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Basics of Soil Erosion
Published in Abrar Yousuf, Manmohanjit Singh, Watershed Hydrology, Management and Modeling, 2019
Manmohanjit Singh, Kerstin Hartsch
Gully erosion is a highly visible form of soil erosion that affects soil productivity, restricts land use and can threaten roads, fences and buildings. The large channels that cannot be removed by tillage are called gullies. A large gully is also called a ravine. Gullies are relatively steep sided watercourses which experience ephemeral flows during heavy or extended rainfall. A gully channel may be U or V shaped depending upon the strength of the sub soils’ resistance or its resistance to water’s cutting action. Gullies are formed when the surface and sub soil materials are uniformly weak. V shaped gullies are formed when the sub soil is more resistant to erosion than the surface soil. Gullies are having relatively greater death and smaller width, carry large sediment loads and display very erratic behaviour so that relationships between sediment discharge and run off are frequently poor. Gully erosion has become a field of growing interest among the research community but there sre still are numerous knowledge gaps that need to be addressed (Castillo and Gomez 2016).
Water Resources Engineering
Published in P.K. Jayasree, K Balan, V Rani, Practical Civil Engineering, 2021
P.K. Jayasree, K Balan, V Rani
Sheet erosion is the uniform removal of soil without the development of visible water channels. It is the least apparent of the four erosion types. Rill erosion is soil removal through the cutting of many small, but conspicuous, channels. Gully erosion is the consequence of water that cuts down into the soil along the line of flow. Gullies develop more quickly in places like animal trails, plow furrows, and vehicle ruts. Tunnel erosion may occur in soils with sublayers that have a greater tendency to transport flowing water than does the surface layer.
Global Climate Change Impacts on Watershed Hydrology
Published in Moonisa Aslam Dervash, Akhlaq Amin Wani, Climate Change Alleviation for Sustainable Progression, 2022
Vishnu Prasad, Abrar Yousuf, Parminder Singh Sandhu
The change in precipitation is projected to impact soil erosion directly, in terms of rainfall amount, intensity and spatiotemporal distributions. Impacts of the change in rainfall temporal distributions are often combined with the effects of land use. For example, if the frequency of precipitation changes overlapping planting dates or if precipitation increases in winter when vegetation is lesser, soil degradation is likely to increase due to less protection and increased rainfall force (Garbrecht and Zhang, 2015; O’Neal et al., 2005; Serpa et al., 2015; Zhang and Nearing, 2005). The longer rainfall duration could also reduce solar radiation and therefore harm plant growth, resulting in less cover and increased soil erosion (Wang et al., 2015). Spatial rainfall variability also contributes to varying soil erosion patterns. Soil erosion can be indirectly affected in various ways by rising temperature. When atmospheric carbon dioxide levels and temperatures increase, evapotranspiration rates increase and soil moisture decreases, which increases the soil's infiltration capacity and reduces runoff and soil erosion. Increasing the concentration of CO2 in the atmosphere can also contribute to increased production of plant biomass (Rosenzweig and Hillel, 1998), which also helps to increase canopy interception and reduce runoff and soil erosion. Water erosion mainly includes rain-splash erosion and gully erosion (McCool and Williams, 2008). Splash erosion takes place under erosive raindrops. Gully erosion occurs when runoff accumulates and removes the soil from narrow channels to considerable depths (Poesen et al., 2003). Rain-splash erosion mainly causes soil detachment within a certain distance of the raindrop while gully erosion can cause off-site sediment transport and deposition. Gully erosion is the main form of water erosion in many places around the world, including the USA, Australia, Europe, China and Ethiopia (Valentin et al., 2005). The close relationship between high intense rainfall and water erosion is due to (1) the high erosivity of raindrops in convective storms causes detachment of soil particles and subsequently splash erosion (Mohamadi and Kavian, 2015); (2) the high-intensity rainfall causes infiltration excess runoff that accumulates and removes the soil from narrow channels to considerable depths, thus leading to gully erosion (Poesen et al., 2003). Infiltration excess runoff, or Hortonian runoff takes place when high-intensity rainfall arrives at a rate greater than the infiltration capacity of the soil. Areas that are susceptible to gully erosion caused by Hortonian runoff are generally in semi-arid and sub-humid regions. In these climatic regions, Hortonian runoff is often responsible for the majority of soil erosion (Baartman et al., 2012). Wang et al. (2016) reported that rainfall regimes that featured short-duration and high-intensity caused 55% to 68% of soil loss in Beijing, where the climate is semi-humid
Selected AI optimization techniques and applications in geotechnical engineering
Published in Cogent Engineering, 2023
Kennedy C. Onyelowe, Farid F. Mojtahedi, Ahmed M. Ebid, Amirhossein Rezaei, Kolawole J. Osinubi, Adrian O. Eberemu, Bunyamin Salahudeen, Emmanuel W. Gadzama, Danial Rezazadeh, Hashem Jahangir, Paul Yohanna, Michael E. Onyia, Fazal E. Jalal, Mudassir Iqbal, Chidozie Ikpa, Ifeyinwa I. Obianyo, Zia Ur Rehman
The findings showed that RF recorded the most exceptional output and was recommended to model the GES, not only for the area studied, but also for areas with similar geo-environmental conditions. From the recommended model, rainfall and elevation contributed the most vital factors to gully erosion. Similarly, Seyed et al. (2020) used four different algorithms namely, Logistic Ratio (LR), Frequency Ratio (FR), Imperialist Competitive Algorithm (ICA) and Ensemble of radial Basis Function (RBF) to evaluate a developed gully erosion susceptibility map (GESM). The authors considered twelve (12) variables as factors affecting gully erosion which were prepared in Geographic Information System (GIS) environment. The results showed that LR model was the best among the models considered and slope aspect factor was the most critical factor that caused gully erosion, while lithology is the least critical factor that caused gully erosion.
Head-cut gully erosion susceptibility modelling based on ensemble Random Forest with oblique decision trees in Fareghan watershed, Iran
Published in Geomatics, Natural Hazards and Risk, 2020
Quoc Bao Pham, Kaustuv Mukherjee, Akbar Norouzi, Nguyen Thi Thuy Linh, Saeid Janizadeh, Kourosh Ahmadi, Artemi Cerdà, Thi Ngoc Canh Doan, Duong Tran Anh
Gully erosion is a threat to the sustainability of the many regions of the world as they trigger soil erosion and then land degradation as a consequence of the lowering of soil productivity. Gully development also hampers the economic activities and threat the agriculture productivity and human development. Therefore, proper identification and forecasting of head cut gully erosion zones is much essential for the protection and management of the land resource. The scientific community is working to develop gully erosion prediction using various quantitative techniques. Machine learning models and their ensemble with hybrid meta-classifiers are giving very good result as these are able to overcome the challenges of over-fitting and noise. In this study, three machine learning based models (i.e., SVM, RF and Oblique RF) have been used and all of them have performed accurately. The validation metrics like sensitivity, specificity, PPV, NPV and AUC have shown that all these models are excellent to predict both the gully erosion and non-erosion prone zones with high accuracy and among them Oblique RF has become the best, which is the recommended for future researches. From the case study of Farghan watershed we conclude that selecting suitable variables and coupling machine learning with GIS is the best option for heat cut gullies mapping. The susceptible maps produced by this study will surely help the planners and decision makers for the protection and management of erosion prone zones.
A GIS-based simulation and visualization tool for the assessment of gully erosion processes
Published in Journal of Spatial Science, 2022
Adel Omran, Dietrich Schröder, Christian Sommer, Volker Hochschild, Michael Märker
Soil erosion by water, such as gullying, is acknowledged as a global main driver of land degradation (Park et al. 2009). Gully erosion is typically defined as a deep channel that has been eroded by concentrated water flow, removing surface soils and materials (Torri et al. 2018). Gullies are distinguished from rills based on a critical cross-sectional area that corresponds to the size of the channel that can no longer be erased by normal tillage operations (Baade 1994, Bull and Kirkby 1997). Gully erosion is related to a variety of on-site and off-site damages, particularly impacting agricultural areas. On-site damages include the direct loss of arable land resulting in significant soil losses, reduced soil fertility, loss of crops and vegetation cover, as well as damages to infrastructures such as roads, power lines and communication networks (Ionita 2006, Haregeweyn et al. 2008a, Hayas et al. 2017). As an outcome of their high erosion rates, gullies enhance the connectivity of slope systems and lead to an increased sediment delivery. Estimates indicate that gullies are accountable for up to 80% of a catchment’s mean sediment yield (e.g. Flügel et al. 2003, Maerker 2001; Vanmaercke et al. 2012). In particular, the produced sediments washed into the drainage network are related to off-site damages including the reduction of water quality within the adjacent river systems. Moreover, the gully-related sediments can be a transport medium for chemical, physical and biological pollutants. This strongly impairs freshwater ecosystems and their ecosystem services (e.g. Kroon et al. 2016) and leads to increased costs in physical, chemical and biological water treatment in order to provide drinking water as well as water for industrial (e.g. cooling, hydropower) and agricultural use (irrigation) (e.g. Zabihi et al. 2018).