Effect of land use land cover change on soil erosion potential in an agricultural watershed

Universal soil loss equation (USLE) was used in conjunction with a geographic information system to determine the influence of land use and land cover change (LUCC) on soil erosion potential of a reservoir catchment during the period 1989 to 2004. Results showed that the mean soil erosion potential of the watershed was increased slightly from 12.11 t ha^???1 year^???1 in the year 1989 to 13.21 t ha^???1 year^???1 in the year 2004. Spatial analysis revealed that the disappearance of forest patches from relatively flat areas, increased in wasteland in steep slope, and intensification of cultivation practice in relatively more erosion-prone soil were the main factors contributing toward the increased soil erosion potential of the watershed during the study period. Results indicated that transition of other land use land cover (LUC) categories to cropland was the most detrimental to watershed in terms of soil loss while forest acted as the most effective barrier to soil loss. A p value of 0.5503 obtained for two-tailed paired t test between the mean erosion potential of microwatersheds in 1989 and 2004 also indicated towards a moderate change in soil erosion potential of the watershed over the studied period. This study revealed that the spatial location of LUC parcels with respect to terrain and associated soil properties should be an important consideration in soil erosion assessment process.     

Effects of land conversion from native shrub to pistachio orchard on soil erodibility in an arid region

Land-use change through degrading natural vegetation for agricultural production adversely affects many of soil properties particularly organic carbon content of soils. The native shrub land and grassland of Gaziantep-Adiyaman plateau that is an important pistachio growing eco-region have been cleared to convert into pistachio orchard for the last 50 to 60 years. In this study, the effects of conversion of natural vegetation into agricultural uses on soil erodibility have been investigated. Soil samples were collected from surface of agricultural fields and adjacent natural vegetation areas, and samples were analyzed for some soil erodibility indices such as dispersion ratio (DR), erosion ratio (ER), structural stability index (SSI), Henin’s instability index (I _s ), and aggregate size distribution after wet sieving (AggSD). According to the statistical evaluation, these two areas were found as different from each other in terms of erosion indices except for I _s index (P < 0.001 for DR and ER or P < 0.01 for SSI). In addition, native shrub land and converted land to agriculture were found different in terms of AggSD in all aggregate size groups. As a contrary to expectations, correlation tests showed that there were no any interaction between soil organic carbon and measured erodibility indices in two areas. In addition, significant relationships were determined between measured variables and soil textural fractions as statistical. These obtaining findings were attributed to changing of textural component distribution and initial aggregate size distribution results from land-use change in the study area. Study results were explained about hierarchical aggregate formation mechanism.     

Assessing the effects of land use changes on soil sensitivity to erosion in a highland ecosystem of semi-arid Turkey

There has been increasing concern in highlands of semiarid Turkey that conversion of these systems results in excessive soil erosion, ecosystem degradation, and loss of sustainable resources. An increasing rate of land use/cover changes especially in semiarid mountainous areas has resulted in important effects on physical and ecological processes, causing many regions to undergo accelerated environmental degradation in terms of soil erosion, mass movement and reservoir sedimentation. This paper, therefore, explores the impact of land use changes on land degradation in a linkage to the soil erodibility, RUSLE-K, in Cankiri–Indagi Mountain Pass, Turkey. The characterization of soil erodibility in this ecosystem is important from the standpoint of conserving fragile ecosystems and planning management practices. Five adjacent land uses (cropland, grassland, woodland, plantation, and recreational land) were selected for this research. Analysis of variance showed that soil properties and RUSLE-K statistically changed with land use changes and soils of the recreational land and cropland were more sensitive to water erosion than those of the woodland, grassland, and plantation. This was mainly due to the significant decreases in soil organic matter (SOM) and hydraulic conductivity (HC) in those lands. Additionally, soil samples randomly collected from the depths of 0–10 cm (D ₁) and 10–20 cm (D ₂) with irregular intervals in an area of 1,200 by 4,200 m sufficiently characterized not only the spatial distribution of soil organic matter (SOM), hydraulic conductivity (HC), clay (C), silt (Si), sand (S) and silt plus very fine sand (Si + VFS) but also the spatial distribution of RUSLE-K as an algebraically estimate of these parameters together with field assessment of soil structure to assess the dynamic relationships between soil properties and land use types. In this study, in order to perform the spatial analyses, the mean sampling intervals were 43, 50, 64, 78, 85 m for woodland, plantation, grassland, recreation, and cropland with the sample numbers of 56, 79, 72, 13, and 69, respectively, resulting in an average interval of 64 m for whole study area. Although nugget effect and nugget effect–sill ratio gave an idea about the sampling design adequacy, the better results are undoubtedly likely by both equi-probable spatial sampling and random sampling representative of all land uses.     

Soil erosion and sediment fluxes analysis: a watershed study of the Ni Reservoir,Spotsylvania County,VA, USA

Anthropogenic forces that alter the physical landscape are known to cause significant soil erosion, which has negative impact on surface water bodies, such as rivers, lakes/reservoirs, and coastal zones, and thus sediment control has become one of the central aspects of catchment management planning. The revised universal soil loss equation empirical model, erosion pins, and isotopic sediment core analyses were used to evaluate watershed erosion, stream bank erosion, and reservoir sediment accumulation rates for Ni Reservoir, in central Virginia. Land-use and land cover seems to be dominant control in watershed soil erosion, with barren land and human-disturbed areas contributing the most sediment, and forest and herbaceous areas contributing the least. Results show a 7 % increase in human development from 2001 (14 %) to 2009 (21.6 %), corresponding to an increase in soil loss of 0.82 Mg ha^-1 year^-1 in the same time period. ²¹⁰Pb-based sediment accumulation rates at three locations in Ni Reservoir were 1.020, 0.364, and 0.543 g cm^-2 year^-1 respectively, indicating that sediment accumulation and distribution in the reservoir is influenced by reservoir configuration and significant contributions from bedload. All three locations indicate an increase in modern sediment accumulation rates. Erosion pin results show variability in stream bank erosion with values ranging from 4.7 to 11.3 cm year^-1. These results indicate that urban growth and the decline in vegetative cover has increased sediment fluxes from the watershed and poses a significant threat to the long-term sustainability of the Ni Reservoir as urbanization continues to increase.     

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.     

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.     

Desertification Evaluated Using an Integrated Environmental Assessment Model

Desertification has been defined as land degradation in arid, semi-arid and dry sub-humid areas resulting from various factors, including climatic variations and human activities (United Nations, 1992). A technique for identifying and assessing areas at risk fordesertification in the arid, semi-arid, and subhumid regionsof the United States was developed by the Desert Research Institute and the U.S. Environmental Protection Agency (EPA), using selected environmental indicators integrated into a Geographic Information System (GIS). Five indicators were selected: potential erosion, grazing pressure, climatic stress (expressed as a function of changesin the Palmer Drought Severity Index [PDSI]), change invegetation greenness (derived from the Normalized DifferenceVegetation Index [NDVI]), and weedy invasives as a percentof total plant cover. The data were integrated over aregional geographic setting using a GIS, which facilitateddata display, development and exploration of data relationships, including manipulation and simulation testing. By combining all five data layers, landscapes having a varying risk for land degradation were identified, providing a tool which could be used to improve landmanagement efficiency.     

Use of USLE/GIS Methodology for Predicting Soil Loss in a Semiarid Agricultural Watershed

The Universal Soil Loss Equation (USLE) is an erosion model to estimate average soil loss that would generally result from splash, sheet, and rill erosion from agricultural plots. Recently, use of USLE has been extended as a useful tool predicting soil losses and planning control practices in agricultural watersheds by the effective integration of the GIS-based procedures to estimate the factor values in a grid cell basis. This study was performed in the Kazan Watershed located in the central Anatolia, Turkey, to predict soil erosion risk by the USLE/GIS methodology for planning conservation measures in the site. Rain erosivity (R), soil erodibility (K), and cover management factor (C) values of the model were calculated from erosivity map, soil map, and land use map of Turkey, respectively. R values were site-specifically corrected using DEM and climatic data. The topographical and hydrological effects on the soil loss were characterized by LS factor evaluated by the flow accumulation tool using DEM and watershed delineation techniques. From resulting soil loss map of the watershed, the magnitude of the soil erosion was estimated in terms of the different soil units and land uses and the most erosion-prone areas where irreversible soil losses occurred were reasonably located in the Kazan watershed. This could be very useful for deciding restoration practices to control the soil erosion of the sites to be severely influenced.     

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.     

Field assessment of flood event suspended sediment transport from ephemeral streams in the tropical semi-arid catchments

An assessment of suspended sediment transport was carried out in a number of semiarid catchments during flood events in order to quantify the degradation rates. In order to quantify these, a systematic sampling procedure of the episodic flood events was proposed for representative catchments. The procedure allows for an integration over the whole run-off episode using both the rising and falling limbs of the run-off hydrograph to compute the sediment quantities for each individual flood event. Higher sediment concentrations occurred in the rising limb than those at the recession for any stage of flow. The maximum suspended sediment concentration was observed at the peak of the flood hydrograph. An integration of the sediment concentration over its duration gave the total sediment yield from the flood event. For the ephemeral channels, only a small number of flood events were observed over a three-year experimental period each with a duration of the order of 3–6 h. It is notable that high sediment loads were associated with high flow volumes which were effectively the result of the catchment characteristics and incident rainfall causing the flood events in the respective catchments. A large percentage of the annual sediment yield from a catchment is transported by the ephemeral streams during a small number of flood events. The correct determination of the total sediment yield from any of the flood events depends entirely on the accuracy of the measurements. The understanding of run-off and sediment loss for the representative catchments aims at assisting planning, management and control of water and land resources for sustainable development in the semi-arid parts of the tropics. The sediment rates reveal the degradation of catchments which have repercussions on the crop and pasture production and this has a bearing on the soil and water conservation programmes in the delicate ecological balance of the semi-arid areas. Further, these rates will determine the lifespan of the reservoirs planned for the dry river valleys (ephemeral streams) and existing ones which serve livestock and domestic needs. These occasionally will require costly rehabilitation and scooping to increase effective storage unless conservation measures are taken, and these measures are bound to vary from place to place as per the representative catchments output.     

基于 GIS和USLE/RUSLE的小流域土壤侵蚀量研究

依据实地调查资料,建立了典型小流域地理数据库;应用采样分析数据结果及坡面单元法,确定了定量计算通用土壤流失方程RUSLE因子指标的方法.在地理信息系统ArcGIS支持下,根据USLE/RUSLE土壤侵蚀预测模型对数据库实施运算操作,预测了小流域土壤侵蚀量.结果表明:①流域总体土壤侵蚀为中度,治理难度仍很大;②坡耕地是流...     

An evaluation of grid size uncertainty in empirical soil loss modeling with digital elevation models

This paper presents a study on the effect of topographic variability on grid-based empirical estimation of soil erosion and sediment transport with raster geographic information systems (GIS). An original digital elevation model (DEM) of 10 m resolution for a case watershed is resampled to six realizations of greater grid sizes for a comparative examination. The Universal Soil Loss Equation (USLE) and a distance-based sediment delivery equation are applied to the watershed to calculate soil loss from each cell and total sediment transport to streams, respectively. The results suggest that the selection of the DEM gird size has considerable influence on the soil loss estimation with the empirical models. The estimate of total soil loss from the watershed decreases significantly with the increasing DEM cell size as the spatial variability is reduced by the cell aggregation. The empirical modeling approach is a useful tool for qualitative assessment of soil erosion, provided that spatial variability can be adequately represented by applied DEMs. However, discretion is suggested for its applications to quantitative estimation of soil loss concerning the sensitivity to the grid size selection.     

Spatial and temporal estimation of soil loss for the sustainable management of a wet semi-arid watershed cluster

The ungauged wet semi-arid watershed cluster, Seethagondi, lies in the Adilabad district of Telangana in India and is prone to severe erosion and water scarcity. The runoff and soil loss data at watershed, catchment, and field level are necessary for planning soil and water conservation interventions. In this study, an attempt was made to develop a spatial soil loss estimation model for Seethagondi cluster using RUSLE coupled with ARCGIS and was used to estimate the soil loss spatially and temporally. The daily rainfall data of Aphrodite for the period from 1951 to 2007 was used, and the annual rainfall varied from 508 to 1351 mm with a mean annual rainfall of 950 mm and a mean erosivity of 6789 MJ mm ha^?1 h^?1 year^?1. Considerable variation in land use land cover especially in crop land and fallow land was observed during normal and drought years, and corresponding variation in the erosivity, C factor, and soil loss was also noted. The mean value of C factor derived from NDVI for crop land was 0.42 and 0.22 in normal year and drought years, respectively. The topography is undulating and major portion of the cluster has slope less than 10°, and 85.3 % of the cluster has soil loss below 20 t ha^?1 year^?1. The soil loss from crop land varied from 2.9 to 3.6 t ha^?1 year^?1 in low rainfall years to 31.8 to 34.7 t ha^?1 year^?1 in high rainfall years with a mean annual soil loss of 12.2 t ha^?1 year^?1. The soil loss from crop land was higher in the month of August with an annual soil loss of 13.1 and 2.9 t ha^?1 year^?1 in normal and drought year, respectively. Based on the soil loss in a normal year, the interventions recommended for 85.3 % of area of the watershed includes agronomic measures such as contour cultivation, graded bunds, strip cropping, mixed cropping, crop rotations, mulching, summer plowing, vegetative bunds, agri-horticultural system, and management practices such as broad bed furrow, raised sunken beds, and harvesting available water using farm ponds and percolation tanks. This methodology can be adopted for estimating the soil loss from similar ungauged watersheds with deficient data and for planning suitable soil and water conservation interventions for the sustainable management of the watersheds.     

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.     

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.     

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.     

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.     

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.     

Retrospective assessment of dryland soil stability in relation to grazing and climate change

Accelerated soil erosion is an aspect of dryland degradation that is affected by repeated intense drought events and land management activities such as commercial livestock grazing. A soil stability index (SSI) that detects the erosion status and susceptibility of a landscape at the pixel level, i.e., stable, erosional, or depositional pixels, was derived from the spectral properties of an archived time series (from 1972 to 1997) of Landsat satellite data of a commercial ranch in northeastern Utah. The SSI was retrospectively validated with contemporary field measures of soil organic matter and erosion status that was surveyed by US federal land management agencies. Catastrophe theory provided the conceptual framework for retrospective assessment of the impact of commercial grazing and soil water availability on the SSI. The overall SSI trend was from an eroding landscape in the early drier 1970s towards stable conditions in the wetter mid-1980s and late 1990s. The landscape catastrophically shifted towards an extreme eroding state that was coincident with the “The Great North American Drought of 1988”. Periods of landscape stability and trajectories toward stability were coincident with extremely wet El Niño events. Commercial grazing had less correlation with soil stability than drought conditions. However, the landscape became more susceptible to erosion events under multiple droughts and grazing. Land managers now have nearly a year warning of El Niño and La Niña events and can adjust their management decisions according to predicted landscape erosion conditions.     

Spatial 3D distribution of soil organic carbon under different land use types

Soil organic carbon (SOC) has been assessed in three dimension (3D) in several studies, but little is known about the combined effects of land use and soil depth on SOC stocks in semi-arid areas. This paper investigates the 3D distribution of SOC to a depth of 1 m in a 4600-ha area in southeastern Iran with different land uses under the irrigated farming (IF), dry farming (DF), orchards (Or), range plants on the Gachsaran formation (RaG), and range plants on a quaternary formation (RaQ). Predictions were made using the artificial neural networks (ANNs), regression trees (RTs), and spline functions with auxiliary covariates derived from a digital elevation model (DEM), the Landsat 8 imagery, and land use types. Correlation analysis showed that the main predictors for SOC in the topsoil were covariates derived from the imagery; however, for the lower depths, covariates derived from both the DEM and imagery were important. ANNs showed more efficiency than did RTs in predicting SOC. The results showed that 3D distribution of SOC was significantly affected by land use types. SOC stocks of soils under Or and IF were significantly higher than those under DF, RaG, and RaQ. The SOC below 30 cm accounted for about 59% of the total soil stock. Results showed that depth functions combined with digital soil mapping techniques provide a promising approach to evaluate 3D SOC distribution under different land uses in semi-arid regions and could be used to assess changes in time to determine appropriate management strategies.