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The automated recognition of landforms holds significant importance within the framework of digital geomorphological mapping, serving as a pivotal focal point for research and practical applications alike. Over the last decade, various methods have been developed to achieve this goal, ranging from grid-based to object-based approaches, covering a range from supervised to completely unsupervised techniques. Furthermore, the vast majority of the methods mentioned depend on Digital Elevation Models (DEMs) as their primary input, highlighting the crucial significance of meticulous preparation and rigorous quality assessment of these datasets. In this study, we compare the outcomes of grid-based methods for landforms extraction and surficial process type assessment, leveraging various DEMs as input data. Initially, we employed a photogrammetric Digital Terrain Model (DTM) generated at a regional scale, along with two LiDAR datasets. The first dataset originates from an airborne survey conducted by the national government approximately a decade ago, while the second dataset was acquired by UAV as part of this study's framework. The results highlight how the higher resolution and level of detail of the LiDAR datasets allow the recognition of a higher number of features at higher scales; but, in contrast, generally, a high level of detail corresponds with a higher risk of noise within the dataset, mostly due to unwanted natural features or anthropogenic disturbance. Utilizing these datasets for generating geomorphological maps harbors significant potential in the framework of natural hazard assessment, particularly concerning phenomena associated with geo-hydrological processes. [ABSTRACT FROM AUTHOR]

Understanding natural phenomena with the help of modern scientific approaches helps to reach sustainable solutions for current and future water-related problems. In this context, present study aims to assess relative influencing level of physical factors in controlling groundwater level, using a novel grid-based delineation technique, in Lower Palar River Basin, in Kanchipuram and Chengalpattu districts of South India. The influencing factors viz-a-viz: rainfall, soil texture, land use/land cover, terrain slope, geomorphology, lithology, and drainage characteristics were considered for the study. Archived data (2011 to 2020) of monthly rainfall at four rain gauge stations and monthly groundwater level of 22 locations, soil texture, lithology, and geomorphology data were considered for the study. SRTM digital elevation model with 30-m resolution was used for analyzing drainage characteristics and terrain slope. Thematic maps for considered factors were prepared, using common grid delineation method in GIS platform that divided study area into 52 grids, to inter-relate the discrete and continuous parameters with groundwater level. Results indicate that level of influence increases in the order of precipitation followed by lithology, land use/land cover, terrain slope, geomorphology, infiltration number, and soil texture. The study shows groundwater resilience is highly influenced by soil texture and infiltration number compared to other factors considered. It can be concluded that grid-based delineation successfully identifies grids with significant influence of individual factors by comparing with groundwater resilience. Common grid-based delineation method proves to be more effective in assessing groundwater resilience and can be used more efficiently in groundwater studies. [ABSTRACT FROM AUTHOR]

A 0.5-degree grid-based assessment of the scarcity of global water resources including virtual water trading has been made. The three components of water availability considered for each grid were local runoff, routed flow from upstream and virtual water trading. Several assumptions were postulated to convert country-base estimations of virtual water trading to grid values. The results show that unequal spatial distribution of global water resources had been considerably neutralized by virtual water trading. A large proportion of people in the Middle-East, North-Africa and Sub-Sahara region are able to relieve their water stress through virtual water import. The paper also reports two hypothetical scenarios with extremes of natural flow availability based on the presence and absence of routed upstream flow. [ABSTRACT FROM AUTHOR]