Impacts of peatland drainage on the properties of typical water flow paths determined from a digital elevation model

2008 ◽  
Vol 39 (5-6) ◽  
pp. 359-368 ◽  
Author(s):  
Timo Korkalainen ◽  
Ari Laurén ◽  
Harri Koivusalo ◽  
Teemu Kokkonen
Keyword(s):  
Digital Elevation Model ◽  
Water Flow ◽  
Water Body ◽  
Water Bodies ◽  
Flow Paths ◽  
Digital Elevation ◽  
The Mean ◽  
Growth Changes ◽  
Elevation Model ◽  
Water Flow Paths

Peatland drainage enhances tree growth, changes catchment hydrology and increases export of nutrients and suspended solids to water bodies. In this study, impacts of peatland drainage on the properties of water flow paths in terrestrial parts of catchments were assessed in terms of slope, elevation, length and soil type. Three study catchments (area 31.8–153.5 km2) were delineated using a 25 m × 25 m digital elevation model (DEM). Typical water flow paths were calculated for each catchment to characterize the mean elevation above the receiving water body as a function of distance along water flow paths. The resulting two-dimensional (2D) profile also allowed calculations of horizontally distributed properties of catchments as a function of distance to the water body. Peatland drainage decreased the length and elevation of the typical water flow path, and increased the area near water bodies. Increasing drainage from 10.7% to 55.4% of the total catchment area increased the area residing close to a water body (no farther than 25 m) from 17.1% to 60.7%. This area estimate is useful for assessing the costs of water protection, arising from restricting forestry operations in the vicinity of water bodies.

Precise computation of the direct and indirect topographic effects of Helmert's 2nd method of condensation using SRTM30 digital elevation model

2011 ◽  
Vol 1 (4) ◽  
pp. 305-312 ◽  
Author(s):  
Y. Wang
Keyword(s):  
Standard Deviation ◽  
Digital Elevation Model ◽  
Outer Zone ◽  
Mean Value ◽  
Constant Density ◽  
Topographic Effects ◽  
Topographic Effect ◽  
Digital Elevation ◽  
The Mean ◽  
Elevation Model

Precise computation of the direct and indirect topographic effects of Helmert's 2nd method of condensation using SRTM30 digital elevation modelThe direct topographic effect (DTE) and indirect topographic effect (ITE) of Helmert's 2nd method of condensation are computed using the digital elevation model (DEM) SRTM30 in 30 arc-seconds globally. The computations assume a constant density of the topographic masses. Closed formulas are used in the inner zone of half degree, and Nagy's formulas are used in the innermost column to treat the singularity of integrals. To speed up the computations, 1-dimensional fast Fourier transform (1D FFT) is applied in outer zone computations. The computation accuracy is limited to 0.1 mGal and 0.1cm for the direct and indirect effect, respectively.The mean value and standard deviation of the DTE are -0.8 and ±7.6 mGal over land areas. The extreme value -274.3 mGal is located at latitude -13.579° and longitude 289.496°, at the height of 1426 meter in the Andes Mountains. The ITE is negative everywhere and has its minimum of -235.9 cm at the peak of Himalayas (8685 meter). The standard deviation and mean value over land areas are ±15.6 cm and -6.4 cm, respectively. Because the Stokes kernel does not contain the zero and first degree spherical harmonics, the mean value of the ITE can't be compensated through the remove-restore procedure under the Stokes-Helmert scheme, and careful treatment of the mean value in the ITE is required.

scholarly journals VALIDATION OF THE ASTER GLOBAL DIGITAL ELEVATION MODEL VERSION 3 OVER THE CONTERMINOUS UNITED STATES

2016 ◽  
Vol XLI-B4 ◽  
pp. 143-148 ◽  
Author(s):  
D. Gesch ◽  
M. Oimoen ◽  
J. Danielson ◽  
D. Meyer
Keyword(s):  
United States ◽  
Land Cover ◽  
Digital Elevation Model ◽  
Ground Level ◽  
Land Cover Type ◽  
Mean Error ◽  
Digital Elevation ◽  
The Mean ◽  
Vertical Accuracy ◽  
Elevation Model

The ASTER Global Digital Elevation Model Version 3 (GDEM v3) was evaluated over the conterminous United States in a manner similar to the validation conducted for the original GDEM Version 1 (v1) in 2009 and GDEM Version 2 (v2) in 2011. The absolute vertical accuracy of GDEM v3 was calculated by comparison with more than 23,000 independent reference geodetic ground control points from the U.S. National Geodetic Survey. The root mean square error (RMSE) measured for GDEM v3 is 8.52 meters. This compares with the RMSE of 8.68 meters for GDEM v2. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset from true ground level. The GDEM v3 mean error of −1.20 meters reflects an overall negative bias in GDEM v3. The absolute vertical accuracy assessment results, both mean error and RMSE, were segmented by land cover type to provide insight into how GDEM v3 performs in various land surface conditions. While the RMSE varies little across cover types (6.92 to 9.25 meters), the mean error (bias) does appear to be affected by land cover type, ranging from −2.99 to +4.16 meters across 14 land cover classes. These results indicate that in areas where built or natural aboveground features are present, GDEM v3 is measuring elevations above the ground level, a condition noted in assessments of previous GDEM versions (v1 and v2) and an expected condition given the type of stereo-optical image data collected by ASTER. GDEM v3 was also evaluated by differencing with the Shuttle Radar Topography Mission (SRTM) dataset. In many forested areas, GDEM v3 has elevations that are higher in the canopy than SRTM. The overall validation effort also included an evaluation of the GDEM v3 water mask. In general, the number of distinct water polygons in GDEM v3 is much lower than the number in a reference land cover dataset, but the total areas compare much more closely.

scholarly journals Uncertainty in Catchment Delineations as a Result of Digital Elevation Model Choice

Hydrology ◽  
2019 ◽  
Vol 6 (1) ◽  
pp. 13 ◽  
Author(s):  
Laura Keys ◽  
Jussi Baade
Keyword(s):  
Digital Elevation Model ◽  
Correlation Coefficients ◽  
Significant Negative Correlation ◽  
Nam Co ◽  
Digital Elevation ◽  
Environment Variables ◽  
The Mean ◽  
Elevation Model ◽  
Resolution Dataset ◽  
Median Slope

Nine digital elevation model (DEM) datasets were used for separate delineations of the Nam Co, Tibet catchment and its subcatchments, and these delineated areas were compared using the highest resolution dataset, TanDEM-X 12 m, as a baseline. The mean delineated catchment area was within 0.1% percent of the baseline delineation, with a standard error of the mean (SEM) that was 0.13% of the baseline. In a comparison of 49 subcatchment areas, TanDEM-X and ALOS datasets delineated similar areas, followed closely by SRTM 30 m, then SRTM 90 m, ACE2, and ASTER GDEM1. ASTER GDEM2 was a noteworthy outlier, having the largest mean subcatchment area that was nearly three times that of the baseline mean. Correlation coefficients were calculated for subcatchment parameters, SEM, and each DEM’s subcatchment area error. SEM had a weak but significant negative correlation with the mean and median slope. ASTER GDEM1 and GDEM2 were the only datasets that showed any significant correlations with the subcatchment environment variables, though these correlations were also weak. The 30 m posting ASTER GDEMs performed worse against the baseline than the other 30 m and 90 m datasets, showing that posting alone does not determine how good a dataset is. Our results show general small errors for catchment delineations, though there is the possibility for large errors, particularly in the older ASTER and SRTM datasets.

scholarly journals VALIDATION OF THE ASTER GLOBAL DIGITAL ELEVATION MODEL VERSION 3 OVER THE CONTERMINOUS UNITED STATES

2016 ◽  
Vol XLI-B4 ◽  
pp. 143-148 ◽  
Author(s):  
D. Gesch ◽  
M. Oimoen ◽  
J. Danielson ◽  
D. Meyer
Keyword(s):  
United States ◽  
Land Cover ◽  
Digital Elevation Model ◽  
Ground Level ◽  
Land Cover Type ◽  
Mean Error ◽  
Digital Elevation ◽  
The Mean ◽  
Vertical Accuracy ◽  
Elevation Model

The ASTER Global Digital Elevation Model Version 3 (GDEM v3) was evaluated over the conterminous United States in a manner similar to the validation conducted for the original GDEM Version 1 (v1) in 2009 and GDEM Version 2 (v2) in 2011. The absolute vertical accuracy of GDEM v3 was calculated by comparison with more than 23,000 independent reference geodetic ground control points from the U.S. National Geodetic Survey. The root mean square error (RMSE) measured for GDEM v3 is 8.52 meters. This compares with the RMSE of 8.68 meters for GDEM v2. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset from true ground level. The GDEM v3 mean error of −1.20 meters reflects an overall negative bias in GDEM v3. The absolute vertical accuracy assessment results, both mean error and RMSE, were segmented by land cover type to provide insight into how GDEM v3 performs in various land surface conditions. While the RMSE varies little across cover types (6.92 to 9.25 meters), the mean error (bias) does appear to be affected by land cover type, ranging from −2.99 to +4.16 meters across 14 land cover classes. These results indicate that in areas where built or natural aboveground features are present, GDEM v3 is measuring elevations above the ground level, a condition noted in assessments of previous GDEM versions (v1 and v2) and an expected condition given the type of stereo-optical image data collected by ASTER. GDEM v3 was also evaluated by differencing with the Shuttle Radar Topography Mission (SRTM) dataset. In many forested areas, GDEM v3 has elevations that are higher in the canopy than SRTM. The overall validation effort also included an evaluation of the GDEM v3 water mask. In general, the number of distinct water polygons in GDEM v3 is much lower than the number in a reference land cover dataset, but the total areas compare much more closely.

The influence of digital elevation model resolution on overland flow networks for modelling urban pluvial flooding

2009 ◽  
Vol 60 (12) ◽  
pp. 3137-3149 ◽  
Author(s):  
J. P. Leitão ◽  
S. Boonya-aroonnet ◽  
D. Prodanović ◽  
Č. Maksimović
Keyword(s):  
Digital Elevation Model ◽  
Overland Flow ◽  
Temporary Ponds ◽  
Flow Networks ◽  
Flow Paths ◽  
Digital Elevation ◽  
Pluvial Flooding ◽  
Generate Surface ◽  
Elevation Model ◽  
Urban Pluvial Flooding

This paper presents the developments towards the next generation of overland flow modelling of urban pluvial flooding. Using a detailed analysis of the Digital Elevation Model (DEM) the developed GIS tools can automatically generate surface drainage networks which consist of temporary ponds (floodable areas) and flow paths and link them with the underground network through inlets. For different commercially-available Rainfall–Runoff simulation models, the tool will generate the overland flow network needed to model the surface runoff and pluvial flooding accurately. In this paper the emphasis is placed on a sensitivity analysis of ponds and preferential overland flow paths creation. Different DEMs for three areas were considered in order to compare the results obtained. The DEMs considered were generated using different acquisition techniques and hence represent terrain with varying levels of resolution and accuracy. The results show that DEMs can be used to generate surface flow networks reliably. As expected, the quality of the surface network generated is highly dependent on the quality and resolution of the DEMs and successful representation of buildings and streets.

STUDY OF THE LANDSLIDE MORPHOLOGY BASED ON GNSS DATA AND AIRBORNE SOUNDING (ON THE EXAMPLE OF A SECTION OF THE PROTVA RIVER VALLEY)

2018 ◽  
Vol 12 (5-6) ◽  
pp. 50-57 ◽  
Author(s):  
I. S. Voskresensky ◽  
A. A. Suchilin ◽  
L. A. Ushakova ◽  
V. M. Shaforostov ◽  
A. L. Entin ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Geodetic Network ◽  
Aerial Survey ◽  
River Valley ◽  
Ease Of Use ◽  
Digital Elevation ◽  
Loose Deposits ◽  
Positioning Method ◽  
Landslide Body ◽  
Elevation Model

To use unmanned aerial vehicles (UAVs) for obtaining digital elevation models (DEM) and digital terrain models (DTM) is currently actively practiced in scientific and practical purposes. This technology has many advantages: efficiency, ease of use, and the possibility of application on relatively small area. This allows us to perform qualitative and quantitative studies of the progress of dangerous relief-forming processes and to assess their consequences quickly. In this paper, we describe the process of obtaining a digital elevation model (DEM) of the relief of the slope located on the bank of the Protva River (Satino training site of the Faculty of Geography, Lomonosov Moscow State University). To obtain the digital elevation model, we created a temporary geodetic network. The coordinates of the points were measured by the satellite positioning method using a highprecision mobile complex. The aerial survey was carried out using an unmanned aerial vehicle from a low altitude (about 40–45 m). The processing of survey materials was performed via automatic photogrammetry (Structure-from-Motion method), and the digital elevation model of the landslide surface on the Protva River valley section was created. Remote sensing was supplemented by studying archival materials of aerial photography, as well as field survey conducted immediately after the landslide. The total amount of research results made it possible to establish the causes and character of the landslide process on the study site. According to the geomorphological conditions of formation, the landslide refers to a variety of landslideslides, which are formed when water is saturated with loose deposits. The landslide body was formed with the "collapse" of the blocks of turf and deluvial loams and their "destruction" as they shifted and accumulated at the foot of the slope.

Sign in / Sign up

Export Citation Format

Share Document