Global satellite-based river gauging and the influence of river morphology on its application

Hou, Jiawei; Dijk, Albert I. J. M. van; Beck, Hylke E.

doi:10.1016/j.rse.2019.111629

Cited by 31 publications

(21 citation statements)

References 54 publications

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“…Finding the ‘best’ DEM cell has also been a consideration in other areas of hydrology (e.g. Hou et al, 2020), when the exact location of a channel is unknown with respect to any given cell in a remote sensing product. Walker and Willgoose (1999) compared drainage area estimates of streams across different DEMs and resolutions and found that the optimal cell from which to measure drainage area (i.e.…”

Section: Methodsmentioning

confidence: 99%

“…Finding the 'best' DEM cell has also been a consideration in other areas of hydrology (e.g. Hou et al, 2020), when the exact location of a channel is unknown with respect to any given cell in a remote sensing product. Walker and Willgoose (1999) this, but found errors occurred due to incorrect cells being compared when multiple possible stream outlet candidates existed close to one another.…”

Section: Defining Gully Head Drainage Areamentioning

confidence: 99%

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A comparison of hillslope drainage area estimation methods using high‐resolution DEMs with implications for topographic studies of gullies

Walker

Dijk

Wilkinson

et al. 2021

Earth Surf Processes Landf

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Topographic models provide a useful tool for understanding gully occurrence in the landscape but require reliable estimates of gully head drainage areas. Modern highresolution topography data (collected using structure from motion photogrammetry or light detection and ranging) is increasingly used for topographic studies of gullies, but little work has been done to assess the variability of gully head drainage area estimates using different methods. This study evaluated alternative approaches to using high-resolution digital elevation models (DEMs) so that gully topographic models can be more readily applied to any area with suitably high-resolution data. Specifically, we investigated the impact of single-or multiple-direction flow routing algorithms, DEM hydrologic-enforcement procedures and spatial resolution on gully head drainage area estimation. We tested these methods on a 40 km 2 site centred on Weany Creek, a low-relief semi-arid landscape draining towards the Great Barrier Reef, Australia. Using a subroutine to separate gully heads into those with divergent or convergent flow patterns upslope, we found that divergent flow conditions occurred at half of 484 studied gullies. Drainage areas estimated by different flow routing algorithms were more variable in these divergent cases than for convergent cases. This variation caused a significant difference between topographic threshold parameters (slope b and intercept k) derived from single-or multiple-direction flow routing algorithms, respectively. Different methods of hydrologic enforcement (filling or breaching) also affected threshold analysis, resulting in estimates of the exponent b being $188% higher if the DEM was filled than if breached. The testing of the methods to date indicates that a finer resolution (≤2 m) DEM and a multiple-direction flow routing algorithm achieve the most realistic drainage area estimates in low-relief landscapes. For Weany Creek we estimated threshold parameters k = 0.033 and b = 0.189, indicating that it is highly susceptible to gully erosion.

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Section: Methodsmentioning

confidence: 99%

Section: Defining Gully Head Drainage Areamentioning

confidence: 99%

A comparison of hillslope drainage area estimation methods using high‐resolution DEMs with implications for topographic studies of gullies

Walker

Dijk

Wilkinson

et al. 2021

Earth Surf Processes Landf

View full text Add to dashboard Cite

show abstract

“…Remote Sens. 2021, 13, x FOR PEER REVIEW 5 of 28 9. Use the Polsby-Popper test [53] to identify and manually split very large polygons.…”

Section: Workflowmentioning

confidence: 99%

“…Multi-decadal archives of satellite imagery provide insight into water resource availability in two key ways. Firstly, they have the ability to map and monitor catchment-wide and continent-wide surface water dynamics, supplementing or replacing surface networks in data-sparse regions [9][10][11]. Secondly, the multi-decadal perspective of these archives means that the changes in surface water that are currently taking place can be placed into the context of historical surface water dynamics [12,13].…”

Section: Introductionmentioning

confidence: 99%

Mapping and Monitoring the Multi-Decadal Dynamics of Australia’s Open Waterbodies Using Landsat

et al. 2021

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Water detection algorithms are now being routinely applied to continental and global archives of satellite imagery. However, water resource management decisions typically take place at the waterbody rather than pixel scale. Here, we present a workflow for generating polygons of persistent waterbodies from Landsat observations, enabling improved monitoring and management of water assets across Australia. We use Digital Earth Australia’s (DEA) Water Observations from Space (WOfS) product, which provides a water classified output for every available Landsat scene, to determine the spatial locations and extents of waterbodies across Australia. We generated a polygon set of waterbodies that identified 295,906 waterbodies ranging in size from 3125 m2 to 4820 km2. Each polygon was used to generate a time series of WOfS, providing a history of the change in surface area of each waterbody every ~16 days since 1987. We demonstrate the applications of this new dataset, DEA Waterbodies, to understanding local through to national-scale surface water spatio-temporal dynamics. DEA Waterbodies provides new insights into Australia’s water availability and enables the monitoring of important landscape features such as lakes and dams, improving our ability to use earth observation data to make meaningful decisions.

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“…Previous research on river network extraction has focused on basins that are not intensely urbanized, thus neglecting anthropogenic impacts [10]. Remote sensing provides a complementary source of river network analysis, yielding data on surface water extent, surface runoff, and evapotranspiration, which creates opportunities to derive river-related information where and when in-situ data are not available [38]. Global, high-resolution, DEMs have become available.…”

Section: Introductionmentioning

confidence: 99%

Setting the Flow Accumulation Threshold Based on Environmental and Morphologic Features to Extract River Networks from Digital Elevation Models

Zhang

Loáiciga

Liao

et al. 2021

IJGI

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Determining the flow accumulation threshold (FAT) is a key task in the extraction of river networks from digital elevation models (DEMs). Several methods have been developed to extract river networks from Digital Elevation Models. However, few studies have considered the geomorphologic complexity in the FAT estimation and river network extraction. Recent studies estimated influencing factors’ impacts on the river length or drainage density without considering anthropogenic impacts and landscape patterns. This study contributes two FAT estimation methods. The first method explores the statistical association between FAT and 47 tentative explanatory factors. Specifically, multi-source data, including meteorologic, vegetation, anthropogenic, landscape, lithology, and topologic characteristics are incorporated into a drainage density-FAT model in basins with complex topographic and environmental characteristics. Non-negative matrix factorization (NMF) was employed to evaluate the factors’ predictive performance. The second method exploits fractal geometry theory to estimate the FAT at the regional scale, that is, in basins whose large areal extent precludes the use of basin-wide representative regression predictors. This paper’s methodology is applied to data acquired for Hubei and Qinghai Provinces, China, from 2001 through 2018 and systematically tested with visual and statistical criteria. Our results reveal key local features useful for river network extraction within the context of complex geomorphologic characteristics at relatively small spatial scales and establish the importance of properly choosing explanatory geomorphologic characteristics in river network extraction. The multifractal method exhibits more accurate extracting results than the box-counting method at the regional scale.

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Global satellite-based river gauging and the influence of river morphology on its application

Cited by 31 publications

References 54 publications

A comparison of hillslope drainage area estimation methods using high‐resolution DEMs with implications for topographic studies of gullies

A comparison of hillslope drainage area estimation methods using high‐resolution DEMs with implications for topographic studies of gullies

Mapping and Monitoring the Multi-Decadal Dynamics of Australia’s Open Waterbodies Using Landsat

Setting the Flow Accumulation Threshold Based on Environmental and Morphologic Features to Extract River Networks from Digital Elevation Models

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