluate the retention capacity of green roofs. The Storm Water Management Model (SWMM) is a widely utilized rainfall-runoff modeling software. It recently released its version 5.1 which includes green roof as a basic LID control and no study was found to evaluate it yet. Therefore, the goal of this study is to evaluate the performance of SWMM 5.1 Green Roof LID control in predicting runoff volume. The performance of sensitivity analysis showed that field capacity and wilting point are the most influential parameters that affect runoff volume. The highest NSE coefficient produced in the calibration was 0.508 which is considered unsatisfactory. This is due to the extreme overestimation in high runoff events. Further improvements involving factors affecting the drying of the substrate layer (e.g. evapotranspiration) are needed.
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Assessment of Metals Loading in an Acid Mine Drainage Watershed
Pak, G.,Jung, M.,Kim, H.,Mallari, K. J.,Chung, G.,Kim, S.,Kim, Y.,Oa, S.,Yoon, J. Springer Science + Business Media 2016 Mine water and the environment Vol.35 No.1
<P>Watershed-scale modeling can be useful in identifying the main environmental factors and the physical mechanisms responsible for acid mine drainage (AMD) formation, attenuation, and impacts. Since flow rates and water quality of the AMD and receiving streams are related to the rainfall-runoff relationship and associated contaminant dissolution, we thought that hydrologic analysis of the mined area and surrounding drainage basin should be the starting point in documenting the source and fate of AMD contaminants. Further modeling of AMD pollutants could then be performed in terms of metal concentrations and loading at the watershed scale. In this study, monitoring was conducted in the Geopung mine watershed; the watershed analysis risk management framework (WARMF) model was used to evaluate the effect of AMD contributions to downstream metal concentrations. The hydrologic model of the basin was calibrated and verified with rainfall and streamflow data, and the water quality model was calibrated for the dissolved concentrations of metals (Cd, Cu, Zn, and Pb), using discharge data gathered in 2009. There was a strong correlation (r = 0.93) between the observed and simulated runoff values plus high Nash-Sutcliffe model efficiency (NSE = 0.89) and low average percent difference between predicted and measured values (%Diff = 0.46). Subsequent model validation using data gathered in 2010 also showed good agreement (%Diff = 9.76; NSE = 0.77; r = 0.91) between the observed and simulated values. For the metals, the model was calibrated using data from 2010; the correlation between the observed and simulated values was quite good (r = 0.80-0.41).</P>
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Johnson Jesse A.,Kashka F. Mallari,Pepe Vincent M.,Treacy Taylor,McDonough Gregory,Khaing Phue,McGrath Christopher,George Brandon J.,Yoo Erika J. 대한중환자의학회 2023 Acute and Critical Care Vol.38 No.3
Background: There is increasing heterogeneity in the clinical phenotype of patients admitted to the intensive care unit (ICU) with coronavirus disease 2019 (COVID-19), and reasons for mechanical ventilation are not limited to COVID pneumonia. We aimed to compare the characteristics and outcomes of intubated patients admitted to the ICU with the primary diagnosis of acute hypoxemic respiratory failure (AHRF) attributed to COVID pneumonia with those of patients admitted for an alternative diagnosis.Methods: This was a retrospective cohort study of adults with confirmed severe acute respiratory syndrome coronavirus 2 infection admitted to one of nine ICUs between March 18, 2020, and April 30, 2021, at an urban university institution. We compared characteristics between the two groups using appropriate statistics and performed logistic regression to identify risk factors for death in the mechanically ventilated COVID-19 population. Results: After exclusions, the final sample consisted of 319 patients with respiratory failure secondary to COVID pneumonia and 150 patients intubated for alternative diagnoses. The former group had higher rates of ICU mortality (57.7% vs. 36.7%, P<0.0001) and hospital mortality (58.9% vs. 39.3%, P<0.0001). Patients with AHRF secondary to COVID-19 pneumonia also had longer lengths of stay in the ICU (12 vs. 6 days, P<0.0001) and hospital (20 vs. 13.5 days, P=0.0001). Following risk adjustment, these COVID-19 patients had 2.25 times greater odds of death (95% confidence interval, 1.42¬–3.56; P=0.001).Conclusions: Mechanically ventilated patients admitted to the ICU with COVID-19–associated respiratory failure are at higher risk of hospital death and have worse utilization outcomes than those whose reason for ICU admission is unrelated to COVID pneumonia.
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