Assessment of the potential of semi-arid plants to reduce soil erosion in the Konartakhteh watershed,Iran

Soil erosion is a major environmental problem in arid and semi-arid areas. Although bioengineering is important in preventing soil erosion, plant architecture and mechanical properties in these areas are rarely studied. In this study, in order to evaluate the potential of native plants to reduce soil erosion in semi-arid regions, their above-ground (e.g., stem density, radius of the stem, etc.) and below-ground (e.g., root area ratio, root tensile strength, etc.) characteristics were measured in the field and laboratory. Five indicators, namely, stem density (SD), sediment obstruction potential (SOP), plant stiffness (MEI), relative soil detachment (RSD), and root cohesion (Cr), were taken into account. Each indicator was scored according to a five-point scale (0?=?low, 4?=?high), and then, the score of each indicator was represented on an ameba diagram. Finally, for understanding traits of plants and evaluating their potential to control rill and gully erosion, the area occupied by the ameba diagram was studied. The results indicated that the shrub Ziziphus spina-christi (MEI?=?108.35 N, RSD?=?0.398, Cr?=?8.34 kPa, SOP?=?0.097, and SD?=?0.00270) is a very suitable native plant species for controlling both the gully and rill erosion. In addition, Scariola orientalis is effective for sediment obstruction, but its low scores on the MEI and RSD indicators imply that it is not able to control gully development. Furthermore, Noaea mucronata, Platychaete glaucescens, Astragalus gummifer, Alhagi persarum, Lycium shawii, and Prosopis farcta have a distinct potential to reduce the rate of gully erosion. These results have wide applicability for adopting soil conservation measures to other semi-arid environments.     

An assessment of soil erosion probability and erosion rate in a tropical mountainous watershed using remote sensing and GIS

Remote sensing data and Geographical Information System (GIS) has been integrated with the weighted index overlay (WIO) method and E ₃₀ model for the identification and delineation of soil erosion susceptibility zones and the assessment of rate of soil erosion in the mountainous sub-watershed of River Manimala in Kerala (India). Soil erosion is identified as the one of the most serious environmental problems in the human altered mountainous environment. The reliability of estimated soil erosion susceptibility and soil loss is based on how accurately the different factors were estimated or prepared. In the present analysis, factors that are considered to be influence the soil erosion are: land use/land cover, NDVI, landform, drainage density, drainage frequency, lineament frequency, slope, and relative relief. By the WIO analysis, the area is divided into zones representing low (33.30%), moderate (33.70%), and high (33%) erosion proneness. The annual soil erosion rate of the area under investigation was calculated by carefully determining its various parameters and erosion for each of the pixels were estimated individually. The spatial pattern thus created for the area indicates that the average annual rate of soil erosion in the area was ranging from 0.04 mm yr⁻¹ to 61.80 mm yr⁻¹. The high soil erosion probability and maximum erosion rate was observed in areas with high terrain alteration, high relief and slopes with the intensity and duration of heavy precipitation during the monsoons.     

Evaluation of sediment yield and soil loss by the MPSIAC model using GIS at Golestan watershed, northeast of Iran

Watershed degradation due to soil erosion and sedimentation is considered to be one of the major environmental problems in Iran. In order to address the critical conditions of watershed degradation in arid and semiarid regions, a study based on the Modified Pacific Southwest Inter-Agency Committee (MPSIAC) model was carried out at Golestan watershed, northeast of Iran. The model information layers comprising nine effective factors in erosion and sedimentation at the watershed site were obtained by digitalization and spatial interpolation of the basic information data in a GIS program. These factors are geology, soil, climate, runoff, topography, land cover, land use, channel, and upland erosion. The source data for the model were obtained from available records on rainfall and river discharge and sediment, topography, land use, geology, and soil maps as well as field surveys and laboratory analysis. The results of the MPSIAC model indicated that 60.75 % (194.4 km²) and 54.97 % (175.9 km²) of the total watershed area were classified in the heavy sedimentation and erosion classes, and the total basin sediment yield and erosion were calculated as 4,171.1 and 17,813.4 m³ km^?2 year^?1, respectively. In the sensitivity analysis, it was found that the most sensitive parameters of the model in order of importance were topography (slope), land cover and use, runoff, and channel erosion (R ²?=?0.92–0.94), while geology, climate (rainfall), soil, and upland erosion factors were found to have moderate effect to the model output (R ²?=?0.74–0.59).     

Estimation of soil erosion using RUSLE in Caijiamiao watershed,China

Soil erosion is a serious environmental and production problem in China. In particular, natural conditions and human impact have made the Chinese Loess Plateau particularly prone to intense soil erosion area. To decrease the risk on environmental impacts, there is an increasing demand for sound, and readily applicable techniques for soil conservation planning in this area. This work aims at the assessment of soil erosion and its spatial distribution in hilly Loess Plateau watershed (northwestern China) with a surface area of approximately 416.31 km². This study was conducted at the Caijiamiao watershed to determine the erosion hazard in the area and target locations for appropriate initiation of conservation measures using the revised universal soil loss equation (RUSLE). The erosion factors of RUSLE were collected and processed through a geographic information system (GIS)-based approach. The soil erosion parameters were evaluated in different ways: The R-factor map was developed from the rainfall data, the K-factor map was obtained from the soil map, the C-factor map was generated based on Landsat-5 Thematic Mapper image and spectral mixture analysis, and a digital elevation model with a spatial resolution of 25 m was derived from topographic map at the scale of 1:50,000 to develop the LS-factor map. Support practice P factor was from terraces that exist on slopes where crops are grown. By integrating the six-factor maps in GIS through pixel-based computing, the spatial distribution of soil loss in the study area was obtained by the RUSLE model. The results showed that spatial average soil erosion at the watershed was 78.78 ton ha^?1 year^?1 in 2002 and 70.58 ton ha^?1 year^?1 in 2010, while the estimated sediment yield was found to be 327.96 × 10⁴ and 293.85 × 10⁴ ton, respectively. Soil erosion is serious, respectively, from 15 to 35 of slope degree, elevation area from 1,126 to 1,395 m, in the particular area of soil and water loss prevention. As far as land use is concerned, soil losses are highest in barren land and those in waste grassland areas are second. The results of the study provide useful information for decision maker and planners to take appropriate land management measures in the area. It thus indicates the RUSLE–GIS model is a useful tool for evaluating and mapping soil erosion quantitatively and spatially at a river watershed scale on a cell basis in Chinese Loess Plateau and for planning of conservation practices.     

Catchment-scale soil erosion and sediment yield simulation using a spatially distributed erosion model

Increasing rainfall intensity and frequency due to extreme climate change and haphazard land development are aggravating soil erosion problems in Korea. A quantitative estimate of the amount of sediment from the catchment is essential for soil and water conservation planning and management. Essential to catchment-scale soil erosion modeling is the ability to represent the fluvial transport system associated with the processes of detachment, transport, and deposition of soil particles due to rainfall and surface flow. This study applied a spatially distributed hydrologic model of rainfall–runoff–sediment yield simulation for flood events due to typhoons and then assessed the impact of topographic and climatic factors on erosion and deposition at a catchment scale. Measured versus predicted values of runoff and sediment discharge were acceptable in terms of applied model performance measures despite underestimation of simulated sediment loads near peak concentrations. Erosion occurred widely throughout the catchment, whereas deposition appeared near the channel network grid cells with a short hillslope flow path distance and gentle slope; the critical values of both topographic factors, providing only deposition, were observed at 3.5 (km) (hillslope flow path distance) and 0.2 (m/m) (local slope), respectively. In addition, spatially heterogeneous rainfall intensity, dependent on Thiessen polygons, led to spatially distinct net-erosion patterns; erosion increased gradually as rainfall amount increased, whereas deposition responded irregularly to variations in rainfall.     

Assessment of soil erosion in a small watershed covered by loess

Loose sediments like loess are easily erodable especially on hillslopes used for agriculture. Erosion contributes to the sedimentation and pollution of lakes such threatening quasi-natural ecosystems. On the other hand soil erosion damages fertile soils.The aim of the present paper is the assessment of soil and nutrient loss in a tributary catchment of Lake Balaton, including geoecological aspects of the lake ecosystem and of the slopes mantled by loess.The USLE is applied for small topological units, for the so called erotops. Rainfall simulation experiments were applied for the determination of the erodibility of soils. The calculation is based on a new, GIS aided method. Control measurements have been going on for four years at a gauging station to check how much sediment and water actually leaves the catchment.Results of sediment yield measurements were compared with the results obtained by the application of USLE for the whole catchment. According to this comparison only 2% leaves the catchment so that redeposition processes within the catchment are very important whereas the contribution of soil erosion to the eutrophication of the lake is not very significant in the small tributaries in the northern part of Lake Balaton catchment.     

Inverse modeling of variable-density groundwater flow in a semi-arid area in Iran using a genetic algorithm

Flow and mass transport parameter estimation was done by creating an inverse model of a seawater intrusion system using a genetic algorithm (GA) method as the optimization procedure. Firstly, the SEAWAT code was used for the forward solution part and then a program was written in MATLAB for coupling the forward and inverse processes. The auto-calibration objective function was defined with the root mean square errors (RMSE) between the observed and the simulated values. A simple GA was used to minimize the RMSE criterion. The methodology was applied to a coastal aquifer with heterogeneous formations in a semi-arid area near salty Tashk Lake (electrical conductivity 61,420 µS/cm), Fars province, Iran. In the last two decades, the overexploitation of groundwater has caused a major water level drawdown and, consequently, salt-water intrusion. Firstly, flow and transport parameters (hydraulic conductivity, porosity, specific storage coefficient and longitudinal dispersivity) were estimated simultaneously in steady-state and, secondly, in the developed code, these results were used as initial values of the parameters in transient-state. Results show a good match for observed and simulated data. It can be concluded that GA is a helpful tool for automatic calibration of variable density fluid systems such as seawater intrusion cases.     

Soil erosion and sediment yield modeling using RS and GIS techniques: a case study, Iran

Water erosion is a serious and continuous environmental problem in many parts of the world. The need to quantify the amount of erosion, sediment delivery, and sediment yield in a spatially distributed form has become essential at the watershed scale and in the implementation of conservation efforts. In this study, an effort to predict potential annual soil loss and sediment yield is conducted by using the Revised Universal Soil Loss Equation (RUSLE) model with adaptation in a geographic information system (GIS). The rainfall erosivity, soil erosivity, slope length, steepness, plant cover, and management practice and conservation support practice factors are among the basic factors that are obtained from monthly and annual rainfall data, soil map of the region, 50-m digital elevation model, remote sensing (RS) techniques (with use of Normalized Difference Vegetation Index), and GIS, respectively. The Ilam dam watershed which is located southeast part of Ilam province in western Iran is considered as study area. The study indicates that the slope length and steepness of the RUSLE model are the most effective factors controlling soil erosion in the region. The mean annual soil loss and sediment yield are also predicted. Moreover, the results indicated that 45.25%, 12.18%, 12.44%, 10.79%, and 19.34% of the study area are under minimal, low, moderate, high, and extreme actual erosion risks, respectively. Since 30.13% of the region is under high and extreme erosion risk, adoption of suitable conservation measures seems to be inevitable. So, the RUSLE model integrated with RS and GIS techniques has a great potential for producing accurate and inexpensive erosion and sediment yield risk maps in Iran.     

Modeling soil erosion using RUSLE and GIS in a watershed occupied by rural settlement in the Brazilian Cerrado

The installation of a rural settlement complex in the watershed stream Indaiá has promoted changes in land-use and vegetation cover dynamics; however, the effects of intensive agriculture and cattle farming in rural settlements on soil loss rates are not well known. Predictive models implemented in geographic information systems have proven to be effective tools for estimating erosive processes. The erosion predictive model Revised Universal Soil Loss Equation (RUSLE) is a useful tool for analyzing, establishing and managing soil erosion. RUSLE has been widely used to estimate annual averages of soil loss, by both interrill and rill erosion, worldwide. Therefore, the aim of this work was to estimate the soil loss in the watershed stream Indaiá, using the RUSLE model and geoprocessing techniques. To estimate soil loss, the following factors were spatialized: erosivity (R), erodibility (K), topography (LS), land-use and management (C) and conservation practices (P); the annual soil loss values were calculated using the RUSLE model equation. The estimated value of soil loss in the hydrographic basin ranged from 0 to 4082.16 Mg ha^?1 year^?1 and had an average value of 47.81 Mg ha^?1 year^?1. These results have demonstrated that 68.16 % of the study area showed little or no soil loss based on the Food and Agriculture Organization’s (FAO 1980) classification. When comparing the average value of soil loss obtained using the RUSLE model with the Natural Potential for Erosion, a 16-fold reduction in soil was found, which highlighted the fact that vegetation cover (C factor) has a greater influence than other factors (R, K and LS) on soil loss prediction attenuation. These results lead to the conclusion that soil loss occurs by different methods in each settlement in the basin and that erosive processes modeled by geoprocessing have the potential to contribute to an orderly land management process.     

Estimation of soil erosion rates in a subtropical mountain watershed using 137Cs radionuclide

The formulation of watershed management strategies to protect water resources threatened by soil erosion and sedimentation requires a thorough understanding of sediment sources and factors that drive soil movement in the watershed. This paper describes a study of medium-term water-driven soil erosion rates in a mountainous watershed of the Shihmen Reservoir in Taiwan. A total of 60 sampling sites were selected along a hillslope. At each sampling site, the inventory ¹³⁷Cs activity was determined and then calculated with the diffusion and migration model to derive soil erosion rates. The rates are one to two orders of magnitude lower than estimates using the Universal Soil Loss Equation, a soil erosion model often used in Taiwan. Results of multiple regression analysis indicate that the spatial variability of soil erosion rates is associated with the relative position of a sampling site to the nearest ridge and soil bulk densities (r ² = 0.33, p < 0.01). Finally, the patterns of soil redistribution rates on the hillslope follow the ¹³⁷Cs hillslope model as soil erosion increases in the downslope direction. No deposition site is found at footslope because soil deposition is swept away by regular flooding along the stream channel. This study is an important first step in using ¹³⁷Cs as a tracer of soil redistribution in mountainous watersheds of Taiwan.     

Evaluating soil erosion by water in a small alpine catchment in Northern Italy: comparison of empirical models

Acta Geochimica - To quantify water erosion rates and annual soil loss in mountainous areas, two different empirical models were used to estimate the effects of soil erosion in a small mountain...     

An integrated assessment of soil erosion dynamics with special emphasis on gully erosion in the Mazayjan basin,southwestern Iran

Soil erosion by water is a significant problem in arid and semi-arid areas of large parts of Iran. Water erosion is one of the most effective phenomena that leads to decreasing soil productivity and pollution of water resources; especially, in the Mazayjan watershed in the southwest of Fars Province gully erosion contributes to the sediment dynamics in a significant way. Consequently, the intention of this research is to identify the different types of soil erosion processes acting in the area and to assess the process dynamics in an integrative way. Therefore, we applied GIS and satellite image analysis techniques to derive input information for the numeric models. For sheet and rill erosion the Unit Stream Power-based Erosion Deposition Model (USPED) was utilized. The spatial distribution of gully erosion was assessed using a statistical approach, which used three variables (stream power index, slope, and flow accumulation) to predict the spatial distribution of gullies in the study area. The eroded gully volumes were estimated for a 7-year period by fieldwork and Google Earth high-resolution images. Finally the gully retreat rates were integrated into the USPED model. The results show that the integration of the SPI approach to quantify gully erosion with the USPED model is a suitable method to qualitatively and quantitatively assess water erosion processes. The application of GIS and stochastic model approaches to spatialize the USPED model input yields valuable results for the prediction of soil erosion in the Mazayjan catchment. The results of this research help to develop an appropriate management of soil and water resources in the southwestern parts of Iran.     

Geospatial assessment of soil erosion intensity and sediment yield: a case study of Potohar Region,Pakistan

Estimation of spatial extent of soil erosion, one of the most serious forms of land degradation, is critical because soil erosion has serious implications on soil fertility, water ecosystem, crop productivity and landscape beauty. The primary objective of the current study was to assess and map the soil erosion intensity and sedimentation yield of Potohar region of Pakistan. Potohar is the rainfed region with truncated and complex topography lying at the top of the Indus Basin, the world’s largest irrigation networks of canals and barrages. Spatially explicit Revised Universal Soil Loss Equation (RUSLE) Model integrated with Remote Sensing-GIS techniques was used for detecting/mapping of erosion prone areas and quantification of soil losses. The results show that the Potohar region is highly susceptible to soil erosion with an average annual soil loss of 19 tons ha^?1 year^?1 of which the maximum erosion (70–208 tons ha^?1 year^?1) was near the river channels and hilly areas. The sediment yield due to the erosion is as high as 148 tons ha^?1 year^?1 with an average of 4.3 tons ha^?1 year^?1. It was found that 2.06% of the total area falls under severe soil erosion, 13.34% under high erosion, 15.35% under moderate soil erosion while 69.25% of the area lies in the low (tolerable) soil erosion. Chakwal and Jhelum districts of the region are seriously affected by erosion owing to their topography and soil properties. The information generated in this study is a step forward towards proper planning and implementation of strategies to control the erosion and for protection of natural resources. It is, hence, necessary that suitable water harvesting structures be made to control water to prevent soil erosion and provision of water in the lean season in this region. Tree plantation and other erosion control practices such as strip cropping can also minimize soil erosion in this region.     

Spatial estimation of soil erosion risk using RUSLE/GIS techniques and practices conservation suggested for reducing soil erosion in Wadi Mina watershed (northwest,Algeria)

The Wadi Mina Watershed, western area of Algeria is characterized by rare and irregular rains and a fragile and weak vegetable cover. The sediments resulting from erosion are transported and contributed to silting dam Sidi Mhamed Benaouda. The combination of the thematical maps of the various erosive factors according to the Revised Universal Soil Loss Equation (RUSLE) in SIG by ArcGIS 10.2 software provided a reliable forecast of the annual rates of soil loss by delimiting the areas prone to erosive risk in the catchment above mentioned. The estimated potential average annual soil loss is 11.2 t/ha/yr., and the potential erosion rates from recognized erosion classes ranged from 0.0 to plus 100 t/ha/yr. About 50% of the catchment area was predicted to have very low to low erosion risk, with soil loss between 0 and 7.4 t/ha/yr. Erosion risk is moderate over 13.9% of the catchment, where calculated soil loss is between 7.4 and 12 t/ha/yr. Erosion risk is high to dangerous over 36.1% of the catchment, where calculated soil loss is more than 12 t/ha/yr. According to this study, it appeared clearly that we must intervene quickly by using reliable and effective conservation techniques.     

Evaluation of watershed soil erosion hazard using combination weight and GIS: a case study from eroded soil in Southern China

Natural Hazards - On September 20, 2017, Maria, the eleventh-most intense Atlantic hurricane ever recorded, made landfall at 6:15 am local time, the second category 5 hurricane to strike the island...     

Deforestation effects on soil properties,runoff and erosion in northern Iran

Improper cultivation practices are seriously degrading native forest ecosystems in northern Iran. Hence, the objectives of this study are to compare selected soil properties, runoff amount, erosion and also introducing equations to predict the runoff and soil erosion in three types of land use (forest, garden and cultivated). A simple portable rainfall simulator has been set in 90 random points to create experimental rainfall. Result showed that changes in natural forest led to a significant clay, organic carbon of soil, total N and antecedent soil moisture decrease and sand, pH and bulk density increasing. The rainfall runoff experiments indicate that runoff content of the natural forest soils was 35 % and respectively 38.45 % higher than the garden and cultivated land soils .This result could be related to the higher antecedent soil moisture in natural forest compared with the other land uses. According to the obtained results, garden soil erosion and cultivated land was 1.351 and respectively 1.587 times higher than the forest. The correlation matrix revealed that runoff content was positively correlated with antecedent soil moisture, bulk density and silt, and negatively with soil organic carbon, total N and sand. Also, soil organic carbon, total N, clay and sand showed negative correlation with soil erosion, while there is a positive correlation between erosion and silt, bulk density, pH and antecedent soil moisture. The results of multiple linear regression showed that runoff in forest, garden and cultivated land can be predicted with correlation coefficient of 0.637, 0.547 and 0.624, respectively. The correlation coefficients of 0.798, 0.628 and 0.560 in equations indicate their moderate potential in simulating soil erosion.     

Groundwater exploration using remote sensing and geographic information systems in a semi-arid area (Southwest of Urmieh, Northwest of Iran)

Shortage of water required for drinking and agricultural uses is a subject with a vital importance in most arid and semi-arid regions. The area of this study is one of the semi-arid regions located in southwest of Urmieh lake, northwest of Iran, between N 37°00′, 37°15′ latitude and E 45°05′, 45°30′ longitude which is composed of Permian dolomitic limestone, limestone, and post-Jurassic granite with a very low primary porosity/permeability character. In order to delineate groundwater potential zones in this area, the study focused on identifying secondary porosity/permeability indicators such as lineaments, vegetation cover, lithology, drainage pattern, drainage density, etc. In this regard, a remote sensing and geographic information system-based methodology was selected. Landsat ETM, IRS (pan), SPOT data, digital elevation model, and digital image processing techniques such as filtering, false color composite, principal component analysis, band rationing and classification have been applied to reach the purposes. Information layers extracted for analysis and interpretation stage were then integrated with other data and modeled through the use of existing geographic information system (GIS) software and their related analytical functions. Finally, based on determined ground water favorability index for different sub zones, layers, weighting, and overlapping, a ground water potential index (GWPI) was defined which respectively was utilized to groundwater potential zoning and preparation of GWPI map of the region. Within the six different sub zones defined, two sub zones labeled with high and very good potential areas were highly recommended for further development and exploration purposes. Geophysical investigations in target areas confirm the labeled subzones. Based on the obtained results of the study, it can be concluded that remote sensing data are very useful tool to extract information of groundwater exploration. Also, application of geographic information systems to find target areas for groundwater exploration are effective to save time and cost.     

Estimation of soil erosion using RUSLE in a GIS framework: a case study in the Buyukcekmece Lake watershed,northwest Turkey

This study was aimed at predicting soil erosion risk in the Buyukcekmece Lake watershed located in the western part of Istanbul, Turkey, by using Revised Universal Soil Loss Equation (RUSLE) model in a GIS framework. The factors used in RUSLE were computed by using different data obtained or produced from meteorological station, soil surveys, topographic maps, and satellite images. The RUSLE factors were represented by raster layers in a GIS environment and then multiplied together to estimate the soil erosion rate in the study area using spatial analyst tool of ArcGIS 9.3. In the study, soil loss rate below 1 t/ha/year was defined as low erosion, while those >10 t/ha/year were defined as severe erosion. The values between low and severe erosion were further classified as slight, moderate, and high erosion areas. The study provided a reliable prediction of soil erosion rates and delineation of erosion-prone areas within the watershed. As the study revealed, soil erosion risk is low in more than half of the study area (54%) with soil loss <1 t/ha/year. Around one-fifth of the study area (19%) has slight erosion risk with values between 1 and 3 t/ha/year. Only 11% of the study area was found to be under high erosion risk with soil loss between 5 and 10 t/ha/year. The severe erosion risk is seen only in 5% of the study area with soil loss more than 10 t/ha/year. As the study revealed, nearly half of the Buyukcekmece Lake watershed requires implementation of effective soil conservation measures to reduce soil erosion risk.     

Modeling runoff and soil erosion in a catchment area, using the GIS, in the Himalayan region, India

Remote sensing data and GIS techniques have been used to compute runoff and soil erosion in the catchment area along the NH-1A between Udhampur and Kud covering an area of approximately 181 km². Different thematic layers, for example lithology, a landuse and landcover map, geomorphology, a slope map, and a soil-texture map, were generated from these input data. By use of the US Soil Conservation Service curve number method, estimated runoff potential was classified into five levels—very low, low, moderate, high, and very high. Data integration was performed by use of the weighting rating technique, a conventional qualitative method, to give a runoff potential index value. The runoff potential index values were used to delineate the runoff potential zones, namely low, moderate, high, and very high. Annual spatial soil loss estimation was computed using the Morgan–Morgan–Finney mathematical model in conjunction with remote sensing data and GIS techniques. Greater soil erosion was found to occur in the northwestern part of the catchment area. When average soil loss from the catchment area was calculated it was found that a maximum average soil loss of more than 20 t ha⁻¹ occurred in 31 km² of the catchment area.