Regionalized Design Rainfall Estimation: an Appraisal of Inundation Mapping for Flood Management Under Data-Scarce Situations

Mohanty, Mohit Prakash; Sherly, Mazhuvanchery Avarachen; Karmakar, Subhankar; Ghosh, Subimal

doi:10.1007/s11269-018-2080-8

Cited by 23 publications

(6 citation statements)

References 42 publications

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“…As a result, the computational complexity of the model is simplified, resulting in lower computational time without compromising the output of the model. To account for floodplain roughness, Manning's resistance values for various land use classes are provided (Mohanty et al., 2018). The governing equations for shallow water equations in two dimensions are provided in Equations .…”

Section: Methodsmentioning

confidence: 99%

A Novel Response Priority Framework for an Urban Coastal Catchment Using Global Weather Forecasts‐Based Improved Flood Risk Estimates

Ghosh,

Shastri,

Ghosh

et al. 2023

JGR Atmospheres

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A novel flood risk forecasting‐based response priority framework is proposed in this study, which will facilitate efficient decision‐making ahead of an extreme precipitation event. This study is demonstrated over a highly flood‐prone and geomorphologically diverse coastal catchment in Mumbai city, the financial capital of India, and is subjected to high spatio‐temporal variability of precipitation. A regional precipitation forecast model is developed, where a quantile regression‐based statistical approach is applied to the global weather forecasts for improvement in finer resolution extreme precipitation estimates. A quantile regression is performed between the observed synoptic‐scale predictors obtained from ERA Interim Reanalysis dataset and the observed sub‐daily precipitation within the study area. Subsequently, a set of reliably well‐simulated forecasted predictors obtained from the ensemble members of the Global Ensemble Forecast System (GEFS) are used in the established relationship to obtain extreme precipitation forecasts for higher quantile levels. The forecasted precipitation data serves as an essential input to a comprehensive hydrodynamic flood modelling framework. The flood inundation maps corresponding to different quantiles of forecasted precipitation are quantified to identify the flood hotspots. The set of flood inundations maps developed for different quantiles are utilized to demarcate the areas based on critical response time, i.e., the time required by each cell within the study area to be inundated to a certain threshold depth, and the response priority levels for each cell are determined. This information is combined with socio‐economic vulnerability, a critical component of flood risk, to derive conjugated socio‐economic vulnerability‐based response priority maps.

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Section: Methodsmentioning

confidence: 99%

A Novel Response Priority Framework for an Urban Coastal Catchment Using Global Weather Forecasts‐Based Improved Flood Risk Estimates

Ghosh,

Shastri,

Ghosh

et al. 2023

JGR Atmospheres

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“…There are many expressions of kernel function, such as Gaussian kernel function, Triangle kernel function, Uniform (or Box) kernel function, etc. The Gaussian kernel function is used in the study since it is the most widely used kernel function and has been extensively studied in hydrology fields [31][32][33]. The equation of the Gaussian kernel function is as follows:…”

Section: F(x) Parametersmentioning

confidence: 99%

Investigating Flood Risks of Rainfall and Storm Tides Affected by the Parameter Estimation Coupling Bivariate Statistics and Hydrodynamic Models in the Coastal City

Wang

et al. 2022

IJERPH

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: The public health risk caused by urban floods is a global concern. Flood risks are amplified by the interaction of rainfall and storm tides in coastal cities. In this study, we investigate the flood risks of rainfall and storm tides coupling statistical and hydrodynamic models and evaluate the influence of different parameter estimation methods and bivariate return periods (RPs) on flood risks in the coastal city. The statistical model is used to obtain the bivariate design of rainfall and storm tides with the integration of copula function, most-likely weight function and Monte Carlo simulation method. The bivariate designs are adopted as the input boundaries for the hydrodynamic model established by Personal Computer Storm Water Management Model (PCSWMM), and the flood risk is evaluated by the hydrodynamic model. Subsequently, the influence of different parameter estimation approaches (that is, parametric and non-parametric) and bivariate RPs (that is, co-occurrence RP, joint RP, and Kendall RP) on bivariate designs and flood risks are investigated. With Haikou coastal city in China as the case study, the results show that: (1) Gumbel copula is the best function to describe the correlation structure between rainfall and storm tides for the parametric and non-parametric approaches, and the non-parametric approach is a better fit for the observed data; (2) when the Kendall RP is large (more than 100 years), the flood risk is underestimated with an average of 17% by the non-parametric estimation, and the parametric estimation approach is recommended as it is considered the most unfavorable scenario; (3) the types of bivariate RP have the important impact on the flood risk. When there is no specific application need, the Kendall RP can be adopted as the bivariate design standard of flooding facilities since it can describe the dangerous areas more accurately for multivariate scenario. The results can provide references for reasonable flood risk assessment and flooding facility design in coastal cities.

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“…The design rainfall time-series ( R) is computed by employing a novel regionalization technique introduced by Mohanty et al 2018). Here, the rainfall information from the monitoring stations is utilized to form a R by employing the Depth-Duration-Frequency information and design temporal pattern in a non-linear optimization framework.…”

Section: Hydrodynamic Flood Simulations With Design Rainfall and Stormentioning

confidence: 99%

“…For the stations, a comprehensive multivariate frequency analysis composing of marginal depth-frequency and marginal-duration frequency is performed using various parametric and non-parametric distributions. More details on the list of distributions/models are provided in Sherly et al (2015) and Mohanty et al (2018). The marginals from these distributions are used to derive the conditional probability using copula functions.…”

Section: Hydrodynamic Flood Simulations With Design Rainfall and Stormentioning

confidence: 99%

Tide-rainfall flood quotient: an incisive measure of comprehending a region’s response to storm-tide and pluvial flooding

Mohanty

Sherly

Ghosh

et al. 2020

Environ. Res. Lett.

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It is undeniable that coastal regions worldwide are facing unprecedented damages from catastrophic floods attributable to storm-tide (tidal) and extreme rainfall (pluvial). For flood-risk assessment, although recognizing compound impact of these drivers is a conventional practice, the marginal/individual impacts cannot be overlooked. In this letter, we propose a new measure, Tide-Rainfall Flood Quotient (TRFQ), to quantify the driver-specific flood potential of a coastal region arising from storm-tide or rainfall. A set of inundation and hazard maps are derived through a series of numerical and hydrodynamic flood model simulations comprising of design rainfall and design storm-tide. These experiments are demonstrated on three different geographically diverse flood-affected coastal regions in India. The new measure throws light on existing knowledge gaps on the propensity of coastal flooding induced by the marginal/individual contribution of storm-tide and rainfall. It shall prove useful in rationalizing long-term flood management strategies customizable for storm-tide and pluvial dominated global coastal regions.

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Regionalized Design Rainfall Estimation: an Appraisal of Inundation Mapping for Flood Management Under Data-Scarce Situations

Cited by 23 publications

References 42 publications

A Novel Response Priority Framework for an Urban Coastal Catchment Using Global Weather Forecasts‐Based Improved Flood Risk Estimates

A Novel Response Priority Framework for an Urban Coastal Catchment Using Global Weather Forecasts‐Based Improved Flood Risk Estimates

Investigating Flood Risks of Rainfall and Storm Tides Affected by the Parameter Estimation Coupling Bivariate Statistics and Hydrodynamic Models in the Coastal City

Tide-rainfall flood quotient: an incisive measure of comprehending a region’s response to storm-tide and pluvial flooding

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