Development and application of GIS based K-DRUM for flood runoff simulation using radar rainfall

Park, Jin Hyeog; Hur, Young Teck

doi:10.1016/j.jher.2011.05.005

Cited by 6 publications

(2 citation statements)

References 22 publications

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“…It plays a hastily escalating role in the field of hydrology and sustainable water resources development and management. These techniques have been extensively applicable in nearly all fields of watershed aspects, like, estimation of evapotranspiration (Bashir et al 2008;Elhag et al 2011), soil erosion (Vemu and Pinnamaneni 2011;Esteves et al 2012;Conoscenti et al 2013), rainfall runoff modelling (Shrivastava et al 2004;Rawat et al 2011;Kim et al 2012;López-Vicente et al 2013), flood management (Mason et al 2003;Park and Hur 2012;Steinfeld et al 2013) and irrigation water management (Saidi et al 2009;Georgoussis et al 2009;Nahry et al 2011;Liyantonoa et al 2013). …”

Section: Role Of Geographic Information System (Gis) and Remote Sensimentioning

confidence: 99%

Information System for Integrated Watershed Management Using Remote Sensing and GIS

Aher

Adinarayana

Gorantiwar

et al. 2014

Society of Earth Scientists Series

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Watershed management is an endowed approach to mitigate the gap between demand and supply of water and other natural resources, particularly in the fragile arid and semi-arid tropics (SAT). As this is a complex phenomenon, there is need for a reliable Information System/Decision Support System (DSS). Watershed Management Information System (WATMIS) is a viable and generic toolkit for integrated watershed planning and management of its natural resources using multiple technologies like Geographical Information System (GIS), Remote Sensing (RS), Global Positioning System (GPS), hydrological modelling and soft computing tools. In this system, an attempt has been made to integrate dimensions in Agriculture-Water-Soil-Climate continuum for sustainable management of land and water resources judiciously. The application of WATMIS will be useful to various stakeholders such as agriculturists, rural extension community and water resources managers for better decision making.

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Section: Role Of Geographic Information System (Gis) and Remote Sensimentioning

confidence: 99%

Information System for Integrated Watershed Management Using Remote Sensing and GIS

Aher

Adinarayana

Gorantiwar

et al. 2014

Society of Earth Scientists Series

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“…The advanced FFWSs are usually based on the rainfall–runoff modeling with forecasted rainfall (provided by radar data or numerical weather forecasts) or real‐time precipitation of rain gauges on the watershed and then issuing the alarm if the simulated runoff exceeds a threshold at target points (e.g. see Toth et al ., ; Moore et al ., ; Norbiato et al ., ; Golian et al ., ; Park and Hur, among others). Most of large‐scale FFWSs uses numerical weather forecasted data as the inputs of rainfall–runoff models; such examples are the European FFWS (De Roo et al ., ), EFAS FFWS (Thielen et al ., ) and National Weather Service River Forecast System in USA (Day, ).…”

Section: Introductionmentioning

confidence: 97%

A stochastic framework to assess the performance of flood warning systems based on rainfall‐runoff modeling

Yazdi

Neyshabouri

Golian

2013

Hydrological Processes

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Nowadays, Flood Forecasting and Warning Systems (FFWSs) are known as the most inexpensive and efficient non‐structural measures for flood damage mitigation in the world. Benefit to cost of the FFWSs has been reported to be several times of other flood mitigation measures. Beside these advantages, uncertainty in flood predictions is a subject that may affect FFWS's reliability and the benefits of these systems. Determining the reliability of advanced flood warning systems based on the rainfall–runoff models is a challenge in assessment of the FFWS performance which is the subject of this study. In this paper, a stochastic methodology is proposed to provide the uncertainty band of the rainfall–runoff model and to calculate the probability of acceptable forecasts. The proposed method is based on Monte Carlo simulation and multivariate analysis of the predicted time and discharge error data sets. For this purpose, after the calibration of the rainfall–runoff model, the probability distributions of input calibration parameters and uncertainty band of the model are estimated through the Bayesian inference. Then, data sets of the time and discharge errors are calculated using the Monte Carlo simulation, and the probability of acceptable model forecasts is calculated by multivariate analysis of data using copula functions. The proposed approach was applied for a small watershed in Iran as a case study. The results showed using rainfall–runoff modeling based on real‐time precipitation is not enough to attain high performance for FFWSs in small watersheds, and it seems using weather forecasts as the inputs of rainfall–runoff models is essential to increase lead times and the reliability of FFWSs in small watersheds. Copyright © 2013 John Wiley & Sons, Ltd.

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Role of Geospatial Technologies in Natural Resource Management

Kala

Kumar

2021

Climate Impacts on Sustainable Natural Resource Management

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Development and application of GIS based K-DRUM for flood runoff simulation using radar rainfall

Cited by 6 publications

References 22 publications

Information System for Integrated Watershed Management Using Remote Sensing and GIS

Information System for Integrated Watershed Management Using Remote Sensing and GIS

A stochastic framework to assess the performance of flood warning systems based on rainfall‐runoff modeling

Role of Geospatial Technologies in Natural Resource Management

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