Adapting the RUSLE and GIS to model soil erosion risk in a mountains karst watershed, Guizhou Province, China

Soil erosion is a serious environmental problem in Guizhou Province, which is located in the centre of the karst areas of southwestern China. Unfortunately, Guizhou Province suffers from a lack of financial resources to research, monitor and model soil erosion at large watershed. In order to assess the soil erosion risk, soil erosion modeling at the watershed scale are urgently needed to be undertaken. This study integrated the Revised Universal Soil Loss Equation (RUSLE) with a Geographic Information System (GIS) to estimate soil loss and identify the risk erosion areas in the Maotiao River watershed, which is a typical rural watershed in Guizhou Province. All factors used in the RUSLE were calculated for the watershed using local data. It was classified into five categories ranging from minimal risk to extreme erosion risk depending on the calculated soil erosion amount. The soil erosion map was linked to land use, elevation and slope maps to explore the relationship between soil erosion and environmental factors and identify the areas of soil erosion risk. The results can be used to advice the local government in prioritizing the areas of immediate erosion mitigation. The integrated approach allows for relatively easy, fast, and cost-effective estimation of spatially distributed soil erosion. It thus indicates that RUSLE-GIS model is a useful and efficient tool for evaluating and mapping soil erosion risk at a large watershed scale in Guizhou Province.     

Assessment of spatial distribution of soil loss over the upper basin of Miyun reservoir in China based on RS and GIS techniques

Soil conservation planning often requires estimates of the spatial distribution of soil erosion at a catchment or regional scale. This paper applied the Revised Universal Soil Loss Equation (RUSLE) to investigate the spatial distribution of annual soil loss over the upper basin of Miyun reservoir in China. Among the soil erosion factors, which are rainfall erosivity (R), soil erodibility (K), slope length (L), slope steepness (S), vegetation cover (C), and support practice factor (P), the vegetative cover or C factor, which represents the effects of vegetation canopy and ground covers in reducing soil loss, has been one of the most difficult to estimate over broad geographic areas. In this paper, the C factor was estimated based on back propagation neural network and the results were compared with the values measured in the field. The correlation coefficient (r) obtained was 0.929. Then the C factor and the other factors were used as the input to RUSLE model. By integrating the six factor maps in geographical information system (GIS) through pixel-based computing, the spatial distribution of soil loss over the upper basin of Miyun reservoir was obtained. The results showed that the annual average soil loss for the upper basin of Miyun reservoir was 9.86 t ha(-1) ya(-1) in 2005, and the area of 46.61 km(2) (0.3%) experiences extremely severe erosion risk, which needs suitable conservation measures to be adopted on a priority basis. The spatial distribution of erosion risk classes was 66.9% very low, 21.89% low, 6.18% moderate, 2.89% severe, and 1.84% very severe. Thus, by using RUSLE in a GIS environment, the spatial distribution of water erosion can be obtained and the regions which susceptible to water erosion and need immediate soil conservation planning and application over the upper watershed of Miyun reservoir in China can be identified.     

Kriging for estimating spatial pattern of contaminants: Potential and problems

This paper discusses and illustrates the use of kriging techniques for estimating the spatial pattern of contaminants in environmental media, particularly soil. The assumptions underlying kriging are reviewed as are some advantages and disadvantages of the method. Lognormal kriging (kriging applied to logarithmic-transformed data) is illustrated using a set of radionuclide soil concentrations at a nuclear testing area on the Nevada Test Site. This example shows how lognormal kriging can be used to estimate average concentrations at points or for blocks of land, concentration contours over space, confidence bands about these contours, and radionuclide inventory in soil. The validity of kriging estimates depends on the accurate estimation and modeling of the spatial correlation structure of the phenomenon. Accuracy is especially important when lognormal kriging is used and estimates of means and their standard deviations are required in the original, untransformed scale. This paper illustrates the bias that can result when a changing correlation structure over space is ignored.Operated for the U.S. Department of Energy by Battelle Memorial InstituteWork supported by Nevada Applied Ecology Group, U.S. Department of Energy, Nevada Operations Office under Contract DE-AC06-76RLO 1830.     

CLFUG: A GIS‐scaleable model of pesticide fate in the soil–groundwater system based on clearance and fugacity paradigms

A model of pesticide transport through the soil profile based on clearance and fugacity paradigms is presented, and an example of its application in a GIS environment is shown. A validation of the model at the field plot scale is presented using data obtained at a crop in a semiarid irrigated agricultural basin which was treated with Lindane. The adequacy at the regional scale is tested by inspection of the model predictions and the measured concentrations of the pesticide obtained from a regional phreatimetric net. The clearance concept is used to obtain estimates of the volumes of some environmental phases. These are further used to solve the equations of thermodynamic equilibrium at equal fugacity and obtain concentration estimates. The model closely reproduces the observed percolation trends, and is consistent with the regional pattern of Lindane distribution in groundwater. An application of the model as unitary module for the simulation of non‐point pesticide sources in a raster GIS frame is shown. Its performance (run time, data needed, etc.) is comparable to that of other existing algorithms, and presents some advantages to planners and evaluators of environmental quality in that it incorporates an explicit 2‐D approach and allows the identification of polluted areas downslope with respect to those directly treated with the pesticides. Further, it can be implemented in a variety of GIS and spatial data processors.     

A method to assess soil erosion from smallholder farmers’ fields

Soil erosion by water is a major threat to sustainable food production systems in Africa. This study presents a qualitative soil erosion assessment method that links the number of broken ridges (NBRS) observed on a smallholder farmer’s field after a rain event to factors of soil erosion (e.g., rainfall intensity, slope steepness, crop canopy height, and conservation practice) and to soil loss data measured from a runoff plot and receiving small streams. The assessment method consists of a rapid survey of smallholder farmers combined with field monitoring. Results show an indirect relationship between NBRS and factors of soil erosion. Results also show a direct relationship between NBRS and suspended sediment concentrations measured from an experimental runoff plot and receiving streams that drain the sub-watersheds where farmers’ fields are located. Given the limited human and financial resources available to soil erosion research in developing countries, monitoring NBRS is a simple, cost-effective, and reliable erosion assessment method for regions where smallholder farmers practice contour ridging.     

An experimental method to verify soil conservation by check dams on the Loess Plateau, China

A successful experiment with a physical model requires necessary conditions of similarity. This study presents an experimental method with a semi-scale physical model. The model is used to monitor and verify soil conservation by check dams in a small watershed on the Loess Plateau of China. During experiments, the model–prototype ratio of geomorphic variables was kept constant under each rainfall event. Consequently, experimental data are available for verification of soil erosion processes in the field and for predicting soil loss in a model watershed with check dams. Thus, it can predict the amount of soil loss in a catchment. This study also mentions four criteria: similarities of watershed geometry, grain size and bare land, Froude number (Fr) for rainfall event, and soil erosion in downscaled models. The efficacy of the proposed method was confirmed using these criteria in two different downscaled model experiments. The B-Model, a large scale model, simulates watershed prototype. The two small scale models, D_a and D_b, have different erosion rates, but are the same size. These two models simulate hydraulic processes in the B-Model. Experiment results show that while soil loss in the small scale models was converted by multiplying the soil loss scale number, it was very close to that of the B-Model. Obviously, with a semi-scale physical model, experiments are available to verify and predict soil loss in a small watershed area with check dam system on the Loess Plateau, China.     

Quantification and site-specification of the support practice factor when mapping soil erosion risk associated with olive plantations in the Mediterranean island of Crete

Due to inappropriate agricultural management practices, soil erosion is becoming one of the most dangerous forms of soil degradation in many olive farming areas in the Mediterranean region, leading to significant decrease of soil fertility and yield. In order to prevent further soil degradation, proper measures are necessary to be locally implemented. In this perspective, an increase in the spatial accuracy of remote sensing datasets and advanced image analysis are significant tools necessary and efficient for mapping soil erosion risk on a fine scale. In this study, the Revised Universal Soil Loss Equation (RUSLE) was implemented in the spatial domain using GIS, while a very high resolution satellite image, namely a QuickBird image, was used for deriving cover management (C) and support practice (P) factors, in order to map the risk of soil erosion in Kolymvari, a typical olive farming area in the island of Crete, Greece. The results comprised a risk map of soil erosion when P factor was taken uniform (conventional approach) and a risk map when P factor was quantified site-specifically using object-oriented image analysis. The results showed that the QuickBird image was necessary in order to achieve site-specificity of the P factor and therefore to support fine scale mapping of soil erosion risk in an olive cultivation area, such as the one of Kolymvari in Crete. Increasing the accuracy of the QB image classification will further improve the resulted soil erosion mapping.     

Check dam sediments: an important indicator of the effects of environmental changes on soil erosion in the Loess Plateau in China

Check dam sediments document the process of soil erosion for a watershed. The main objectives of this research are as follows: first, to determine whether the sediments trapped in check dams can provide useful information about local erosion and the environment, and second, to obtain the extent to which they can be stratigraphically interpreted and correlated to the land use history of an area controlled by check dams. Particle size and the concentration of ¹³⁷Cs in sediments are the indicators used to study the effects of environmental changes on soil erosion in the Loess Plateau, China. A total of 216 soil samples were collected from four sediment profile cores at the Yangjuangou watershed check dam constructed in 1955 and fully silted with sediments by 1965. The results indicated that ¹³⁷Cs dating and sediment particle size can characterize the sediment deposition process. Silt makes up more than 50 % of the sediment; both the clay and silt sediment fractions decrease gradually in the upstream direction. The sediment profiles are characterized by three depositional layers. These layers suggest changes in the land use. The top layer showed tillage disturbance, with moderate sediments and new soil mixed from 0 to 20 cm. A transition stage from wetlands (characterized by vegetation such as bulrush) to cropland is inferred from sediments at depths of 20–85 cm. Below 85 cm, sedimentary layering is obvious and there is no tillage disturbance. At the downstream site, A0, the average rate of sediment deposition from 1958 to 1963 was approximately 6,125.4 t year^?1 km^?2. Because of their high time resolution, check dam sediments indicate the effects of environmental changes on soil erosion, and they can provide a multiyear record of the soil erosion evolution at the local scale in the middle reaches of the Yellow River.     

Properties and erosional response of soils in a degraded ecosystem in Crete (Greece)

To study desertification processes relating to soil erosion, a climatological and altitudinal gradient from south to north was selected in Crete (Greece) and four locations were selected along the gradient. At the locations precipitation ranged from 1400 mm/year at the highest location to 400 mm/year at the lowest. All locations are affected by the actual land use: intensive grazing, small controlled fires, and abandoned agricultural terraces. Representative soil profiles were described in the field and analyzed in the laboratory, and rainfall simulation experiments in the field measured soil erosion over different soil surfaces and land uses. Data on physical and chemical properties were obtained from the soil profiles and soil hydrology, and erosion data were obtained from the rainfall simulation experiments. Soil aggregation was studied with samples taken from the soil in the rainfall simulation plots and special attention being paid to the aggregate size distribution and the water-stable microaggregation. The interaction between climatological conditions and land use seems to be the main factor controlling soil erosion. This paper describes how the expected erosion along the gradient (from the most humid to the driest site) can be affected and disturbed by specific processes derived from land use.     

Identification of effective best management practices in sediment yield diminution using GeoWEPP: the Kasilian watershed case study

Identifying areas that are susceptible to soil erosion is crucial for water resource planning and management efforts. Furthermore, modeling has proven helpful in recognizing and monitoring high-risk areas at the watershed scale. The Water Erosion Prediction Project (WEPP) geospatial interface (GeoWEPP) software integrates GIS with the WEPP to analyze the spatial variation in soil loss, and it has been used as a modeling tool to determine the areas that are most prone to soil erosion and to evaluate best management practices for the Kasilian watershed in Iran. As much as 62.4 % of the agronomic land in the Kasilian watershed is affected by a high magnitude of erosion (>5 t/ha). On the basis of this study, by using soybeans, high fertilization levels, and the drill-no-tillage system, reductions of erosion by almost 32.68–34.02 % are perceivable in three critical subwatersheds that are located in the cultivated lands. Also, it is projected that reductions in the production of sediment in the range of about 36.7–47.1 % are achievable by structural management within two critical, upland subwatersheds. So, by utilizing the best management strategies, sediment yield can be lowered and the conservation of soil and water is feasible at the watershed scale. These results objectively indicate that GeoWEPP can be efficaciously used for evaluating effective management practices for developing watershed conservation.     

Erosivity, surface runoff, and soil erosion estimation using GIS-coupled runoff–erosion model in the Mamuaba catchment, Brazil

This study evaluates erosivity, surface runoff generation, and soil erosion rates for Mamuaba catchment, sub-catchment of Gramame River basin (Brazil) by using the ArcView Soil and Water Assessment Tool (AvSWAT) model. Calibration and validation of the model was performed on monthly basis, and it could simulate surface runoff and soil erosion to a good level of accuracy. Daily rainfall data between 1969 and 1989 from six rain gauges were used, and the monthly rainfall erosivity of each station was computed for all the studied years. In order to evaluate the calibration and validation of the model, monthly runoff data between January 1978 and April 1982 from one runoff gauge were used as well. The estimated soil loss rates were also realistic when compared to what can be observed in the field and to results from previous studies around of catchment. The long-term average soil loss was estimated at 9.4 t ha^?1 year^?1; most of the area of the catchment (60 %) was predicted to suffer from a low- to moderate-erosion risk (<6 t ha^?1 year^?1) and, in 20 % of the catchment, the soil erosion was estimated to exceed >?12 t ha^?1 year^?1. Expectedly, estimated soil loss was significantly correlated with measured rainfall and simulated surface runoff. Based on the estimated soil loss rates, the catchment was divided into four priority categories (low, moderate, high and very high) for conservation intervention. The study demonstrates that the AvSWAT model provides a useful tool for soil erosion assessment from catchments and facilitates the planning for a sustainable land management in northeastern Brazil.     

Investigation of wind erosion process for estimation, prevention, and control of DSS in Yazd–Ardakan plain

Wind erosion is a phenomenon that is reasonably common in regions where dry winds blow. For the most part, these regions correspond to the dry lands; areas where the soil, generally, is dry and shifting and lacks vegetation for most of the year. The winds are sufficiently strong to lift and move sands and soil particles. The repeated removal of superficial layers by the action of winds can modify the texture of the topsoil, by removing the fine particles and leaving the larger particles. Dust and sandstorm (DSS) is the generic term for a serious environmental phenomenon that involves strong winds that blow a large quantity of dust and fine sand particles away from the ground and carry them over a long distance with significant environmental impacts along the way. In the realm of DSS in Iran country, the people who live in Yazd and Sistan–Baluchestan provinces form a single ecological community due to their geographic proximity and climatic contiguity. The major sources of DSS in the region are believed to be the desert and semidesert areas of the Yazd–Ardakan plain in Yazd province. Both Sistan and Baluchestan are the recipients of this dust. To address the long-range transboundary environmental problem of DSS, a regional cooperation mechanism must be established among the provinces in the region. Yazd–Ardakan plain, with area of about 650,000 ha, is located in the center of Iran, between Yazd and Ardakan cities. The mean annual rainfall is less than 65 mm. Rainfall distribution is a simple modal and more than 70% of it occurs in winter. Plant density varies from 0% to 25%, and Artemisia sieberi is the dominant plant species. The major part of Yazd–Ardakan plain is bare land. According to the recent investigation, more than 20,000-m³ dust with less than 100-μm diameter falls down annually on Yazd city with an area of 7,000 ha. Horizontal visibility is reduced to less than 6 m in stormy days in some parts of Yazd–Ardakan plain. This phenomenon causes car accidents on the main roads of Yazd–Ardakan and can cancel the airplane flights in the stormy days. At present, it is estimated that wind erosion causes more than $6.8 million damages to socioeconomic resources in Yazd plain each year. This paper describes the pattern of occurrence of wind erosion and major contributing factors, summarizes measured rates of wind erosion, outlines the techniques used to mitigate wind erosion hazard, and suggests research priorities. Also, damages of DSS have been estimated and methods for prevention and control are suggested.     

Estimates of soil erosion using cesium-137 tracer models

The soil erosion was studied by ¹³⁷Cs technique in Yatagan basin in Western Turkey, where there exist intensive agricultural activities. This region is subject to serious soil loss problems and yet there is not any erosion data towards soil management and control guidelines. During the soil survey studies, the soil profiles were examined carefully to select the reference points. The soil samples were collected from the slope facets in three different study areas (Kırtas, Peynirli and Kayısalan Hills). Three different models were applied for erosion rate calculations in undisturbed and cultivated sites. The profile distribution model (PDM) was used for undisturbed soils, while proportional model (PM) and simplified mass balance model (SMBM) were used for cultivated soils. The mean annual erosion rates found using PDM in undisturbed soils were 15 t ha⁻¹ year⁻¹ at the Peynirli Hill and 27 t ha⁻¹ year⁻¹ at the Kırtas Hill. With the PM and SMBM in cultivated soils at Kayışalan, the mean annual erosion rates were obtained to be 65 and 116 t ha⁻¹ year⁻¹, respectively. The results of ¹³⁷Cs technique were compared with the results of the Universal Soil Loss Equation (USLE).     

Distributed process modeling for regional assessment of coastal vulnerability to sea-level rise

Sea-level rise involves increases in the coastal processes of inundation and erosion which are affected by a complex interplay of physical environmental parameters at the coast. Many assessments of coastal vulnerability to sea-level rise have been detailed and localised in extent. There is a need for regional assessment techniques which identify areas vulnerable to sea-level rise. Four physical environmental parameters – elevation, exposure, aspect and slope, are modeled on a regional scale for the Northern Spencer Gulf (NSG) study area using commonly available low-resolution elevation data of 10 m contour interval and GIS-based spatial modeling techniques. For comparison, the same parameters are modeled on a fine-scale for the False Bay area within the NSG using high-resolution elevation data. Physical environmental parameters on the two scales are statistically compared to coastal vulnerability classes as identified by Harvey et al. [1] using the Spearman rank-correlation test and stepwise linear regression. Coastal vulnerability is strongly correlated with elevation and exposure at both scales and this relationship is only slightly stronger for the high resolution False Bay data. The results of this study suggest that regional scale distributed coastal process modeling may be suitable as a first cut in assessing coastal vulnerability to sea-level rise in tide-dominated, sedimentary coastal regions. Distributed coastal process modeling provides a suitable basis for the assessment of coastal vulnerability to sea-level rise of sufficient accuracy for on-ground management and priority-setting on a regional scale.     

Empirical evaluation of spatial and non-spatial European-scale multimedia fate models: results and implications for chemical risk assessment

Multimedia environmental fate models are commonly-applied tools for assessing the fate and distribution of contaminants in the environment. Owing to the large number of chemicals in use and the paucity of monitoring data, such models are often adopted as part of decision-support systems for chemical risk assessment. The purpose of this study was to evaluate the performance of three multimedia environmental fate models (spatially- and non-spatially-explicit) at a European scale. The assessment was conducted for four polycyclic aromatic hydrocarbons (PAHs) and hexachlorobenzene (HCB) and compared predicted and median observed concentrations using monitoring data collected for air, water, sediments and soils. Model performance in the air compartment was reasonable for all models included in the evaluation exercise as predicted concentrations were typically within a factor of 3 of the median observed concentrations. Furthermore, there was good correspondence between predictions and observations in regions that had elevated median observed concentrations for both spatially-explicit models. On the other hand, all three models consistently underestimated median observed concentrations in sediment and soil by 1-3 orders of magnitude. Although regions with elevated median observed concentrations in these environmental media were broadly identified by the spatially-explicit models, the magnitude of the discrepancy between predicted and median observed concentrations is of concern in the context of chemical risk assessment. These results were discussed in terms of factors influencing model performance such as the steady-state assumption, inaccuracies in emission estimates and the representativeness of monitoring data.     

Redistribution of Cesium-137 as an example of a chemical indicator of environmental stress

The use of the artificially-produced radioactive isotope Cesium-137 for the measurement of soil erosion is examined in this article as an example of the development of a chemical indicator of a specific environmental stress. The theoretical and methodological bases of the technique ar examined in the context of seven criteria developed to assess the suitability of a technique as a chemical indicator. The type of results available from the application of the technique are demonstrated for research in agricultural ecosystems in Saskatchewan, Canada. The research indicates that mean soil losses within agricultural fields are 2 to 3 times higher than the tolerable soil losses for the area and that net soil export from fields is a poor indicator of the intensity of erosion within the field. The major remaining constraint to the use of the technique is the lack of a standardized sampling and analytical framework for researchers using the procedure.     

Assessing soil quality indicator under different land use and soil erosion using multivariate statistical techniques

Soil degradation associated with soil erosion and land use is a critical problem in Iran and there is little or insufficient scientific information in assessing soil quality indicator. In this study, factor analysis (FA) and discriminant analysis (DA) were used to identify the most sensitive indicators of soil quality for evaluating land use and soil erosion within the Hiv catchment in Iran and subsequently compare soil quality assessment using expert opinion based on soil surface factors (SSF) form of Bureau of Land Management (BLM) method. Therefore, 19 soil physical, chemical, and biochemical properties were measured from 56 different sampling sites covering three land use/soil erosion categories (rangeland/surface erosion, orchard/surface erosion, and rangeland/stream bank erosion). FA identified four factors that explained for 82 % of the variation in soil properties. Three factors showed significant differences among the three land use/soil erosion categories. The results indicated that based upon backward-mode DA, dehydrogenase, silt, and manganese allowed more than 80 % of the samples to be correctly assigned to their land use and erosional status. Canonical scores of discriminant functions were significantly correlated to the six soil surface indices derived of BLM method. Stepwise linear regression revealed that soil surface indices: soil movement, surface litter, pedestalling, and sum of SSF were also positively related to the dehydrogenase and silt. This suggests that dehydrogenase and silt are most sensitive to land use and soil erosion.     

How does environmental pollution erode political trust in China? A multilevel analysis

The impacts of environmental pollution extend beyond the issue of health. Using Chinese survey and administrative data, this study sheds new light on the political costs of environmental pollution. We show that citizens' trust in government officials declines significantly with higher levels of measured pollution, perceptions of increased pollution, and a greater degree of willingness to support environmental protection. Political trust is particularly low when measured as well as perceived pollution are severe. However, the effect of greater willingness to support environmental protection on the erosion of political trust is independent of measured pollution. Our findings suggest that there is a tipping point at which legitimacy acquired primarily through economic achievements could be undermined by environmental degradation, which is a byproduct of economic achievements. It is imperative for the Chinese government to achieve a balance between fast-paced growth and environmental sustainability, to pay attention to the potential political consequences of environmental issues, and to permit more public dialogues and deliberations on the topic of environmental governance.     

Morphometry and land cover based multi-criteria analysis for assessing the soil erosion susceptibility of the western Himalayan watershed

Complex mountainous environments such as Himalayas are highly susceptibility to natural hazards particular those that are triggered by the action of water such as floods, soil erosion, mass movements and siltation of the hydro-electric power dams. Among all the natural hazards, soil erosion is the most implicit and the devastating hazard affecting the life and property of the millions of people living in these regions. Hence to review and devise strategies to reduce the adverse impacts of soil erosion is of utmost importance to the planners of watershed management programs in these regions. This paper demonstrates the use of satellite based remote sensing data coupled with the observational field data in a multi-criteria analytical (MCA) framework to estimate the soil erosion susceptibility of the sub-watersheds of the Rembiara basin falling in the western Himalaya, using geographical information system (GIS). In this paper, watershed morphometry and land cover are used as an inputs to the MCA framework to prioritize the sub-watersheds of this basin on the basis of their different susceptibilities to soil erosion. Methodology included the derivation of a set of drainage and land cover parameters that act as the indicators of erosion susceptibility. Further the output from the MCA resulted in the categorization of the sub-watersheds into low, medium, high and very high erosion susceptibility classes. A detailed prioritization map for the susceptible sub-watersheds based on the combined role of land cover and morphometry is finally presented. Besides, maps identifying the susceptible sub-watersheds based on morphometry and land cover only are also presented. The results of this study are part of the watershed management program in the study area and are directed to instigate appropriate measures to alleviate the soil erosion in the study area.     

Land degradation assessment by geo-spatially modeling different soil erodibility equations in a semi-arid catchment

Land degradation by soil erosion is one of the most serious problems and environmental issues in many ecosystems of arid and semi-arid regions. Especially, the disturbed areas have greater soil detachability and transportability capacity. Evaluation of land degradation in terms of soil erodibility, by using geostatistical modeling, is vital to protect and reclaim susceptible areas. Soil erodibility, described as the ability of soils to resist erosion, can be measured either directly under natural or simulated rainfall conditions, or indirectly estimated by empirical regression models. This study compares three empirical equations used to determine the soil erodibility factor of revised universal soil loss equation prediction technology based on their geospatial performances in the semi-arid catchment of the Saraykoy II Irrigation Dam located in Cankiri, Turkey. A total of 311 geo-referenced soil samples were collected with irregular intervals from the top soil layer (0-10?cm). Geostatistical analysis was performed with the point values of each equation to determine its spatial pattern. Results showed that equations that used soil organic matter in combination with the soil particle size better agreed with the variations in land use and topography of the catchment than the one using only the particle size distribution. It is recommended that the equations which dynamically integrate soil intrinsic properties with land use, topography, and its influences on the local microclimates, could be successfully used to geospatially determine sites highly susceptible to water erosion, and therefore, to select the agricultural and bio-engineering control measures needed.