Applicability of a flood forecasting system for Nebraska watersheds. (June 2023)

• Record Type: Journal Article
• Authors: Rasiya Koya, Sinan; Giron, Nicolas Velasquez; Rojas, Marcela; Mantilla, Ricardo; Harvey, Kirk; Ceynar, Daniel; Quintero, Felipe; Krajewski, Witold F.; Roy, Tirthankar
• Is Part Of: Environmental modelling & software. Volume 164(2023)
• Publication Date: 2023-06
• Subjects: Flood forecasting -- Snow hydrology -- IFIS -- HLM -- Bridge vulnerability; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2023.105693
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Accurate and timely flood prediction can reduce the risk of flooding, bolster preparedness, and help build resilience. In this study, we have developed a flood forecasting system prototype and checked its potential for carrying out operational flood forecasting in the state of Nebraska. This system builds upon some of the core components of the Iowa Flood Information System (IFIS), which is a state-of-the-art platform widely recognized around the world. We implemented our platform on a pilot basin in Nebraska (Elkhorn River basin) by installing eight stream sensors and setting up the hydrologic model component of IFIS, i.e., the Hillslope Link Model (HLM). Due to their importance in the Midwest, we particularly emphasized the snow processes and developed an improved HLM model that can account for different aspects of snow (rain-snow-partitioning, snowmelt, and snow accumulation) through simple parameterizations. Results show that the more thorough treatment of snow processes in the hydrologic model, as proposed herein, leads to better flood peak simulations. In this paper, we discuss different steps involved in developing the flood forecasting system prototype, along with the associated challenges and opportunities. Highlights: We developed a flood forecasting system prototype for a pilot basin in Nebraska. We developed an improved version of the popular HLM model to include snow processes. We identified the vulnerability of eight bridges to flooding. We designed a simple web interface showing the streamflow in a distributed manner in the basin.