Advanced Tools for Studying Soil Erosion Processes. Erosion Modelling, Soil Redistribution Rates, Advanced Analysis, and Artificial Intelligence

Table of Contents

Part-I Erosional processes and impacts 1. Mapping land subsidence using time-series analysis of Sentinel-1 InSAR in various land use areas 2. Use of hydrological models in erosion and sediment studies: a review 3. Comprehensive introduction to Digital Elevation Models, as a key dataset in soil erosion mapping 4. Eco-geomorphic reconstruction and illustration of the erosional landforms from a geomorphological point of view 5. Extraction of water bodies using machine learning and water body indices in an arid region, comparison, and application: A case study Naser Lake Egypt 6. Leveraging remote sensing data and machine learning models to estimate suspended sediment concentration (SSC), a vital water quality parameter to assess soil erosion effects 7. The messianic tail of cyanobacteria: Revival role of microbial biological crust on restoring degraded soils 8. Analyzing the homogeneity of the paired catchments using the fractal dimension of the drainage network and catchment shape 9. Fractal analysis of drainage network and its relationship with flooding potential in arid areas 10. Climate change and soil erosion dynamics: An overview 11. Mapping rangeland vegetation types sensitive to soil erosion in semi-arid of Iran Part-II Advanced computing techniques to quantify soil erosion 12. Event-based soil erosion estimation in a tropical watershed using OpenLISEM 13. A scenario-based approach for modeling and monitoring the impacts of climate change on forest fire using MODIS time series images 14. Soil erosion analysis based on UAV and SPOT-6 satellite images 15. Gully erosion susceptibility assessment using machine learning methods and geostatistical multivariate approach 16. Land subsidence modeling and mapping in Darab region, Iran 17. Review of multihazards research with the basis of soil erosion 18. Prediction of soil erosion using machine learning 19. Artificial Intelligence including Machine Learning and Deep Learning algorithms 20. Understanding piping process on large dimension piping: Erosion versus weathering 21. Quantile random forest technique for soil moisture contents digital mapping, Sarvestan Plain, Iran 22. Modeling spatial variability of soil loss tolerance (T-value) using geostatistical approaches (case study: Dorudzan Watershed, Fars Province, Iran) Part-III Methods of soil analysis 23. Potential of spectroscopy-based approaches for predicting soil erosion-related parameters: A short review 24. Spatiotemporal variations in land use of Mahvelat plain in Iran using Google Earth Engine from 2011 to 2030 25. Detecting soil salinization, sodicity, and alkalization hazards within cultivated lands using digital soil mapping approaches 26. The impact of geomorphological hazards (i.e., mass movements/landslides) on soil erosion 27. Involvement of erosion processes in the development of landslides in the locality of Echiock-Santchou (West Cameroon) 28. Digital mapping of soil pH in arid and semi-arid regions 29. Unraveling the spatial signature of gully erosion in the arid and semi-arid regions of the northeast of Iran: Every single factor matters! 30. Soil erosion monitoring using the perpendicular soil moisture index as a remote sensing index (case study: Salehiya Wetland, Iran) 31. Scrutinizing of soil erosion spatial distribution through explicit spatial HRU approaches in SWAT model 32. Application of ANSWERS model for calculating runoff and sediment prediction from steep agricultural watersheds in northern Iran and its comparison with the other related models 33. Susceptibility of the erosional landforms (Case study: Razavi Khorasan Province, Iran)

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Authors

Hamid Reza Pourghasemi Professor, Department of Natural Resources and Environment Engineering, College of Agriculture, Shiraz University, Shiraz, Iran. Hamid Reza Pourghasemi is a professor of watershed management engineering in the College of Agriculture, Shiraz University, in Iran. His main research interests are GIS-based spatial modelling using machine learning/data mining techniques in different fields such as landslides, floods, gully erosion, forest fires, land subsidence, species distribution modelling, and groundwater/hydrology. Professor Pourghasemi also works on multi-criteria decision-making methods in natural resources and environmental science. He has published over 230 peer-reviewed papers in high-quality journals and seven edited books for Springer and Elsevier and is an active reviewer for over 90 international journals. He was selected as one of the five young scientists under 40 by The World Academy of Science (TWAS 2019) and was a highly cited researcher in 2019 and 2020 Narges Kariminejad PhD Researcher, Department of Natural Resources and Environment Engineering, College of Agriculture, Shiraz University, Shiraz, Iran. Narges Kariminejad is a geomorphologist with about 10 years of work experience in field and laboratory-based soil erosion research in arid and semi-arid environments. She is also currently a researcher at the Department of Natural Resources and Environment Engineering in the College of Agriculture at Shiraz University, in Iran. Her research interests are in soil erosion, especially in rill, soil piping, and gully erosion. She has served as a guest scientist or visiting researcher at various research institutes and universities in different countries all over the world. Dr. Kariminejad has been a guest lecturer in difference courses, including quantitative geomorphology, spatial analysis and satellite imagery, plant ecology, and geostatistics. She has published more than 20 papers in international scientific journals.