Simulation of Urban Drainage System Using Disaggregated Rainfall Data

Rangari, Vinay Ashok; Gopi, K. Veerendra; Umamahesh, N. V.; Patel, Ajey Kumar

doi:10.1007/978-981-10-5801-1_10

Cited by 6 publications

(6 citation statements)

References 17 publications

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“…The field survey is used to estimate all physical parameters in this analysis. Rangari et al (2018) divided the study area into nine sub basins by considering the drainage line. The same methodology has followed in the current study.…”

Section: Resultsmentioning

confidence: 99%

“…The first computerised models of urban storm drainage were created in the late 1960s, and various models have been used since then (Zoppou, 2001;Mitchell, 2001). Design models, flow prediction models, and planning models are the three types of models (Rangari et al, 2016, Hunter et al, 2007. Modelling of urban floods became simpler with the implementation of Graphical User Interface (GUI) software such as SWMM, HEC-HMS, HEC-RAS, MIKE FLOOD, and others.…”

Section: Introductionmentioning

confidence: 99%

“…In densely urbanised catchments, the most significant variables in the study area are land use and land cover (Patil and Chaudhary, 2014). Flood modelling is primarily used to investigate all facets of flood in the urban environment, including the effects of heavy rainfall on the drainage of urban sub-catchments and the different socio-economic aspects of the flood ( Rangari et al, 2018). It was using the US EPA's Storm Water Management Model in a metropolitan setting using an RS and GIS-based solution.…”

Section: Introductionmentioning

confidence: 99%

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Runoff assessment by Storm water management model (SWMM)- A new approach

Vidya

2021

JANS

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The present study investigated the storm wise runoff collected in farm pond with the runoff estimated by Storm Water Management Model (SWMM) and Soil Conservation Service (SCS-CN) models. The SWMM and SCS-CN models estimated runoff depth storm wise. The runoff depths correspond to the catchment area given the runoff volume from the catchment. The runoff depth estimated from the Storm Water Management Model and Soil Conservation Service model was compared against the depth of runoff estimated from the Water balance model. For small rainfall depths, the runoff estimated from the Storm Water Management Model was at par with the actual runoff volume stored at the pond. It is necessary to know the watershed runoff contribution to the river or streams due to rainfall in order to determine environmental risk or flood potential. In larger rainfall depth, the runoff volume estimated from the SWMM model was less than the stored runoff volume at Farm Pond. The Soil Conservation Service Model gave better results for larger rainfall depth compared to Storm Water Management Model. SWMM was able to simulate runoff depth for small rainfall depths of 2mm. The peak runoff depths were produced by rainfall depths of 35.5mm. Initial abstractions of the study area for antecedent moisture content i.e. AMC I, AMCII and AMCIII are 53.2, 23.91 and 10.43mm, respectively. The comparison showed that both SWMM and SCS-CN models gave better runoff quantification results.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Runoff assessment by Storm water management model (SWMM)- A new approach

Vidya

2021

JANS

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“…Again flooding of streets affects the traffic system and day-to-day life. Hyderabad-2000, Ahmedabad-2001, Delhi-2002, 2003, 2009, Chennai-2004, Mumbai-2005, Surat-2006, Kolkata-2007, Jamshedpur-2008, Guwahati-2010and Srinagar-2014(Rafiq et al, 2016Rangari et al, 2016). The most recent devastating ones are Chennai-2015, Hyderabad-2016and Kerala-2018 Avoiding Such events is not promising but hydrologic modeling will help us in understanding of process and develop combat strategies to deal with it.…”

Section: Corresponding Authormentioning

confidence: 99%

1d-2d Modeling of Urban Floods and Risk Map Generation for the Part of Hyderabad City

Rangari

Gonugunta

Umamahesh

et al. 2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> Space for water is now becoming guiding principle of urban planning because urban flooding is the major problem facing by most of the cities in India. Urban development in developing countries like India usually occurs with high population concentrating in small areas, with poor drainage conditions. People occupy floodplain areas in low flood years and when larger flood occurs it causes high damage. The origin for urban floods is floodplains encroachment and unplanned drainage systems. Complexities in the urban environment and drainage infrastructure have an inherent influence on surface runoff. This runoff generates urban flooding which poses challenges to modeling urban flood hazard and risk. As like in river flooding satellite images are not available for unban flooding scenario. So better modelling provides minimizing loss of life and property. The present study focuses on recognizing the highly effected areas which are liable to flooding when extreme rainfall occurs for part of Hyderabad city (Zone XIII). The entire Hyderabad city is divided into 16 zones and each zone having details of existing drain network. A coupled 1D-2D flood modelling approach is used to identify flood prone areas and develop flood inundation and flood risk maps. 1D model for pilot area is developed using storm water management model (SWMM) and coupled with 2D PCSWMM. A web based GIS platform INPPINS is used to geo reference the existing network details and exported to 1D SWMM model. The model is simulated for extreme flood event occurred in past. The simulation run results identifies overflowing drainage nodes and flood inundation maps and risk maps prepared. The flood risk maps identify the low lying areas which need immediate attention in case of emergency. The overflowing nodes suggest the need of improvement of drainage in the area to safely dispose of the storm water and minimize the flooding.</p>

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“…Figure5shows that in the 24 research simulations[3,16,36,41,[43][44][45][46][47][48][49][50][51][52], the accuracy of the model in six verification periods was lower than that in the calibration period, and the accuracy of the model in 18 verification periods was higher than that in the calibration period. Calibration accuracy is 0.07 higher than verification accuracy on average and the overall trend of model calibration accuracy is positive.This study also summarizes the comparison articles to compare the accuracy of the models for single-run (refers to a single historical flood to calibrate the model) and multiple-run (refers to calibrating the model with multiple historical floods) rainfall-runoff event calibration.…”

mentioning

confidence: 99%

Evaluation of the Impact of Rainfall Inputs on Urban Rainfall Models: A Systematic Review

Liu

Yao

et al. 2020

Water

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Over the past several decades, urban flooding and other water-related disasters have become increasingly prominent and serious. Although the urban rain flood model’s benefits for urban flood simulation have been extensively documented, the impact of rainfall input to model simulation accuracy remains unclear. This systematic review aims to provide structured research on how rain inputs impact urban rain flood model’s simulation accuracy. The selected 48 peer-reviewed journal articles published between 2015 and 2019 on the Web of Science™ database were analyzed by key factors, including rainfall input type, calibration times and verification times. The results from meta-analysis reveal that when a traditional rain measurement was used as the rainfall input, model simulation accuracy was higher, i.e., the Nash–Sutcliffe efficiency coefficient (NSE) of traditional technology for rain measurement was higher than the 0.18 for the new technology rain measurement with respect to flow simulation. In addition, the single-field sub-flood calibration model was better than the multi-field sub-flood calibration model. NSE was higher than 0.14. The precision was better for the verification period; NSE of the calibration value showed a 0.07 higher verification value on average in flow simulation. These findings have certain significance for the development of future urban rain flood models and propose the development direction of the future urban rain flood model. Finally, in view of the rainfall input problem of the urban storm flood model, we propose the future development direction of the urban storm flood model.

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Simulation of Urban Drainage System Using Disaggregated Rainfall Data

Cited by 6 publications

References 17 publications

Runoff assessment by Storm water management model (SWMM)- A new approach

Runoff assessment by Storm water management model (SWMM)- A new approach

1d-2d Modeling of Urban Floods and Risk Map Generation for the Part of Hyderabad City

Evaluation of the Impact of Rainfall Inputs on Urban Rainfall Models: A Systematic Review

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