Geomorphometry is a quantitative land surface analysis science that could be applied to compute land surface characteristics (for example slope, aspect, topographic wetness index, and so on) and objects (such as a watershed line, cirque, alluvial fan, drainage network, and so on) (Beheshti Javid et al., 2018; Hengl & Evans, 2009). Analysing basin morphometry and delineating watershed are important in river basin studies because it provides essential information about the drainage networks (Abdeta et al., 2020), topographic factors (Nikolova et al., 2021), geology (Ghosh et al., 2020), and climatic (Gebremeskel & Kebede, 2018) features of the basin. As a consequence, numerous researchers across the world have been determining the morphometric properties of basins in respect of better understand the physical aspects of their research regions and obtain thorough information concerning them.
Several methodologies and techniques may be used in basin studies to extract borders, drainage networks, and morphometric characteristics. While some researchers choose conventional methods such as topographical maps and field surveys to support their investigations, others prefer modern methods such as GIS-produced DEMs and digital surface models (DSMs) and remote-sensing techniques (Bove et al., 2020; Rogers et al., 2020). DEMs could be acquired from a variety of sources, including topographic maps, DGPS field surveys, radar interferometry, satellite data, drones, and contour maps. Satellite-based DEMs have grown admiration resulting from their accessibility and ease of usage. More improved resolutions and open access to DEMs have become accessible in the last decade, such as the Advanced Spaceborne Thermal Emission and Refection Radiometer (ASTER) (version 2, 30 m), SRTM with 90 m and 30 m, Advanced Land Observing Satellite (ALOS), Panchromatic Remote-sensing Instrument for Stereo Mapping—30 m (PRISM). As a result, DEM and DSM are sophisticated techniques that can accurately compute features. The use of remote sensing data in this regard is very effective as GIS and image-processing techniques can be functional for demarcation of morphological parameters of the basin and drainage patterns (Tribhuvan & Sonar, 2016). DEMs have been frequently utilised in basin morphometric investigations. The spatial resolution of DEMs influences their capacity to reveal surface topography characteristics (López-Vicente & Álvarez, 2018). High-resolution DEMs can give more comprehensive topographic information (H. Zhao et al., 2017).
A watershed is an area that acts as a catchment for water to convey the water to common outlets (Bajjali, 2018). It is a fundamental hydrologic unit used for hydrologic design and for studying the movement, distribution, quality, and quantity of water in a specific area (Bajjali, 2018). Watershed properties are important for determining and predicting hydrological systems as well as for designing watershed management strategies (Liu et al., 2016). Accurate delineation of watersheds is important for simulating runoff and drainage (Li et al., 2019). However, because of large depressions and subtle elevation differences on a local scale it is difficult to derive an accurate river network from conventional Digital Elevation Model (DEM) processing methods (Lai et al., 2016; Li et al., 2019). Satellite images in combination with different algorithms and analysis techniques are helpful in this regard to developing more accurate watersheds and river networks (Lai et al., 2016; Li et al., 2019).
Watershed parameters constitute the basic units for monitoring the health of the watershed as well as understanding natural resources and environmental issues (Hazbavi, 2018). Using a Geographic Information System (GIS) to analyze morphometric parameters such as stream ordering has been shown in studies to be a useful method for studying the hydrological behaviours of watersheds (Kumar et al., 2018). These parameters, such as basin area, bifurcation ratio, and sinuosity of a stream channel all have direct impact the storm hydrograph and the magnitude of peak and mean runoff (Chorley, 2019). The drainage characteristics show the effect of these drivers' variance from location to location. Detailed morphometric investigations shed light on basin succession and the function of drainage morphometry in the formation of landforms and their features. The slope, size, form, drainage density, and length of streams are all physiographic features of drainage basins that can be linked to several significant hydrologic phenomena and it's an important technique in any hydrological research, such as identification of groundwater potential zone, paedology, environmental evaluation, and it's a topic that both geomorphologists and hydrologists are interested in (Kumar et al., 2018; Sahu et al., 2018). The morphometric parameters are used to define and compare the basin traits and processes that illustrate the drainage basin's geologic and geomorphic evolution (Strahler, 1964). Understanding the dynamics of a watershed requires morphometric study. Basically, drainage basin morphometry aims to illustrate and forecast long-term basin dynamics that lead in morphological changes within the basin (Mahala, 2020), as well as to outline physical changes in the drainage system through time in consequence to natural or human interruptions (Kuntamalla et al., 2018).
Morphometric investigation has been widely used as an indirect technique for soil estimation, groundwater movement prediction, landslide susceptibility mapping, and topography analysis in earth science and engineering domains (Basu & Pal, 2019). This work aims to examine the morphometric characteristics and delineate the watershed using the SRTM DEM, which can have better precision than the ASTER GDEM (Elkhrachy, 2018; Khasanov, 2020). Although, the present compares the accuracy of ASTER GDEM and SRTM DEM to compute and delineate watershed and its morphometric features. Both Ozdemir and Bird (2009) and Karabulut and Özdemir (2016) used a 1:25.000 scaled topographic map and a 10 m resolution DEM to create drainage networks. They used this DEM as a baseline for analysing the performance of the ASTER GDEM (30 m) and SRTM DEM analyses (30 m). In addition to SRTM (90 m), ASTER GDEM (30 m), and CartoDEM, Das et al. (2016) employed DEMs generated from 1:50.000 and 1:250.000 topographic maps. DEMs generated from a 1:50.000 topographical map and ASTER GDEM V2 data have been considered to be more reliable and dependable in regards to absolute accuracy in their analysis. For the appropriate management and planning of watersheds, Ahmed et al. (2010) evaluated certain morphometric characteristics generated from topographic maps (1:50,000), ASTER DEM (30 m), and SRTM DEM (90 m). They came to the conclusion that both the ASTER and SRTM datasets produce satisfactory findings, and that the DEM cell size is also essential. Zhao et al. (2011) Topography maps were used to test the efficacy of ASTER DEM (30 m) and SRTM DEM (90 m) in expressing elevation data. In certain locations, both the ASTER and the SRTM produced comparable findings, while the ASTER failed in flat or slightly sloping terrain.
The low elevation terrain of coastal Bangladesh, combined with the abundance of rivers and the monsoon season, makes the region extremely vulnerable to natural disasters (Rahman & Rahman, 2015). The south-eastern hilly region is highly susceptible to flash flooding following heavy rainfall events. As a result, a thorough study of the river basins in this region, which are dominated by the Karnaphuli and Sangu rivers, is essential (Adnan et al., 2019). The Chittagong seaport plays the biggest role in the economy of Bangladesh; hence, the importance of understanding the Karnaphuli River is undeniable (S. K. Roy & Navera, 2018). However, waterlogging due to intense rainfall events is a longstanding problem in Chittagong city and the region covered by the Karnaphuli River basin (Mahmood & Matin, 2018). Progressive changes in the landscape within the basin, and the reduction of drainage capacity for various reasons, along with the impacts of climate change, make the situation even worse (Masum et al., 2020). Number of studies have been carried out focusing on flash flood susceptibility, land use-land cover, morphological changes, water security, contamination, flow parameters, and economic development in the estuary of the Karnaphuli River (Adnan et al., 2019; Akter & Tanim, 2021; Alam & Hossain, 2020; Ali et al., 2016; Islam et al., 2017; S. K. Roy & Navera, 2018; Sultana et al., 2020), which indicate the importance of this region (Akter & Tanim, 2021). In a watershed, the catchment is the lowest spatial entity of the delineated region where collective management of water can be implemented (Akram et al., 2012). Also, DEMs are very applicable to various aspects, where this is one of the most primary conditions for diverse applications, where they are mostly useful in areas that are derived from detailed topographic outline (Kim & Kang, 2001; Vadon, 2003).
The major goal of this research is to find out, "Which form of digital elevation model offers realistic results in terms of surface morphology and morphometry?" Even, no such studies have been undertaken in the study area and also very rare studies have been conducted in Bangladesh. Most of the studies have to rely on the watershed and drainage network as their basis. Therefore, it is important to improve the understanding and accuracy of the watershed and drainage patterns that underpin all of the studies. Continuous improvement in this regard is necessary, which is why this study has been carried out with the overall objective of enhancing the current understanding of the Karnaphuli River and its basin area. Specifically, this study was conducted to outline the catchment delineation and evaluate the drainage network of the Karnaphuli River in Chittagong, Bangladesh using DEM data and GIS techniques. By studying the morphometric analysis utilizing Remote Sensing and GIS, the current study elucidates the varied drainage characteristics of one of the watersheds of the Karnaphuli Water Basin in Chittagong. The research will help researchers better understand the hydrological behaviour of the watershed, including different climatic factors.