Book chapter
A Multisource, Data‐Driven, Web‐GIS‐Based Hydrological Modeling Framework for Flood Forecasting and Prevention
Remote Sensing of Water‐Related Hazards, pp.105-122
John Wiley & Sons, Inc
04/14/2022
DOI: 10.1002/9781119159131.ch6
Abstract
Modeling is widely applied in hydrologic research and practices through synthesis and simulation of hydrologic processes. Configuring and executing stand‐alone hydrologic models can be difficult due to data limitations, lack of expertise, and hardware limitations. The objective of this research is to develop a web‐accessible lumped hydrological modeling framework for researchers and practitioners, enabling them to organize hydrologic data, execute hydrologic models, and analyze and visualize results. By adopting the Hadoop Distributed File System and Apache Hive, the efficiency of data processing and query was significantly improved. Lumped Coupled Routing and Excess STorage (CREST) and Hydrological MODel (HyMOD) were integrated as a proof‐of‐concept in this framework. Evaluation of 323 selected basins over the conterminous United States were performed as a demonstration. Both models present high correlations (r ≥ 0.72 for lumped CREST model and r ≥ 0.75 for HyMOD) between calibration and validation time periods for correlation coefficient and the Nash‐Sutcliffe coefficient of efficiency. Our vision is to simplify the processes of using hydrologic models in flood forecasting and prevention for researchers and practitioners, as well as to unlock the potential and educate the less experienced public on hydrologic models.
Details
- Title: Subtitle
- A Multisource, Data‐Driven, Web‐GIS‐Based Hydrological Modeling Framework for Flood Forecasting and Prevention
- Creators
- Zhanming WanXianwu XueKe ZhangYang HongJonathan J GourleyHumberto Vergara
- Contributors
- Ke Zhang (Editor)Yang Hong (Editor)Amir AghaKouchak (Editor)
- Resource Type
- Book chapter
- Publication Details
- Remote Sensing of Water‐Related Hazards, pp.105-122
- Publisher
- John Wiley & Sons, Inc; Hoboken, NJ, USA
- DOI
- 10.1002/9781119159131.ch6
- Number of pages
- 18
- Language
- English
- Date published
- 04/14/2022
- Academic Unit
- Civil and Environmental Engineering
- Record Identifier
- 9984446066102771
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