Identification Of Watersheds Research Articles

Watershed prioritization and hydro-morphometric analysis for the potential development of Tabuk Basin, Saudi Arabia using multivariate statistical analysis and coupled RS-GIS approach

The Tabuk province of Saudi Arabia (SA) has an arid zone, few aquifers, high groundwater salinity (seawater intrusion), and accelerated population, industrial, and agricultural development. The development of Tabuk Basin is essential for the addition of new freshwater resources and the enhancement of aquifer recharge potential. The hydrological characteristics of the drainage basin aid in the identification of watersheds, enabling the protection and management of land erosion and ground/surface water resources. This study analyzed hydro-morphometric data from the eighteen sub-basins of the Tabuk Basin using multivariate statistical approaches and coupled remote sensing (RS) and geographic information systems (GIS) for water priority determination. The results show that the four principal components(PC1-4) have a variance of90.4% concerningbifurcation ratio (Rb), ruggedness number (Rn), elongation ratio (Re), drainage density (Dd), basin relief (Bh), circularity ratio (Rc), and relief ratio (Rh). The Al Ula, Thaibah, Hamd, Dama, Al Wajh, Al Ghamra, and Azlam sub-basins showed the highest priority, indicating soil erosion and the necessity for mitigating measures to reduce infrastructure damage. Mostexposed geology (67%) exhibited strong permeability and good infiltration (sedimentary cover and Quaternary sediments). The rest(23%) showed low to medium permeability(igneous, metamorphic, and carbonate rocks). The bestpromisingsitesfor building new wells can reduce surface runoff and soil erosion through aquifer infiltration and abstraction. The aquifer potentiality map was accomplished for Al Ula, Thaibah, Hamd, and Dama drainage basins. The most prospective groundwater investigation regions were identified, coincidingwith the drilled wells that confirmed and validated the results. The estimated zones of high to very high aquifer potentiality were used to add additional wells for investment reduce soil erosion, mitigate alternatives, agriculture,urbanization, etc. The other sub-basins have a medium to low priority, with less soil erosion and aquifer recharge.

SRTM resample with short distance‐low nugget kriging

The shuttle radar topography mission (SRTM), was flow on the space shuttle Endeavour in February 2000, with the objective of acquiring a digital elevation model of all land between 60° north latitude and 56° south latitude, using interferometric synthetic aperture radar (InSAR) techniques. The SRTM data are distributed at horizontal resolution of 1 arc‐second (∼30 m) for areas within the USA and at 3 arc‐second (∼90 m) resolution for the rest of the world. A resolution of 90 m can be considered suitable for the small or medium‐scale analysis, but it is too coarse for more detailed purposes. One alternative is to interpolate the SRTM data at a finer resolution; it will not increase the level of detail of the original digital elevation model (DEM), but it will lead to a surface where there is the coherence of angular properties (i.e. slope, aspect) between neighbouring pixels, which is an important characteristic when dealing with terrain analysis. This work intents to show how the proper adjustment of variogram and kriging parameters, namely the nugget effect and the maximum distance within which values are used in interpolation, can be set to achieve quality results on resampling SRTM data from 3” to 1”. We present for a test area in western USA, which includes different adjustment schemes (changes in nugget effect value and in the interpolation radius) and comparisons with the original 1” model of the area, with the national elevation dataset (NED) DEMs, and with other interpolation methods (splines and inverse distance weighted (IDW)). The basic concepts for using kriging to resample terrain data are: (i) working only with the immediate neighbourhood of the predicted point, due to the high spatial correlation of the topographic surface and omnidirectional behaviour of variogram in short distances; (ii) adding a very small random variation to the coordinates of the points prior to interpolation, to avoid punctual artifacts generated by predicted points with the same location than original data points and; (iii) using a small value of nugget effect, to avoid smoothing that can obliterate terrain features. Drainages derived from the surfaces interpolated by kriging and by splines have a good agreement with streams derived from the 1” NED, with correct identification of watersheds, even though a few differences occur in the positions of some rivers in flat areas. Although the 1” surfaces resampled by kriging and splines are very similar, we consider the results produced by kriging as superior, since the spline‐interpolated surface still presented some noise and linear artifacts, which were removed by kriging.