Soil Erosion Model Research Articles

Process-based modelling of soil erosion: scope and limitation in the Indian context

Process-based modelling of soil erosion: scope and limitation in the Indian context

Comment on “Multi-fractal characteristics of reconstructed landform and its relationship with soil erosion at a large opencast coal-mine in the loess area of China” by Shi et al. (2021)

We were intrigued by the soil erosion modeling conducted by Shi et al. (2021) on post-mining areas in China. However, we discovered that the authors employed an incorrect empirical equation to calculate the rainfall erosivity factor, which resulted in a severe underestimation of the true rate of soil erosion. We presented our findings and discussed a possible source for the true equation.

Soil erosion dynamic monitoring in the Northeast Inner Mongolia of China from 1978 to 2018

The black soil area in Northeast Inner Mongolia is an important ecological barrier and food production base in China and the soil erosion is a key risk factor in regional ecological security and sustainable development. Multi-source satellite remote sensing and auxiliary data, including meteorology, land use, vegetation coverage and digital elevation were collected to establish a distributed model of soil erosion. Then, the quantitative analysis of soil erosion in the Northeast Inner Mongolia from 1978 to 2018 was carried out. The results show the following: (1) the areas of soil erosion in 1978 and 2018 were 203,538 km2 and 102,886 km2 respectively, and the area of soil erosion was decreased by 100,653 km2. The decreased of soil erosion was mainly located in the Songliao Plain Sand Prevention Farmland Protection Zone; (2) wind erosion is the main erosion type in the Northeast Inner Mongolia. Wind erosion area decreased from 188,982 km2 in 1978 to 88,466 km2 in 2018, and water erosion area decreased from 14,556 km2 in 1978 to 14,420 km2 in 2018.(3) the intensity of soil erosion is mainly mild. The area change rates of mild, moderate, strong, intensive and severe soil erosion intensity are -48.91%, -41.41%, 32.63%, -91.15% and -91.14% respectively. This study demonstrated how to use multi-source remote sensing technology to explore the long term series soil erosion dynamic monitoring and provided support for decision-making and management of soil erosion in Northeast Inner Mongolia under the background of sustainable development.

A new high resolution object-oriented approach to define the spatiotemporal dynamics of the cover-management factor in soil erosion modelling

The cover management factor (C-factor) calculation requires the assessment of the intra‐annual spatiotemporal variability of biomass cover, owed to the natural growth cycle of vegetation and the impact of agriculture on land cover. However, this is frequently omitted, and the vegetation conditions are approximated by assigning constant values to static classified Land Use/Land Cover (LULC) maps, such as the Coordination of Information on the Environment (CORINE) Land Cover (CLC). Using as test site the Sperchios River catchment, Central Greece, this study introduces a new approach to estimate C-factor in a spatiotemporally exhaustive manner. The goal is to increase estimation accuracy in erosion modelling applications. The C-factor computations are performed on monthly scale, based on LULC maps that portray the basin’s agricultural areas in unprecedented detail. The methodology involves the use of a biophysical index, namely Fraction of Vegetation Cover (Fcover) and empirical literature data on crop types. Fcover was developed from Sentinel-2 (S2) imagery in 10-m analysis. Such analysis (compared to the 300-m one provided by the EU) is a major improvement towards a more precise estimation of C-factor. The study identified the monthly C-factor fluctuation at basin scale, and the most susceptible months seasons at localities in terms of land cover/soil loss potential. The higher C-factor values were acquired in October and the lower in May. Mean annual (numerical) C-factor complies with the value of July. All monthly values are significantly higher – almost double – than the mean annual stationary one. The revealed patterns would not have been detected in a lower temporal (e.g., annual) resolution without the incorporation of vegetation density seasonality. The study shows high reproducibility and upscaling potential, as the utilized datasets are available in all European Union (EU) Member States, having similar structure, thus they can be harmonized towards a unified continental approach.

Soil Loss Assessment Using the Revised Universal Soil Loss Equation (RUSLE) Model

Many catchment areas have suffered from exhaustive changes because of various land use activities over the recent past. These land use changes are associated with intensified environmental degradation witnessed in catchment areas. Such environmental problems include extreme soil erosion. Soil erosion is one of the most critical problems responsible for the degradation of land worldwide. This phenomenon occurs as a result of the complex interactions that exist between natural and human-induced factors. Most factors experience spatiotemporal variations, hence complicating the soil erosion phenomenon. This complexity in the erosion process makes it difficult to quantify soil loss. Without proper information on soil loss, it becomes quite hard for decision-makers and managers to manage catchment areas. However, the availability of soil erosion models has made it easy to estimate soil loss. Many models have been developed to consider these complexities in soil erosion studies. Empirical models such as RUSLE provide a simple and broad methodology through which soil erosion is assessed. The RUSLE model integrates well geographic information system (GIS) and above all remote sensing. This paper presents an overview of the developmental milestones in estimating soil loss using the RUSLE model. The parameterization of the RUSLE model has been adequately reviewed with much emphasis on challenges and successes in derivation of each individual factor. From the review, it was established that different equations have been developed by researchers for modeling the five factors for the RUSLE model. The development of such equations was found to take into account the different variations that depict the soil erosion process.

Design Optimization of Biocrust-Plant Spatial Configuration for Dry Ecosystem Restoration Using Water Redistribution and Erosion Models

Land degradation is one of the main threats to dryland sustainability in the next decades, hence restoration of the degraded land from drylands is an urgent need to maintain ecosystem functionality and their ability to provide ecosystem services. To achieve this goal, restoration practices should pursue the recovery of the main ground components, arranged in an optimal spatial configuration, to mimic undisturbed natural conditions. Drylands function as complex ecohydrologically coupled systems in which interplant source areas, frequently covered by biocrusts, act as sources of runoff and nutrients to adjacent vegetation, which act as sinks for these resources. Thus, one way to increase dryland restoration success is through an optimal spatial configuration of biocrusts and plants that maximizes an efficient use of the limited resources within the system. In this study, we selected a degraded slope from a limestone quarry located in Almería province (SE Spain) and modeled how active restoration of the biocrust through soil inoculation with cyanobacteria and its combination with different spatial configurations of vegetation affected runoff redistribution and erosion. For that, we applied the spatially distributed Limburg Soil Erosion Model (LISEM) which was able to predict the erosion measured on the slope during the study period with low error (RMSE = 17.8%). Modeling results showed that the introduction of vegetation on the degraded slope reduced runoff between 2 and 24% and erosion between 4 and 17% for the scenario with plants compared to the one without restoration management. Of all the vegetation spatial configurations tested, the one that provided better results was the scenario in which plants were located in the areas of higher water accumulation (higher topographic wetness index). Moreover, we found that active biocrust restoration by cyanobacteria inoculation significantly reduced erosion by 70–90%, especially during the first stages of plant development, while maintaining water supply to vegetation. These findings highlight the potential of water redistribution and erosion simulation models to identify the most optimal spatial configuration of ground covers that maximizes water and nutrient supply to vegetation, while minimizes water, sediment, and nutrient losses by erosion, thus serving as an efficient tool to plan restoration actions in drylands.

Anthropogenic versus natural control on lacustrine sediment yield records from the French Massif Central

A quantitative assessment of historical sediment yields (SY) was performed using sediment budgets from lacustrine records located in the Mont Dore and Cezallier volcanic provinces (French Massif Central). A source-to-sink approach combining hydro-acoustic images, organic geochemistry (Rock-Eval and quantitative organic petrography) and radiocarbon dating of sediment cores has been adopted on three lake-catchment systems, namely Pavin, Chauvet and Montcineyre. SY was estimated from the quantification of red Amorphous Particles (rAP), a terrigenous organic tracer identified in both soils and sediments. Historical SY range between 3 and 320 t km−2.yr−1, which is comparable to the magnitude reached in other European lake-based SY records in similar geographical and climatic settings. Comparison of recent SY with predicted values of soil erosion rates from the RUSLE2015 model highlights large differences linked to scale differences between the model at plot scale and lake-based SY reflecting erosion export from the catchment to the lake. In this sense, the role of peatlands as sediment traps within two studied catchments must be considered to explain the large differences between modelled soil erosion rates and reconstructed SY data. SY differences between sites can be firstly attributed to morphology, size and lithology of the catchments as well as to vegetation cover whereas fluctuations reconstructed for each record seem to be mainly related to human-induced land use management. Historical SY from Chauvet and Montcineyre synchronously recorded two events in 850 CE and 1450 CE, respectively. The first marked the rise of SY to their maxima following land-use changes in the catchments. Nearby palaeoenvironmental records from Lake Aydat, Chambedaze peatland, and Espinasse marsh suggest this rise was consecutive to intensification of agro-pastoral activities recorded at regional scale. The second event followed a land-use shift characterized by a ten to fifteen-fold decrease in SY values. The driver remains unclear but could be possibly related to historical events causing a demographic decline (i.e., the Black Plague and/or the Hundred Years War) and/or cultural adaption in response to the onset of the Little Ice Age. Overall, both records suggest erosion in the area has been historically more susceptible to human-induced land use change rather than to precipitation and temperature changes induced by climate variability of the past millennium.

Impacts of raindrops increase particle sedimentation in a sheet flow

AbstractInterrill erosion is driven by raindrops and sheet flow. Raindrop impacts cause sediment detachment and splash, but can also affect flow transport. Even if these processes have been studied for long, the actual effect of raindrop impacts on particle settling velocities has not been experimentally assessed. This leads to unconstrained adjustments in the soil erosion models, the settling velocity of particles being a freely adjustable parameter allowing for better fitting the particle flux measured at the outlet. To address the effect of raindrop impacts on the settling of particles in sheet flow, a laboratory flume experiment was designed, using an upstream feeder of sediment (100–200 μm) and simulated rainfalls. It reproduced conditions close to sheet flow, while not allowing for the detachment of particles from the flume bottom. Two series of experiments were run: a series with a high rainfall intensity (175 mm/h) generated by an oscillating‐nozzle rainfall simulator, and a series with lower rainfall intensities (10, 15, 25, 35, 55 mm/h) generated by a drop‐former rainfall simulator. When a rainfall was applied, it systematically decreased the sediment concentration at the outflow compared to the no rain condition; however, no obvious relationship was found with the rainfall intensity. This shows that raindrop impacts increase particle settling velocities in sheet flow. Two underlying mechanisms are suggested, related to the momentum of the raindrops or to the turbulence caused by the raindrops into the flow. Further studies should be carried out, using computational fluid dynamics and collaboration with the fluid mechanics community.

Outreach and Post-Publication Impact of Soil Erosion Modelling Literature

Back in the 1930s, the aphorism “publish or perish” first appeared in an academic context. Today, this phrase is becoming a harsh reality in several academic environments, and scientists are giving increasing attention to publishing and disseminating their scientific work. Soil erosion modelers make no exception. With the introduction of the bibliometric field, the evaluation of the impact of a piece of scientific work becomes more articulated. The post-publication impact of the research became an important aspect too. In this study, we analyse the outreach and the impact of the literature on soil erosion modelling using the altmetric database, i.e., Altmetric. In our analysis, we use only a small fraction (around 15%) of Global Applications of Soil Erosion Modelling Tracker (GASEMT) papers because only 257 papers out of 1697 had an Altmetric Score (AS) larger than 0. We observed that media and policy documents mentioned more frequently literature dealing with global-scale assessments and future projection studies than local-scale ones. Papers that are frequently cited by researchers do not necessarily also yield high media and policy outreach. The GASEMT papers that had an AS larger than 0 were, on average, mentioned by one policy document and five Twitter users and had 100 Mendeley readers. Only around 5% and 9% of papers with AS > 0 appeared in news articles and blogs, respectively. However, this percentage was around 45% for Twitter and policy mentions. The top GASEMT paper’s upper bound was around 1 million Twitter followers, while this number was around 10,000 for the 10th ranked GASEMT paper. The exponentially increasing trend for erosion modelling papers having an AS has been confirmed, as during the last 3 years (2014–2017), we estimated that the number of entries had doubled compared to 2011–2014 and quadrupled if we compare it with 2008–2011.

基于遥感RMMF模型的喀斯特地区水土保持功能评价

PDF HTML阅读 XML下载 导出引用 引用提醒 基于遥感RMMF模型的喀斯特地区水土保持功能评价 DOI: 10.5846/stxb202104221057 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 科技兴蒙重大专项课题（KJXM-EEDS-2020006） Evaluation of soil and water conservation function in karst region based on Remote Sensing RMMF Model Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:为支撑我国重点生态功能区生态效益补偿工作，以半物理水土模型RMMF （The Revised Morgan，Morgan and Finney Model）为基础，通过对模型部分输入物理量进行遥感化改进建立了遥感RMMF模型（RS-RMMF）。为在评价中进一步排除气象要素波动带来的水土流失量变化，通过RS-RMMF模型构建了单位降水截留率、单位径流冲蚀量以及单位径流运输量3项评价指标来综合评价区域生态系统本身的水土保持能力。研究选取了《全国主体功能区规划》中的桂黔滇喀斯特功能区为典型区，分别基于上述评价指标和经典RUSLE （Revised Universal Soil Loss Equation）模型开展了2011年至2019年水土保持功能计算与对比。结果表明：相比2011年，2019年喀斯特功能区的降水截留率PI0升高1.94%，径流冲蚀量H0下降5.96×10-4 Mg/hm2，径流运输量TC0下降6.0×10-7Mg/hm2，水土保持功能综合得分增加0.83，水土保持功能整体上得到小幅改善。计算结果与RUSLE模型对比结论基本一致，但在空间相对强弱的分布上存在显著差异，RS-RMMF模型的评价得分空间分布明显由植被属性主导，且受降水等因素影响较小。该模型可客观核算生态系统水土保持能力，为生态补偿机制的实施应用提供科学支撑。 Abstract:To support the ecological benefit compensation system of key ecological function areas in China, Remote Sensing RMMF (RS-RMMF) soil erosion model is established by selecting the optimized remote sensing factors and RMMF (The revised Morgan, Morgan and Finney model) model. RS-RMMF model eliminates the soil erosion changes caused by the fluctuation of meteorological elements. The function of soil and water conservation is evaluated by constructing three evaluation indexes of unit rainfall interception rate, unit runoff erosion amount and unit runoff transportation volume. Karst functional areas in Guangxi, Guizhou and Yunnan are taken as the study area based on RS-RMMF model. The results show that compared with 2011, the rainfall interception rate PI0 in 2019 increased by 1.94%, the runoff erosion amount H0 decreased by 5.96×10-4 Mg/hm2, the runoff transportation volume TC0 decreased by 6.0×10-7 Mg/hm2, and the comprehensive score increased by 0.83. The overall water and soil conservation function has been slightly improved. Compared with RUSLE, the results of RS-RMMF model are basically consistent in the overall trend from 2011 to 2019. There are significant differences in the spatial distribution of the model results. The spatial distribution of the evaluation score of RS-RMMF is dominated by vegetation, but is less affected by precipitation factors. RS-RMMF model can objectively calculate the soil and water conservation capacity of the ecosystem, and provide scientific support for the application of ecological benefit compensation system. 参考文献 相似文献 引证文献

Representing Global Soil Erosion and Sediment Flux in Earth System Models

AbstractSoil erosion produces enormous amounts of sediment, carbon, and nutrient fluxes from land to rivers, thus playing crucial roles in global biogeochemical cycles and food security. To predict soil erosion in the context of climate and land use changes, we explicitly parameterize cropland management actions (i.e., irrigation, conserved agriculture, and crop residue management) and geological factors (i.e., lithology and glacier) in the Energy Exascale Earth System Model (E3SM) soil erosion module. The erosion model is calibrated using a global‐scale regionalized parameter calibration method. The spatial variabilities of the modeled and the Revised Universal Soil Loss Equation (RUSLE) based benchmark soil erosion are consistent across vegetation, climate and soil properties. Compared with independent data, our model shows a bias reduction in 59% of the observations relative to the RUSLE‐based soil erosion, with 53% of the bias reduction exceeding 50%. This improvement is mainly due to a better representation of the topographic effect on soil erosion. Our results indicate that conserved agriculture practices have effectively reduced soil erosion in cropland by over 25% in the United States and Argentina. In contrast, irrigation has increased soil erosion in many Asian countries. For upland sediment flux, our model is consistent with the WBMsed benchmark data in inter‐basin variability but could be more skillful in simulating intra‐basin variability because it couples soil erosion and sediment flux explicitly. The developed model provides useful skills for more realistic predictions of soil erosion and river sediment dynamics under environmental changes.

ВОПРОСЫ ОЦЕНКИ СОСТОЯНИЯ ЭРОЗИОННОСТИ ПОЧВЫ В ЛЕСНЫХ МАССИВАХ МЕТОДАМИ ДИСТАНЦИОННОГО ЗОНДИРОВАНИЯ

Introduction. There are a number of factors influencing and accelerating erosion processes. At the same time, the erosion of the soil itself plays an important role. To assess the erosion state of soils, various methods and means of remote sensing are widely used. The purpose of the study. The purpose of the study is to somewhat simplify the well-known multiplicative model for studying soil erosion in forests by some combination of indicators of individual factors and the formation of new composite functionals – indicators of vegetation stress as part of an improved model. Methods. The functionals introduced in the article can be considered as indices of the state of plants in forest areas. The first component in these functionals is an indicator of stress, i.e. the greater this component, the deeper the state of stress of the plant. At the same time, the second component in these functionals is an indicator of the healthy state of vegetation. Therefore, in general, the weighted average of these indicators is an indicator of the state of vegetation. Results. An extremal property of this functional, called the plant state functional, is shown. It is determined that this functional can be defined as a linearly weighted or geometric mean. In the first case, in the graph of the dependence of this functional on the indicator of the reflected signal in the Green zone, to the right of the extremum (minimum) point, there is a zone of deterioration in the state of vegetation, and to the left is an improvement zone. In the second case, when using the geometric mean, this picture changes as follows: conditions are revealed when the extremum turns into a minimum or maximum. In the case of a maximum, to the right of the maximum point there is a zone of improvement in the state of vegetation, and to the left of deterioration. Practical depend_ ency. Based on the results obtained, new methods can be developed to assess the state of soil erosion using the results of spectral remote sensing. in forests. Discussion. The issue of assessing soil erosion in forest areas is considered. Based on the well-known model of soil erosion in forest areas, an improved erosion model is proposed that contains an extreme functional of the state of vegetation, depending on two indica% tors characterizing the nitrogen content in the plant and the stress level, respectively. The introduction of such an extreme factor into the multiplicative erosion model makes it possible to more objectively assess the degree of soil erosion.

Application of GSA/GLUE methods to evaluate the representation of suspended sediment transport during flash floods in a rainfall-runoff model

This study looks at the impact of different parameters involved in the simulation of suspended sediment transport during flash flood on the performances of a distributed event-based soil erosion model. The results of GSA/GLUE methodologies implemented on three flash flood events show the model sensitivity to two parameters: the coefficient of soil sensitivity to shear erosion and the median diameter of sediment particles. The need to take into account the spatial variability of this soil sensitivity to shear erosion and therefore the location of potential sources of sediment is also stressed.

Comparison of the Applicability of Different Soil Erosion Models of the Effects of Climate Change on the Rate of Soil Erosion: A Case Study in the Naip Dam Basin, Turkish Thrace, Turkey

Comparison of the Applicability of Different Soil Erosion Models of the Effects of Climate Change on the Rate of Soil Erosion: A Case Study in the Naip Dam Basin, Turkish Thrace, Turkey

Field Verification of Soil Erosion Models in a Small Catchment for Different Time Windows with Changing Cropland Boundary (Tula Region, Russia)

Field Verification of Soil Erosion Models in a Small Catchment for Different Time Windows with Changing Cropland Boundary (Tula Region, Russia)

Detachment rates of purple soil rills affected by subsurface water flow depth

Subsurface water flow, considered as a specific hydrological condition, can couples with overland flow, which likely lead to notable effects on soil detachment process in rills. Clarifying the change in soil detachment rate under different subsurface flow conditions is beneficial to understand the mechanisms of soil erosion and improve process-based erosion model. In this study, the maximum sediment delivery rates at sediment transport capacity were used to determine the conditions when soil detachment rates reached zero. Then, a numerical method (NM) and modified numerical method (MNM) were utilized to estimate the detachment rates through sediment delivery amounts along a rill affected by subsurface water flow depths (5 cm, 10 cm, and 15 cm). The experiments were performed under combined conditions of four slope gradients (5°, 10°, 15°, and 20°) and three flow rates (2, 4, and 8 L min−1). The results showed that the detachment rates could be fitted by a linear function of the sediment concentration computed by the NM and MNM under different subsurface water flow depths. When the depths of subsurface water were 5 cm, 10 cm and 15 cm below the soil surface, soil detachment rates estimated by the NM were approximately 1.23, 1.31 and 1.12 times those obtained by the MNM, respectively. The MNM yielded more reasonable detachment rates than the NM. This method is applicable to estimate detachment rates affected by different subsurface water flow depths. Soil detachment rates of subsurface water flow 5 cm below the surface were similar to those of saturated soil with a 20° slope gradient and a flow rate of 8 L min−1. Soil detachment rate for subsurface water flow at 15 cm below the surface were similar to those of unsaturated soil under low hydrodynamic conditions. The results of this study are helpful to understand the mechanisms of soil erosion affected by subsurface flow and provide a theoretical basis for improving the soil erosion model.

Are compacted tramlines underestimated features in soil erosion modeling? A catchment‐scale analysis using a process‐based soil erosion model

AbstractProcess‐based model ling has long been used as a well‐suited tool to simulate soil erosion. Despite a large number of scientific articles that emphasize the role of compacted tramlines for soil erosion and surficial nutrient transport, no study exists that integrates these artificial structures into process‐based modelling at catchment scales. Thus, this study aims to quantify the effects of tramline compaction on soil erosion dynamics within a catchment. For this reason, high‐resolution spatial data (1 × 1 m) have been incorporated into the model EROSION 3D, which was used, calibrated, and tested for a soil erosion event with measured discharge and soil loss data. To quantify the contribution of tramlines to soil erosion, two different model parameterizations have been used: the tramline parameterization (TLP) and the common model parameterization (CP) that disregards the tramlines. The results reveal that: (i) the parameterization of tramlines improved model outcomes; (ii) tramlines significantly contribute to overall soil loss and sediment entrance into the channel network; (iii) the bulk density of tramlines is the most important driver of increases in soil erosion and runoff. Moreover, our investigation suggests that the impact of compacted tramlines have long been underestimated in soil erosion modelling and can assist in the assessment of surficial flow path connectivity. Thus, the integration of tramlines into soil erosion modeling is important for the implementation of adequate soil conservation and water protection measures.

Assessment of soil erosion hazard and its mapping using GIS technologies

The article presents a method for creating a territory erosion hazard integrated map using RUSLE integral model, Earth remote sensing data and GIS technologies. The studies carried out on this topic are presented, the analysis of which has shown a more active use of integral indicators of water-erosion processes in foreign scientific works. Urgency of updating methodology for studying erosion processes has been substantiated. Theoretical foundations of the application of integral models of soil erosion are given, the application of the RUSLE model is substantiated, and the optimal way of using this model is proposed. The research methodology has been developed, consisting of primary processing of remote sensing data, calculation of the factors of erosion development and creation of a territory erosion hazard integrated map. Based on the processing of aerial photography materials, a point cloud, a digital elevation model and an orthomosaic map of the study area were created. The results of the geoinformation analysis of the remote sensing data, which included calculation of the soil erodibility factor and the topographic factor, are presented. Based on the integral indicator of watererosion hazard, a complex map of the erosion hazard of the territory has been created. Main patterns of geographical distribution of the values of the integral indicator of the water-erosion hazard of the territory are revealed, devised methodology is assessed. It was found that the schematic map reflects the general pattern of water erosion processes: they are more active in places where more dissected relief is spread. Influence of the soil factor on the pattern of the schematic map is shown: the pattern in the territories occupied by sod-podzolic loamy soils qualitatively differs from the pattern on the lands where sod-podzolic sandy loam soils are widespread. Patterns on the schematic map of different parts of the developed linear forms of relief, formed by temporary streams, are described. It is shown that the proposed method can be used to assess the water-erosion hazard of the territory. The need to take into account a larger number of factors and to refine the assessment of existing ones is concluded.

Modeling soil erodibility and critical shear stress parameters for soil loss estimation

The rate of soil erosion from agricultural fields is driven by climate erosivity and by soil erodibility or resistance, commonly represented through the interrill (Ki) and rill erodibility (Kr), and critical shear stress (τc) parameters. These parameters are affected by factors showing high variability in time and space, such as soil properties, land use, and management practices. Estimating the site-specific time-varying values for Ki, Kr, and τc can require laborious field or laboratory experiments and detailed datasets. The objective of this research was to develop a non-linear regression model for estimating temporal adjustments for Ki, Kr, and τc considering different types of crops and management practices. One thousand sampling sites were randomly selected across the Kaskaskia watershed in Illinois, and the needed parameters to develop the regression models were extracted from the two-year simulation results of the Water Erosion Prediction Project (WEPP) model on a daily basis. The predicted values of the regression models showed good agreements with the sample data, with the coefficient of determination (r2) ranging from 0.62 to 0.98, capturing the spatio-temporal variations of the three variables under different crops and management practices. In addition, daily soil loss estimations using the predicted adjustments showed good agreements with the WEPP simulations, with r2 ranged from 0.98 to 0.99, confirming their possible use in soil erosion models. This is especially useful as the regression models require only a few explanatory variables, which are available at high resolution across the United States. Therefore, the models will facilitate estimating spatio-temporal variations of interrill and rill erodibility, and critical shear stress and thus a new platform of large-scale soil erosion models can be developed using readily available environmental datasets.

Soil Erodibility Analysis and Mapping in Gilgel Gibe-I Catchment, Omo-Gibe River Basin, Ethiopia

The soil erosion factor, erodibility, measures the susceptibility of soil particles to transport and detachment by erosive agents. Soil erosion and sedimentation models use soil properties and erodibility as the main input. However, in developing countries such as Ethiopia, data on soil erosion and soil-related properties are limited. For this reason, different researchers use different data sources that are adopted from a large scale and come with very different results. For this reason, the study was proposed to analyze and map the soil erodibility of the catchment area using primary data. 80 mixed soil samples were taken from the catchment with GPS coordinates and analyzed in the laboratory for soil texture class and soil organic matter. Accordingly, sandy clay loam is a dominant soil texture class covering 65% of the catchment area with 2.46% average soil organic matter, which is high in the mountainous part and lower in the lower valley of the catchment area. Most of the catchment area, which accounts for more than 78% of the area, was dominated by medium- or coarse-grained soil structure, and in the upper parts of the catchment area, 21% of the catchment area was covered with fine-grained soil structure. Similarly, 66% of the catchment area was covered with slow to moderate soil permeability, followed by slow soil permeability covering 21% of the area. Finally, the soil erodibility value of the Gilgel Gibe-I catchment was determined to be 0.046 ton h·MJ−1·mm−1 with a range of 0.032 to 0.063 ton·h·MJ−1·mm−1. In general, soils with slow permeability, high silt content, and medium- to fine-grained soil structures are the most erodible. They are conveniently separate; they tend to crust and form high drainage. Knowing this, the catchment has a moderate soil erodibility value. Thus, the study recommends evidence of land cover and the protection of arable land through suitable soil and water protection measures to improve soil permeability and soil structure.