Amount Of Soil Erosion Research Articles

1988-2013年基于BP神经网络的植被叶面积指数遥感定量反演

PDF HTML阅读 XML下载 导出引用 引用提醒 1988-2013年基于BP神经网络的植被叶面积指数遥感定量反演 DOI: 10.5846/stxb201703290547 作者: 作者单位: 南京林业大学,南京林业大学,南京林业大学,南京林业大学,南京林业大学,南京林业大学 作者简介: 通讯作者: 中图分类号: 基金项目: 国家重点研发计划资助项目（2017YFC0505505）；国家自然科学基金项目（31200534）；江苏高校优势学科建设工程资助项目；2014年江苏省普通高校学术学位研究生科研创新计划项目 Quantitative inversion of long sequential leaf area index using remote sensing based on BP neural network from 1988 to 2013 Author: Affiliation: Key Laboratory of Soil and Water Conservation and Ecological Restoration in Jiangsu Province,Collaborative Innovation Center of Sustainable Forestry in Southern China of Jiangsu Province,Nanjing Forestry University,Nanjing,Key Laboratory of Soil and Water Conservation and Ecological Restoration in Jiangsu Province,Collaborative Innovation Center of Sustainable Forestry in Southern China of Jiangsu Province,Nanjing Forestry University,Nanjing,Key Laboratory of Soil and Water Conservation and Ecological Restoration in Jiangsu Province,Collaborative Innovation Center of Sustainable Forestry in Southern China of Jiangsu Province,Nanjing Forestry University,Nanjing,Key Laboratory of Soil and Water Conservation and Ecological Restoration in Jiangsu Province,Collaborative Innovation Center of Sustainable Forestry in Southern China of Jiangsu Province,Nanjing Forestry University,Nanjing,Key Laboratory of Soil and Water Conservation and Ecological Restoration in Jiangsu Province,Collaborative Innovation Center of Sustainable Forestry in Southern China of Jiangsu Province,Nanjing Forestry University,Nanjing,Key Laboratory of Soil and Water Conservation and Ecological Restoration in Jiangsu Province,Collaborative Innovation Center of Sustainable Forestry in Southern China of Jiangsu Province,Nanjing Forestry University,Nanjing 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:叶面积指数（Leaf Area Index，LAI）高度综合了植被水平覆盖状况和垂直结构，以及枯枝落叶层厚薄和地下生物量多少，是植被影响土壤侵蚀的主要方面。区域尺度的时间序列叶面积指数揭示了区域土壤侵蚀的演化过程。因此，及时准确地掌握区域尺度上长时间序列的植被LAI，对研究土壤侵蚀动态变化与植被的关系至关重要。选择南京市1988-2013年10期遥感影像，基于反向传播（Back Propagation，BP）神经网络构建LAI反演模型，进行了长时间序列的叶面积指数反演。结合2009和2010年LAI实测值，验证与探讨了该模型的评价精度与适应性。结果表明：（1）该模型拟合度较高，2009和2010年平均相对误差、均方根误差、相关系数分别是0.2395和0.2174，0.2962和0.2581，0.7713和0.6844，各项精度评价指标均较好；（2）统计分析去除耕地后全市LAI变化，低植被覆盖（LAI<2）面积不断增加，高植被覆盖区（LAI>3）面积先减少后增加，耕地面积不断减少，符合南京市的发展变化规律；（3）主城区LAI年际变化与其他学者得到的南京市植被盖度变化趋势一致，反演结果的时序性较高。本文提出的基于反向传播神经网络模型反演长时间序列LAI是可行的，为区域尺度土壤侵蚀定量遥感监测提供新途径。 Abstract:Leaf Area Index(LAI) can reflect the horizontal coverage, vertical structure of vegetation, the thickness of the litter layer and the amount of underground biomass, which is the main aspect of vegetation affecting soil erosion. It is very important to monitor the changes in the amount of soil erosion, for useful information to guide the planning of soil and water conservation, protect the soil and water resources and control the soil erosion. Therefore, the method by which we obtain high quality and long sequential LAI at a regional scale is very important for analyzing the relationship between the dynamic changes in soil erosion and vegetation. Previous studies showed that the neural network had an incomparable superiority in terms of complex, nonlinear data fitting and pattern recognition, and had been successfully applied to inverse the LAI in Nanjing based on the multi-spectral remote sensing data derived from the Landsat 8 Operational Land Imager(OLI), four types of vegetation indices(Normalized Difference Vegetation Index, NDVI; Ratio Vegetation Index, RVI; Soil-adjusted Vegetation Index, SAVI; Modified Soil adjusted Vegetation Index, MSAVI), and measured LAI data. The results showed that the accuracy of retrieval was good. In this paper, we used the Back Propagation(BP) neural network model to inverse the LAI in Nanjing during 1988-2013 based on the data derived from Landsat 8 OLI and Landsat 5 Thematic Mapper(TM). Based on the measured values of LAI in 2009 and 2010, the evaluation accuracy and adaptability of the model were verified and discussed. The results showed that:(1) The model had a fitting of higher degree, and average relative errors(MAPE), root mean square errors(RMSE), and correlation coefficients(R) in 2009 and 2010 of 0.2395 and 0.2174, 0.2962 and 0.2581, and 0.7713 and 0.6844, respectively. Each accuracy evaluation index was good.(2) Following statistical analysis, we found that the low vegetation coverage area(LAI < 2) exhibited an increasing trend, the high vegetation coverage area(LAI > 3) presented a first decreasing and then increasing trend, while the cultivated land area decreased with the rapid development in Nanjing.(3) To analyze accurately the LAI, we extracted the LAI in the main urban area, and found that there was a relatively high inversion value, and the inter-annual change in LAI was consistent with the change in vegetation coverage in Nanjing reported by other studies. Therefore, we could see that the BP neural network model had a high accuracy for the time series LAI inversion. It provides a new way for quantitative remote sensing monitoring of regional soil erosion. Moreover, because of other potential limiting factors, such as the errors produced by the BP neural network model, the large area of the inversion area, the complexity of vegetation types and community structure, etc., the inversion accuracy of LAI through remote sensing still needs to be explored, and the inversion method improved. We will try to establish a multi-angle LAI inversion method to construct the coupling model of LAI and soil erosion or quantitative fusion of multi-source remote sensing images in the future study. 参考文献 相似文献 引证文献

Comparing watershed soil erosion of Taiwan and Thailand

Tropical watersheds in Taiwan and Thailand face the same severe soil erosion problem that is increasing at an alarming rate. In order to evaluate the severity of soil erosion, we quantitatively investigate the issue using a common soil erosion model (Universal Soil Loss Equation, USLE) on the Shihmen reservoir watershed of Taiwan and the Lam Phra Ploeng basin of Thailand, and compare their respective erosion factors. The results show an interesting contrast between the two watersheds. Some of the factors (rainfall factor, slope-steepness factor) are higher in the Shihmen reservoir watershed, while others (soil erodibility factor, cover and management factor) are higher in the Lam Phra Ploeng basin. The net result is that these factors cancel each other out, and the amount of soil erosion of the two watersheds are very similar at 68.03 t/ha/yr and 67.57 t/ha/yr, respectively.

Investigation of RS and GIS techniques on MPSIAC model to estimate soil erosion

Soil erosion due to surface water is a standout among the serious threat land degradation problem and an hazard environmental destruction. The first stage for every kind of soil conservation planning is recognition of soil erosion status. In this research, the usability of two new techniques remote sensing and geographical information system was assessed to estimate the average annual specific sediments production and the intensity erosion map at two sub-basins of DEZ watershed, southwest of Lorestan Province, Iran, namely Absorkh and Keshvar sub-basins with 19,920 ha, using Modified Pacific Southwest Inter-Agency Committee (MPSIAC) soil erosion model. At the stage of imagery data processing of IRS-P6 satellite, the result showed that an overall accuracy and kappa coefficient were 90.3% and 0.901, respectively, which were considered acceptable or good for imagery data. According to our investigation, the study area can be categorized into three level of severity of erosion: moderate, high, and very high erosion zones. The amount of specific sediments and soil erosion predicted by MPSIAC model was 1374.656 and 2396.574 m3 km−2 year−1, respectively. The areas situated at the center and south parts of the watershed were subjected to significant erosion because of the geology formation and ground cover, while the area at the north parts was relatively less eroded due to intensive land cover. Based on effective of nine factors, the driving factors from high to low impact included: Topography > Land use > Upland erosion > Channel erosion > Climate > Ground cover > Soil > Runoff > Surface geology. The measured sediment yield of the watershed in the hydrometric station (Keshvar station) was approximately 2223.178 m3 km−2 year−1 and comparison of the amount of total sediment yield predicted by model with the measured sediment yield indicated that the MPSIAC model 38% underestimated the observed value of the watershed.

Development of web-based WERM-S module for estimating spatially distributed rainfall erosivity index (EI30) using RADAR rainfall data

Despite technological advances, soil erosion modeling is a very complicated process as the amount and rate of soil erosion vary considerably over space and time. Universal Soil Loss Equation (USLE) is one of the oldest and popular models used for soil loss estimation worldwide. USLE R-factor is one of the six input parameters accounting for the impact of rainfall amount and intensity on soil erosion in USLE. The USLE R factor is calculated by averaging annual long time rainfall erosivity index (EI30) values, computed by multiplying maximum rainfall intensity during 30min periods and the kinetic energy of the rainfall. The gage rainfall data are used for the determination of such EI30 index, and one representative value is given for the entire area. Due to the spatial and temporal variability of rainfall pattern, the value may vary considerably over space and time. It is required to obtain the rainfall data over a surface (heterogeneous) rather than at a point (homogeneous) so that spatially distributed erosivity index values can be calculated. Even though RADAR can provide spatially and temporally distributed rainfall data, the process of manual erosivity index calculation for each raster pixel is very tedious, time-consuming and practically not feasible. To overcome these limitations, the web-based WERM-S module was developed to compute a spatial EI30 index from the 10-min interval spatial rainfall data. The WERM-S consists of three different Fortran modules (Convert Module, R-factor calculation module, and R-factor ASCII module). The Jaun-ri watershed was selected as the study area to test the module since the RADAR rainfall data was available for 2015. June, July, and August were found to be the months receiving the maximum amount of rainfall and the average erosivity indices for June, July and August were found to be 2096, 1002, and 993MJ·mm/ha-hr-month, respectively. The maximum erosivity index for a pixel within the study area was observed to be 9821MJ·mm/ha-hr-month for June 4382MJ·mm/ha-hr-month for July and 6093MJ·mm/ha-hr-month for August respectively. The higher value of standard deviations of 1850, 950 and 1115MJ·mm/ha-hr-month for June, July, and August were observed respectively representing that the erosivity index of individual space widely deviated from the mean monthly erosivity index. Thus spatial erosivity index is suggested to be used over average annual R factor values to calculate soil loss using USLE. Furthermore, the WERM-S module can be a very useful tool to automatically calculate the spatially distributed rainfall erosivity index from 10-min interval RADAR rainfall data.

Modeling soil erosion by data-driven methods using limited input variables

Abstract Soil is one of the main elements of natural resources. Accurate estimation of soil erosion is very important in optimum soil resources development and management. Analyzing soil erosion by water on cultivated lands is an important task due to the numerous problems caused by erosion. In this study, the performance of three different data-driven approaches, e.g. multilayer perceptron artificial neural network (ANN), grid partitioning (GP), and subtractive neuro-fuzzy (NF) models were evaluated for estimating soil erosion. Land use, slope, soil and upland erosion amount were used as input parameters of the applied models and the erosion values obtained by MPSIAC method were considered as the benchmark for evaluating the ANN and NF models. The applied models were assessed using the coefficient of determination (R2), the root mean square error (RMSE), the BIAS, and the variance accounted for (VAF) indices. The results showed that the subtractive NF model presented the most accurate results with the minimum RMSE value (3.775) and GP, NF and ANN models were ranked successively.

Quantifying Soil Erosion from Hiking Trail in a Protected Natural Area in the Spanish Pyrenees

AbstractRecreational activities may impose adverse impacts on the environment of natural landscapes and protected areas owing to persistent tourist influx. Here, we use a dendrogeomorphic approach to estimate soil erosion induced by hikers at trails in the Ordesa and Monte Perdido National Park (north‐eastern Spain). For the first time, exposed roots of Pinus uncinata Ramond ex DC and Fagus sylvatica L. were used on the Iberian Peninsula to reconstruct the timing and amount of soil erosion induced by hikers based on dendrogeomorphology. In addition, we propose a new characterization of ground microtopography using a microtopographic profile gauge and validate results of this approach with 3D point clouds derived from terrestrial laser scanning. Determination of the first year of root exposure was based on the analysis of changes in roots, at both the macroscopic and tissue levels. Analysis shows that a distinctive footprint is observable at macroscopic and microscopic scales following initial exposure and thus confirms results of previous work realized with roots of other tree species (e.g. Pinus sylvestris L.). Our results also indicate that a characterization of erosion based on microtopographic profiles can replace terrestrial laser scanning measurements, which are often difficult to obtain in remote areas. Estimates of soil erosion ranged between 3·1 ± 1·5 and 8·9 ± 4·3 mm y−1 (or 52·7 ± 25·5 to 151·3 ± 73·1 t ha−1 y−1). The approach deployed here could help improve management of and access to natural protected areas and thus reduce the potentially negative impacts of recreational activities on these sensitive environments. Copyright © 2017 John Wiley &amp; Sons, Ltd.

The carbon flux of global rivers: A re-evaluation of amount and spatial patterns

Global rivers connect three large carbon reservoirs in the world: soil, atmosphere, and ocean. The amount and spatial pattern of riverine carbon flux are essential for the global carbon budget but are still not well understood. Therefore, three linear regression models for riverine DOC (dissolved organic carbon), POC (particulate organic carbon), and DIC (dissolved inorganic carbon) fluxes were established with related generating and transfer factors based on an updated global database. The three models then were applied to simulate the spatial distribution of riverine DOC, POC, and DIC fluxes and to estimate the total global riverine carbon flux. The major conclusions of this study are as follows: the correlation analysis showed that riverine DOC flux is significantly related to discharge (r2=0.93, n=109) and soil organic carbon amount (r2=0.60), POC flux increases with discharge (r2=0.55, n=98) and amount of soil erosion (r2=0.48), and DIC flux is strongly linked to CO2 consumption by rock weathering (r2=0.66, n=111) and discharge (r2=0.63). In addition, Asia exports more DOC and POC than other continents and North America exports more DIC. The Atlantic Ocean accepts the major portion of riverine DOC, POC, and DIC fluxes of all the oceans. The highest riverine DOC flux occurs in the 0–30°S zone, and the highest riverine POC and DIC fluxes appear in the 30–60°N zone. Furthermore, re-estimation revealed that global rivers export approximately 1.06PgC to oceans every year, including 0.24Pg DOC, 0.24Pg POC, 0.41Pg DIC, and 0.17Pg PIC.

125 Years of Soil and Crop Management on Sanborn Field

Long-term management systems cause changes to soil physical properties that may affect soil erosion and erodibility. A study was conducted to evaluate the effects of 125 years of continuous crop management on Sanborn Field for selected soil physical properties. Intact soil cores were collected from continuous corn (Zea mays L.), continuous wheat (Triticum aestivum L.), continuous timothy (Phleum pratense L.), and a rotation of corn–wheat–red clover (Trifolium pratense L.). Soil samples were collected from the surface horizon throughout 1 year (April, July, and November 2014 sampling dates). Aggregate stability, soil splash detachment, bulk density, and soil strength were measured. Significant differences in aggregate stability (P < 0.01), splash detachment (P < 0.01), soil shear strength (P < 0.05), and bulk density (P < 0.05) were found among the treatments. Continuous timothy had three to four times better aggregate stability and 50% to 75% less splash detachment compared with continuous wheat and corn, respectively. Lowest aggregate stability, lowest soil strength, highest bulk density, and highest soil splash detachment were found under continuous corn. Highest aggregate stability was found during July. Annual crops with tillage have a negative effect on soil quality and erodibility. Comparing results after 125 years with data collected after 105 years illustrates that properties have not changed dramatically during the past 20 years. Assessing the effects of long-term soil management on soil quality and erodibility is critical for society to determine the amount of soil erosion associated with selected soil management and to develop appropriate conservation practices to minimize this challenge and promote long-term sustainability.

Spatio-Temporal Variations of Vegetation Coverage Based on EVI: A Case Study in Tuwei River Basin

Tuwei River Basin is a sensitive region of soil erosion, which located in midstream of Yellow River. The vegetation coverage is one of the most important factors to affect the amount of soil erosion. In order to analyze the dynamic change of vegetation coverage in Tuwei River Basin from 2000 to 2013 ， MODIS Enhanced Vegetation Index (EVI) data were used to extract the series characteristics of vegetation changes. The method for reconstructing EVI time-series data set based on the Time series reconstruction Savitzky-Golay filter was application for noise reduction. Finally, we analyzed the spatial and temporal variations of the vegetation coverage in the Tuwei River Basin. The results showed that from 2000 to 2013 the total vegetation coverage had a trend of improvement and ecological conditions were getting for the better.

Soil Loss Vulnerability Assessment in the Mekong River Basin

The Mekong River plays an extremely important role in Southeast Asia. Flowing through six countries, including China, Myanmar, Thailand, Laos PDR, Cambodia, and Vietnam, it is a site of great biological and ecological diversity and the habitat of numerous species of fish. It also supports a very large population that lives along the river basin. Therefore, much attention has been focused on the giant Mekong River Basin, particularly, its soil erosion and sedimentation problems. In fact, many methods have been used to calculate and simulate these problems. However, in the case of the Mekong River Basin, the available data is limited because of the extreme size of the area (about 795,000 ㎢) and lack of equipment systems in the countries through which the Mekong River flows. In this study, we applied the Universal Soil Loss Equation (USLE) model in a GIS (Geographic Information System) framework to calculate the amount of soil erosion and sediment load during the selected period, from 1951 to 2007. The result points out dangerous areas, such as the Upper Mekong River Basin and 3S Basin (containing the Sekong, Sesan, and Srepok Rivers) that are suffering the serious consequences of soil erosion problems. Moreover, the present model is also useful for supporting river basin management in the implementation of sustainable management practices in the Mekong River Basin and other basins.

Characteristics of Suspended Sediment Loadings under Asian Summer Monsoon Climate Using the Hydrological Simulation Program-FORTRAN

The extreme variation in the amount of annual precipitation and rainfall during single events is typical of the East Asian monsoon climate and may greatly influence the characteristics of the suspended sediment load. The turbidity in Lake Imha which is the eighth largest multipurpose dam in Korea has been the cause of major water quality problems for use as drinking water. The turbidity rose to 882 NTU, and it remained over 30 NTU continuously for 170 days during 2002, as the result of significant amounts of soil erosion from the watershed during the Asian monsoon typhoon. In this study, characteristics of suspended sediment loadings under the Asian summer monsoon climate was investigated by comparing the variation of yearly suspended sediment loads and the ratio of maximum suspended sediment loads in a single event to yearly suspended sediment load from Lake Imha watershed using the Hydrologic Simulation Program-FORTRAN (HSPF). The model calibration is performed according to the 2009–2010 events, and simulation results characterized suspended sediment loadings under the Asian summer monsoon climate for 2001–2010. Water sampling and flow rate measurements were performed every 4–6 h, and calibration was performed using hourly simulated sediment loads. The calibration results demonstrated good agreement with the observed data. The characteristics of suspended sediment loadings under the Asian summer monsoon climate are a high variance of the yearly suspended sediment load and a significant of amount of suspended sediment load during a single event influenced by the typhoon intensity. The maximum yearly suspended sediment load was 10 times higher than the minimum yearly value. About half of the yearly suspended sediment load was loaded with a single event under the Asian summer monsoon climate and the ratio of suspended sediment loads by a single event to total yearly loads ranged from 29% to 90%. Structural best management practices (BMPs) to trap suspended sediment in stormwater such as stormwater ponds or wetlands rely on much more storage volume or area and non-structural BMPs to minimize soil erosion by source control such as mulching or revegetation in disturbed areas, which are important BMPs, especially in the Asian summer monsoon region.

Soil organic carbon losses by water erosion in a Mediterranean watershed

Soil organic carbon (SOC) is one of the primary elements required in the functioning of ecosystems. Soil erosion, a major mechanism of land degradation, removes SOC and transfers it to the hydrosphere or the atmosphere, thereby affecting key ecosystem functions and services. The Mediterranean region is highly susceptible to land degradation because of erosion due to heavy rains following long, dry, hot summers. Although the Mediterranean landscape typically has a high altitude and incline, the soil is brittle and soft and is easily washed away by rain. Thus, vast regions in Turkey have been afflicted by this type of soil degradation. This study aimed to (1) estimate the temporal distribution of water erosion in the Seyhan River Basin, (2) assess the spatial distribution of SOC and (3) estimate the depletion of SOC through soil erosion using the Pan-European Soil Erosion Risk Assessment model, a physically based, regionally scaled soil erosion model. The annual amount of soil eroded from the Seyhan River Basin is estimated to be 7.8million tonnes per hectare (tha–1year–1). The amount of fertile soil loss from agricultural areas is ~1.2million tonnes per year. The maximum amount of soil erosion occurs in maintenance scrubland and degraded forest areas, contributing to 68% of erosion, followed by that in agricultural land, contributing to 27% of erosion, with the remaining in forests and urban areas.

Sediment Yield Deduction from Check–dams Deposition in the Weathered Sandstone Watershed on the North Loess Plateau, China

AbstractAs the basic unit of erosion and sediment yield, it was critical to determine the amount of soil erosion and sediment yield in the small watersheds for sustaining a reasonable water resource and sediment regulation system. In this study, we determined the sediment yield from the dams‐controlled watershed on the North Loess Plateau. Three check dams in the watershed were investigated by drilling ten‐hole sedimentation cores. The corresponding flood couplets were dated according to thickness of deposition layers, distribution of sediment particle size and historical erosive rainfall events. On the basis of the check dams capacity curve, the soil bulk density and the thickness of couplets, the deposit mass of check dams, and then the sediment yield of watershed at different temporal and spatial scale were deducted. In total of the 33, 60 and 55 couplets were corresponded to individual flood events in the dam MH1# from 1976 to 1984, the dam MH2# from 1985 to 2007, and the dam MH4# from 1981 to 2009, respectively. The specific sediment yield for flood events was 1,188.5–11,527.9 Mg km−2, 1,278.6–17,136.7 Mg km−2, and 3,395.9–33,698.5 Mg km−2, and the annual average sediment yield was 10,728.6 Mg (km2 · a)−1, 12,662.9 Mg (km2 · a)−1, and 16,753.3 Mg (km2 · a)−1 in dam MH1#, MH2# and MH4# controlled watershed, respectively. The sediment yields were inversely proportional to the dams – controlled areas. For the whole watershed, the annual average sediment yield was 14,011.1 Mg (km2 · a)−1 from 1976 to 2009. There were large amounts of sediments (42.3–50.5%) were intercepted gradually along the way from small watersheds to the river channel. And the minimum rainfall for sediment deposited in the dams was greater than 20 mm in this watershed. The results of this study suggested that the sediments retained behind check dams were helpful to quantifying the amount of erosion sediment yield and understanding the soil erosion evolution in the small and ungauged watersheds. Copyright © 2016 John Wiley &amp; Sons, Ltd.

The influences of row grade, ridge height and field slope on the seepage hydraulics of row sideslopes in contour ridge systems

Seepage plays an important role in soil erosion in contour ridge systems. Seepage generated from subsurface flow causes hillslope instability by reducing the soil shear strength and mobilizing soil particles and can produce cave-like features called seepage undercuts that can lead to contour failure. As the main threat to contour plowing, seepage results in large amounts of soil erosion due to row grade. Models used to predict seepage over a time series will provide a basis for modeling soil erosion resulting from seepage in contour ridging systems. Understanding seepage and its effects will advance our knowledge regarding seepage erosion mechanisms in contour ridge systems. In this study, 23 treatments were arranged using an orthogonal rotatable central composite design to model a seepage time series, build a simple seepage prediction model and investigate the effects of row grade, field slope and ridge height on seepage discharge.Most of the seepage discharge time series followed an S-shaped curve. The seepage discharge processes were fit by an exponential model with a determination coefficients (R2) greater than 0.995. Furthermore, the physical meaning of the exponential model was consistent with the experimental results. The seepage discharge continuously increased before the inflection point and then decreased. Finally, the seepage discharge approached a steady value. The maximum seepage discharge growth rate was achieved within 14 min, and the seepage discharge became steady within 106 min. Second-order polynomial regression models were used to determine the total and predicted steady seepage discharge using independent variables of row grade, field slope and ridge height, which produced R2 values of 0.66 (p < 0.05) and 0.68 (p < 0.05), respectively. Ridge height and row grade significantly affected (p < 0.05) the total and predicted steady seepage discharge. Field slope (and its related factors) was ignored because it had no significant effects on seepage discharge. The effects of row grade resulted in a concave curve with an increasing factor value, and ridge height exerted a positive linear effect on seepage discharge.

Trade-offs among ecosystem services in a typical Karst watershed, SW China

Nowadays, most research results on ecosystem services in Karst areas are limited to a single function of an ecosystem service. Few scholars conduct a comparative study on the mutual relationships among ecosystem services, let alone reveal the trade-off and synergic relationships in typical Karst watershed. This research aims to understand and quantitatively evaluate the relationships among ecosystem services in a typical Karst watershed, broaden the depth and width of trade-off and synergic relationships in ecosystem services and explore a set of technical processes involved in these relationships. With the Shibantang Karst watershed in China as the research site, we explore the trade-off and synergic relationships of net primary productivity (NPP), water yield, and sediment yield by coupling Soil and Water Assessment Tool (SWAT) and Carnegie–Ames–Stanford Approach (CASA), and simulating and evaluating these three ecosystem services between 2000 and 2010. Results of this study are as follows. (1) The annual average water yield decreased from 528mm in 2000 to 513mm in 2010, decreasing by 2.84%. (2) The annual average sediment yield decreased from 26.15t/ha in 2000 to 23.81t/ha in 2010, with an average annual reduction of 0.23t/ha. (3) The annual average NPP increased from 739.38gCm−2a−1 in 2000 to 746.25gCm−2a−1 in 2010, increasing by 6.87gCm−2a−1 . (4) Water yield and sediment yield are in a synergic relationship. The increase of water yield can accumulate the soil erosion amount. NPP is in a trade-off relationship with water yield and sediment yield. The improvement of NPP is good for decreasing water yield and soil erosion amount and increasing soil conservation amount. This study provides policy makers and planners an approach to develop an integrated model, as well as design mapping and monitoring protocols for land use change and ecosystem service assessments.

Characteristics of the surface–subsurface flow generation and sediment yield to the rainfall regime and land-cover by long-term in-situ observation in the red soil region, Southern China

Land cover and rainfall regime are two important factors that affect soil erosion. In this paper, three land cover types – grass cover, litter cover and bare land – were employed to analyze surface runoff, subsurface flow and sediment loss processes in relation to the rainfall regimes in the red soil region of China. Five rainfall regimes were classified according to 393 rainfall events via a k-means clustering method based on the rainfall depth, duration and maximum 30-min intensity. The highest surface runoff coefficient and erosion amount were found on bare land in all five rainfall regimes, and the lowest were found on grass cover. The litter cover generated the highest subsurface flow rate, followed by the grass cover; the lowest was on bare land. For grass cover and litter cover plots, rainfall events of rainfall regime IV which had the longest duration, greatest depth and lowest intensity had the highest surface runoff coefficient, soil erosion amount and subsurface flow rate. For bare land, storm rainfall events of rainfall regime V had the highest intensity, lowest depth and duration, had the highest surface runoff coefficient and soil erosion amount, but the lowest subsurface flow rate. The highest subsurface flow rate of bare land happened in rainfall regime IV. Surface cover was urgently needed to reduce soil erosion. When the lands under dense surface cover, more attention should be paid to rainfall events that of long duration, high depth but low in intensity which commonly occurred in spring. The interactions of surface–subsurface flow and its effects on soil erosion and nutrient loss were worth considering in the red soil region.

Fractal features of soil particle size distribution in layered sediments behind two check dams: Implications for the Loess Plateau, China

The layered sediment deposited behind a check dam can provide useful information about soil erosion processes in the dam-controlled area. This study aims to evaluate the possible fractal nature of layered sediments behind check dams, assessing whether fractal dimension can serve as a feasible index for evaluating the impact of land use types on the area controlled by the check dam. Fractal dimension measurement was employed to analyze the features of soil particle size distribution (PSD) for different layered sediments of the Shipanmao and Zhangshan check dams in the Dalihe River Basin of the Loess Plateau, China. Results show that the predominant soil particle sizes of the sediment layers behind the Shipanmao and Zhangshan dams are silt–clay (<0.05mm) and fine sand (0.25–0.05mm). The overall gradients of the trends for silt–clay and fine sand are 0.0622 (slight increase) and −0.0618 (slight decrease), respectively, for Shipanmao, and −0.8415 (decrease) and 0.8448 (increase), respectively, for Zhangshan. There are considerable differences in the PSDs among different layers, especially in the coarse and fine sand fractions. The coefficient of variation (CV) for the coarse sand fraction is highest, followed by the fine sand and the silt–clay size fractions. Larger soil particle sizes coincide with larger CV values. The fractal dimension (Dm) of the PSD ranges from 2.111 to 2.219, and 2.144 to 2.447 for Shipanmao and Zhangshan, respectively. The Dm values tend to increase and decrease for the layered sediments from top to bottom with some turning points. The turning points of Dm are related to the trends of the soil PSDs in the adjacent sediment layers. Although Dm has significant positive and negative correlations with the silt–clay and the fine sand size fractions, respectively, no correlation with the coarse sand fraction was observed. Soil PSD is a more dominant factor affecting Dm than the time lag between soil erosion and sediment deposition. Overall, Dm decreased for Shipanmao during the deposition period (1972–1979). The total increment of the C factor in the universal soil loss equation and the soil erosion amount per rainfall erosivity were applied to analyze land use changes between 1972 and 1979 for the dam-controlled area of the Shipanmao dam. The total increment of C during 1972–1979 was 0.021 and the soil erosion amount per rainfall erosivity was smaller in 1972 than in 1979, indicating desertification in the dam-controlled area. In addition, the land use types prevalent in 1979 were more prone to soil loss than those in 1972. Dm is a useful parameter to assess land use types and soil degradation processes in dam-controlled areas of the Loess Plateau.

Digital close range photogrammetry for the study of rill development at flume scale

Soil erosion is a continuous process of detachment, transportation, and deposition of soil particles. Obtaining accurate descriptions of soil surface topography is crucial for quantifying changes to the soil surface during erosion processes. The objective of this study was to develop an improved close-range photogrammetric technique to assess soil erosion under rainfall conditions. Based on high overlapping image acquisition, digital point cloud matching, digital elevation model (DEM) generation and soil erosion calculation, a digital close-range photogrammetric observation system was explored and established. The results showed that the established digital photogrammetric observation system could accurately calculate the digital point cloud from the underlying surface with a 2min time interval and a 1.5mm spatial resolution. In addition, based on the DEM generated from digital point clouds, the amount of soil erosion in different topographic positions within various time periods was calculated. The digital photogrammetric observation methods explored in our study provide a reliable way to monitor soil erosion processes, especially under rainfall conditions. This approach can accurately resolve the evolution of the underlying surface soil erosion, which is of great importance in understanding soil erosion mechanisms.

The cover-management factor (C) on woodlands of the hilly areas of the Loess Plateau in North China

Soil erosion is one of most serious environmental andproduction problems on the Loess Plateau in China. The objectivesof this study were to quantify the influence of forest vegetation onsoil erosion on slope areas in the Loess Plateau. This was made byusing the subfactor method to calculate the vegetation cover managementfactor (C) of the Universal Soil Loss Equation (USLE).Proper local subfactor parameter values were obtained to offer atheoretical basis and practical guidance for studying the relationshipbetween vegetation and soil erosion on the Loess Plateau. Three subfactorsincluding prior land use (PLU), canopy cover (CC), surfacecover (SC), surface Roughness (SR), soil moisture (SM), and covermanagementfactor (C) were observed at three plant growth stages:initial, blooming and end of growing season. All observations andmeasurements were made on 13 runoff plots in the Caijiachuan Watershed.The annual runoff sediment volume, and the subfactor andindirect methods were adopted separately to calculate the vegetationcover and management factor C of each stand, and then carry outcomparative tests and comprehensive analyses. The results showedthat the cover-management factor (C) calculated by the subfactorand indirect methods were in good agreement. The order reflectedwas forest SC>SR>SM>CC. This indicatedthat plant roots, soil organisms in the surface soil layers andsurface cover had a larger impact on soil loss fate than the other subfactors.Stand density was negatively correlated with vegetation coverand management factor C, suggesting that only stand density influencedsoil erosion. The stand density of Robinia pseudoacacia rangedfrom 1200 to 2204 stems/ha. Management factor C ranged from0.020 to 0.037. The subfactor method could be adopted to monitor the amount of soil erosion in the Loess Plateau, with the parametersbeing Cb=0.951, Cur=0.004513kg/(ha.cm), Cus=0.001887kg/(ha.cm), Cuf=0.5, b=0.025. The vegetation cover and management factorC of different stands in the Loess Plateau varied between 0.009 and0.062.

Soil Erosion Hazard Mapping in Central Zab Basin Using Epm Model in GIS Environment

Soil losses and erosion are the primary concerns that decrease soil fertility, deposition materials in waterways, flooding, environmental pollution, and declining dam capacity. The aim of this study is zonation of soil erosion hazard and sediment yield in central Zab basin in southwest of West-Azerbaijan province in Iran. The Sardasht dam construction is established on its main branches that estimate amount of soil erosion and sedimentation of behind the dam is necessary. Hence EPM model have been used to soil erosion hazard mapping using series of GIS data, Landsat ETM+ satellite images, aerial photos in GIS environment. Required layers information was used in this research including slope, aspect, lithology, soil, land use, rainfall, and river erosion. Hence, GIS databases and their weighting of each map layers were extracted according to the hydrologic units. Also, GIS database was prepared based on EPM model to extract of erosion and sedimentation maps The obtained result using EPM model showed that south and southwest parts of central Zab basin near the Sardasht Dam construction are very highly eroded due to their soil erosion and lithology while the northern parts of case study are moderately eroded because of the intensive land cover.