Suitability of open-access elevation models for micro-scale watershed planning

Abstract

Watershed planning is a major issue in Turkey and other parts of the world. Surrounded by seawater on almost three-quarters of its international borders and by sheer mountains along the coastal regions and throughout the country, Turkey experiences a range of climatic changes, which constantly shape its topography. Recently, the occurrences of floods, landslides, and torrents have increased, forcing decision-makers to come up with solutions to manage and rehabilitate the upper watersheds in order to stop or limit the impact of disasters on downstream areas. Possible solutions should reduce flow coefficients, erosion, and sedimentation and increase reservoir capacities. It is expected that torrent volumes will decrease, drainage regimes on slopes will be better organized and adjusted, thawing snow will be better deposited and delayed, evapotranspiration will increase, surface runoffs will be delayed, and water regimes will be better managed, meaning that flood and torrent control will be achieved. For the reasons mentioned above, watershed parameters need to be firmly set. In the scope of this study, the elevation, slope acreage, and reservoir capacity of a small watershed, as extracted from open-access elevation models, were compared to a real-time kinematic (RTK) global positioning system (GPS)-generated point cloud and the resulting elevation model through various geospatial and analytical means. The Shuttle Radar Topography Mission (SRTM) C-band digital elevation model (DEM) (version 3) proved to be a satisfactory method in making residual, correlation, mean, and reservoir capacity comparisons. An L-band Advanced Land Observing Satellite (ALOS) phased-array-type synthetic aperture radar (PALSAR) and an X-band DLR_SRTM ASTER were slightly superior methods in terms of defining a greater number of slope categories than the other models. Finally, DLR_SRTM and SRTMv3 could match a greater number of slope façades than the other models. Seventeen years after its acquisition, SRTM and its derivatives have continued leading the topographic definition of the Earth.

Enhancing the GDEMs of Egypt Using a Surface Subtraction Approach

“…Table 2 illustrates the parameters of the regression models and the R square for the three GDEMs based on the 500 control points. The new height values (H enh ) at the 390 check points were determined for validation using Equation (1). The errors between the observed height values (H ob ) and the enhanced height values (H enh ) at the check points were calculated using Equation (2):…”

“…Comprehensive information about the elevation of ground points is of profound importance for many fields of civil works including; gravity field modelling, topographic mapping, imageries ortho-rectifying and hydrological modelling studies. Planning irrigation networks, determining optimal dam locations, simulating floods, calculating cut and fill volumes, determining storage capacity of reservoirs, and many more are among the applications in water resource management works that require ground elevation information [1]. The Digital Elevation Model (DEM), as a digital representation of the Earth's surface and a description of its height, is a common source of ground level information [2].…”

Global Digital Elevation Model Comparison Criteria: An Evident Need to Consider Their Application

“…For example, ref. [117] is focused on the suitability of GDEMs for microscale watershed planning, and three watershed-defining parameters (elevation, slope, and reservoir capacity) were tested in order to determine which performs better. Below are some examples of fitness for use.…”

Determination of Some Stand and Site Parameters Influencing the Snow Damage in Trees: A Case Study of Boyabat Forest Enterprise, Turkey

“…One seriously damaged compartment from both Yedicam and Burnuk forest directorates was compared to a similarly conditioned and structured control compartment in the respected directorate. Thirty 800 m 2 circular sample plots were randomly selected from each compartment, and the following parameters were measured and computed; -Quadratic mean diameter (dq, cm), was calculated for each sample plot after the diameter at breast height (dbh, cm) had been measured for all the trees included within the sample plots, -Stand age (t, year) was determined through the averaging of number of tree rings from increment cores acquired from eight to ten trees within the sample plots, -For each sample plot, aspect, slope, elevation and terrain roughness values were extracted from digital elevation model(s) (Altunel, 2018) i. e. flat, east, west, north, south; 0-10% (1), 10-30% (2), >30% (3); 1000-1200m (1), 1200-1400m…”