A new approach for dealing with depressions in digital elevation models when calculating flow accumulation values

2010 ◽  
Vol 34 (6) ◽  
pp. 781-809 ◽  
Author(s):  
Neil Arnold
Keyword(s):  
Digital Elevation Models ◽  
Physical Geography ◽  
Main Flow ◽  
High Quality ◽  
Common Procedure ◽  
New Approach ◽  
Flow Accumulation ◽  
Digital Elevation ◽  
Fine Spatial Resolution ◽  
Very High

Calculation of flow accumulation (also known as upstream area) matrices from digital elevation models (DEMs) is a very common procedure in hydrological studies, and also has been used in other disciplines within physical geography, such as glaciology. A problem with such calculations has always been the presence of closed depressions in DEMs; flow is directed towards such areas, but then cannot ‘escape’. In many implementations of flow accumulation algorithms such depressions have been removed from the DEM with some form of pre-processing algorithm which typically transform depressions into flat areas, across which area can then be routed. This approach effectively assumes that all depressions in a DEM are therefore artifacts, and not true features within the landscape. The proliferation of very high quality, high precision, and fine spatial resolution DEMs in recent years means that such an assumption is increasingly difficult to support. In this paper, some of the main flow accumulation algorithms and some existing techniques for dealing with closed depressions in DEMs are reviewed. A new algorithm is presented which assumes that such depressions are real features in the landscape, and which allows them to ‘fill’ and then ‘overflow’ into downstream areas within the DEM. Examples with a synthetic and two real DEMs suggest that, at least in these cases, the assumption that depressions are real is justified. These results also suggest that determining the size distribution for depressions within a DEM could form the basis for identifying whether artifact depressions are a problem in individual DEMs.

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

2021 ◽  
Vol 10 (3) ◽  
pp. 186
Author(s):  
HuiHui Zhang ◽  
Hugo A. Loáiciga ◽  
LuWei Feng ◽  
Jing He ◽  
QingYun Du
Keyword(s):  
Spatial Scales ◽  
Digital Elevation Models ◽  
Regional Scale ◽  
Drainage Density ◽  
River Network ◽  
Landscape Patterns ◽  
Estimation Methods ◽  
River Networks ◽  
Flow Accumulation ◽  
Digital Elevation

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.

scholarly journals A practical approach to lake water density from electrical conductivity and temperature

2016 ◽  
Vol 20 (7) ◽  
pp. 2975-2986 ◽  
Author(s):  
Santiago Moreira ◽  
Martin Schultze ◽  
Karsten Rahn ◽  
Bertram Boehrer
Keyword(s):  
Electrical Conductivity ◽  
Common Procedure ◽  
New Approach ◽  
Circulation Patterns ◽  
Lakes And Reservoirs ◽  
High Concentrations ◽  
Lake Waters ◽  
Very High ◽  
Limited Accuracy ◽  
Better Than

Abstract. Density calculations are essential to study stratification, circulation patterns, internal wave formation and other aspects of hydrodynamics in lakes and reservoirs. Currently, the most common procedure is the use of CTD (conductivity, temperature and depth) profilers and the conversion of measurements of temperature and electrical conductivity into density. In limnic waters, such approaches are of limited accuracy if they do not consider lake-specific composition of solutes, as we show. A new approach is presented to correlate density and electrical conductivity, using only two specific coefficients based on the composition of solutes. First, it is necessary to evaluate the lake-specific coefficients connecting electrical conductivity with density. Once these coefficients have been obtained, density can easily be calculated based on CTD data. The new method has been tested against measured values and the most common equations used in the calculation of density in limnic and ocean conditions. The results show that our new approach can reproduce the density contribution of solutes with a relative error of less than 10 % in lake waters from very low to very high concentrations as well as in lakes of very particular water chemistry, which is better than all commonly implemented density calculations in lakes. Finally, a web link is provided for downloading the corresponding density calculator.

scholarly journals EVALUATION OF DIGITAL ELEVATION MODELS FOR GEOMORPHOMETRIC ANALYSES ON DIFFERENT SCALES FOR NORTHERN CHILE

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1229-1235 ◽  
Author(s):  
T. Kramm ◽  
D. Hoffmeister
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Large Scale ◽  
Thermal Emission ◽  
Digital Elevation Models ◽  
Regional Scale ◽  
Laser Altimeter ◽  
Absolute Deviation ◽  
Digital Elevation ◽  
Very High

<p><strong>Abstract.</strong> The resolution and accuracy of digital elevation models (DEMs) have direct influence on further geoscientific computations like landform classifications and hydrologic modelling results. Thus, it is crucial to analyse the accuracy of DEMs to select the most suitable elevation model regarding aim, accuracy and scale of the study. Nowadays several worldwide DEMs are available, as well as DEMs covering regional or local extents. In this study a variety of globally available elevation models were evaluated for an area of about 190,000&amp;thinsp;km<sup>2</sup>. Data from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 30 m, Shuttle Radar Topography Mission (SRTM) 30&amp;thinsp;m and 90&amp;thinsp;m, Advanced Land Observing Satellite (ALOS) World 3D 30&amp;thinsp;m and TanDEM-X WorldDEM&amp;trade; &amp;ndash; 12&amp;thinsp;m and 90&amp;thinsp;m resolution were obtained. Additionally, several very high resolution DEM data were derived from stereo satellite imagery from SPOT 6/7 and Pléiades for smaller areas of about 100&amp;ndash;400&amp;thinsp;km<sup>2</sup> for each dataset. All datasets were evaluated with height points of the Geoscience Laser Altimeter System (GLAS) instrument aboard the NASA Ice, Cloud, and land Elevation (ICESat) satellite on a regional scale and with nine very high resolution elevation models from UAV-based photogrammetry on a very large scale. For all datasets the root mean square error (RMSE) and normalized median absolute deviation (NMAD) was calculated. Furthermore, the association of errors to specific terrain was conducted by assigning these errors to landforms from the topographic position index (TPI), topographic roughness index (TRI) and slope. For all datasets with a global availability the results show the highest overall accuracies for the TanDEM-X 12&amp;thinsp;m (RMSE: 2.3&amp;thinsp;m, NMAD: 0.8&amp;thinsp;m). The lowest accuracies were detected for the 30&amp;thinsp;m ASTER GDEM v3 (RMSE: 8.9&amp;thinsp;m, NMAD: 7.1&amp;thinsp;m). Depending on the landscape the accuracies are higher for all DEMs in flat landscapes and the errors rise significantly in rougher terrain. Local scale DEMs derived from stereo satellite imagery show a varying overall accuracy, mainly depending on the topography covered by the scene.</p>

scholarly journals Bumps in river profiles: the good, the bad, and the ugly

2017 ◽  
Author(s):  
Wolfgang Schwanghart ◽  
Dirk Scherler
Keyword(s):  
Quantile Regression ◽  
Uncertainty Quantification ◽  
Landscape Evolution ◽  
Digital Elevation Models ◽  
Combined Effect ◽  
New Approach ◽  
Digital Elevation ◽  
Steep Topography ◽  
River Profiles ◽  
New Algorithms

Abstract. The analysis of longitudinal river profiles is an important tool for studying landscape evolution. However, characterizing river profiles based on digital elevation models (DEM) suffers from errors and artifacts that particularly prevail along valley bottoms. The aim of this study is to characterize uncertainties that arise from the analysis of river profiles derived from different, near-globally available DEMs. We devised new algorithms – quantile carving and the CRS algorithm – that rely on quantile regression to enable hydrological correction and uncertainty quantification of river profiles. We find that globally available DEMs commonly overestimate river elevations in steep topography. The distributions of elevation errors become increasingly wider and right-skewed if adjacent hillslope gradients are steep. Our analysis indicates that the AW3D DEM has the highest precision and lowest bias for the analysis of river profiles in mountainous topography. The new 12-m resolution TanDEM-X DEM has a very low precision, most likely due to the combined effect of steep valley- walls and the presence of water surfaces in valley bottoms. Compared to the conventional approaches of carving and filling, we find that our new approach is able to reduce the elevation bias and errors in longitudinal river profiles.

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