Soil Erodibility Values Research Articles

PREDIKSI EROSI PADA BEBERAPA TIPE AGROEKOSISTEM DI SUB-DAS SERANG HULU DAERAH TANGKAPAN WADUK KEDUNG OMBO JAWA TENGAH

Erosion Prediction on the Agroecosystem Types at Serang Hulu Sub‐Watershed Catchment Area Kedung Ombo Reservoir in Central Java. The research about erosion prediction on the agroecosystem types at Serang Hulu Sub‐Watershed catchment area Kedung Ombo reservoir in Central Java. The results showed that rain fall were classified slightly low‐high (1276‐2970 mm/year), rain erosivity index (R) 1546‐3894. The highest soil erosion value on the agroecosystem type of inhabitants forest is 166,56‐264,83 ton/ha/year. The lowest erosion value on the agroecosystem type irrigated paddy‐soil (1,74‐11,83 ton/ha/year), followed by rainfed field (7,28 ton/ha/year), forest protect (14,29 ton/ha/year), production forest (20,90 ton/ha/year), agroforestry (56,31 ton/ha/year), dryland ( 77,86 ton/ha/year), and mixed garden(134,34‐155,49 ton/ha/year). The efforts of soil and water conservation technique must be conducted especially for the agroecosystem inhabitants forest, mixed garden, dryland, and agroforestry to stabilize and sustainablize land productivity. Keywords: Agroecosystem, Erosion, Serang Hulu Sub‐Watershed

Modelling the dynamics of soil redistribution induced by sheet erosion using the Universal Soil Loss Equation and cellular automata

As a landscape changes, so do the flows of matter that run across it. These flows modify the landscape and can thereby alter their own course in a feedback mechanism. This study focuses on one instance of this process: medium-term background soil redistribution induced by sheet erosion. Previous studies that have modelled this phenomenon have either focused exclusively on a feedback loop, or have not included it at all. We incorporate all relevant soil-environmental variables, including a feedback loop, into a single model. A unique feature of the proposed model is in the handling of the fluvial sediment flux (qs), which may be determined from the Universal Soil Loss Equation (USLE). The USLE itself does not explicitly incorporate a feedback loop, but can readily be made to incorporate it by calculating a new, spatially distributed value for qs at each time step in response to topographical changes. Hence, the objective of this study was to develop a soil redistribution model that considers qs as being both spatially distributed and temporally dynamic.Rainfall erosivity was derived from mean annual precipitation, vegetation cover from satellite imagery, and slope characteristics from a DEM; in addition, soil erodibility values were derived from legacy soil survey data. The developed model was tested on Bowen Island, British Columbia, Canada at a 25m spatial resolution. Soil redistribution simulations were made for 100years, where 95% of the soil depth change was between a 3.01cm loss and a 2.40cm accumulation. The model was tested in order to assess the effects of different flow routing algorithms, resolutions, and soil deposition regimes on soil redistribution. Incorporating a feedback loop into the model yielded a disproportionate effect on soil redistribution; hence, small changes in the model state resulted in effects that are several orders of magnitude larger than the original change.

Volume-based soil particle fractal relation with soil erodibility in a small watershed of purple soil

The particle size distribution in small watershed changes under different land uses and affects soil erodibility. The aims of this study were (1) to investigate the volume fractal dimension of particle size distribution under different land uses in a typical small watershed of purple soil, (2) to estimate soil erodibilities of various land uses utilizing the Erosion-Productivity Impact Calculator (EPIC) model and the nomogram (NOMO) model, and (3) to relate volume fractal dimension with the soil erodibility used in the Universal Soil Loss Equation (USLE) in purple soil areas. Laser diffractions and double-logarithmic model were used to measure and calculate volume fractal dimension values. The results show that soil volume fractal dimensions were well linearly fitted to the double-logarithmic model with high correlation coefficients of 0.902–0.936 under six land uses in the small watershed. The averaged volume fractal dimension values under different land uses, from high to low were in the order of Zea mays L, Ipomoea batatas, Citrus reticulata Blanco, Setaria viridis, Robinia pseudoacacia L, Pinus massoniana Lamb. The volume fractal dimension was positively correlated to clay particle fraction (R = 0.933). The average soil erodibility values under different land uses from high to low were in the order of Setaria viridis, Citrus reticulata Blanco, Pinus massoniana Lamb, Zea mays L, Ipomoea batatas, Robinia pseudoacacia L while average soil erodibilities from high to low values were in the order of Setaria viridis, Citrus reticulata Blanco, Zea mays L, Ipomoea batatas, Pinus massoniana Lamb, Robinia pseudoacacia L. The soil erodibilities calculated by the two models were similar, and positively correlated (R = 0.630–0.877). The volume fractal dimension values of six land uses were negatively correlated to both soil erodibility estimated by EPIC and by NOMO models. Moreover, the correlations of the volume fractal dimension values of Zea mays L, Ipomoea batatas and Citrus reticulata Blanco estimated by EPIC or NOMO were lower than those of Pinus massoniana Lamb, Robinia pseudoacacia L and Setaria viridis. Further research is needed to determine the influence of volume fractal dimension on the soil erodibility under different land use and managements.

Comparison of soil erodibility factors in USLE, RUSLE2, EPIC and Dg models based on a Chinese soil erodibility database

Soil erodibility (K-value) is a key parameter in erosion prediction and is important for conservation planning in the face of a rising need for protecting the limited land resources. This study investigated the predictive capability of the K-value estimated by Universal Soil Loss Equation (USLE), Revised Universal Soil Loss Equation (RUSLE), Erosion Productivity Impact Calculator (EPIC) and Dg models for different soil regions using a Chinese soil erodibility database covering 51 natural runoff plots. Model performance was evaluated using R 2 (coefficient of determination), relative error (RE), Nash–Sutcliff efficiency (NSE) and P value (Mann–Whitney U test) statistics. The results showed that the existing four models overestimated almost all the K-values for the Chinese erodibility database, with most observed values concentrated in the range of 0.015–0.035. Without calibration, only the USLE and Dg models could be reliable and directly applied for the black soil region and the loess soil region, respectively. The Dg–OM model (R 2=0.67, n=32) was established by the non-linear best fitting techniques of multiple regression. In the Dg–OM model, K-values accounted for the vibration in a combination of the D g (geometric mean diameter) and OM (soil organic matter). NSE, R 2 and the average RE was 0.94, 0.67 and 9.5% for the Dg–OM model's calibration based on the Chinese erodibility database; similar results were found for the validation process, with NSE of 0.93, R 2 of 0.66 and average RE of 6.5%. The model performances showed that the Dg–OM model reached ‘good’ satisfactory level. Compared with the four existing erodibility models, the Dg–OM model permitted the best parameterization and accuracy, and was proved to be suitable for estimating soil erodibility values in China.

Variability of Soil Erosion under Different Topographical and Vegetation Conditions in Upper Min River Watershed

Soil erosion by water is affected by soil factor, rainfall erosivity, geographical factors, vegetation cover factor, and support practice factors. On the basis of quantitative estimation of soil erosion in the Upper Min River (UMR) watershed (located in the Upper Yangtze River basin, Sichuan, China) by applying the Revised Soil Loss Equation (RUSLE) model, Geographical Information System (GIS) software, and Remote Sensing (RS) technology, we explored the effects of topography and vegetation on soil loss for better erosion control measures, and analyzed ecological restoration approaches for the high soil erosion areas of this mountainous watershed. Totally 625 field plots were sampled for visually verifying soil erosion classification. Zonal statistics in ArcGIS software were used to assess the values of soil loss under different topographic and vegetation gradients. The results showed 58.1% of this watershed suffering moderate, high or extremely high erosion. The average soil erosion values substantially increased as the slope ranges rising. On the slopes of 7 categories (50 degrees), the percent of moderate, high and extreme risks accounted for 12.07%, 21.03%, 36.43%, 62.83%, 82.51%, 91.04%, and 94.02% respectively. The values of soil loss on sunny slopes were higher than those on shady slopes. The mean value was the greatest on the west-facing slope. On each similar slope, vegetation types showed different patterns to soil loss, and higher vegetation cover prevented more soil loss from erosion. In order to alleviate soil loss hazards, conservation measures to change micro-topography including terraces and contour tillage could be implemented in the watershed, and ecological restoration could be effective measure for controlling soil erosion in this degraded mountainous watershed.

Relating Management Practices and Nutrient Export in Agricultural Watersheds of the United States

Relations between riverine export (load) of total nitrogen (N) and total phosphorus (P) from 133 large agricultural watersheds in the United States and factors affecting nutrient transport were evaluated using empirical regression models. After controlling for anthropogenic inputs and other landscape factors affecting nutrient transport-such as runoff, precipitation, slope, number of reservoirs, irrigated area, and area with subsurface tile drains-the relations between export and the area in the Conservation Reserve Program (CRP) (N) and conservation tillage (P) were positive. Additional interaction terms indicated that the relations between export and the area in conservation tillage (N) and the CRP (P) progressed from being clearly positive when soil erodibility was low or moderate, to being close to zero when soil erodibility was higher, to possibly being slightly negative only at the 90th to 95th percentile of soil erodibility values. Possible explanations for the increase in nutrient export with increased area in management practices include greater transport of soluble nutrients from areas in conservation tillage; lagged response of stream quality to implementation of management practices because of nitrogen transport in groundwater, time for vegetative cover to mature, and/or prior accumulation of P in soils; or limitations in the management practice and stream monitoring data sets. If lags are occurring, current nutrient export from agricultural watersheds may still be reflecting the influence of agricultural land-use practices that were in place before the implementation of these management practices.

A comparison between soil loss evaluation index and the C-factor of RUSLE: a case study in the Loess Plateau of China

Abstract. Land use and land cover are most important in quantifying soil erosion. Based on the C-factor of the popular soil erosion model, Revised Universal Soil Loss Equation (RUSLE) and a scale-pattern-process theory in landscape ecology, we proposed a multi-scale soil loss evaluation index (SL) to evaluate the effects of land use patterns on soil erosion. We examined the advantages and shortcomings of SL for small watershed (SLsw) by comparing to the C-factor used in RUSLE. We used the Yanhe watershed located on China's Loess Plateau as a case study to demonstrate the utilities of SLsw. The SLsw calculation involves the delineations of the drainage network and sub-watershed boundaries, the calculations of soil loss horizontal distance index, the soil loss vertical distance index, slope steepness, rainfall-runoff erosivity, soil erodibility, and cover and management practice. We used several extensions within the geographic information system (GIS), and AVSWAT2000 hydrological model to derive all the required GIS layers. We compared the SLsw with the C-factor to identify spatial patterns to understand the causes for the differences. The SLsw values for the Yanhe watershed are in the range of 0.15 to 0.45, and there are 593 sub-watersheds with SLsw values that are lower than the C-factor values (LOW) and 227 sub-watersheds with SLsw values higher than the C-factor values (HIGH). The HIGH area have greater rainfall-runoff erosivity than LOW area for all land use types. The cultivated land is located on the steeper slope or is closer to the drainage network in the horizontal direction in HIGH area in comparison to LOW area. The results imply that SLsw can be used to identify the effect of land use distribution on soil loss, whereas the C-factor has less power to do it. Both HIGH and LOW areas have similar soil erodibility values for all land use types. The average vertical distances of forest land and sparse forest land to the drainage network are shorter in LOW area than that in HIGH area. Other land use types have shorter average vertical distances in HIGH area than that LOW area. SLsw has advantages over C-factor in its ability to specify the subwatersheds that require the land use patterns optimization by adjusting the locations of land uses to minimize soil loss.

A robust algorithm for estimating soil erodibility in different climates

The analysis of global soil erodibility data by Salvador Sanchis et al. (2008) showed that there is a significant climate effect on soil erodibility which allows for a split of the data into two subsets, one for prevailing cool conditions and another for prevailing warm conditions (defined using the Köppen climate classification). Despite the recognition of this new dichotomous variable, prediction of soil erodibility values remained very poor. This paper presents a new technique for dealing with such a variability by calculating probability density functions of soil erodibility K values when the user knows a set of textural parameters and the climatic classification of the site. Finally the user has the possibility to decide, on the basis of local knowledge, which K value to use. The procedure has been implemented in a freeware software named KUERY available for the scientific community. Finally, as an illustration, the methodology is applied to a catchment in south Italy.

Assessing soil redistribution in a complex karst catchment using fallout 137Cs and GIS

Caesium-137 derived from nuclear testing in the past century has been widely used as a sediment tracer of soil redistribution, providing information on medium term (40–50years) erosion rates. To date, most studies have focused on individual fields of limited extent, but estimated rates and patterns of soil redistribution require upscaling to catchment level. An attempt to assess soil redistribution processes with strong geomorphic control on complex terrain, such as an internally drained karst catchment, is presented in this work. A comprehensive geomorphological survey of the Estanya Lake catchment (Spanish Pyrenees) enabled the main geomorphic elements to be identified with a grid resolution of 5×5m, which was the basis for the terrain analyses. A detailed DEM was constructed and improved after field identification of the drainage system and point measures on gentle slopes with Total Topographic Station. A 100×100m sampling grid was established to derive point data of 137Cs inventories across the catchment. Geostatistical interpolation of point samples of 137Cs inventories in soil was carried out to identify and assess the areas of sediment gain and loss by comparing with 137Cs reference inventories. Profile activity models were used to calibrate 137Cs data and to derive estimates of soil redistribution. GIS was used to provide spatially distributed erosion and deposition rates in the landscape for the whole catchment. The median values of soil erosion and deposition of 4.7 and 3.1Mgha−1year−1, respectively, showed a large variability and reveal coupling between erosional and depositional forms in the catchment. The highest erosion and deposition rates were found in cultivated fields at the southern sector of the catchment. The spatial analysis of the results supports the importance of taking into account geomorphological features in karst catchments as relevant controlling factors in soil redistribution processes.

Resistência à erosão em ravinas, em latossolo argiloarenoso

As ravinas consistem em uma das formas de erosão hídrica com escoamento superficial concentrado em encostas de áreas degradadas e, ainda, sem escoamentos de subsuperfície. Os objetivos deste trabalho foram estudar o comportamento hidráulico do escoamento superficial das ravinas e determinar a erodibilidade (Kr) e a tensão crítica de cisalhamento (τc) na superfície de ravinas e, também, a erodibilidade (Kr) ao longo do perfil de encostas degradadas do litoral do Estado de Pernambuco. O experimento foi realizado em 2005, em um Latossolo Amarelo de textura argilosa pertencente à Formação Barreiras no município do Cabo de Santo Agostinho, PE. As parcelas foram delimitadas por chapas metálicas cravadas no solo no sentido do declive (1,0 m de largura por 3,0 m de comprimento). Os testes consistiram na aplicação de quatro níveis de vazão, determinando-se o volume de descarga líquida e a massa de sedimentos desagregados. As taxas de desagregação de solo foram lineares em relação às tensões de cisalhamento. Na superfície das ravinas, a erodibilidade (Kr) foi de 0,0016 kg N-1 s-1 e a tensão crítica de cisalhamento, de τc = 4,37 Pa. O baixo valor de erodibilidade e o alto de tensão crítica de cisalhamento de τc obtidos na superfície das ravinas possivelmente decorreram da formação de uma crosta superficial originada por ciclos de umedecimento e secagem. A erodibilidade (Kr) em profundidade variou entre 0,012 e 0,070 kg N-1 s-1, em função do teor de argila. O regime do escoamento superficial nas ravinas foi turbulento supercrítico e, portanto, semelhante ao do escoamento superficial nos sulcos de erosão, como descrito na literatura.

Negligible soil erosion in a burned mountain watershed, Canadian Rockies: field and modelling investigations considering the role of duff

ABSTRACTIncreased soil erosion in immediate post‐wildfire years has been well documented in the literature, but many unanswered questions remain about the factors controlling erosional responses in different regional settings. The field site for the present study was located in a closed canopy, subalpine forest in Kootenay National Park, British Columbia that was subjected to a high‐intensity crown fire in the summer of 2003. Low soil erosion values were documented at the study site in the years immediately following the 2003 wildfire, with estimates ranging from approximately 10‐1 up to 100 t ha‐1. Following the wildfire, notable duff coverage (the duff layer is the combined fermentation and humus soil organic layers) remained above the mineral soil. This finding supports earlier studies documenting only partial duff consumption by high‐intensity wildfires in the boreal forest of Canada. It is postulated that remnant duff coverage after many high‐intensity wildfires impacts the hydrological and soil erosional response to rainstorm events in post‐wildfire years. In particular, duff provides detention storage for infiltrating rainfall and, therefore, may inhibit the generation of overland flow. Furthermore, duff also provides a physical barrier to soil erosion. The Green–Ampt model of rainfall infiltration is employed to better assess how interactions between rainfall duration/intensity and soil/duff properties affect hydrological response and the generation of overland flow. Model results show that duff provides an effective zone for detention storage and that duff accommodates all rainfall intensities to which it was subjected without the occurrence of surface ponding. In addition, the penetration of the wetting front is relatively slow in duff due to its high porosity and water storage potential. Copyright © 2011 John Wiley & Sons, Ltd.

Assessing the potential effect of different land cover management practices on sediment yield from an abandoned farmland catchment in the Spanish Pyrenees

PurposeSediment delivery from headwater catchments to reservoirs is a serious threat to reservoir sustainability and is a critical issue in Mediterranean environments where water resources are scarce. In this study we assessed the consequences of two landscape management scenarios (natural vegetation recovery and scrub clearance) on soil erosion and sediment yield. The results were analyzed in relation to predicted and measured rates of soil erosion and sediment yield, with the aim of promoting better management practices.Materials and methodsThe study area was the Arnás River catchment (284 ha), which is located in the central Spanish Pyrenees; the area includes abandoned and poorly managed fields. The combination of the RUSLE and SEDD models of soil erosion and sediment delivery was evaluated in terms of its ability to predict annual rates of sediment yield, using field measurement data for seven water years at the gauging station. The consequences of natural plant succession in other areas of the Spanish Pyrenees and scrub clearance practices implemented by certain regional governments to increase grazing meadow areas and reduce the incidence of wildfires were spatially analyzed using GIS. The main sediment source areas were identified, and their specific and total sediment yields were calculated.Results and discussionThe predicted soil loss under existing conditions was 2.6 Mg ha−1 year−1, with 5% of the surface area affected by rates greater than 2 Mg. The measured sediment yield range was 69–534 Mg year−1. The maximum sediment yield detected was associated with an extraordinary debris flow. The predicted rates were strongly correlated to measured rates (Nash–Sutcliffe coefficient = 0.72). The main sources were alluvial deposits [specific sediment yield (SSY) = 51 Mg ha−1 year−1], bare soil (SSY = 12), unpaved trails (SSY = 11), lots (SSY = 4), and pastures (SSY = 1). Under a scenario of vegetation recovery, decreases of 3%, 17%, and 16% in soil loss and sediment delivery and yield (respectively) are predicted, whereas increases of 15%, 5%, and 2% are predicted following scrub clearance practices.ConclusionsCoupling the RUSLE and SEDD models enabled estimation of annual values of soil erosion and sediment delivery in monitored and unmonitored catchments of small and medium size, making this approach a useful tool for risk analysis. Management practices that combine fire-risk control, by the implementation of scrub clearance practices, with the effects of plant succession on sediment production are suggested as the best management strategy.

Measuring medium-term sheet erosion in gullies from trees: A case study using dendrogeomorphological analysis of exposed pine roots in central Iberia

The assessment of gully erosion poses a great challenge because of the complexity and connectivity of the geomorphic processes involved. This study focuses on the quantification of sheet erosion rates in a set of slope gullies located on the northern piedmont of the Guadarrama Mountains (Spanish Central System). In order to delineate accurately the gully areas in which sheet erosion was predominant, the Hydrologic/Erosion Response Unit (HRU/ERU) approach was used and a dendrogeomorphological analysis of exposed tree roots was carried out to quantify sheet erosion rates in one selected HRU/ERU. Identification of the first year of exposure by erosion from anatomical criteria was therefore critical. The 29 samples taken were prepared for anatomical analysis and cross-dated. Anatomical analysis of the samples showed a reduction in the lumen area of earlywood tracheids following root exposure and also, in most cases, a slight increase in growth rings. Moreover, at the end of the ring, latewood tissue and visible annual borders were very clearly defined by several rows of thick-walled tracheids. A non-parametric test was used on the findings derived from this qualitative analysis to objectify determination of the first year of exposure. Estimates of sheet erosion were obtained by dividing the height of eroded soil by the number of years that each root was exposed. The mean value of soil erosion for the entire study site was then determined from statistical inference. Using this procedure, a range of sheet erosion rates between 6.2 and 8.8 mm y −1 (125.2 and 177.8 t ha −1 year −1) was obtained for the dominant HRU/ERU of these gullies in central Iberia. These estimates of eroded soil thickness were adjusted based on the recent finding that root anatomical changes occur prior to their exposure by erosion.

Hillslope runoff and erosion on duplex soils in grazing lands in semi-arid central Queensland. III. USLE erodibility (K factors) and cover - soil loss relationships

Measured Universal Soil Loss Equation (USLE) soil erodibility (K) values are not available for soils in grazing lands in northern Australia. The K values extrapolated from croplands are used in national and river-basin scale assessments of hillslope erosion, using an assumption that the cover factor (C) equals 0.45 for undisturbed (uncultivated) bare soil. Thus, the K needed for input into the models is the measured K for undisturbed soil (KU) divided by 0.45. Runoff and erosion data were available for 7 years on 12 hillslope plots with cover of 10–80%, with and without grazing, with and without tree canopy cover, on a variety of soils according to various soil classification systems. Soils were grouped into those derived from sandstone (SS), mudstone (MS), and eroded mudstone (MSe). These data were used to determine USLE KU, K, and C factor–cover relationships. Methods used to fit the parameters affected the results; minimising the sum of squares of errors in soil losses gave better results than fitting an exponential equation. The USLE LS (length–slope) factor explained the increase in measured average annual soil loss with slope, for plots with low cover. Erodibility (K) was 0.042 for SS and MS soils, irrespective of Australian Soil Classification (Chromosol, Kandosol, Rudosol, Sodosol, Tenosol); K was 0.062 for exposed, decomposing mudstone (MSe Leptic Rudosol). The measured K factor for SS and MS soils was close to that used in catchment-wide soil loss estimation for the site (0.039). This indicates that the method used for estimating K from soil properties (derived from cultivated soils) gave a reasonable estimate of K for the main duplex soils at the study site, as long as the correction for undisturbed soil is used in deriving K from measured data and in applying the USLE model. A 20% increase in K (0.050) for SS and MS soils may be warranted for heavy grazing by cattle. The C factor–cover relationship was different from the standard revised USLE (RUSLE) relationship, requiring a greater exponent (‘bcov’) of 0.075, rather than the default for cropland of 0.035. Increasing cover is therefore more effective at the site than suggested by the USLE. Parameters of USLE were also derived for bedload, allowing suspended load to be calculated by subtracting bedload from total soil loss.

Soil erosion modelled with USLE and PESERA using QuickBird derived vegetation parameters in an alpine catchment

The focus of soil erosion research in the Alps has been in two categories: (i) on-site measurements, which are rather small scale point measurements on selected plots often constrained to irrigation experiments or (ii) off-site quantification of sediment delivery at the outlet of the catchment. Results of both categories pointed towards the importance of an intact vegetation cover to prevent soil loss. With the recent availability of high-resolution satellites such as IKONOS and QuickBird options for detecting and monitoring vegetation parameters in heterogeneous terrain have increased. The aim of this study is to evaluate the usefulness of QuickBird derived vegetation parameters in soil erosion models for alpine sites by comparison to Cesium-137 (Cs-137) derived soil erosion estimates. The study site (67km2) is located in the Central Swiss Alps (Urseren Valley) and is characterised by scarce forest cover and strong anthropogenic influences due to grassland farming for centuries. A fractional vegetation cover (FVC) map for grassland and detailed land-cover maps are available from linear spectral unmixing and supervised classification of QuickBird imagery. The maps were introduced to the Pan-European Soil Erosion Risk Assessment (PESERA) model as well as to the Universal Soil Loss Equation (USLE). Regarding the latter model, the FVC was indirectly incorporated by adapting the C factor. Both models show an increase in absolute soil erosion values when FVC is considered. In contrast to USLE and the Cs-137 soil erosion rates, PESERA estimates are low. For the USLE model also the spatial patterns improved and showed “hotspots” of high erosion of up to 16tha−1a−1. In conclusion field measurements of Cs-137 confirmed the improvement of soil erosion estimates using the satellite-derived vegetation data.

Conditional simulation of USLE/RUSLE soil erodibility factor by geostatistics in a Mediterranean Catchment, Turkey

Soil erosion is a major environmental problem that threatens the sustainability and productivity of agricultural areas. Assessment and mapping of soil erosion are extremely important in the management and conservation of natural resources. The universal soil loss equation (USLE/RUSLE) is an erosion model that predicts soil loss as a function of soil erodibility (K-factor), as well as topographic, rainfall, cover, and management factors. The traditional approach assumes that one soil erodibility value represents the entire area of each soil series. Therefore, that approach does not account for spatial variability of soil series. This study was carried out to evaluate the use of the sequential Gaussian simulation (SGS) for mapping soil erodibility factor of the USLE/RUSLE methodology. Five hundred and forty-four surface soil samples (0–20 cm) were collected from the study area to determine the soil erodibility. A simulation procedure was carried out on 300 realizations, and histogram and semivariogram of the simulation were compared to the observed values. The results showed that the summary statistics, histogram, and semivariogram of the simulation results were close to the observed values. In contrary to the traditional approach and kriging, 95% confidence interval of the simulated realizations was formed in order to determine uncertainty standard deviation map, and the uncertainty was explained numerically. The SGS produced a more reliable soil erodibility map and it can be more successfully used for monitoring and improving effective strategies to prevent erosion hazards especially to improve site specific management plans.

Nomographic estimation and evaluation of soil erodibility under simulated and natural rainfall conditions

AbstractTo evaluate soil erodibility under different land uses and to study the applicability of nomograph for estimation of soil erodibility a field experiment was conducted under both natural and simulated rainfall conditions under four land uses viz. barren, cultivated, grassland, and forest in the sub‐mountainous tract of Punjab (India). Measured soil erodibility (K) values varied from 0·33 to 0·67 under natural rainfall conditions and from 0·23 to 0·40 under simulated rainfall conditions. Among different land uses, measured K was in the order of barren > cultivated > grassland > forest soils. The values of the K estimated by nomograph were very low as compared to the observed values. The trends were also in contrast to these observed values of K under simulated and natural rainfall conditions. To modify nomograph equation, different ranges of aggregate sizes were correlated with soil loss. It was observed that water stable aggregates (WSA) <2 mm size had a significant correlation with soil loss under both natural (r = 0·88) and simulated (r = 0·76) rainfall conditions. So the nomograph equation was modified to include the M parameter based on WSA <2 mm size. The value of K estimated from the modified nomograph had a significant correlation with measured values of K under both the natural and simulated rainfall conditions. Copyright © 2009 John Wiley & Sons, Ltd.

Predicting Soil Erosion With RUSLE in Mediterranean Agricultural Systems at Catchment Scale

Accurate assessment of soil loss is essential for sustainable agricultural production, management, and conservation planning, especially in productive rain-fed agroecosystems and protected areas. The European Union considers soil as a nonrenewable resource and identifies that soil degradation has strong impacts on soil and water resources. In this work, the Revised Universal Soil Loss Equation model was applied within a geographic information system in the Estaña catchment (Spanish pre-Pyrenees) as representative of a Mediterranean agroecosystem to elaborate a map of soil erosion at high spatial resolution (5 × 5-m cell size). The soil erodibility factor (K) was calculated from three different approaches to evaluate the importance of spatial variations in soil texture, field infiltration measurements (Kfs), and amount of coarse fragments. The average value of estimated soil loss for the whole study area was 2.3 Mg ha−1 year−1, and the highest rates were estimated in crops in steep areas (5.8 Mg ha−1 year−1) and trails (18.7 Mg ha−1 year−1). Cultivated soils with high soil erosion rates (>8 Mg ha−1 year−1) represented 20% of the cultivated area. The average value of soil loss in areas with human disturbances (4.21 Mg ha−1 year−1) was 4.4-fold that estimated for areas with natural vegetation (0.96 Mg ha−1 year−1). Field validation with 137Cs showed that the estimated value of soil loss in barley fields with the K-Kfs-rocks factor improves the model predictions in comparison with those obtained with the K texture and K-Kfs factors. The Revised Universal Soil Loss Equation model predicted a decrease in soil erosion in fields in accordance with the increase of the age of abandonment. Predicted values of soil erosion and measured soil organic matter and stoniness in old abandoned fields agreed with those in areas of natural forest and indicated the recovery of the original conditions of the soil. Statistical analysis highlights that the C factor contributed most of the variability of the values of predicted soil erosion; the K and LS factors contributed in a similar way. The P factor contributed least to the variability of soil erosion. Cultivated soils developed over clay materials in high slope areas are the most susceptible to soil degradation processes in comparison with soils developed over limestones in gentle and medium slope areas. The recovery of terraces in steep fields and conservation of crop residues are proposed as soil conservation practices to reduce the magnitude of soil loss in the study area.

Physical Indicators of Soil Quality in Relation to Soil Erodibility Under Different Land Uses

Physical indicators of soil quality in relation to soil erodibility were evaluated in the submontaneous tract of Punjab (India). A field experiment was conducted with both natural and simulated rainfall conditions under four land uses—barren, cultivated, grassland, and forest. Sustainability index approach (Gomez, Kelly, Syers, and Coughlan, 1996) and cumulative rating approach (Shukla, Lal, and Ebinger, 2004) were used to measure the sustainability in terms of soil erodibility. According to the sustainability index approach at the Ballowal Saunkhri-I, Ballowal Saunkhri-II, and Saleran locations, only the forest land use system is sustainable. At the fourth location—Kokowal Majari—all four land uses were observed to be sustainable with respect to soil erodibility or soil physical quality. The mean sustainability indices were observed to be highly correlated with the respective soil erodibility values under natural (r = −0.83) and simulated (r = −0.87) rainfall conditions. The cumulative rating approach had a significant positive correlation with soil erodibility both under natural (r = 0.75) and simulated (r = 0.81) rainfall conditions. There was a strong correlation between the sustainability index and cumulative rating (r = −0.93). In conclusion, the sustainability index approach was found to be more suitable for assessing the sustainability of the system in terms of soil erodibility as it required less soil data input and had a higher correlation with soil erodibility. However, the sustainability index provided two categories of sustainability compared to the cumulative rating which produces five categories.

Routing runoff and soil particles in a distributed model with GIS: implications for soil protection in mountain agricultural landscapes

AbstractSoil erosion by water is a serious threat to crop sustainability and one of the main causes of landscape degradation in Mediterranean environments. The accurate assessment of soil erosion is a first requirement to face the problem of soil loss in highly fragile mountain environments. In this work, single flow (D8), multiple flow (MD) and combined flow (MDD) algorithms are used to compute cumulative runoff. Effective runoff is estimated after accounting infiltration and soil surface properties and added to the revised Morgan, Morgan and Finney (RMMF) model of soil erosion at the ‘Laguna Grande de Estaña’ catchment (Spanish pre‐Pyrenees). The combined flow algorithm explicitly associated to the gullies (MDD8‐G) leads to a more realistic assessment of runoff pathways. The MD algorithm generates unrealistic maps of concentrated runoff in gullies and overestimates soil erosion rates (average rate of 75 Mg ha−1 y−1). The D8 and MDD8‐G algorithms estimate similar values of soil erosion (average rates of 37 and 44 Mg ha−1 y−1, respectively). Paths, crops on steep slopes, open Mediterranean forest and sparse scrublands have the highest values of soil erosion (more than 50 Mg ha−1 y−1). The estimated rates with the MDD8‐G algorithm in control points in crops, forest and scrublands fit better with available data from 137Cs than those obtained with the D8 algorithm. Therefore, the MDD8‐G algorithm improves the quality predictions of soil erosion and is of interest to study processes of overland flow in Mediterranean environments with presence of gullies. Copyright © 2009 John Wiley & Sons, Ltd.