Enhancing the Capability of a Simple, Computationally Efficient, Conceptual Flood Inundation Model in Hydrologically Complex Terrain

Abstract

The simple conceptual flood inundation model TVD (Teng-Vaze-Dutta) is more computationally efficient and cost-effective than traditional hydrodynamic models. It is especially useful for applications that do not require velocity output and have low demands on flood dynamic representation. In this study, we have addressed the main inherent limitations of the original TVD model including: the assumption that all the floodplain depressions connected to the river are instantly filled up to the in-stream water level at each time step; the lack of information sharing at the boundary of two modelling reaches; and insufficient soil moisture processes. All of these can affect the model's applicability and accuracy, especially in very flat and hydrologically complex floodplains. A number of improvements to the model structure have been implemented to address mass conservation, reach connectivity and water balance issues. The revised model was set up to simulate a number of flood events in Australia's lower Balonne River and Darling River to test for its enhanced capability. The modelled inundation extents before and after the improvements were assessed against remote sensing water maps. The model developments have improved the accuracy of modelled flood extent. Nevertheless, there are still remaining issues that require the model to be used with caution when simulating flood inundation in difficult-to-model topographies, largely, the demand for reliable input of overbank flow volume and the extrapolating issue with weighting schemes.

InundatEd-v1.0: a height above nearest drainage (HAND)-based flood risk modeling system using a discrete global grid system

“…The practice of flood modeling, which aims to understand, quantify, and represent the characteristics and impacts of flood events across a range of spatial and temporal scales, has long informed the sustainable management of watersheds and water resources including flood risk management (Handmer, 1980;Stevens and Hanschka, 2014;Teng et al, 2017Teng et al, , 2019Towe et al, 2020). Flood modeling research has increased in response to such factors as predicted climate change impacts (Wilby and Keenan, 2012) and advancements in computer, GIS (Geographic Information Systems), and remote sensing technologies, among others (Kalyanapu et al, 2011;Vojtek and Vojteková, 2016;Wang and Cheng, 2007).…”

“…The third model class, simple conceptual, has become increasingly well known in the contexts of large study areas, data scarcity, and/or stochastic modeling and encompasses the majority of recent developments in inundation modeling practices (Teng et al, 2017). Relative to the typically complex hydrodynamic model class, simple conceptual models simplify the physical processes and are characterized by much shorter processing times (Teng et al, 2017(Teng et al, , 2019. A class of model which uses the output of a more complex model as a means of calibrating a relatively simpler model is also gaining popularity (Oubennaceur et al, 2019).…”

“…Access to flood risk maps can build the capacity of individuals to make informed and sustainable investment and residence decisions in an age of climate concern and environmental change (Albano et al, 2018). The current state of public knowledge of flooding risks is unsatisfactory, with an estimated 94 % of 2300 Canadian respondents in highly flood-prone areas lacking awareness of the flood-related risks to themselves and their property, per a 2016 national survey (Calamai and Minano, 2017;Thistlethwaite et al, 2018Thistlethwaite et al, , 2017. Calls for better transparency and access to reliable flood risk maps and data with which to improve public awareness and understanding of flood risks are in line with a contemporary trend toward more open and reproducible environmental models (Gebetsroither-Geringer et al, 2018).…”

InundatEd: A Large-scale Flood Risk Modeling System on a Big-data – Discrete Global Grid System Framework

“…and flood risk management, including the process of public flood risk education, have long been informed by the practice of flood (inundation) modelling, which aims to understand, quantify, and represent the characteristics and impacts of flood events across a range of spatial and temporal scales (Handmer, 1980;Stevens & Hanschka, 2014;Teng et al, 2017Teng et al, , 2019Towe et al, 2020).…”

Dynamic 3D Simulation of Flood Risk Based on the Integration of Spatio-Temporal GIS and Hydrodynamic Models

“…It is crucial for ecologically-based development to understand how to scientifically prevent flood disasters and protect and properly use water resources. Hydrodynamic models are core quantitative calculations in emergency flood disaster management [2][3][4] and can accurately simulate the instantaneous dynamic evolution and medium-to long-term development of a flood [5]. Since hydrodynamic models are very complicated, usually only domain experts can understand the models.…”