Soil Erosion Model Research Articles

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.

Comparison of the Applicability of Different Soil Erosion Models to Predict Soil Erodibility Factor and Event Soil Losses on Loess Slopes in Hungary

Climate change induces more extreme precipitation events, which increase the amount of soil loss. There are continuous requests from the decision-makers in the European Union to provide data on soil loss; the question is, which ones should we use? The paper presents the results of USLE (Universal Soil Loss Equation), RUSLE (Revised USLE), USLE-M (USLE-Modified) and EPIC (Erosion-Productivity Impact Calculator) modelling, based on rainfall simulations performed in the Koppány Valley, Hungary. Soil losses were measured during low-, moderate- and high-intensity rainfalls on cultivated soils formed on loess. The soil erodibility values were calculated by the equations of the applied soil erosion models and ranged from 0.0028 to 0.0087 t ha h ha−1 MJ−1 mm−1 for the USLE-related models. EPIC produced larger values. The coefficient of determination resulted in an acceptable correlation between the measured and calculated values only in the case of USLE-M. Based on other statistical indicators (e.g., NSEI, RMSE, PBIAS and relative error), RUSLE, USLE and USLE-M resulted in the best performance. Overall, regardless of being non-physically based models, USLE-type models seem to produce accurate soil erodibility values, thus modelling outputs.

A field technology for soil erosion research: Conceptual analysis and preliminary results

Soil erosion is a ubiquitous geomorphologic process that critically affects land degradation rates and ecosystem sustainability. Yet we still don’t have a proper field technology to observe it under field-scale experiments let alone having the data for the verification and calibration of soil erosion models. A desirable soil erosion field technology needs to meet at least the following requirements: (1) it does not restrict natural field runoff; (2) it can be conveniently applied to a field-scale experiment with or without vegetation; (3) it is sensitive for short-term soil erosion observations; (4) it provides information on the sediments and (5) it can quantify soil loss and in-field sedimentation budget. There is a mesh-marker method that meets most of the above mentioned requirements except it does not determine soil loss, a major limitation to its application. This study was initiated to develop a soil erosion field technology that can meet the five criteria mentioned. Reported here is the conceptual analysis of the methodology and the preliminary results of the experiments. Other than meeting the above five criteria, the technology can determine soil erosion parameters such as the sediment delivery ratio.

Simulation and mapping of drought and soil erosion in Central Yunnan Province, China

Central Yunnan Province is the political, economic, cultural, and transportation hub of Yunnan Province, China. Climate change has resulted in increased seasonality of global averaged precipitation, temperature, runoff, and evapotranspiration, thereby exacerbating extreme events such as drought and soil erosion. The simulation and mapping of drought and soil erosion within Central Yunnan Province is important for achieving sustainable development. This study constructed a comprehensive drought monitoring model and a soil erosion model based on multiple sources of remote sensing data, considering numerous drought and soil erosion factors. The temporal and spatial characteristics of dry-season drought and soil erosion for 2010 to 2018 in Central Yunnan Province were explored, and the extents of soil erosion in different parts of Central Yunnan Province were quantified using the soil erosion intensity index. The results showed that: (1) The multi-year average percentage dry-season drought coverage and average drought frequency were 33.98% and 18.33 months, respectively. Although drought frequency was higher in areas with high drought intensity, dry-season drought showed a long-term weakening trend. (2) Over the study period, the multi-year average soil erosion of Central Yunnan Province was 1,551.45 t km −2 ·yr −1 . Soil erosion showed an initial overall increasing trend, followed by a decreasing trend, dominated by micro erosion, mild erosion, and moderate erosion, whereas the mountains and valleys in north and southwest parts of Central Yunnan Province experienced severe erosion. Vegetation coverage and slope were identified as the main factors driving soil erosion. (3) The soil erosion intensity index was a good indicator of soil erosion severity across different spatial scales and different drought grades. The soil erosion intensity index showed a positive relationship with drought grade. The correlation coefficients between soil erosion intensity and drought frequency and between soil erosion intensity and drought intensity were 0.2623 and −0.2679, respectively. This study demonstrated that drought affects soil erosion and that water and soil conservation measures such as afforestation and vegetation greening are beneficial to mitigating soil erosion and drought in Central Yunnan Province.

Breakdown of dry aggregates by water drops after applications of poultry manure and spent mushroom wastes

Evaluation of soil properties that enable aggregates to resist breakdown from impacting water drops is useful in modeling soil erosion process and tillage of some tropical soils. The effect of applications of poultry manure and spent mushroom wastes on soil properties related to resistance of aggregates of a degraded ultisol to water drops detachment energy (D) in southern Nigeria was studied. The area was under continuous field trials for maize crop. The treatments were: control (PM0SM0), 5 and 10 t ha−1 poultry manure (PM5 and PM10, respectively), 5 and 10 t ha−1 spent mushroom wastes (SM5 and SM10, respectively), and 5 t ha−1 poultry manure plus 5 t ha−1 spent mushroom wastes (PM5 + SM5) applied in seven consecutive years. Experimental design was a randomized complete block design (RCBD) in five replications. Soil samples were analyzed for texture, organic matter, aggregate stability, water retention, bulk density, clay mineralogy and water drop test. Results revealed that seven-year applications of PM5, SM5, SM10, and PM5 + SM5 treatments had significant positive effects on soil structural and hydraulic properties than PM10. However, in comparison to PM0SM0, applications of 10 t ha−1 PM had significant positive effects on these properties. Saturated hydraulic conductivity was 46.6, 35.4, 32.6 and 25.5 cm h−1 in PM5 + SM5, SM10, SM5 and PM10 soils, respectively; compared to 9.6 cm h−1 in PM0SM0. A low aggregate ratio (AR) obtained for PM10 compared to higher values for SM10 and PM5 + SM5 suggest that PM10 in this case had a disaggregating effect on the soil aggregates. Sand content accounted for 81.2% of negative effect on water drop detachment energy (D), while clay content accounted for 86.8% of the positive correlation with D. Only water-stable aggregates (WSA) 0.5–0.25 mm had a significant positive correlation with D (r = 0.661, p < 0.05). Clay dispersion index (CDI) had a highly negative correlation with D (r = − 0.896, p < 0.01). Volumetric water content at FC (− 10 kPa) and PWP (− 1500 kPa) correlated positively with D (r = 0.618, P < 0.05 and r = 0.614, p < 0.05). There was a non-significant positive correlation of Muscovite and Berlinite with D. Significant positive correlations of calcite with D (r = 0.694, p < 0.05), and between mica and D (r = 0.731, p < 0.05), revealed their strong linkage with macro-aggregate stability. It was found that high rates of poultry manure alone could increased erodibility and decreased water retention at FC and PWP, while a combination of poultry manure and spent mushroom wastes could reduce erodibility. These properties could be used to make a quick inference on the resistance of soil aggregates to water drop impact.

Assessment of soil erosion models for predicting soil loss in cracked vegetated compacted surface layer

Assessment of soil erosion models for predicting soil loss in cracked vegetated compacted surface layer

Integrating GIS-based FAHP and WaTEM/SEDEM for identifying potential RWH areas in semi-arid areas

Rainwater harvesting (RWH) is an alternative technique to potentially overcome the increasing need for water. However, identifying suitable sites for RWH remains a complex task. The present study offers an approach that can enable water managers to use the Water and Tillage Erosion Model and Sediment Delivery Model (WaTEM/SEDEM) as a spatially soil erosion and sediment delivery model, Geographic Information System (GIS) and Fuzzy Analytical Hierarchy Process (FAHP) method to identify potential RWH sites. For this purpose, several data sources were employed to generate needful thematic layers. Five criteria: land use/land cover (LULC), slope, soil texture, drainage density and runoff were used. The Soil Conservation Service-Curve Number (SCS-CN) method was utilized for preparing a yearly runoff potential map. Then, the thematic layers were weighted for generating RWH suitability map. The results show that the average annual runoff is 248 mm. Moreover, approximatly 76.1% of the study area falls within slight soil erosion class. The classified RWH suitability map showed that 6.9% of the watershed falls within an extremely suitable category. Prediction accuracy of the developed map of RWH suitability showed an area under the curve value (AUC) of 59.6% for FAHP method in this study. It is concluded that involving a spatial soil erosion and sediment delivery model with GIS-based FAHP represents a valuable approach for locating suitable RWH sites. So, this method can be used in other parts of the world.

Modeling and Assessing Potential Soil Erosion Hazards Using USLE and Wind Erosion Models in Integration with GIS Techniques: Dakhla Oasis, Egypt

Soil erosion modeling is becoming more significant in the development and implementation of soil management and conservation policies. For a better understanding of the geographical distribution of soil erosion, spatial-based models of soil erosion are required. The current study proposed a spatial-based model that integrated geographic information systems (GIS) techniques with both the universal soil loss equation (USLE) model and the Index of Land Susceptibility to Wind Erosion (ILSWE). The proposed Spatial Soil Loss Model (SSLM) was designed to generate the potential soil erosion maps based on water erosion and wind erosion by integrating factors of the USLE and ILSWE models into the GIS environment. Hence, the main objective of this study is to predict, quantify, and assess the soil erosion hazards using the SSLM in the Dakhla Oasis as a case study. The water soil loss values were computed by overlaying the values of five factors: the rainfall factor (R-Factor), soil erodibility (K-Factor), topography (LS-Factor), crop types (C-Factor), and conservation practice (P-Factor). The severity of wind-driven soil loss was calculated by overlaying the values of five factors: climatic erosivity (CE-Factor), soil erodibility (E-Factor), soil crust (SC-Factor), vegetation cover (VC-Factor), and surface roughness (SR-Factor). The proposed model was statistically validated by comparing its outputs to the results of USLE and ILSWE models. Soil loss values based on USLE and SSLM varied from 0.26 to 3.51 t ha−1 yr−1 with an average of 1.30 t ha−1 yr−1 and from 0.26 to 3.09 t ha−1 yr−1 with a mean of 1.33 t ha−1 yr−1, respectively. As a result, and according to the assessment of both the USLE and the SSLM, one soil erosion class, the very low class (&lt;6.7 t ha−1 yr−1), has been reported to be the prevalent erosion class in the study area. These findings indicate that the Dakhla Oasis is slightly eroded and more tolerable against water erosion factors under current management conditions. Furthermore, the study area was classified into four classes of wind erosion severity: very slight, slight, moderate, and high, representing 1.0%, 25.2%, 41.5%, and 32.3% of the total study area, respectively, based on the ILSWE model and 0.9%, 25.4%, 43.9%, and 29.9%, respectively, according to the SSLM. Consequently, the Dakhla Oasis is qualified as a promising area for sustainable agriculture when appropriate management is applied. The USLE and ILSWE model rates had a strong positive correlation (r = 0.97 and 0.98, respectively), with the SSLM rates, as well as a strong relationship based on the average linear regression (R2 = 0.94 and 0.97, respectively). The present study is an attempt to adopt a spatial-based model to compute and map the potential soil erosion. It also pointed out that designing soil erosion spatial models using available data sources and the integration of USLE and ILSWE with GIS techniques is a viable option for calculating soil loss rates. Therefore, the proposed soil erosion spatial model is fit for calculating and assessing soil loss rates under this study and is valid for use in other studies under arid regions with the same conditions.

Watershed-based soil erosion and sediment yield modeling in the Rib watershed of the Upper Blue Nile Basin, Ethiopia

Soil erosion is a major environmental problem that degrades topsoil and agricultural land productivity in mountainous areas such as Ethiopia. Soil erosion estimation is critical for the planning of erosion control plans in an agriculture-dependent economy. The current study used the Revised Universal Soil Loss Equation (RUSLE) model to evaluate the spatial distribution of annual soil loss and sediment yield in the Rib watershed. The main factors affecting soil erosion and sediment yield include vegetation cover, topography, soil, and climate. Soil erosion and sediment yield maps should be produced with these elements in account to describe locations with high soil erosion and sediment yield risks and to ensure improved erosion mitigation strategies in watersheds. The five input parameters were rainfall erosivity (R), soil erodibility (K), slope length-steepness (LS), cover-management factor (C), and support practice (P). The RUSLE model, when combined with remote sensing technology, has the ability to provide accurate and low-cost erosion and sediment yield risk maps in the Rib watershed. The estimated average annual soil loss was 25.53 t ha−1 yr−1. The soil loss rate was higher in the steeper and topographically dissected part of the watershed. Sediment delivery ratio ranges between 0 and 0.82. The outcome undoubtedly aids in the identification of priority locations for the adoption of sustainable land management and soil erosion mitigation conservation strategies.

Construction of Evaluation Model of Surface Soil Erodibility Factors in Black Soil Area

The increasing soil erosion in black soil area has caused widespread concern from all walks of life. Based on this background, the evaluation model of surface soil erodibility factor in black soil area is studied and constructed. The data of erosion gully is from the general survey data of surface soil erosion gully in black soil area. After quantifying the morphological characteristics of the data, the vector data of erosion gully are gridded by fractal theory. The number of non-empty grids is calculated by the attribute query function of ArcGIS, and the pixel size is transformed in turn to obtain different coverage grids and corresponding fractal parameters. The surface soil runoff and soil erosion process in black soil area are simulated by PESERA model. To build the surface soil erosion model of black soil area, in the process of building the user-defined model, it needs to carefully select the parameters used for modeling, and it needs to consider all the factors that may play a role in the whole process of soil erosion. The factors of surface soil erodibility in black soil area are analyzed, including spatial distribution characteristics of soil erodibility’s K value, semivariance function analysis of soil erodibility’s K value, and spatial distribution characteristics analysis of soil erodibility’s K value. Finally, the evaluation model of surface soil erodibility factor in black soil area is constructed. By testing the quantitative performance and evaluation accuracy of erodibility factors, it is proved that this method has good quantitative performance and evaluation accuracy of erodibility factors, and has strong practicability.

Impact of identical digital elevation model resolution and sources on morphometric parameters of Tena watershed, Ethiopia

Digital elevation models (DEMs) are the primary form of satellite data used to design and analyze the hydrology and hydraulic behavior of watersheds for water resource development. The primary objective of this study is to conduct morphometric parameter analysis using SRTM30m, ASTER30m, and ALOS30m data to determine the impact of identical DEM resolution and DEM sources on the Tena watershed by computing the basic and derived parameters. In this study I used data from two sources for morphometric parameter analysis with ArcGIS software. The results indicate that the DEM sources did not provide similar results for all parameters: ASTER30m was the maximum output for almost all parameters, followed by SRTM30m and ALOS30m. The findings of this study suggest that ASTER30m is the most suitable data source for flood risk assessment, soil erosion, sediment, streamflow, and other watershed modelling, while ALOS30m is best suited for peak discharge analysis. All of the used DEM sources were suitable for computing watershed shape parameters. In general, the resolution of DEMs impacts the hydrological and hydraulic study of any watershed, with resulting effects on decision-making for watershed management and development.

Particulate organic carbon exports from the terrestrial biosphere controlled by erosion

The transport of particulate organic carbon (POC) through rivers from land to sea affects the redistribution of global organic carbon. However, because of the limitation of the quantity and quality of monitoring data, the POC magnitude, scale and global distribution pattern of land-sea migration are still not well understood. Therefore, based on an updated GEMS-GLORI database and other reanalysis data, we use the soil erosion model (Ferosion), total suspended solids model (Ftss), and runoff model (Frunoff) to re-analyze and generate the POC flux of major rivers in the world dataset. The major results are as follows: the POC flux from global terrestrial biosphere rivers exports approximately 0.12–0.20 Pg C to oceans every year, including 0.20 Pg Ferosion, 0.17 Pg Ftss, and 0.12 Pg Frunoff. In contrast to earlier studies that the Pacific and Arctic Oceans are the main recipients of POC flux, we find that the Pacific and Atlantic received more POC flux and received 30.76%–62.51% and 26.77%–53.95%, respectively. This difference may be related to the combined effects of soil erosion, total suspended solids, and runoff. Asia exports more POC than other continents (60.50%–61.69%). The Amazon basin is the major contributor to the Atlantic POC, contributing 53.30%–58.68%. Furthermore, because of the intense human activities and the widespread distribution of many large watersheds in the highly eroded area, it was found that the POC flux has two key zones (25.75–41.5°N and 4.50°N–13.50°S) in the latitude zone. In summary, the above findings increase our understanding of the spatial redistribution of global organic carbon from land to sea.

Combined effects of rainfall and flow depth on the resistance characteristics of sheet flow on gentle slopes

Rainfall and sheet flow (SF) on gentle slopes always appear concurrently. However, the combined effects of rainfall and flow depth on SF resistance are still unclear for gentle slopes. In this study, two sets of experiments, namely, upstream inflow with rainfall and upstream inflow only, were conducted to investigate the resistance characteristics of SF on a flat and smooth flume with three gentle slopes (3°, 5° and 7°). The experimental results indicated that in the tests with upstream inflow only, the Darcy–Weisbach resistance (f) and Manning coefficient (n) decreased following a power function with increasing flow depth. When the Reynolds number (Re) was less than 1070, the n and f of the SF in the upstream inflow alone decreased with increasing Re following the power function. Both the n and f of the SF increased with increasing rainfall intensity for the upstream inflow with the rainfall tests. The rainfall significantly affected the f and n of the SF in the low Re zone (Re < 1070), inflow discharge (<0.06 m2 min−1) and flow energy for all inflow with rainfall cases. Under the conditions of upstream inflow with rainfall, both the f and n of the SF decreased with the increase in the ratio between the flow depth and median raindrop diameter (H/D50) in the power function. This result indicated that a deeper flow could dissipate more raindrop energy. In addition, empirical equations among Re, hydraulic slope and H/D50 were established to predict the n and f of the SF for upstream inflow with rainfall tests. This study will be helpful in understanding the combined effects of rainfall and flow depth on SF and could provide a scientific basis for improving hydrological and soil erosion models.

Modelling soil loss from surface erosion at high-resolution to better understand sources and drivers across land uses and catchments; a national-scale assessment of Aotearoa, New Zealand

Soil erosion is a significant challenge for agricultural regions, with cascading impacts to waterways, land productivity, soil carbon, and ecological health. We provide the first national-scale soil erosion model that incorporates the impacts of grazing on ground cover (Cgr) and soil erodibility (Ktr) into the RUSLE framework. Surface erosion rates for winter-forage paddocks (11 t ha−1 y−1) were substantially higher than pastoral grasslands (0.83 t ha−1 y−1), woody grasslands (0.098 t ha−1 y−1), forests (0.103 t ha−1 y−1) and natural soil production rates (≤1–2 t ha−1 y−1). Validation with empirical measurements from sediment traps, sediment cores, and chemical fingerprinting demonstrated strong linear regressions (r2 = 0.86). Terrain impacted soil erosion directly through slope steepness and flow convergence and indirectly through strong orographic effects on rainfall erosivity (r2 = 0.39–0.83). Annual surface erosion across Aotearoa New Zealand could reach 16.5-29.2 Mt y−1, representing ∼$20M annually and up to 24–31% of sediment yield for two catchments.

Effects of spatial resolution of terrain models on modelled discharge and soil loss in Oaxaca, Mexico

Abstract. The effect of the spatial resolution of digital terrain models (DTMs) on topography and soil erosion modelling is well documented for low resolutions. Nowadays, the availability of high spatial resolution DTMs from unmanned aerial vehicles (UAVs) opens new horizons for detailed assessment of soil erosion with hydrological models, but the effects of DTM resolution on model outputs at this scale have not been systematically tested. This study combines plot-scale soil erosion measurements, UAV-derived DTMs, and spatially explicit soil erosion modelling to select an appropriate spatial resolution based on allowable loss of information. During 39 precipitation events, sediment and soil samples were collected on five bounded and unbounded plots and four land covers (forest, fallow, maize, and eroded bare land). Additional soil samples were collected across a 220 ha watershed to generate soil maps. Precipitation was collected by two rain gauges and vegetation was mapped. A total of two UAV campaigns over the watershed resulted in a 0.60 m spatial-resolution DTM used for resampling to 1, 2, 4, 8, and 15 m and a multispectral orthomosaic to generate a land cover map. The OpenLISEM model was calibrated at plot level at 1 m resolution and then extended to the watershed level at the different DTM resolutions. Resampling the 1 m DTM to lower resolutions resulted in an overall reduction in slope. This reduction was driven by migration of pixels from higher to lower slope values; its magnitude was proportional to resolution. At the watershed outlet, 1 and 2 m resolution models exhibited the largest hydrograph and sedigraph peaks, total runoff, and soil loss; they proportionally decreased with resolution. Sedigraphs were more sensitive than hydrographs to spatial resolution, particularly at the highest resolutions. The highest-resolution models exhibited a wider range of predicted soil loss due to their larger number of pixels and steeper slopes. The proposed evaluation method was shown to be appropriate and transferable for soil erosion modelling studies, indicating that 4 m resolution (&lt;5 % loss of slope information) was sufficient for describing soil erosion variability at the study site.

Two-dimensional hydrodynamic robust numerical model of soil erosion based on slopes and river basins

Two-dimensional hydrodynamic robust numerical model of soil erosion based on slopes and river basins

Towards improved USLE-based soil erosion modelling in India: A review of prevalent pitfalls and implementation of exemplar methods

One of the most common approaches to modelling soil erosion worldwide has been the implementation of the original Universal Soil Loss Equation (USLE) and its revised version, the RUSLE. However, despite its widespread use, often there are discrepancies in the methods used to compute it and in the values elicited for the five individual factors that comprise this function. Such pitfalls subsequently skew the final results obtained and often many studies also fail to adequately examine the accuracy of the enumerated soil loss amounts. We examine these aspects with respect to the raft of USLE-based studies undertaken in India over the last few decades, reviewing a total of 100 investigations in this regard. Results reveal that almost all studies had either over- or underestimated at least one of the five factors, thereby possibly misrepresenting the actual soil loss occurring from their examined areas. Even more worryingly, most studies had failed to document their methods succinctly or in sufficient detail to ascertain their efficacies or provide viable templates for replication elsewhere. Our results also show a marked spatiality in the pursuance of such studies, with these being mostly undertaken in the eastern part of the country, even though the proportionate land affected by soil erosion is considerably less in this region. Thus regions where the USLE would be most pertinent for implementation towards land management have seen a lower number of applications. We hope that by avoiding the missteps highlighted in this paper and following the subsequently detailed exemplar methods of conducting such an investigation along with the relevant model accuracy and uncertainty checks, the USLE can be best utilised in these regions and in the rest of the country for soil erosion mitigation. Though focused on India, the methods outlined can also be used to conduct the most accurate possible USLE-based soil erosion modelling elsewhere.

Mapping bare ground in New Zealand hill-country agriculture and forestry for soil erosion risk assessment: An automated satellite remote-sensing method

Removing vegetation cover from hill-slope land increases risk for soil erosion and delivery of sediment to waterways. In New Zealand's productive landscapes, clear-fell harvesting of forestry blocks and winter forage grazing by agricultural livestock are two significant causes of vegetation removal. Bare ground exposed by these activities varies annually and seasonally in location and spatial extent. Modelling soil erosion therefore requires temporally and spatially explicit mapping of this bare ground. We have developed an automated mapping method using time-series satellite imagery, thereby enabling wide-area coverage and ease of updating. The temporal analysis identifies land use along with the period of vegetation removal. It produces results per land parcel (in vector format) for use in a Geographic Information System. We present a description of our method, national maps and statistics of bare ground extent in New Zealand's hill-country forestry and winter forage grazing land in 2018, and an assessment of accuracy. The attributes of the mapped land parcels are designed for input into a soil erosion estimation model such as the New Zealand Universal Soil Loss Equation.

Nonlinear response of hydrodynamic and soil erosive behaviors to biocrust coverage in drylands

In dryland ecosystems, soil erosion poses severe threats to ecosystem productivity and human well-being. Biological soil crusts (biocrusts) are ubiquitous living covers in these ecosystems and play an important role in soil stabilization and erosion prevention. However, the quantitative relationship between biocrust coverage and soil water erosion as well as the driving mechanism have not yet been fully discussed, which hinders the development of soil erosion models that consider the effect of biocrusts. Accordingly, we set up 19 biocrust plots (10 m × 2.1 m) with coverage ranging from 9.3% to 80.0% on the Loess Plateau of China and conducted a series of simulated rainfall experiments. The quantitative relationship between runoff and sediment yield and biocrust coverage was assessed, and further complex correlations among these variables were analyzed using structural equation modeling (SEM). We found that (1) the runoff rates and sediment yield were significantly related to biocrust coverage. The runoff rates and sediment yield decreased with increasing biocrust coverage via a logarithmic function and an exponential function, respectively. The runoff rate and sediment yield rate from the plot with 9.3% biocrust coverage were 3.2 and 51.5 times higher, respectively, than those from the plot with 78.4% biocrust coverage. (2) The flow pattern and regime of overland flow were significantly affected by biocrust coverage. The overland flow was shifted from tranquil flow to supercritical flow when the biocrust coverage declined to 12.3%. The flow velocity, stream power, Darcy-Weisbach resistance coefficient, Froude number, and Reynolds number were strongly correlated with biocrust coverage (R2 = 0.548–0.830). (3) Biocrust coverage both directly and indirectly affected sediment yield. The anchoring effect of biocrusts directly protected the surface soil from raindrop impacts and runoff scouring (direct effect = −0.59). Additionally, biocrust cover had an indirect negative effect (−0.38) on sediment yield by decreasing the flow velocity and runoff rate with path coefficients of −0.81 and −0.78, respectively. Our results confirm that soil hydrological and erosive behavior have nonlinear relationships with biocrust coverage at the hill-slope scale, and they also reveal that variation in biocrust coverage is one of the main driving factors affecting soil hydrological and erosive behaviors. These results would improve soil water erosion estimation on biocrust-covered slopes and provide guidance for revising soil erosion models to include the effectiveness of biocrusts.