Watershed delineation on a hexagonal mesh grid

Liao, Chang; Tesfa, T. K.; Duan, Zhuoran; Leung, L. Ruby

doi:10.1016/j.envsoft.2020.104702

Cited by 31 publications

(20 citation statements)

References 18 publications

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“…In general, the quality of modeled conceptual flowlines increases as the spatial resolution increases. For structured meshes, the model performances are very close and the hexagon mesh is potentially better (Figure 14), which is constant with our earlier study (Liao et al., 2020). The MPAS mesh‐based conceptual flowlines are the closest to the real flowlines.…”

Section: Discussionsupporting

confidence: 89%

Topological Relationship‐Based Flow Direction Modeling: Mesh‐Independent River Networks Representation

Liao

Zhou

et al. 2023

J Adv Model Earth Syst

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Real-world river networks are complex, depending on landscape features such as elevation, aspect, and lithology. Moreover, the fractal nature of river networks means that they are approximately scale-free (Tarboton et al., 1988) without a well-defined spatial resolution at which they should be represented (Davies & Bell, 2009;Yamazaki et al., 2009). As a result, hydrologic models often use a conceptual representation of river networks. To date, there are mainly three methods for representing river networks at different scales, each with its own advantages and disadvantages. However, limitations remain when representing river networks due to the resolution mismatch and their interactions with other hydrologic features (e.g., ocean).Two methods are useful at the watershed/regional scale, the first of which is the vector-based river networks analysis method. This method uses vector datasets to represent the river networks and their topological relationships (Lin et al., 2018;Mizukami et al., 2016). Vector datasets are often provided by public agencies, for example, the United States Geological Survey (USGS), or are digitized from satellite image processing, for example, vectorization-based river channel extraction. Various graph theory algorithms are then used to perform quality control and network analysis based on the vector river networks (Lindsay et al., 2019). Lindsay et al. reviewed several potential issues in existing vector river networks datasets: (a) the vertex coordinates of river flowlines may not exactly overlap with the actual locations due to digitization error and floating-point rounding errors. (b) A river flowline's starting and ending vertices may be reversed during spatial analysis, resulting in an opposite flow direction. (c) vector datasets obtained from different sources generally use different spatial references and cannot be used or combined directly. Even without these issues, vector datasets still require other pre-processing before use. For example, braided rivers are not universally supported in hydrologic models as multiple flow

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Section: Discussionsupporting

confidence: 89%

Topological Relationship‐Based Flow Direction Modeling: Mesh‐Independent River Networks Representation

Liao

Zhou

et al. 2023

J Adv Model Earth Syst

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“…To use hexagons this way, the raw elevation data would need to be aggregated to hexagons and then hexagon-based catchments could be delineated. Liao et al (2020) used a hexagon grid to delineate watersheds and found improvements over conventional square grids, suggesting the same could be done using H3 or dggridR.…”

Section: Discussionmentioning

confidence: 99%

Discrete Global Grid Systems as scalable geospatial frameworks for characterizing coastal environments

Bousquin

2021

Environmental Modelling & Software

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“…The river networks and flow directions are modeled using HexWatershed (Liao et al, 2020(Liao et al, , 2022Liao, 2022), a watershed and flow direction model that supports both structured and unstructured meshes for river routing models. HexWatershed uses a topological relationship-based approach to define river networks in the mid-Atlantic region (Lehner et al, 2008).…”

Section: Coastal Refined Global Unstructured Mesh and Flow Direction Mapmentioning

confidence: 99%

“…Large-scale river models are one of the major components of Earth system models (ESMs) that couple the atmosphere, land, river and ocean models to simulate the global water cycle (e.g., Golaz et al, 2019;Leung et al, 2020) and assess flood risks (Hirabayashi et al, 2013;Towner et al, 2019). Although hydraulic or hydrodynamic models were used more often in previous studies to simulate storm surgeinduced coastal inundation (Bakhtyar et al, 2020;Muñoz et al, 2020), there have been growing applications of large-scale river models to assess the compound fluvial and coastal flooding at basin (Chen et al, 2013), regional (Ikeuchi et al, 2017;Yamazaki et al, 2012) and global scales (Eilander et al, 2020;Mao et al, 2019) because they are more computationally efficient for a large spatiotemporal assessment.…”

Section: Introductionmentioning

confidence: 99%

Investigating coastal backwater effects and flooding in the coastal zone using a global river transport model on an unstructured mesh

Feng

Tan

Engwirda

et al. 2022

Hydrol. Earth Syst. Sci.

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Abstract. Coastal backwater effects are caused by the downstream water level increase as a result of elevated sea level, high river discharge and their compounding influence. Such effects have crucial impacts on floods in densely populated regions but have not been well represented in large-scale river models used in Earth system models (ESMs), partly due to model mesh deficiency and oversimplifications of river hydrodynamics. Using two mid-Atlantic river basins as a testbed, we perform the first attempt to simulate the backwater effects comprehensively over a coastal region using the MOSART river transport model under an ESM framework, i.e., Energy Exascale Earth System Model (E3SM) configured on a regionally refined unstructured mesh, with a focus on understanding the backwater drivers and their long-term variations. By including sea level variations at the river downstream boundary, the model performance in capturing backwaters is greatly improved. We also propose a new flood event selection scheme to facilitate the decomposition of backwater drivers into different components. Our results show that while storm surge is a key driver, the influence of extreme discharge cannot be neglected, particularly when the river drains to a narrow river-like estuary. Compound flooding, while not necessarily increasing the flood peaks, exacerbates the flood risk by extending the duration of multiple coastal and fluvial processes. Furthermore, our simulations and analysis highlight the increasing strength of backwater effects due to sea level rise and more frequent storm surge during 1990–2019. Thus, backwaters need to be properly represented in ESMs to improve the predictive understanding of coastal flooding.

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Watershed delineation on a hexagonal mesh grid

Cited by 31 publications

References 18 publications

Topological Relationship‐Based Flow Direction Modeling: Mesh‐Independent River Networks Representation

Topological Relationship‐Based Flow Direction Modeling: Mesh‐Independent River Networks Representation

Discrete Global Grid Systems as scalable geospatial frameworks for characterizing coastal environments

Investigating coastal backwater effects and flooding in the coastal zone using a global river transport model on an unstructured mesh

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