Soil Erosion Assessment Research Articles

Risk assessment of soil erosion by application of remote sensing and GIS in Yanshan Reservoir catchment, China

Soil erosion is considered to be a serious problem for environmental sustainability. Healthy and stable soils are crucial for human well-being, providing important ecosystem functions and services. There is a need for a simple and practical approach which estimates and maps soil erosion risk that uses available information as input data to facilitate water and soil conservation. In this work, we developed a predictive approach to estimating the soil erosion risk of the Yanshan Reservoir catchment, which combines remote sensing information, geographic information system spatial analysis technology and a soil erosion risk assessment model. Three dominating factors affecting soil erosion were considered: vegetation coverage, topographic slope and land use. The soil erosion risk was divided into six levels: slight, light, moderate, intense, severe and extremely severe. The slight and light erosion risk accounted for about 83 % of the watershed and was prominent in cultivated land areas, while areas with relatively higher erosion risk were on steep slopes. This approach pointed to inappropriate land use and development as a source of increased risk of soil erosion of the Yanshan Reservoir catchment. Compared with field survey data, the soil erosion modeling approach was shown to have a high accuracy. Therefore, this model could be used to estimate and map soil erosion intensity and distribution at the catchment scale, and could provide useful information for managers and planners to make land management and conservation decisions.

National assessment of soil erosion and its spatial patterns in china

The spatial patterns of soil erosion (SE) are an important part of ecological security patterns and critical to erosion control. We assessed the SE and its spatial distribution in China based on geographic information system (GIS) and spatial data sets using the Universal Soil Loss Equation (USLE). The soil erosion area (SEA) and soil erosion amount (SEM) totaled 173.06 million ha and 8.87 billion Mg, respectively, with an average soil erosion rate (SER) of 9.39 Mg·ha−1·yr−1. Slight erosion dominated from the aspect of SEA, whereas extreme erosion contributed the most in terms of SEM. Spatial heterogeneity in soil erosion was obvious in China, with heavily eroded areas mainly concentrated in the Loess Plateau, the Three Gorges reservoir area, and the hot, dry valley of the Jinsha River. Regionally, the provinces of Tibet, Sichuan, Yunnan, Xinjiang, Inner Mongolia, Gansu, Shaanxi, Shanxi, Guizhou, and Guangxi, and the basins of the Yangtze River, Yellow River, and southwestern rivers made a large contribution to the SEA and SEM. Geographically, soil erosion increased, then decreased with increasing slope and elevation. Slopes of 15–25° and 8–15° and elevations of 1000–2000 m were the most seriously eroded. Cropland and grassland ecosystems were major sources of SE, with their SEA and SEM accounting for 64.44% and 77.96% of the total. This study revealed the current situation and spatial characteristics of SE in China on the national scale, which can serve as a scientific basis for regional SE control and decision‐making policy.

Remote sensing and GIS to assess soil erosion with RUSLE3D and USPED at river basin scale in southern Italy

Soil erosion represents one of the most serious land degradation problems, and Mediterranean areas are particularly prone to this phenomenon. In the light of climate change and human-induced variations on the environment, the threat from soil erosion requires considerable attention. Over the last decades, estimation of soil erosion using empirical models has long been an active research topic. Nevertheless, their application over large areas is still a challenge due to data availability and quality. Successful monitoring can be realised with the integration of ancillary data and remote sensing products within a GIS environment.The main purpose of this research was to quantify the amount of soil erosion rate and to identify the spatial patterns of erosion and deposition in the large heterogeneous semi-agricultural Bradano River basin (southern Italy). This study presents the results of application of the Revised Universal Soil Loss Equation for Complex Terrain (RUSLE3D) and the Unit Stream Power-based Erosion Deposition (USPED) models. In order to appreciate the rate of soil loss and the spatial patterns of soil erosion and deposition, the two models were applied and compared through ancillary data and multi-temporal satellite imagery by GIS application.The analysis shows that the mean annual soil erosion rate ranges between 31 and 34Mgha−1year−1. According to both models the 37% of the Bradano basin ranges between moderate to extreme soil erosion risk. The total amount of gross soil loss ranges between ~1.78∗106Mgyear−1, as computed with the RUSLE3D, and ~2.10∗106Mgyear−1, as computed with the USPED.The analysis and quantification of this phenomenon contribute to an understanding of applicability of those empirical models over large areas.

Assessing soil erosion hazard -a raster based GIS approach with spatial principal component analysis (SPCA)

Soil erosion is one of the most serious environmental problems affecting the quality of soil, land, and water resources upon which humans depend for their sustenance. A soil erosion hazard map is highly useful for environmental planning, soil conservation and management in soil erosion prone areas. In order to assess the soil erosion hazard, remote sensing (RS) and geographical information system (GIS) technologies were adopted, and a numerical model was developed using spatial principal component analysis (SPCA). Here, an integrated soil erosion hazard index (SEHI) was computed and classified into four levels of soil erosion hazard viz. low, average, high, and very high. In the process, nine factors were selected together with the degree of importance of the factors in hazard of the soil erosion. Integrated RS and GIS techniques and models were applied to generate the necessary factors for the SPCA approach. In addition, erosion hazard and calculated rate of soil erosion were used to find out the risk of soil erosion. Soil erosion risk was identified as actual occurrence and potential risk. Results show that, in general, an average hazardous condition of soil erosion was found in the area. The potential risk was more extensive in terms of involved area compared to the actual occurrence, and both actual occurrence and potential risk were higher at the mid-level elevation of the area. This study highlighted that priority should be given where the actual occurrence is high to very high and the probability of potential risk is average to high for protecting the land at present and in the future as well. Therefore, the application of SPCA combined with RS and GIS provided an effective methodology to solve the complex decisional problem for soil erosion hazard and risk assessment.

Soil erosion assessment of a Himalayan river basin using TRMM data

Abstract. In this study, an attempt has been made to assess the soil erosion of a Himalayan river basin, the Karnali basin, Nepal, using rainfall erosivity (R-factor) derived from satellite-based rainfall estimates (TRMM-3B42 V7). Average annual sediment yield was estimated using the well-known Universal Soil Loss Equation (USLE). The eight-year annual average rainfall erosivity factor (R) for the Karnali River basin was found to be 2620.84 MJ mm ha−1 h−1 year−1. Using intensity–erosivity relationships and eight years of the TRMM daily rainfall dataset (1998–2005), average annual soil erosion was also estimated for Karnali River basin. The minimum and maximum values of the rainfall erosivity factor were 1108.7 and 4868.49 MJ mm ha−1 h−1 year−1, respectively, during the assessment period. The average annual soil loss of the Karnali River basin was found to be 38.17 t ha−1 year−1. Finally, the basin area was categorized according to the following scale of erosion severity classes: Slight (0 to 5 t ha−1 year−1), Moderate (5 to 10 t ha−1 year−1), High (10 to 20 t ha−1 year−1), Very High (20 to 40 t ha−1 year−1), Severe (40 to 80 t ha−1 year−1) and Very Severe (>80 t ha−1 year−1). About 30.86% of the river basin area was found to be in the slight erosion class. The areas covered by the moderate, high, very high, severe and very severe erosion potential zones were 13.09%, 6.36%, 11.09%, 22.02% and 16.64% respectively. The study revealed that approximately 69% of the Karnali River basin needs immediate attention from a soil conservation point of view.

A New European Slope Length and Steepness Factor (LS-Factor) for Modeling Soil Erosion by Water

The Universal Soil Loss Equation (USLE) model is the most frequently used model for soil erosion risk estimation. Among the six input layers, the combined slope length and slope angle (LS-factor) has the greatest influence on soil loss at the European scale. The S-factor measures the effect of slope steepness, and the L-factor defines the impact of slope length. The combined LS-factor describes the effect of topography on soil erosion. The European Soil Data Centre (ESDAC) developed a new pan-European high-resolution soil erosion assessment to achieve a better understanding of the spatial and temporal patterns of soil erosion in Europe. The LS-calculation was performed using the original equation proposed by Desmet and Govers (1996) and implemented using the System for Automated Geoscientific Analyses (SAGA), which incorporates a multiple flow algorithm and contributes to a precise estimation of flow accumulation. The LS-factor dataset was calculated using a high-resolution (25 m) Digital Elevation Model (DEM) for the whole European Union, resulting in an improved delineation of areas at risk of soil erosion as compared to lower-resolution datasets. This combined approach of using GIS software tools with high-resolution DEMs has been successfully applied in regional assessments in the past, and is now being applied for first time at the European scale.

Special Issue on Soil Erosion and Sediment Yield Modeling

Soil erosion is one of the most serious environmental problems because it removes fertile soil that is rich in nutrients and, in turn, increases the natural level of sedimentation in rivers and reservoirs, reducing their storage capacity and life span. Land degradation stems from a combination of factors related to land use, agricultural intensification, and intense rainstorms. For maintaining and improving soil productivity, soil resources need to be conserved for optimal land use. In other words, to restore the productivity of soil and prevent further damage, planning for conservation and management of watersheds become vital. For assessing soil erosion and sediment yield from watersheds, several empirical models on the basis of geomorphological parameters have been developed and are available in the literature. Among several methods, the sediment yield index (SYI) method and universal soil loss equation (USLE) are extensively used for the estimation of soil erosion and prioritization of watersheds for their treatment. Research in hydrological modeling and related watershed planning issues form a significant component of the prevailing environmental activities. During the last three decades, a number of empirical and conceptual hydrological models have been developed for the prediction of soil erosion and sediment yield modeling. Thus, there is a need to have another look at different aspects of soil erosion and sediment yield modeling and enhance their understanding for improved practical applications. The present special issue of the Journal of Hydrologic Engineering focuses on soil erosion and sediment yield modeling, including the effects of land use/cover changes, extended applications using empirical and physically based soil erosion and sediment yield models, and watershed management coupling remote sensing and the geographic information system (GIS). Within this framework, the papers of this special issue have been grouped into the following: studies on the basis of physically based, conceptual, and empirical models; advancement and review; watershed management; and experimental work. Papers titled “Identification of Critical Erosion Watersheds for Control Management in Data Scarce Condition Using the SWAT Model,” “Use of Caesium-137 Measurements and Long-Term Records of Sediment Load to Calibrate the Sediment Delivery Component of the SEDD Model and Explore Scale Effect: Examples from Southern Italy,” “Application of SWAT Model and Geospatial Techniques for Sediment-Yield Modeling in Ungauged Watersheds,” “Soil Erosion and Sediment-Yield Prediction at Basin Scale in Upstream Watershed of Miyun Reservoir,” “Improved Hillslope Erosion Module for the Digital Yellow-River Model,” and “Evaluation of GIS-Based Watershed Model for Streamflow and Sediment-Yield Simulation in the Upper Baitarani River Basin of Eastern India” fall in the category of physically based soil erosion and sediment yield modeling. Papers titled “Inductive Group Method of Data Handling Neural Network Approach to Model Basin Sediment Yield,” “Modeling Suspended Sediment Using Artificial Neural Networks and TRMM-3B42 Version 7 Rainfall Dataset,” and “Accounting for Conceptual Soil Erosion and Sediment Yield Modeling Uncertainty in the APEX Model Using Bayesian Model Averaging” deal with conceptual modeling for soil erosion and sediment yield. Papers titled “Application of GISCoupled Modified MMF Model to Estimate Sediment Yield on a Watershed Scale,” “Impact of Climate Change on Future Soil Erosion in Different Slope, Land Use, and Soil-Type Conditions in a Part of the Narmada River Basin, India,” and “Spatially Distributed Sheet, Rill, and Ephemeral Gully Erosion” employ empirical models for the estimation of sediment yield. The paper “Sediment Graphs Based on Entropy Theory,” which derives an instantaneous unit sediment graph (IUSG or USG) to determine sediment discharge and establishes a relation between sediment yield and runoff volume, exhibits an advancement in the field of sediment yield modeling. Conversely, the paper “Geographic Variation of USLE/RUSLE Erosivity and Erodibility Factors” provides a comprehensive review on the subject. The papers “Integrated Modeling Approach to the Response of Soil Erosion and Sediment Export to Land-Use Change at the Basin Scale,” “Evaluating the Impact of the Spatial Distribution of Land Management Practices on Water Erosion: Case Study of a Mediterranean Catchment,” and “Sediment Fingerprinting for Calibrating a Soil Erosion and Sediment-Yield Model in Mixed Land-Use Watersheds” deal with watershed management. The papers “Establishing a Soil Loss Threshold for Limiting Rilling,” “Transport Capacity of Overland Flow with High Sediment Concentration,” “Modeling Rainfall Erosivity by Measured Drop-Size Distributions,” “Modeling Rill Erosion at the Sparacia Experimental Area,” “Rapid Weathering and Erosion of Mudstone Induced by Saltwater Migration near a Slope Surface,” and “Rain Microstructure and Erosivity Relationships under Pressurized Rainfall Simulator” are on the basis of experimental work. The aim of this issue is to present high-quality technical articles representing the most recent developments in the field of soil erosion and sediment yield modeling, including practical applications. This special issue is expected to become the first in a sequence of future issues on this topic.

Comparison of different methods to measure soil erosion in the Central Ebro Valley

Fire is a natural factor of landscape evolution in Mediterranean ecosystems. Due to social and economical changes, wildfires have caused hydrological and geomorphological changes to be more pronounced, resulting in enhanced soil erosion. The study area is located in the Zuera Mountains, near the city of Zaragoza (Spain) in the Middle Ebro Valley. These mountains were affected by two wildfires in 2008 and 2009, burned around 2000 ha and 6000 ha, respectively. Middle Ebro Valley has extreme aridity, which results in a low plant cover and high soil erodibility enhanced by the fire effects. Soil infiltration is one of the properties affected by fire as a consequence of litter and vegetation removal, heating of and changes to the biological, chemical and physical soil properties. The objective was to compare two different methods –rainfall simulations and erosion plots–, to assess soil erosion after forest fires. We compared different measurements with rainfall simulators and erosion plots, applying a woodchip cover –in order to reduce the rain splash effect–, and to measure the erosion reduction. The work showed low sediment rates in both experiments covered with woodchips.

GIS-based effect assessment of soil erosion before and after gully land consolidation: A case study of Wangjiagou project region, Loess Plateau

The Loess Plateau is one typical area of serious soil erosion in the world. China has implemented ‘Grain for Green’ (GFG) project to restore the eco-environment of the Loess Plateau since 1999. With the GFG project subsidy approaching the end, it is concerned that farmers of fewer subsidies may reclaim land again. Thus, ‘Gully Land Consolidation Project’ (GLCP) was initiated in 2010. The core of the GLCP was to create more land suitable for farming in gullies so as to reduce land reclamation on the slopes which are ecological vulnerable areas. This paper aims to assess the effect of the GLCP on soil erosion problems by studying Wangjiagou project region located in the central part of Anzi valley in the middle of the Loess Plateau, mainly using the revised universal soil loss equation (RUSLE) based on GIS. The findings show that the GLCP can help to reduce soil shipment by 9.87% and it creates more terraces and river-nearby land suitable for farming which account for 27.41% of the whole study area. Thus, it is feasible to implement the GLCP in places below gradient 15°, though the GLCP also intensifies soil erosion in certain places such as field ridge, village land, floodplain, natural grassland, and shrub land. In short, the GLCP develops new generation dam land and balances the short-term and long-term interests to ease the conflicts between economic development and environmental protection. Furthermore, the GLCP and the GFG could also be combined preferably. On the one hand, the GFG improves the ecological environment, which could offer certain safety to the GLCP, on the other hand, the GLCP creates more farmland favorable for farming in gullies instead of land reclamation on the slopes, which could indirectly protect the GFG project.

Source of error and uncertainty in sheet erosion rates estimated from dendrogeomorphology

AbstractDendrogeomorphology has been used since the 1960s to estimate sheet erosion rates. To date, most efforts have focused on accurately determining the first year of root exposure. However, an adequate methodological approach that takes into consideration the microtopography of the ground surface when estimating sheet erosion rates using dendrogeomorphology has not been proposed. In this study, terrestrial laser scanning (TLS) was used for the first time to examine how changes in microtopography determine the level of certainty in estimates. To this end, highly accurate TLS‐based digital elevation models representing exposed roots and their immediate vicinity were analysed using geographic information system tools. The results indicate that erosion rates calculated using the standard dendrogeomorphic method have been underestimated by up to 29% because the method does not take into account changes to the microtopography caused by the axial and radial pressure of the roots. Another source of uncertainty, which we estimate to be 50%, was also found and is the result of changes in the ground surface microtopography caused by variations in soil roughness. These findings do not invalidate the usefulness of dendrogeomorphology for assessing soil erosion, although they do show the need for correct characterization of the microtopography to guarantee reliability. Copyright © 2015 John Wiley & Sons, Ltd.

Assessment of soil loss in South Korea based on land-cover type

Soil loss poses a significant threat to the long-term sustainability of hydrological systems, the environment, and agriculture. In this regard, efficient soil management relies on accurate quantification of soil loss. To this end, the Organization for Economic Cooperation and Development (OECD) standard of soil erosion, developed for agricultural areas, has been applied in many countries, including South Korea. Due to the lack of standard methods for assessing soil erosion in South Korea, the OECD standard has been applied to non-agricultural regions of Korea despite the possibility that local soil erosion characteristics may differ from those in agricultural areas. Such an approach might give erroneous information on soil loss to policy and decision makers. This study estimated soil loss for eight different land cover-types in Korea using the universal soil loss equation, and compared the results with those from the unmodified OECD soil erosion standard. Estimated soil loss differed considerably among land-cover types. The results have implications on the limitations in applying the OECD soil erosion standard to soil management in Korea. Thus, this study suggests a modified soil erosion standard for efficient soil management.

Modeling of sediment yield in Maybar gauged watershed using SWAT, northeast Ethiopia

Application of models to identify soil erosion processes, estimate sediment accumulations into lakes, technically design best management practices, and monitor and evaluate different management scenarios in the Ethiopian highlands has been growing. However, proper model implementation will require verification of the model against known output parameters. This study investigated the performance and applicability of one such model, Soil and Water Assessment Tool (SWAT). Sequential Uncertainty Fitting-2 (SUFI-2), a SWAT-CUP2012 sub-module computer program, was applied to optimize the parameters of the SWAT using monthly observed sediment yield data at a monitoring site in Maybar experimental watershed, Ethiopia. Thirteen hydrological years were used for model calibration, validation and uncertainty analysis. Multi-objective function statistics: P-factor (23%, 12%), R-factor (0.63, 0.40), Nash–Sutcliffe efficiency, NSE (0.55, 0.53), root mean square error-observations standard deviation ratio (RSR) (0.67, 0.69), coefficient of determination, R2 (0.55, 0.52), and percent bias, PBIAS (−14.6%, 0.8%) for calibration and validation, respectively were obtained. The model evaluation statistics suggested that SWAT extremely under-predicted peak sediment loads in both calibration and validation periods. However, according to model evaluation guidelines and performance ratings, modeled sediment yield can be rated as satisfactory. Although the accuracy of modeling of soil erosion processes using SWAT is likely affected by spatial variation of watershed characteristics, and scale of management, among other factors, Maybar calibrated SWAT model do suggest a broad guide: prediction of sediment yield at ungauged watershed with SWAT could be possible under comparable topography, land use, soil, management and climate condition for the purpose of soil erosion assessment, scenario analysis, and recommendation of best management practices to support watershed management initiatives in the Ethiopian highlands.

Fundamental Study on Assessment of Soil Erosion by the USLE Method at Rehabilitation Area in Indonesian Coal Mine

Mining operation of open cut mines gives serious impacts on the surrounding environments. Therefore, an appropriate rehabilitation program has to be taken into consideration. Soil erosion is one of the major environmental problems in open cut mines in tropical regions. The soil erosion leads to unsuccessful rehabilitation due to topsoil losses. In order to succeed rehabilitation, the condition of soil erosion in the rehabilitation area has to be predicted accurately. As one of an efficient method for prediction of soil loss, Universal Soil Loss Equation (USLE) is the most widely used method of predicting soil loss in forestry. However, when considering the application of this equation in rehabilitation area, a sufficient consideration is needed because the condition of these areas is very different from that of forestry. This paper describes the reliability to predict soil erosion in rehabilitation area by means of USLE, and discusses the several considerations on soil erosion.

Estimation of soil erosion in some sections of Lower Jinsha River based on RUSLE

Soil erosion increasingly poses a great threat to human food security and environmental quality. It is necessary to implement the assessment of soil erosion so as to provide precautionary measures and relevant suggestions for soil conservation. In this paper, the soil erosion model, revised universal soil loss equation (RUSLE), was used to quantify the soil loss in a large mountainous area of Lower Jinsha River Basin. The analysis of the datasets by means of geographic information systems (GIS) together with RUSLE led to the estimation of soil erosion. Results show that the average annual soil erosion was estimated at 52.1 t ha−1 year−1 and the total annual soil loss was 4.5 × 108 t. The highest erosion was found along the main course of Jinsha River. Soil erosion was serious in the elevation zone between 1,675 and 2,153 m and slope zone with slopes between 15° and 35°. As for land use types, cropland and grassland contributed 84.1 % to total soil loss due to the large areas and higher erosion rates. The results can be used to advice the local government in prioritizing the areas of immediate conservation practices.

Design of self-sustainable land surface against soil erosion at rehabilitation areas in open-cut mines in tropical regions

Soil erosion is one of the major environmental problems in open-cut mines in tropical regions. It causes negative impacts including the removal of nutrient rich topsoil and subsequent reduction of agricultural productivity in the rehabilitation process. Therefore, it is important to predict soil erosion in advance and establish the proper process to minimise the phenomenon for the success of rehabilitation in the disturbed land. Field investigation to understand soil characteristics in rehabilitation areas and artificial rainfall experiment in laboratory scales were used to assess soil erosion. From a series of investigations, the soil characteristics that spread to the rehabilitation areas were uneven due to mixing overburden as contamination; moreover, it can increase the risk of soil erosion when the soil has high soil erodibility. Another study finding shows the importance of selective placement of erosion-resistant soil in an area which has a high potential for soil erosion to occur, such as slope with an establishment of rapid growing cover crop species on the surface. This paper describes soil erosion under the various soil characteristics and effective countermeasures in situ, and discusses the design of the self-sustainable land surface against soil erosion.

Control Over River Bank Erosion: A Case Study of Ganetti Station, Northern States, Sudan

The Ganetti station soil erosion model was used to quantify the amount of runoff in the upper catchment that takes into account effect of land cover change and also how different factors affect surface runoff. The study is constructed using the mathematical modeling language which allows for great flexibility and GIS that uses a raster type representation of the catchment which allows for a detailed representation of the processes. The results show not only the total runoff at the outlet but also the amount of sediment. The overall objectives of this work is to demonstrate bank erosion control using image processing and hydrological model for River bank erosion based on the time series, assess soil erosion in sub-watershed, use Sediment Transport Index (STI) to replace the slope gradient in the revised MMF model and assess erosion prone areas in inaccessible land areas. The Bank Stability and Toe Erosion Model is a physically-based model. It represents the failure by shearing of a soil block of variable geometry and the erosion by flow of bank and bank toe material. The effect of toe erosion, vegetative treatments or other bank and bank toe protection measures can be illustrated by calculating the actual Factor of Safety (Fs) of the bank.

地形对草甸草原植被生产力分布格局的影响

PDF HTML阅读 XML下载 导出引用 引用提醒 地形对草甸草原植被生产力分布格局的影响 DOI: 10.5846/stxb201306201748 作者: 作者单位: 鲁东大学地理与规划学院,中国环境科学研究院生态研究所,中国环境科学研究院生态研究所,中国环境科学研究院生态研究所 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金(41271193);国家环境保护公益性行业科研专项(200909021) Impact of topography on the spatial distribution pattern of net primary productivity in a meadow Author: Affiliation: Ludong University,,, Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:草原植被生产力在陆地生态系统碳平衡分析中扮演重要角色,而地形作为影响植被生产力(NPP)分布格局的重要环境因子在已有的草原遥感监测研究中没有被充分重视。以USGS和GLCF共享MODIS和DEM数据为数据源,选取呼伦贝尔辉河湿地保护区草甸草原核心区为研究对象,在地面光谱生物量模型构建的基础上,采用ARCGIS的空间分析功能对呼伦贝尔草甸草原2000-2012年的NPP分布格局进行了分析。研究结果表明,地形对草甸草原植被生产力分布格局有显著的影响。在海拔高度、坡度和坡向等3个地形因子中,海拔高度引起的NPP变化幅度最大,坡度次之,坡向最小。在总体特征上,海拔高度每升高10m,生产力增加4.78 g/m2;坡度每增加1°生产力增加-1.42 g/m2;N坡向植被生产力水平最高(184.8 g/m2),西南(SW)坡向最低(173.3 g/m2)。从不同地形因子的分布面积特点判断,地形对草甸草原NPP的影响尺度介于土壤环境异质性和草场类型异质性之间。不同生产力水平年份对生产力分布格局的影响趋势一致,但变化幅度不同,在中等生产力水平年份NPP变幅最大。 Abstract:Net primary productivity (NPP) of grassland plays an important role in terrestrial ecosystems, and its spatial heterogeneous traits have significant influence upon regional carbon cycle, grazing capacity, soil erosion, and ecosystem safety assessment. How topography, one of significant environmental factors, affects grassland productivity is not well addressed in the remote sensing of grassland ecosystems. This paper selected a protected meadow of the National Natural Reserve of Huihe wetland, used USGS EOS-MODIS/Terra NDVI data and GLCF DEM data, and adopted spatial analysis function of ARCGIS to analyze the NPP distribution pattern form 2000 to 2012 in Hulunbuir meadow based on the ground spectrum biomass model, topographical controlling factors, and yearly precipitation classification. The results showed that the ground spectrum biomass model can be used to assess meadow productivity, and the most suitable model is y =15.968e3.5434x (Sig=0.000) for predicting Hulunbuir meadow productivity in regional scale (where y and x represent productivity and NDVI, respectively). Simulated results confirmed that topography had a remarkable impact on meadow productivity distribution pattern. Consequently, among three topographical factors of altitude, slope and aspect, altitude gave rise to the most significant changes, the effect of the slope was intermediate, and the aspect played a minimal effect. Firstly, under the conditions of the slope of 0-2 degrees and aspect of NE, NPP increased 0.478 g/m2 per meter rising of elevation in normal yearly precipitation level; 0.414 g/m2 in lower yearly precipitation level; 0.482 g/m2 in moderate yearly precipitation level; and 0.525 g/m2 in higher yearly precipitation level, respectively. Secondly, under the conditions of altitude of 760-780 m and aspect of NE, the meadow productivity decreased 0.142 g/m2 per degree increase of slope in the normal yearly precipitation level, and decreased 0.161 g/m2 in the lower yearly precipitation level, 0.135 g/m2 in the moderate yearly precipitation level, 0.133 g/m2 in the higher yearly precipitation level, respectively. Thirdly, under the conditions of the altitude of 760-780 m and the slope of 0-2 degrees, the highest NPP (184.6 g/m2) occurred on the N aspect and the lowest NPP (173.3 g/m2) on the W aspect, respectively. The NPP was lower on the SW aspect in the lower yearly precipitation level and on the W aspect in the moderate yearly precipitation level. By contrast, lower NPP occupied on the SE aspect in the higher yearly precipitation level. According to NPP distribution area, the topographical factors had higher (lower) effect on NPP of the meadow than soil heterogeneity (grassland type) on spatial scale. The trend of this effect did not vary across years with various NPP but differed in effect degree, being higher in the years with intermediate NPP. 参考文献 相似文献 引证文献

Soil Erosion Is Influenced by Grain for Green Policy in Loess Plateau Area of Northern Shaanxi, China

Grain for Green Policy (GGP), one of China’s important ecological construction and protection policies, have been made remarkable achievements since implementation in 1999. The purpose of this work is to assessment of soil erosion influenced by GGP, which implementation is lead to great change of land use and vegetation cover, using RUSLE model on the basis of land use, MODIS NDVI, DEM and precipitation data in Loess Plateau area of northern Shaanxi, northwest of China. Result showed: (1) GGP implementation in northern Shaanxi was mainly during 1999-2003 and the area of returning farmland in the period accounted for 81.28% of the total area from1999 to 2008. (2) Farmland in northern Shaanxi and slope >25o was decrease 4.94% and 4.84%, respective ly, while grassland was increase 4.04% and 4.05%, respectively. The change of decreasing farmland and increasing grassland was mainly from 2000 to 2005 in northern Shaanxi and slope >25o. (3) Farmland was convert into woodland and grassland, which leaded to increasing of vegetation NDVI. Especially, the vegetation NDVI value of farmland in slope >25o was increase larger than whole area of northern Shaanxi from 2000 to 2010. (4) The change area of soil erosion in northern Shaanxi and slope >25o was decrease in 1 degree, while was increase in other degrees from 2000 to 2010. But when recalculated by rainfall erosivity in 2000, the change area of soil erosion in northern Shaanxi and >25o was increase in 1 degree, while was decrease in other degrees from 2000 to 2010. Vegetation cover change induced by GGP was reduce soil erosion, but due to rainfall erosivity increased, soil erosion was show increase trend in northern Shaanxi and slope >25o.

Assessment and Mapping of the Vulnerability of Soils in Imo State, Nigeria to Erosion Hazard Using Geographic Information System

Soil erosion by water is a critical problem in Imo State terrain due to anthropogenic pressure on its landscape. Assessment and mapping of erosion prone area is essential for soil conservation and watershed management. The objectives of the study are to use satellite imageries to assess and map the land cover, vegetation, land use, topography and hydrology; and to use field sampling to map soil properties and soil erodibility of Imo State with a view to assessing soil erosion hazard in Imo State. The DEM was generated to prepare slope map, elevation map and hill shading map. Results from the study show that 45.4 % of the land cover of Imo State representing 2256.7 Km2 is covered by light vegetation whereas 24.7 % of the land area representing 1229 Km2 is covered by thick vegetation. The result also showed that a large percentage of the entire land area (21%) representing 1046.3 Km2 is cultivated whereas 6.4% representing 319 Km2 is built up with houses and infrastructure like roads, bridges etc. The area covered by thick vegetation (24.7%) is categorized under slightly vulnerable to stable. A larger percentage (45.4%) is covered by light vegetation, and therefore, classified as moderately vulnerable to erosion whereas 27.4% comprising cultivated and built up areas are classified as highly to extremely vulnerable to erosion. Results also show that most parts of the state (4133Km2) representing 84% of the entire landscape fall into slightly to less vulnerable to erosion with a slope class between 1 – 4% slope. The results on hill shading concur with that of slope above. As expected, the dispersion ratios were affected by the type of underlying parent material. Results from the characterization of soil properties of study area show since most soils in the study area have high dispersion rates, depicting high vulnerability to soil erosion and 84% of the entire landscape fall into slightly to less vulnerable to erosion with a slope class between 1 – 4% slope, it then follows that high rates of erosion recorded for the area may be due to land use and management as light vegetation, cultivation and built areas cover 73% of the land area and classified as moderately to extremely vulnerable to erosion. The result at landscape and plot scale varies. Therefore, model results need to be carefully used for local level soil conservation planning.

Plutonium as a tracer for soil erosion assessment in northeast China

Soil erosion is one of the most serious environmental and agricultural problems faced by human society. Assessing intensity is an important issue for controlling soil erosion and improving eco-environmental quality. The suitability of the application of plutonium (Pu) as a tracer for soil erosion assessment in northeast China was investigated by comparing with that of 137Cs. Here we build on preliminary work, in which we investigated the potential of Pu as a soil erosion tracer by sampling additional reference sites and potential erosive sites, along the Liaodong Bay region in northeast China, for Pu isotopes and 137Cs. 240Pu/239Pu atomic ratios in all samples were approximately 0.18, which indicated that the dominant source of Pu was the global fallout. Pu showed very similar distribution patterns to those of 137Cs at both uncultivated and cultivated sites. 239+240Pu concentrations in all uncultivated soil cores followed an exponential decline with soil depth, whereas at cultivated sites, Pu was homogenously distributed in plow horizons. Factors such as planted crop types, as well as methods and frequencies of irrigation and tillage were suggested to influence the distribution of radionuclides in cultivated land. The baseline inventories of 239+240Pu and 137Cs were 88.4 and 1688Bqm−2 respectively. Soil erosion rates estimated by 239+240Pu tracing method were consistent with those obtained by the 137Cs method, confirming that Pu is an effective tracer with a similar tracing behavior to that of 137Cs for soil erosion assessment.