Water Erosion Models Research Articles

Mapping and modeling of water erosion in the Revubué river Sub-Basin, Moatize, Mozambique

This study investigated water erosion in the Revubué River Sub-Basin, Moatize, Mozambique, utilizing advanced mapping and modeling techniques. Through detailed land use surveys and application of the Potential Erosion Model (EPM), we identified areas with moderate to severe erosion rates (φ = 0.54), particularly in zones of intensive agriculture (15% of the study area) and mining (1% of the study area). The results highlighted the influence of undulating topography (average slope of 9%) and intensive agricultural practices on erosion rates (0 – 25 ton/ha). Urgent implementation of soil conservation practices, such as contour plowing and terracing, was recommended to mitigate soil loss, improve agricultural productivity, and promote environmental sustainability. Agricultural sustainability was emphasized, focusing on investments in sustainable agricultural practices to preserve long-term soil health. Raising awareness among farmers about the impacts of soil erosion and implementing effective management practices were considered crucial. Extension services were recognized as key agents in disseminating knowledge for promoting eco-friendly agricultural practices.

Hydrological Connectivity Response of Typical Soil and Water Conservation Measures Based on SIMulated Water Erosion Model: A Case Study of Tongshuang Watershed in the Black Soil Region of Northeast China

The black soil region of Northeast China is the largest commercial grain production base in China, accounting for about 25% of the total in China. In this region, the water erosion is prominent, which seriously threatens China’s food security. It is of great significance to effectively identify the erosion-prone points for the prevention and control of soil erosion on the slope of the black soil region in Northeast China. This article takes the Tongshuang small watershed (Heilongjiang Province in China) as an example, which is dominated by hilly landforms with mainly black soil and terraces planted with corn and soybeans. Based on the 2.5 cm resolution Digital Elevation Model (DEM) reconstructed by unmanned aerial vehicles (UAVs), we explore the optimal resolution for hydrological simulation research on sloping farmland in the black soil region of Northeast China and explore the critical water depth at which erosion damage occurs in ridges on this basis. The results show that the following: (1) Compared with the 2 m resolution DEM, the interpretation accuracy of field roads, wasteland, damaged points, ridges and cultivated land at the 0.2 m resolution is increased by 4.55–27.94%, which is the best resolution in the study region. (2) When the water depth is between 0.335 and 0.359 m, there is a potential erosion risk of ridges. When the average water depth per unit length is between 0.0040 and 0.0045, the ridge is in the critical range for its breaking, and when the average water depth per unit length is less than the critical range, ridge erosion damage occurs. (3) When local erosion damage occurs, the connectivity will change abruptly, and the remarkable change in the index of connectivity (IC) can provide a reference for predicting erosion damage.

Assessing the 3D distribution of soil organic carbon by integrating predictions of water and tillage erosion into a digital soil mapping-approach: a case study for silt loam cropland (Belgium)

Although agricultural intensification has generally increased crop yields, it also resulted in a range of environmental issues. These include increased erosion rates and declined soil organic carbon (SOC) stocks. In order to improve our understanding on how erosion impacts the overall SOC storage capacity of croplands, this study analyses the 3D distribution of SOC as a function of water and tillage erosion in a conventionally ploughed field in the Belgian silt loam region. We present a novel methodological framework to integrate the output of an advanced erosion model as a co-variate within a Digital Soil Mapping (DSM) approach with the objective to create detailed SOC maps. More precisely, we combined (i) the Water and Tillage Erosion Model and Sediment Delivery Model (WaTEM/SEDEM), simulating spatial patterns of soil erosion and sediment deposition due to water and tillage erosions, with (ii) a SOC sampling campaign, resulting in a SOC spatial distribution model that considers both types of erosion. The results show that, as compared to plateaus, SOC stocks are nearly half as large along eroding slopes (i.e. convex slope positions affected by tillage erosion and steep slopes affected by water erosion). Yet, they are up to twice as large in areas characterized by sediment deposition (i.e. concave positions due to tillage erosion and foot slope positions due to water erosion). Our results further show that tillage erosion has a significant influence on the SOC stocks in the top 0.7 m and in particular on the top 0.4 m. The influence of water erosion is less strong but mostly significant along the entire depth profile. Overall, this work demonstrates the relevance of considering different erosion processes when aiming to predict spatial patterns of SOC. Considering the top 1 m and a WaTEM/SEDEM application at a resolution of 10 m our 3D SOC modelling approach obtained a coefficient of determination (R2) of 0.62, a relative root mean square error (RRMSE) of 30.5 % and a relative mean absolute error (RMAE) of 26.0 %. While future work may likely lead to further improvements e.g. a more detailed SOC sampling network along the foot slopes and thalwegs in order to obtain a more spatially detailed prediction of the area characterized by depositions due to water erosion, we demonstrate the great potential of existing erosion and deposition models in doing so.

Advances in a measurement method of rainfall kinetic power and momentum affecting soil erosion processes

AbstractRainfall is one of the factors affecting soil erosion, and rainfall kinetic energy or momentum is used to represent the capability of the precipitation to erode soil, named rainfall erosivity. Accurate measurements of rainfall erosivity are useful for a reliable prediction of soil loss. Rainfall momentum and kinetic energy, both calculated per unit time and area, can be obtained using terminal raindrop velocity and the drop size distribution (DSD) measured by disdrometers, which are instruments expensive and not suitable for large scale use. An innovative patented method to measure the rainfall energy is based on the estimation of DSD by simultaneous detection, in a given time interval, of the rainfall intensity I and the number N of raindrops that hit a specific piezoelectric surface. In this paper, advances of this method are presented. In particular, two new theoretical procedures to estimate the parameters μ and Λ of Ulbrich's distribution, that allow for the calculation of the rainfall kinetic energy and momentum, are proposed. Both procedures (Scenario 1 and 2) are based on the frequency distribution of the momentum M(D) of raindrops detected in a sampling time interval. Specifically, in the Scenario 1, μ and Λ are estimated by using I, N and the standard deviation, s(D), of the drop diameters obtained from the measured momentum distribution. In the Scenario 2 the parameters are estimated using I, N and the mean value, m(D), of the drop diameters deriving from the momentum distribution. The reliability of the proposed procedures was tested using DSD measurements recorded in three different experimental sites. The developed analysis demonstrated that Scenario 2 is the best method to estimate μ and Λ, and to reproduce the DSD, accordingly. The proposed method, associated with a patented device, not yet build, will allow the direct measurement of the rainfall energy characteristics, which are usually roughly estimated from rainfall intensity. The possibility to easily measure these energy variables can support the development of research in the field of soil erosion and, in general, of hydrogeological instability. In particular, the proposed measurement method and the construction of the device could stimulate the scientific community to deepen the study of the effect of the rainfall energy on soil erosion for improving the predictive capability of water erosion models.

An explainable integrated machine learning model for mapping soil erosion by wind and water in a catchment with three desiccated lakes

Soil erosion by water and wind is a critical challenge for sustainable management of catchments in drylands and accurate spatial information can help in mitigation of its destructive consequences. Here, seven machine learning (ML) models were applied to map simultaneously the water and wind erosions in the Bakhtegan catchment, south Iran, with three dried lakes in its southern part and three dams established in upstream parts of the lakes. The analysis identified 10 and 11 effective variables controlling water and wind erosions, among 20 and 17 potential variables, respectively, via the MARS feature selection algorithm. According to the most accurate ML models (artificial neural network for water erosion, and Cubist for wind erosion), an integrated model was developed to map soil erosion by water and wind simultaneously. Permutation feature importance (PFI) and Shapley additive exPlanation (SHAP) interpretation techniques were employed to explain the model outputs, revealing that 19.7 % of the total area belonged to high and very high susceptibility classes to soil erosion by water and wind. The PFI plot revealed that the slope and wind speed were the most influencing factors for water and wind erosion, respectively. According to SHAP decision plot, slope had the highest contribution on the predictive water erosion model’s output, whereas vegetation cover exhibited the highest contribution on the predictive wind erosion model’s output. Due to climate change and intensified drought during the recent years, as well as due to construction of dams upstream of the lakes, the southern part of the study area was converted to a source of sand and dust storms. The hotspots with severe water erosion are distributed all over the study area, rendering it quite vulnerable to adverse climate change projections.

An overview of water erosion modeling in china: a bibliometric and statistical analysis

An overview of water erosion modeling in china: a bibliometric and statistical analysis

Multi-temporal spatial modelling to assess runoff and sediment dynamics under different microtopographic patterns

Soil erosion is a multi-scale geographical interface process with high spatiotemporal variability. This study aimed to assess runoff and sediment dynamics under different microtopographic patterns based on wavelet analysis and SIMulated Water Erosion model (SIMWE). Three rainfall intensities of 1.0 mm min−1, 1.5 mm min−1, and 2.0 mm min−1, combined with three slope gradients of 10°, 15°, and 20°, were utilized to conduct rainfall simulations on three soil boxes measuring 4 m in length and 0.8 m in width. The soil boxes exhibited distinct microtopographic patterns, including smooth slope (CK), artificial digging (AD), and ridge tillage (RT). The results showed that the runoff and sediment reduction benefits of different tilled slopes decreased with an increase in both slope and rainfall intensity. The AD and RT slopes reduced runoff yields by 8.4% − 50.2% and 17.3% − 75.0% respectively compared to CK slope. Although sediment yields from AD and RT slopes were reduced by 4.2% − 51.6% and 1.8% − 53.0%, respectively, the sediment control benefits of AD and RT slopes were basically lost when the slope gradient increased to 20°. The rill erosion was the main source of soil erosion on different tilled slopes, accounting for 72% − 87% of the total soil loss. And the rates of both soil erosion and rill erosion exhibited a power function relationship with an increase in rainfall intensity and slope. The impact of slope gradient on soil erosion on the RT slope was greater than those on the CK and AD slopes. During the development of rill erosion, non-stationary and multi-scale periodic phenomena exist in the time series of runoff and sediment on different microreliefs. As surface microrelief increased, the fluctuations in runoff and sediment on tilled slopes intensified, resulting in a gradual shortening of the variation period. And this study verified the feasibility of the SIMWE model to simulate the runoff and sediment dynamics on microtopographic scale under a single rainfall event. The results can provide a theoretical basis for the scientific layout of soil and water conservation practices in sloping farmland and the construction of soil erosion model in purple soil area.

Improving estimation of water soil erosion by introducing lithological formation for environmental remediation

Soil erosion is a serious and complex environmental problem worldwide, especially in the centre west of Tunisia. Whereas the construction of hill reservoirs is part of the soil and water conservation strategy, many of these have a siltation problem. Dhkekira is one of the smallest watersheds in central Tunisia whose most lithological formation consists of materials that are quite susceptible to water erosion. Due to the lack of low-scale lithological data, digital IR aerial photos with 2 m spatial resolution were considered. A semi-automatic classification of aerial photos, based on the image's textural indices is developed. The lithologic map extracted from aerial photos was used as input for ANSWERS-2000 water erosion model. Results obtained indicate first, with the semi-automatic classification of the mean and standard deviation of the thumbnail histograms that image output could help to give an idea about the existence of some surface lithological formation. The model applied to Dhkekira watershed showed that the spatial difference in water erosion was not caused only by land cover and slope, but also by lithological formation. The percentage of each lithological formation in sediment yield at the Dhkekira hill reservoir was estimated to be 69% sediment yield from Pleistocene and 19.7% from Lutetian-Priabonian.

Soil Water Erosion Modeling in Tunisia Using RUSLE and GIS Integrated Approaches and Geospatial Data

Soil erosion is an important environmental problem that can have various negative consequences, such as land degradation, which affects sustainable development and agricultural production, especially in developing countries like Tunisia. Moreover, soil erosion is a major problem around the world because of its effects on soil fertility by nutriment loss and siltation in water bodies. Apart from this, soil erosion by water is the most serious type of land loss in several regions both locally and globally. This study evaluated regional soil erosion risk through the derivation of appropriate factors, using the Revised Universal Soil Loss Equation (RUSLE), which was applied to establish a soil erosion risk map of the whole Tunisian territory and to identify the vulnerable areas of the country. The RUSLE model considers all the factors playing a major role in erosion processes, namely the erodibility of soils, topography, land use, rainfall erosivity, and anti-erosion farming practices. The equation is, thus, implemented under the Geographic Information System (GIS) “Arc GIS Desktop”. The results indicated that Tunisia has a serious risk of soil water erosion, showing that 6.43% of the total area of the country is affected by a very high soil loss rate, estimated at more than 30 t/ha/year, and 4.20% is affected by high mean annual soil losses, ranging from 20 to 30 t/ha/year. The most eroded areas were identified in the southwestern, central, and western parts of the country. The spatial erosion map can be used as a decision support document to guide decision-makers towards better land management and provide the opportunity to develop management strategies for soil erosion prevention and control on the global scale of Tunisia.

Estimating nutrient transport associated with water and wind erosion across New South Wales, Australia

Nutrient transported from soils to water bodies not only threatens agricultural productivity and food security but also causes the degradation of water quality and the environment in many parts of the world. However, nutrient transport through soil erosion is often ignored in nutrient cycle studies; there is little understanding of how much nutrient is lost through water and wind erosion. In this study, we attempted to assess soil nutrient transport due to both water and wind erosion and its spatial and temporal variability across New South Wales (NSW), Australia. We estimated the mass fraction (%) of total nitrogen (N), total phosphorus (P) and soil organic carbon (SOC) in the eroded soil, and the total nutrient stock of the soil layer down to 200 cm using water and wind erosion models and digital soil mapping. The estimated average N, P and SOC stocks in NSW topsoils (0–5 cm) are 160, 43, and 2970 kg ha−1 respectively. There are great variations in the transport of nutrients by erosion in space and time, ranging from near zero in the Western region to 395 kg ha−1 yr−1 in the North Coast region. The average total nutrient transport rate is about 2.4 % of the surface soil (0–5 cm) total stock in NSW due to both water and wind erosion. The total cost of nutrient transport is estimated at 4.2 billion Australian dollars for the entire state of NSW and 0.2 billion dollars from the cropping lands per year. The areas with the highest nutrient transport rates are the North Coast and Hunter regions due to the relatively high water erosion and nutrient content of the soils. On average, water erosion contributes up to 98 % of the total nutrient transport across the state as a whole, but wind erosion can contribute up to 12 % of the total transport in Spring (i.e., September). This study is the first attempt to investigate nutrient transport from both water and wind erosion in Australia. The methodology and findings contribute to the knowledge of nutrient transport due to erosion in broad nutrient cycle studies.

A conceptual-model-based sediment connectivity assessment for patchy agricultural catchments

Abstract. The accelerated sediment supply from agricultural soils to riverine and lacustrine environments leads to negative off-site consequences. In particular, the sediment connectivity from agricultural land to surface waters is strongly affected by landscape patchiness and the linear structures that separate field parcels (e.g. roads, tracks, hedges, and grass buffer strips). Understanding the interactions between these structures and sediment transfer is therefore crucial for minimising off-site erosion impacts. Although soil erosion models can be used to understand lateral sediment transport patterns, model-based connectivity assessments are hindered by the uncertainty in model structures and input data. Specifically, the representation of linear landscape features in numerical soil redistribution models is often compromised by the spatial resolution of the input data and the quality of the process descriptions. Here we adapted the Water and Tillage Erosion Model and Sediment Delivery Model (WaTEM/SEDEM) using high-resolution spatial data (2 m × 2 m) to analyse the sediment connectivity in a very patchy mesoscale catchment (73 km2) of the Swiss Plateau. We used a global sensitivity analysis to explore model structural assumptions about how linear landscape features (dis)connect the sediment cascade, which allowed us to investigate the uncertainty in the model structure. Furthermore, we compared model simulations of hillslope sediment yields from five subcatchments to tributary sediment loads, which were calculated with long-term water discharge and suspended sediment measurements. The sensitivity analysis revealed that the assumptions about how the road network (dis)connects the sediment transfer from field blocks to water courses had a much higher impact on modelled sediment yields than the uncertainty in model parameters. Moreover, model simulations showed a higher agreement with tributary sediment loads when the road network was assumed to directly connect sediments from hillslopes to water courses. Our results ultimately illustrate how a high-density road network combined with an effective drainage system increases sediment connectivity from hillslopes to surface waters in agricultural landscapes. This further highlights the importance of considering linear landscape features and model structural uncertainty in soil erosion and sediment connectivity research.

Contribution of MODIS image to hydrologic and erosion modeling

Erosion is the most dangerous phenomenon of environmental and economic threat to arable land. By FAO. 35 % of Tunisian land are threatened by water erosion and varies regionally. Quantification and estimation of soil loss by water erosion is now essential to install the best management practices. In our study, we used a continuous physical based simulation version of a hydrological and water erosion model ANSWERS-2000. The aim of this study is to investigate the introduction of land use parameters extracted by MODIS image. This study is focused on El Azire watershed, is characterized by a moderate Mediterranean climate and a high spatial heterogeneity of soil and land use proprieties. Describing, monitoring, and predicting land-use and land-cover change in the watershed is a difficult process. However, the usefulness of MODIS image with their daily temporal resolution and spatial resolutions of 250 m and 500 m can make utilization of continuous physical-based models easier for great scale watersheds. A sensitivity analysis was conducted on each application such that the variability in erosion map output and can be assessed and incorporated into the interpretation of results with an acceptable level of confidence.

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.

Using WaTEM/SEDEM to Configure Catchment Soil Conservation Measures for the Black Soil Region, Northeastern China

In recent years, to combat soil erosion, large-scale soil conservation measures have been implemented in the world. Evaluation of the integrated catchment management is urgently required. In the present study, soil erosion and sediment yield under 24 scenarios were predicted, based on the water and tillage erosion model and sediment delivery deposition model (WaTEM/SEDEM). The current catchment management was not ideal, with a catchment soil loss rate (SLR) of 599.88 t km−2 yr−1 and a sediment yield of 240.00 t km−2 yr−1. The catchment management with contour tillage on <3° slopes, hedgerow planting on 3–5° slopes, terracing on 5–8° slopes, and forestation on >8° slopes with trenches along the forest and dams in gullies was the best catchment management to control soil loss, with catchment SLR that was less than the tolerable value of 200 t km−2 yr−1. However, the SLR on the <3° slopes was still higher than the tolerable value. It is not enough to control soil loss by only implementing contour tillage measure on <3° slopes, and other measures should be further implemented on these slopes. In gullies, more measures should be implemented to prevent sediment flowing out of the catchments, in Northeastern China.

Multi-temporal modeling of road-induced overland flow alterations in a terraced landscape characterized by shallow landslides

The presence of roads in high steep agricultural systems is often linked with landslides occurrence. This research aims to model multi-temporal overland flow dynamics in a shallow landslides-prone terraced landscape (northern Italy).The combined use of Remotely Piloted Aircraft Systems (RPAS) and photogrammetric techniques (e.g., Structure from Motion-SfM) allowed to elaborate multi-temporal high-resolution Digital Elevation Models (DEMs). Hydrological analyses of water flow's depth alterations due to the road presence were carried out adopting the SIMulated Water Erosion model (SIMWE), focusing on different scenarios considering the presence of the road and assuming its absence through a specific DEM smoothing procedure. The possibility to perform multi-temporal hydrological simulations at a hillslope scale so as to analyse the role played by the road in overland flows alteration is still a challenge to be investigated. Results proved the role played by the road in water flows change above the two observed shallow landslides, with respective maximum water depth values equal to 0.18 m and 0.14 m. On the contrary, no-road simulations not revealed significant water flows deviations towards landslides, with water depth values around 0 m, underlining that the absence of the road would avoid relevant changes in water flow paths toward the collapsed surfaces. This work could be a solid starting point for analyse road impact on runoff dynamics and hillslopes stability also at a wider scale, as well as for planning efficient mitigation intervention so as to reduce the occurrence of similar future scenarios.

Prediction of water erosion in a watershed located in southeastern Brazil

Water erosion modeling is a fast and accurate way to estimate erosion potential in watersheds. Among the models, we have the Revised Universal Soil Loss Equation (RUSLE) which has a simple structure, low implementation cost and can be used with readily available information, contributing to the planning of soil conservation practices. In this context, the objective of the work was to apply RUSLE to estimate water erosion in the Córrego da Laje watershed affluent directly from the reservoir of the Furnas Hydroelectric Plant, located in the south of Minas Gerais, a region of southeastern Brazil. In this region, water erosion is a serious problem that has caused the silting up of the hydroelectric reservoir and the depreciation of water quality. Soil losses were calculated in Geographic Information System based on topographic, edaphoclimatic characteristics, soil cover, and management practices. The average soil loss of the watershed was 26.80 Mg ha-1 year-1 with the predominance of highintensity erosive rates (> 15 Mg ha-1 year-1). Considering the basin use classes, sediment generation was higher in pasture areas (35.87 Mg ha-1 year-1), and in areas under maize cultivation (32.05 Mg ha-1 year-1). As areas with severe erosion are distributed throughout the watershed, a comprehensive water erosion mitigation plan should be adopted to reduce the environmental damage of the process.

Analysis of the Influence of DTM Source Data on the LS Factors of the Soil Water Erosion Model Values with the Use of GIS Technology

Counteracting soil degradation is one of the strategic priorities for sustainable development. One of the most important current challenges is effective management of available resources. Multiple studies in various aspects of soil water erosion are conducted in many research institutions in the world. They concern, among others, the development of risk estimation models and the use of new data for modelling. The aim of the presented research was a discussion on the impact of the accuracy and detail of elevation data sources on the results of soil water erosion topographic factors modelling. Elevation data for this research were chosen to reflect various technologies of data acquisition, differences in the accuracy and detail of field forms mapping and, consequently, the spatial resolution of the digital terrain models (DTMs). The methodology of the universal soil loss equation USLE/RUSLE was used for the L and S factors modelling and calculation. The research was carried out in three study areas located in different types of geographical regions in Poland: uplands, highlands and lake districts. The proposed methodology consisted of conducting detailed comparative elevation and slope value assessments, calculating the values of topographical factors of the universal soil loss equation: slope length (L) and slope (S) and a detailed analysis of the total LS factors values. An approach to assess LS factors values within homogeneous areas such as agricultural plots has also been proposed. The studies draw the conclusion that the values of topographical factors obtained from various DTM sources were significantly different. It was shown that the choice of the right modelling data has a significant impact on the L and S factors values and, thus, also, on the decision-making process. The conducted research has definitely shown that data of the highest accuracy and detail should be used to study local phenomena (inter alia erosion), even analysing a large area.

A hillslope version of the revised Morgan, Morgan and Finney water erosion model

The revised Morgan, Morgan and Finney (rMMF) water erosion model calculates annual surface runoff and soil loss from field-sized areas. The original version of the rMMF is neither suited to calculate water erosion along irregular hillslopes, nor capable to allow infiltration of once generated surface runoff at places where the runoff speed slows down, and infiltration could occur under natural conditions. The aim of this article is to describe a new hillslope version of the rMMF model that allows infiltration of surface runoff, and to show examples of soil erosion modelling along real and hypothetical hillslopes. The new hillslope version (hMMF) splits the entire hillslope into a number of sections that have individual properties, such as slope angle, slope length, soil properties and vegetation characteristics. The surface runoff along the slope is calculated by summing the volume of surface runoff generated in a particular section with the surface runoff coming from the immediate upslope section. The related sediment transport is calculated for each section using the calculated detachment for the section, the sediment coming from the upslope section and the transport capacity. A new variable is introduced to account for infiltration of surface runoff and allows simulating the effects of soil and water conservation structures on water erosion. The model was tested using measured data from plots in Africa, Asia, the US and Europe, as well as for a surveyed hillslope in Tunisia (Barbara watershed). Overall, the performance of the hMMF was reasonable for surface runoff and poor for soil loss when recommended input variable values are used. Calibration of the model resulted in a good performance, which shows the capability of the hMMF model to reproduce measured surface runoff and erosion amounts. In addition, realistic water erosion patterns on hillslopes with soil and water conservation can be simulated.

Soil Water Erosion Vulnerability and Suitability under Different Irrigation Systems Using Parametric Approach and GIS, Ismailia, Egypt

Preserving the sustainable agriculture concept requires identifying the plant response to the water regime and rationing the water for irrigation. This research compares different irrigation designs coupled with a parametric evaluation system on soil water erosion and soil suitability to assess the sites vulnerable to soil erosion based on a soil water erosion model (ImpelERO) in an area of 150.0 hectares, Ismailia Governorate, Egypt. Land suitability maps are prepared using the Geographic Information System (GIS), and the soil properties are analyzed and evaluated for the different surface, sprinkler, and drip irrigation methods. The results show that the sprinkler and drip irrigation strategies are more practical irrigation methods and additional environment friendly than surface irrigation for enhancing land productivity. Moreover, the principle acumen for creating use of the surface irrigation on this space is for lowering the soil salinity. Land capability index for surface irrigation ranges from 20.5 to 72.2% (permanently not suitable N2 to moderately suitable S2); and the max capability index (Ci) for drip irrigation was 81.3% (highly suitable-S1), while the mean capability index (Ci) was 42.87% (Currently not suitable-NI). The land suitability of the study area using sprinkler irrigation was ranked as highly suitable (S1), moderately suitable (S2), marginally suitable (S3), and currently not suitable (N1). Thus, the obtained data indicated that applying drip irrigation (trickle irrigation) was the most efficient system compared to the sprinkle and surface irrigation systems. To identify the soil, water erosion vulnerability, and soil optimal management strategies for the agricultural parcel in that region, the ImpelERO model (soil erosion vulnerability/impact/management) was applied. Erosion risk classes ranged from V2 (small) to V3 (moderate), that that region categorized as small-sensitive to water erosion by alfalfa, to moderate-sensitive to water erosion by olive. The results of soil losses varied from 7.1 to 37.9 t ha−1 yr−1 with an average of 17.7 t ha−1 yr−1. Thus, guarantee efficient water use and soil suitability for food production in the future will require the use of an efficient irrigation system.

Applicability of laser diffraction method for soil particle size distribution analysis of five soil orders in the water erosion region of China

Soil particle size distribution (PSD) is a critical parameter for soil loss estimation in many water erosion models. The laser diffraction method (LDM) has been increasingly applied for soil PSD determination in recent decades, and its applicability and reliability need systematical examinations. The objective was to evaluate the performance of LDM for PSD determination of five soil orders in the water erosion region of China relative to the traditional sieve-pipette method (SPM). A total of 465 soil samples were collected in the five water erosion subregions of China, which correspond to five soil orders of Mollisols, Alfisols, Entisols, Inceptisols, and Oxisols. All the samples were analyzed with LDM for the four size fractions widely employed in water erosion models (i.e., 100 to 2,000, 53 to 100, 2 to 53, and &lt;2 μm), and the corresponding results were compared to those obtained by SPM. The comparisons show varying results between LDM and SPM for the sand content, or the two sand-sized fractions of 100 to 2,000 and 53 to 100 μm. LDM consistently overestimated the silt content and underestimated the clay fraction, yet the magnitude of either the overestimation or underestimation varied among soil orders. The PSD discrepancies shifted the textural classes of 44.8% to 96.2% of the soil samples and, on average, increased the soil erodibility <i>K</i> factor by 0.010 to 0.034 t MJ^–1 h mm^–1 for different soil orders. The optimal clay/silt and silt/sand boundaries of LDM were derived to match the size fractions measured by SPM. Nevertheless, except for the silt/sand boundary of 58.2 μm for one soil order, each of the other threshold boundaries held a Lin’s concordance correlation coefficient less than 0.8, suggesting moderate or poor agreement between LDM and SPM. Linear regression models were also established to convert the four size fractions between the two methods for all the samples as well as for each soil order. However, not all the conversion models were statistically significant at the level of 0.05. Those that were significant varied among soil orders for each size fraction. These findings hold important practical implications for soil PSD determination and water erosion modeling in China and elsewhere.