Fate of Soil Carbon Transported by Erosional Processes

The accelerated process of soil erosion by water and wind, responsible for transport and redistribution of a large amount of carbon-enriched sediments, has a strong impact on the global carbon budget. The breakdown of aggregates by erosivity of water (raindrop, runoff) and wind weakens the stability of soil C (organic and inorganic) and aggravates its vulnerability to degradation processes, which lead to the emission of greenhouse gases (GHGs) including CO2, CH4, and N2O, depending on the hydrothermal regimes. Nonetheless, a part of the eroded soil C may be buried, reaggregated and protected against decomposition. In coastal steep lands, (e.g., Taiwan, New Zealand) with a short distance to burial of sediments in the ocean, erosion may be a sink of C. In large watersheds (i.e., Amazon, Mississippi, Nile, Ganges, Indus, etc.) with a long distance to the ocean, however, most of the C being transported is prone to mineralization/decomposition during the transit period and is a source of GHGs (CO2, CH4, N2O). Land use, soil management and cropping systems must be prudently chosen to prevent erosion by both hydric and aeolian processes. The so-called plague of the soil, accelerated erosion by water and wind, must be effectively curtailed.

Application of Angot precipitation index in the assessment of rainfall erosivity: Vojvodina Region case study (North Serbia)

The paper aims to provide an overview of the most important parameters (the occurrence, frequency and magnitude) in Vojvodina Region (North Serbia). Monthly and annual mean precipitation values in the period 1946–2014, for the 12 selected meteorological stations were used. Relevant parameters (precipitation amounts, Angot precipitation index) were used as indicators of rainfall erosivity. Rainfall erosivity index was calculated and classified throughout precipitation susceptibility classes liable of triggering soil erosion. Precipitation trends were obtained and analysed by three different statistical approaches. Results indicate that various susceptibility classes are identified within the observed period, with a higher presence of very severe rainfall erosion in June and July. This study could have implications for mitigation strategies oriented towards reduction of soil erosion by water.

Geomorphic Control on Soil Erosion – a Case Study in the Subarnarekha Basin, India

<p>Geomorphology depicts the qualitative and quantitative characteristics of both terrain and landscape features combined with the processes responsible for its evolution. Soil erosion by water involves processes, which removes soil particles and organic matter from the upper sheet of the soil surface, and then transports the eroded material to distant location under the action of water. Very few studies have been conducted on the nature and dynamics of soil erosion in the different geomorphologic features. In the present investigation, an attempt has been made to assess the control of geomorphologic features on the soil loss. Universal Soil Loss Equation (USLE) was used to determine soil loss from the various geomorphological landforms. Principal component analysis (PCA) was implemented on the USLE parameters to determine the degree of association between the individual principal components and the USLE-derived soil loss. Results obtained from the investigation signify the influence of the various landforms on soil erosion. PC5 is found to be significantly correlated with the USLE-derived soil loss. The results ascertained significant association between the soil loss and geomorphological landforms, and therefore, suitable strategies can be implemented to alleviate soil loss in the individual landforms.</p>

Advances in techniques to assess soil erodibility

Soil erodibility is the susceptibility of soil to the erosive forces of rainsplash, runoff and wind. It is a significant factor in determining present and future soil erosion rates. Focusing on soil erosion by water, this chapter shows that erodibility is determined by static and dynamic soil properties that control a range of sub-processes affecting soil erosion, but there is no standardised test procedure, making comparison of erodibility assessment techniques and their results challenging. Most researchers agree that aggregate stability is the best indicator of soil erodibility. Selection of techniques to measure aggregate stability need to consider the type of disruptive forces and breakdown processes to which field aggregates are subjected. New indices must incorporate spatial and temporal variabilities in erodibility; the different erosion processes operating; the impact of climate change; and the role of soil biology. New analytical techniques such as computer aided tomography show promise in considering soil erodibility as a dynamic continuum operating over 3 dimensions.

REVISITING THE METHODOLOGICAL DEVELOPMENT IN SOIL EROSION RESEARCH

Soil erosion (by water) is a major land degradation process that may threat the Sustainable Development Goals (SDG) by its negative impact on environment and human well-being. Soil erosion research demands scientific methods, tools and techniques to assess soil erosion with more accuracy and reliability. Soil erosion research has had experienced crude field-based techniques in early twentieth century to model-based approaches since the 1970s and very recent machine learning and artificial intelligence models to predict soil erosion susceptibility and risk. The paper aims to review the trend in methodological development in soil erosion by water through time. The brief background of different approaches, their relative advantages and disadvantages are reviewed. Depending on the time of establishment and wide application the approaches are classified and represented as erosion plot/runoff approach, erosion pin technique followed by environmental tracer method and model approach in combination with Remote Sensing (RS) and Geographic Information System (GIS). Recent advancement in artificial intelligence and application of statistical techniques have a great potential to contribute in soil erosion research by identifying various degrees of susceptibility in large scale and also to quantify the erosion rate with high accuracy. The Remote sensing (RS) and Geographic Information System (GIS) contribute to develop regional scale data base with exploration of real time data and spatial analysis. The combination of RS & GIS and process-based models must be more effective than the traditional soil erosion model in the context of prediction with greater reliability and validity. The future research on soil erosion is better to focus on the theoretical analysis and development of erosion prediction model with more quantitative refinement and to model the future.

Modeling Approaches to Assess Soil Erosion by Water at the Field Scale with Special Emphasis on Heterogeneity of Soils and Crops

Information on soil erosion and related sedimentation processes are very important for natural resource management and sustainable farming. Plenty of models are available for studying soil erosion but only a few are suitable for dynamic soil erosion assessments at the field-scale. To date, there are no field-scale dynamic models available considering complex agricultural systems for the simulation of soil erosion. We conducted a review of 51 different models evaluated based on their representation of the processes of soil erosion by water. Secondly, we consider their suitability for assessing soil erosion for more complex field designs, such as patch cropping, strip cropping and agroforestry (alley-cropping systems) and other land management practices. Several models allow daily soil erosion assessments at the sub-field scale, such as EPIC, PERFECT, GUEST, EPM, TCRP, SLEMSA, APSIM, RillGrow, WaNuLCAS, SCUAF, and CREAMS. However, further model development is needed with respect to the interaction of components, i.e., rainfall intensity, overland flow, crop cover, and their scaling limitations. A particular shortcoming of most of the existing field scale models is their one-dimensional nature. We further suggest that platforms with modular structure, such as SIMPLACE and APSIM, offer the possibility to integrate soil erosion as a separate module/component and link to GIS capabilities, and are more flexible to simulate fluxes of matter in the 2D/3D dimensions. Since models operating at daily scales often do not consider a horizontal transfer of matter, such modeling platforms can link erosion components with other environmental components to provide robust estimations of the three-dimensional fluxes and sedimentation processes occurring during soil erosion events.

Selecting suitable climate models for examining future changes in soil erosion

&lt;p&gt;Climate models consistently project large increases in the frequency and magnitude of extreme precipitation events in the 21st century, revealing the potential for widespread impacts on various aspects of society. While the impacts on flooding receive particular attention, there is also considerable damage and associated cost for other precipitation driven phenomena, including soil erosion and muddy flooding. Multiple studies have shown that climate change will worsen the impacts of soil erosion and muddy flooding in various regions. These studies typically drive erosion models with a single model or a few models with little justification. A blind approach to climate model selection increases the risk of simulating a narrower range of possible scenarios, limiting vital information for mitigation planning and adaptation. This study provides a comprehensive methodology to efficiently select suitable climate models for simulating soil erosion and muddy flooding. For a case study region in eastern Belgium using the WEPP soil erosion model, we compare the performance of our novel methodology against other model selection methods for a future period (2081 &amp;#8211; 2100). The main findings reveal that our novel methodology is successful in generating the widest range of future scenarios from a small number of models, when compared with other ways of selecting climate models. This approach has not previously been achieved for modelling soil erosion by water. Other precipitation-driven impact sectors may also wish to consider applying this method to assess the impact of future climatic changes, so that the worst- and best-case scenarios can be adequately prepared for.&lt;/p&gt;

Computing slope length (USLE): return to original definitions.

&lt;p&gt;Soil erosion is an important process of consideration in different erosion risk models and in planning soil conservation. Common erosion models, such as the USLE and its derivatives are widely used. In this context, the slope length is the variable with the most difficulties due to the different scales and procedures available that lead to very different results. Furthermore, many of the calculation procedures are based on a hydrological network definition that poses many problems in areas with a complex topography.&lt;/p&gt;&lt;p&gt;We propose an algorithm implemented in GIS, returning to the original field perspective form defined by the USLE and RUSLE, which is detached from the hydrological network definition. The calculation procedure is based on 5 m DEM and defines overland water flow at the field scale.&lt;/p&gt;&lt;p&gt;This method has been applied in three areas with different climate and geomorphology. The results are similar to those derived from aerial photograph observation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;Honghu Liu, Jens Kiesel, Georg H&amp;#246;rmann, Nicola Fohrer. (2011). Effects of DEM horizontal resolution and methods on calculating the slope length factor in gently rolling landscapes. Catena, 87, 368&amp;#8211;375&lt;/p&gt;&lt;p&gt;Renard, K.G., Foster, G.R., Weesies, G.A., Mc. Cool, D.K y Yoder, D.C. (1997). Predicting Soil Erosion by Water: A Guide To Conservation Planning With The Revised Universal Soil Los Equation. Agricultural Handbook 703. USA: US Department of Agriculture.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Acknowledgements&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;Authors are grateful to Authors are grateful to Agroseguro funding this research.&lt;/p&gt;