Flood modeling of a large transboundary river using WRF-Hydro and microwave remote sensing

Dubey, Amit Kumar; Kumar, Prashant; Chembolu, Vinay; Dutta, Subashisa; Singh, R. P.; Rajawat, A. S.

doi:10.1016/j.jhydrol.2021.126391

Cited by 27 publications

(8 citation statements)

References 88 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is used by many researchers in river water level, discharge, and estimation of river hydraulic properties (de Oliveira Campos et al ., 2001; Birkett et al ., 2002; Papa et al ., 2012; Jarihani et al ., 2013; Duan and Bastiaanssen, 2013; Dubey et al ., 2015a; 2020). The satellite altimetry has also shown great potential in calibration and validation of hydrology and hydrodynamic models in many research studies (Chander et al ., 2014; Dubey et al ., 2014; 2015b; 2021; Gupta et al ., 2015c; Chembolu et al ., 2019). The water level data were used to generate a pseudo‐rating curve for the Ayodhya and Turtipar gauge stations and this relationship was used to convert water level into discharge.…”

Section: Data Preparationmentioning

confidence: 99%

Modelling of hydrological and environmental flow dynamics over a central Himalayan river basin through satellite altimetry and recent climate projections

Dubey

Goswami

Singh

2022

Intl Journal of Climatology

Self Cite

View full text Add to dashboard Cite

The Himalayan region is vulnerable to climate change, which is triggering extreme hydrological events. To understand the impact of climate emission scenarios on different hydrological flow dynamics of the Himalayan region, a thorough hydrological investigation is needed for improved water resource management. Hence, this research exemplifies the use of remote sensing, modelling techniques, and recent climate projections (CMIP5 and CMIP6) for the assessment of hydrological flow dynamics in the central Himalayan catchment. The SWAT model is calibrated/validated using gauge observation and satellite altimetry-derived river discharge and used for long-term hydrological simulations . CMIP6 models predicted that there would be a steady rise in high flows in all the projected scenarios. Flow duration curve for CMIP5 and CMIP6 models depicted that high flow of short duration would be frequent in future. The environmental flow components (EFCs) were calculated using the indicator of hydrologic alteration tool. The SWAT model simulations of hydrological and EFCs under CMIP6 climate projections are found to be significantly more vulnerable to climate warming than CMIP5, which could be due to socioeconomic pathway emission scenarios.

show abstract

Section: Data Preparationmentioning

confidence: 99%

Modelling of hydrological and environmental flow dynamics over a central Himalayan river basin through satellite altimetry and recent climate projections

Dubey

Goswami

Singh

2022

Intl Journal of Climatology

Self Cite

View full text Add to dashboard Cite

show abstract

“…Recently, for example, Galanaki and colleagues [8] and Kim and colleagues [9] use WRF-Hydro for operational flood forecasting in the Sarantapotamos basin in Greece and the USA, respectively. White and colleagues [10] estimate the flow of the Brahmaputra River located between India and Bangladesh, verifying good results in model performance. Liu and colleagues [5] simulate typical 24-hour storm events, providing a reference for model application.…”

Section: Introductionmentioning

confidence: 81%

Modeling of an Extreme Flooding Event in the Amazon Basin Using the WRF-Hydro Model

Vieira¹,

Júnior²,

Silva³

et al. 2022

JBTH

View full text Add to dashboard Cite

In the Amazon, the frequency of extreme events has been increasing notably in recent decades. In April, May, and June 2021, the city of Manaus faced the greatest flood in 119 years, and the Rio Negro reached at a level of 29.98 m. Because of this, the present work aims to evaluate the performance of the WRF-Hydro model in simulating precipitation during an extreme flood event in the Amazon Basin. The simulations were performed with 1 km spatial resolution and a 250 m channel network from April 30 to June 5, 2021. Such applications were evaluated using comparisons of the variability of accumulated precipitation with observed data from National Water Agency rainfall stations. The results showed a tendency for the model to underestimate the accumulated precipitation, slightly reproducing some observed precipitation patterns. We concluded that the tool presents a capacity for precipitation estimation, with potential for operational purposes.

show abstract

“…Traditionally, gauge station‐observed discharge and water stage data have been assimilated into hydrological models to predict water depths and flood inundation (Cao et al., 2019; Jafarzadegan et al., 2021). Currently, an increasing number of river flood‐plain elevation and inundation maps, which are derived from satellite synthetic aperture radar (SAR) images and altimetry data, have been assimilated into hydrological models to forecast flood inundation (Cooper et al., 2019; Dasgupta et al., 2021; Dubey et al., 2021; Matgen et al., 2010). Apart from satellite and gauge stations, observations can be derived from social media platforms; for example, water depth values gathered from volunteered geographic information (VGI) can be assimilated into a 2D hydraulic model for real time flood forecasting (Annis & Nardi, 2019).…”

Section: Applications Of Land Data Assimilation In Estimating Land Su...mentioning

confidence: 99%

Land Data Assimilation: Harmonizing Theory and Data in Land Surface Process Studies

Li,

Liu,

et al. 2024

Reviews of Geophysics

View full text Add to dashboard Cite

Data assimilation plays a dual role in advancing the “scientific” understanding and serving as an “engineering tool” for the Earth system sciences. Land data assimilation (LDA) has evolved into a distinct discipline within geophysics, facilitating the harmonization of theory and data and allowing land models and observations to complement and constrain each other. Over recent decades, substantial progress has been made in the theory, methodology, and application of LDA, necessitating a holistic and in‐depth exploration of its full spectrum. Here, we present a thorough review elucidating the theoretical and methodological developments in LDA and its distinctive features. This encompasses breakthroughs in addressing strong nonlinearities in land surface processes, exploring the potential of machine learning approaches in data assimilation, quantifying uncertainties arising from multiscale spatial correlation, and simultaneously estimating model states and parameters. LDA has proven successful in enhancing the understanding and prediction of various land surface processes (including soil moisture, snow, evapotranspiration, streamflow, groundwater, irrigation and land surface temperature), particularly within the realms of water and energy cycles. This review outlines the development of global, regional, and catchment‐scale LDA systems and software platforms, proposing grand challenges of generating land reanalysis and advancing coupled land‒atmosphere DA. We lastly highlight the opportunities to expand the applications of LDA from pure geophysical systems to coupled natural and human systems by ingesting a deluge of Earth observation and social sensing data. The paper synthesizes current LDA knowledge and provides a steppingstone for its future development, particularly in promoting dual driven theory‐data land processes studies.

show abstract

Flood modeling of a large transboundary river using WRF-Hydro and microwave remote sensing

Cited by 27 publications

References 88 publications

Modelling of hydrological and environmental flow dynamics over a central Himalayan river basin through satellite altimetry and recent climate projections

Modelling of hydrological and environmental flow dynamics over a central Himalayan river basin through satellite altimetry and recent climate projections

Modeling of an Extreme Flooding Event in the Amazon Basin Using the WRF-Hydro Model

Land Data Assimilation: Harmonizing Theory and Data in Land Surface Process Studies

Contact Info

Product

Resources

About