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An updated isoerodent map of the conterminous United States

International Soil and Water Conservation Research 2022年第1期10卷 1-16页

作者： Ryan P.McGehee Dennis C.Flanagan Puneet Srivastava Bernard A.Engel Chi-Hua Huang Mark A.Nearing Purdue University Agricultural and Biological Engineering225 South University StreetWest LafayetteIN47907USA United States Department of Agriculture-Agricultural Research Service National Soil Erosion Research Laboratory275 S Russell StWest LafayetteIN47907USA University of Maryland Agricultural Experiment StationSymons Hall7998 Regents DriveCollege ParkMD20742-3131USA Purdue University Agricultural Administration Building615 West State StreetWest LafayetteIN47907-2053USAUnited States Department of Agriculture-Agricultural Research ServiceNational Soil Erosion Research Laboratory275 S Russell StWest LafayetteIN47907USA United States Department of Agriculture-Agricultural Research Service Southwest Watershed Research Center2000 E Allen RdTucsonAZ85719USA

Maps of erosivity,which are also commonly referred to as isoerodent maps,have played a critical role in soil conservation efforts in the United States and around the world.Currently available erosivity maps for the United States are either outdated,conflict with erosivity benchmarking studies,or utilized less advanced spatial mapping methods.Furthermore,it is possible that the same underlying issues with US maps are impacting global maps as well.In this study,we used more than 340015-min,fixed-interval precipitation gauges to update the isoerodent map of the conterminous United States.Erosivity values were interpolated using universal kriging under several spatial model configurations and resolutions.The optimal spatial model was selected based on which result had the lowest sample variogram error.Rainfall,erosivity,and erosivity density maps were compared to existing products.Some average annual and annual erosivity results were compared to high-quality erosivity benchmarking publications.Erosivity values from both Rusle2 and Panagos et al.(2017)were generally lower in the eastern United States and mixed in the western United States compared to our results.Topographic effects resulted in much greater erosivity differences in this study as compared to prior maps.Benchmark comparisons revealed that erosivity maps from this study and others were lower than the benchmark by 14%or more(up to 38%).These findings suggest current practices of storm omission and intensity dampening correction need to be revisited,especially in locations with relatively low-to-moderate rainfall erosivity such as the Midwest or Northeast United States,for example.

关键词： Erosion index Erosivity United States usle Rusle2 Soil loss

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Assessment of Soil Erosion and Sediment Yield in Liao Watershed, Jiangxi Province, China, Using usle, GIS, and RS

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Journal of Earth Science 2010年第6期21卷 941-953页

作者：李辉陈晓玲 Kyoung Jae Lim 蔡晓斌 Myung Sagong Faulty of Earth Sciences China University of Geosciences Three Gorges Research Center for Geo-hazard Ministry of Education China University of Geosciences The Key Lab of Poyang Lake Ecological Environment and Resource Development Jiangxi Normal University State Key Laboratory for Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Department of Agricultural Engineering Kangwon National University Institute of Geodesy and Geophysics Chinese Academy of Sciences Track & Civil Engineering Research Department Korea Railroad Research Institute

Soil erosion by water is a serious problem all over the world. In China, about 1 790 000 km2 of land suffers from water erosion, which accounts for 18.3% of China＇s total area. This study was conducted in the Liao （潦） watershed in Jiangxi （江西） Province to assess annual soil erosion and sediment yield using the Universal Soil Loss Equation （usle）. A geographic information system （GIS） was used to generate maps of the usle factors, which include rainfall erosivity （R）, soil erodibility （K）,slope length and steepness （LS）, cover （C）, and conservation practice （P） factors. By integrating these factors in a GIS, a spatial distribution of soil erosion over the Liao watershed was obtained. The soil erosion was found to vary from nil for flat and well-covered areas to more than 500 t/ha/a in mountainous places with sparse vegetation. The average soil erosion is 18.2 t/ha/a with a standard deviation of 109.3 t/ha/a. The spatial distribution of erosion classes was estimated. About 39.5% of the watershed is under the tolerant erosion rate, and 60.5% of the study area experienced erosion to different extents. A spatially distributed sediment delivery ratio （SDR） module was developed to account for soil erosion and deposition. It was found that the SDR value at the outlet of the Liao watershed was 0.206, and the sediment yield was 1.32 million t/a, which was 20% higher than the measured sediment. The results can be used to identify the soil erosion hot spots and develop the best soil erosion management practices and help estimate the quantity of soil that was transported into the downstream Poyang （鄱阳） Lake.

关键词： soil erosion usle GIS sediment delivery ratio.

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Effect of time resolution of rainfall measurements on the erosivity factor in the usle in China

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International Soil and Water Conservation Research 2020年第4期8卷 373-382页

作者： Tianyu Yue Yun Xie Shuiqing Yin Bofu Yu Chiyuan Miao Wenting Wang State Key Laboratory of Earth Surface Processes and Resource Ecology Faculty of Geographical ScienceBeijing Normal University100875BeijingChina Australian Rivers Institute School of Engineering and Built Environment Griffith UniversityNathanQueenslandAustralia

Rainfall erosivity,one of the factors in the Universal Soil Loss Equation.quantifies the effect of rainfall and runoffon soil erosion.High-resolution data are required to compute rainfall erosivity,but are not widely available in many parts of the world.As the temporal resolution of rainfall measurement decreases,computed rainfall erosivity decreases.The objective of the paper is to derive a series of conversion factors as a function of the time interval to compute rainfall erosivity so that the R factor computed using data at different time intervals could be converted to that computed using 1-min data.Rainfall data at 1-min intervals from 62 stations over China were collected to first compute the~ue'R factor values.Underestimation of the R factor was systematically evaluated using data aggregated at 5,6.10,15,20,30,and 60-min to develop conversion factors for the R factor and the 1-in-10-year storm EI30 values.Compared with true values,the relative error in R factor using data at fixed intervals of≤10min was10%using 15-min data for 66.1%of stations and>20%using 30-min data for 61.3%of stations.The conversion factors for the R factor,ranging from 1.051 to 1.871 for 5 to 60-min data,are higher than those for the 1-in-10-years storm EI30,ranging from 1.034 to 1.489 for the 62stations.

关键词： Soil erosion Rainfall erosivity 1-in-10-year EI30 usle CSLE

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Integrated universal soil loss equation (usle) and Geographical Information System (GIS) for soil erosion estimation in A Sap basin:Central Vietnam

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International Soil and Water Conservation Research 2018年第2期6卷 99-110页

作者： Tung Gia Pham Jan Degener Martin Kappas Cartography GIS and Remote Sensing DepartmentGottingen UniversityGermany University of Agriculture and Forestry Hue UniversityVietnam

Central Vietnam is very susceptible to soil erosion due to its complicated terrain and heavy rainfall. The objective of this study was to quantify soil erosion in the A Sap river basin, A Luoi district, Thua Thien Hue Province, Vietnam, using the Universal Soil Loss Equation (usle) and Geographical Informa-tion System (GIS). The results showed that 34% of land area lost accumulated to 10 t ha-1 year-1 while 47% of the total area lost less than 1 t ha-1 year-1. Natural forest land lost the most with an average of about 19 t ha-1 year-1, followed by plantation forest with approximately 7 t ha-1 year-1 and other agricultural lands at 3.70 and 1.45 t ha-1 year-1 for yearly crops and paddy rice, respectively. Soil erosion was most sensitive to the topographic factor (LS), followed by the practice support factor (P), soil erodibility factor (K), cropping management (C), and the rainfall erosivity factor (R). Implications are that changes to the cultivated calendar and implementing intercropping are effective ways to prevent soil erosion in cultivated lands. Furthermore, introducing broad leaves trees for mountainous areas in A Sap basin was the most effective practice in reducing soil erosion. The study also pointed out that the combination of available data sources used with the usle and GIS technology is a viable option to cal-culate soil erosion in Central Vietnam, which would allow targeted attention toward a solution is to reduce future soil erosion.

关键词： Central Vietnam GIS Soil erosion usle

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Impacts of horizontal resolution and downscaling on the usle LS factor for different terrains

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International Soil and Water Conservation Research 2020年第4期8卷 363-372页

作者： Chunmei Wang Linxin Shan Xin Liu Qinke Yang Richard M.Cruse Baoyuan Liu Rui Li Hongming Zhang Guowei Pang Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity Northwest UniversityXi'an710127PR China College of Urban and Environmental Sciences Northwest UniversityXi'an710127PR China Key Laboratory of National Forestry Administration on Ecological Hydrology and Disaster Prevention in Arid Regions Xi'an University of TechnologyXi'an 710048PR China Department of Agronomy Iowa State UniversityAmesIA50011USA Xi'an Institute of Prospecting and Mapping Xi'an710054PRChina Faculty of Geographical Science Beijing Normal UniversityBeijing100875PR China State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau Institute of Soil and Water ConservationNorthwest A&F UniversityYangling712100ShaanxiPR China College of Information Engineering Northwest A&F UniversityYanglingShaanxi712100China

Slope length and slope steepness are critical topographic factors(L and S)in the Universal Soil Loss Equation(usle)and Chinese Soil Loss Equation(CSLE)for soil erosion modelling.Both slope length and slope gradient are potentially sensitive to spatial resolution when calculated in a GIS framework.The resolution effect on the LS factor and approaches suitable for improving the LS factor at a coarse resolution have not been well identified.To address this problem,the LS factor at 5-m and 30-m resolution in twenty-four watersheds with various terrains was estimated.And a downscale model based on matching of the lower resolution LS cumulative frequency curves to a higher resolution("Histogram Matching"method)was tested for its potential to improve LS factor estimation accuracy.In the larger relief mountainous area,compared to 5-m resolution,the 30-m resolution generated LS was generally overestimated by more than 20%and in lower relief areas underestimated by more than 15%.This bias is less than 10%in medium relief areas.The downscale model improved LS factor estimates compared to the 30-m resolution estimate by more than 10%when comparing frequency distribution curves and more than 20%in mean values in larger relief areas.The downscale model worked well in all regions except for the low relief areas,which intuitively are the low soil erosion potential areas.The results of this research help quantify the uncertainty in soil erosion estimates and may ultimately help to improve the assessment of soil erosion through its impact on LS factor estimates,especially at regional and global scales.

关键词： LS factor SRTM Resolution Downscale usle

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Modelling monthly soil losses and sediment yields in Cyprus

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International Journal of Digital Earth 2016年第8期9卷 766-787页

作者： Christos G.Karydas Panos Panagos School of Agriculture Forestry and Natural Environment Aristotle University of ThessalonikiThessalonikiGreece European Commission Joint Research CentreInstitute of Environment and SustainabilityIspraVAItaly

The aim of this study was to map soil erosion on the Mediterranean island of Cyprus.The G2 model,an empirical model for month-time step erosion assessments,was used.Soil losses in Cyprus were mapped at a 100 m cell size,while sediment yields at a sub-basin scale of 0.62 km^(2) mean size.The results indicated a mean annual erosion rate of 11.75 t ha^(−1)y−^(1),with October and November being the most erosive months.The 34%of the island’s surface was found to exceed non-sustainable erosion rates(>10 t ha^(−1)y−^(1)),with sclerophyllous vegetation,coniferous forests,and non-irrigated arable land being the most extensive non-sustainable erosive land covers.The mean sediment delivery ratio(SDR)was found to be 0.26,while the mean annual specific sediment yield(SSY)value for Cyprus was found to be 3.32 t ha^(−1)y−^(1).The annual sediment yield of the entire island was found to be 2.746 Mt y−1.This study was the first to provide complete and detailed erosion figures for Cyprus at a country scale.The geodatabase and all information records of the study are available at the European Soil Data Centre(ESDAC)of the Joint Research Centre(JRC).

关键词： Soil erosion G2 model usle Gavrilovic digital earth

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Prediction of spatial soil loss impacted by long-term land-use/land-cover change in a tropical watershed

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Geoscience Frontiers 2019年第2期10卷 389-403页

作者： J.H.Abdulkareem B.Pradhan W.N.A.Sulaiman N.R.Jamil Department of Environmental Science Faculty of Environmental StudiesUniversiti Putra Malaysia (UPM) Department of Soil Science Institute for Agricultural Research/Faculty of AgricultureAhmadu Bello University Department of Civil Engineering Faculty of EngineeringGeospatial Information Science Research Center (GISRC)Universiti Putra Malaysia (UPM) Centre for Advanced Modeling and Geospatial Information Systems (CAMGIS) Faculty of Engineering and Information TechnologyUniversity of Technology Sydney Department of Energy and Mineral Resources Engineering Choongmu-gwanSejong University

The devastating effect of soil erosion is one of the major sources of land degradation that affects human lives in many ways which occur mainly due to deforestation, poor agricultural practices, overgrazing,wildfire and urbanization. Soil erosion often leads to soil truncation, loss of fertility, slope instability, etc.which causes irreversible effects on the poorly renewable soil resource. In view of this, a study was conducted in Kelantan River basin to predict soil loss as influenced by long-term land use/land-cover(LULC) changes in the area. The study was conducted with the aim of predicting and assessing soil erosion as it is influenced by long-term LULC changes. The 13,100 km^2 watershed was delineated into four sub-catchments Galas, Pergau, Lebir and Nenggiri for precise result estimation and ease of execution. GIS-based Universal Soil Loss Equation(usle) model was used to predict soil loss in this study. The model inputs used for the temporal and spatial calculation of soil erosion include rainfall erosivity factor,topographic factor, land cover and management factor as well as erodibility factor. The results showed that 67.54% of soil loss is located under low erosion potential(reversible soil loss) or 0-1 t ha^(-1) yr^(-1) soil loss in Galas, 59.17% in Pergau, 53.32% in Lebir and 56.76% in Nenggiri all under the 2013 LULC condition.Results from the correlation of soil erosion rates with LULC changes indicated that cleared land in all the four catchments and under all LULC conditions(1984-2013) appears to be the dominant with the highest erosion losses. Similarly, grassland and forest were also observed to regulate erosion rates in the area. This is because the vegetation cover provided by these LULC types protects the soil from direct impact of rain drops which invariably reduce soil loss to the barest minimum. Overall, it was concluded that the results have shown the significance of LULC in the control of erosion. Maps generated from the study may be useful to planners and land use managers to take app

关键词： Soil erosion usle Landuse/cover changes GIS Malaysia

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Estimating rainfall erosivity by incorporating seasonal variations in parameters into the Richardson model

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Journal of Geographical Sciences 2017年第3期27卷 275-296页

作者： WANG Yousheng TAN Shi LIU Baoyuan YANG Yang State Key Laboratory of Earth Surface Processes and Resources Ecology Beijing Normal University Beijing 100875 China State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin China Institute of Water Resources and Hydropower Research Beijing 100048 China College of Education Science Hunan First Normal University Changsha 410205 China

Rainfall erosivity is an important climatic factor for predicting soil loss. Through the application of high-resolution pluviograph data at 5 stations in Huangshan City, Anhui Prov- ince, China, we analyzed the performance of a modified Richardson model that incorporated the seasonal variations in parameters α andβ. The results showed that （1） moderate to high seasonality was presented in the distribution of erosive rainfall, and the seasonality of rainfall erosivity was even stronger; （2） seasonal variations were demonstrated in both parameters α and β of the Richardson model; and （3） incorporating and coordinating the seasonality of parameters αandβgreatly improved the predictions at the monthly scale. This newly modi- fied model is therefore highly recommended when monthly rainfall erosivity is required, such as, in planning soil and water conservation practices and calculating the cover-management factor in the Universal Soil Loss Equation （usle） and Revised Universal Soil Loss Equation （Rusle）.

关键词： seasonal rainfall erosivity Richardson model cover-management factor usle Rusle

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Hydrology and Estimation of Real Erosion in the Patria Nueva Micro-Basin for Five Return Periods

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Journal of Water Resource and Protection 2022年第12期14卷 783-789页

作者： Martín Mundo-Molina José Luis Pérez-Díaz Investigation Centre Faculty of Engineer Autonomous University of Chiapas Chiapas Mexico

This paper will discuss the actual erosion estimation of the Patria Nueva micro basin in tons/ha/year (E), located in Tuxtla Gutiérrez Chiapas, Mexico. We used the universal soil loss equation (usle), considered one of the best theoretical tools for planning and soil preservation in the USA and other countries. The actual erosion rates were estimated for 5, 20, 50, 100, and 500 years return periods (Rp), with elevated results due to high degrees of anthropogenic alteration of the micro-basin, especially in the last 50 years. High erosion rates generate the following problems: loss of soil, which is unfavorable for plant life, due to the soil being a non-renewable resource, the undermine can never renovate, the hydraulic area in the main channel reduces during the rainy season (when the river overflows). The sediment accumulates at the lower part of the micro-basin along with waste, garbage, and mud.

关键词： Erosion Return Periods Basins usle Sediment

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Use of ^(137)Cs and ^(210)Pb_(ex) fallout radionuclides for spatial soil erosion and redistribution assessment on steeply sloping agricultural highlands

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Journal of Mountain Science 2021年第11期18卷 2888-2899页

作者： Jung-Hwan YOON Young-Nam KIM Kye-Hoon KIM M.B.KIRKHAM Hyuck Soo KIM Jae E.YANG Kangwon Institute of Inclusive Technology Kangwon National UniversityChuncheon 24341Republic of Korea Department of Biological Environment Kangwon National UniversityChuncheon 24341Republic of Korea Institute of Agriculture and Life Science Gyeongsang National UniversityJinju 52828Republic of Korea Department of Environmental Horticulture University of SeoulSeoul 02504Republic of Korea Department of Agronomy Kansas State UniversityManhattanKS 66506-0110USA

The steeply sloping agricultural highlands in Korea have severe soil erosion.Estimation of both soil erosion and sedimentation in these highlands is necessary to make plans for soil-conservation measures,but it is not feasible using existing soil-erosion models.This study measured the site-specific concentrations of ^(137)Cs and ^(210)Pb_(ex) on both a highland slope(33%slope)and a reference site(undisturbed flat area)to estimate soil erosion and redistribution.The use of the fallout radionuclide(FRN)method was evaluated to see if it is a suitable method for characterizing soil erosion.Results were compared with those obtained with the Universal Soil Loss Equation(usle),which is an empirical model that estimates annual soil erosion.The average concentrations of ^(137)Cs and ^(210)Pb_(ex) at the reference site were 11.57±0.24 Bq kg^(-1) and 59.74±4.2 Bq kg^(-1),respectively.Concentrations of ^(137)Cs and ^(210)Pb_(ex) in the experimental slope were 16.4%and 10.8%,respectively,of those at the reference site.Radionuclide inventories were lower at the upper point of the slope than those at the basal point of the slope.Concentrations of ^(137)Cs and ^(210)Pb_(ex) were significantly correlated with available phosphorus,organic matter,CEC,and exchangeable cations.Estimation of soil redistribution rate using ^(137)Cs and ^(210)Pb_(ex) showed site-specific variations at different points along the slope,and respective ranges were^(-1)7.46~-207.51 and 1.55~-581.38 Mgha^(-1) yr^(-1),which indicated that more erosion was assessed by ^(210)Pb_(ex) than by ^(137)Cs.Redistribution analysis showed that soil erosion occurred along the entire slope,except for the bottom point of the slope where 1.55 Mgha^(-1) yr^(-1) of sediment accumulated.The usle provided a single value of the average annual soil loss in the entire slope,which was either 166 or 398 Mgha^(-1) yr^(-1),depending on the soil erodibility factor(soil series factor and calculated factor from soil sample analysis)used in the model.We conclude that the FRN method using ^

关键词： Soil erosion Steep highland Fallout radionuclide ^(137)Cs ^(210)Pb_(ex) usle

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