999 resultados para Erosion risk
Resumo:
This study evaluated the genetic erosion risk factors and the strategic points for the conservation of Lychnophora ericoides population in “Paraíso Perdido” farm, Serra da Canastra (20° 37’ 54” S; 46° 19’ 37” W; 833 m height) in São João Batista do Glória City, Minas Gerais State, Brazil. The number of young and adult plants, the soil and the phenology were evaluated in two sample areas of 125 m2. Information about the species utilization was obtained with local informants. Data on the region were obtained through literature review, in loco evaluation, GPS and geo-referenced map. In addition, local use of the plant for mixtures of drug was evaluated. According to the results obtained, the soil of the population is lithic with a weathered portion of frank-sandy texture, very acidic and dystrophic. The population density is 0.16 individuals/m2, 0.078 young/adult plant. The predominant phenophase was fruiting (100% plants) followed by flowering (21.62% plants). The local community uses the leaves of the plant in the form of hydroalcoholic extracts, as anti-inflammatory. Based on the evaluated parameters, the population is at 73% risk of genetic erosion. The detected key points were the development of activities including the participation of the local community for habitat protection as well as germplasm collection, seedlings production and reintroduction, together with environmental education, supervision, and reduction in the propensity for fire.
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Soil erosion models and soil erosion risk maps are often used as indicators to assess potential soil erosion in order to assist policy decisions. This paper shows the scientific basis of the soil erosion risk map of Switzerland and its application in policy and practice. Linking a USLE/RUSLE-based model approach (AVErosion) founded on multiple flow algorithms and the unit contributing area concept with an extremely precise and high-resolution digital terrain model (2 m × 2 m grid) using GIS allows for a realistic assessment of the potential soil erosion risk, on single plots, i.e. uniform and comprehensive for the agricultural area of Switzerland (862,579 ha in the valley area and the lower mountain regions). The national or small-scale soil erosion prognosis has thus reached a level heretofore possible only in smaller catchment areas or single plots. Validation was carried out using soil loss data from soil erosion damage mappings in the field from long-term monitoring in different test areas. 45% of the evaluated agricultural area of Switzerland was classified as low potential erosion risk, 12% as moderate potential erosion risk, and 43% as high potential erosion risk. However, many of the areas classified as high potential erosion risk are located at the transition from valley to mountain zone, where many areas are used as permanent grassland, which drastically lowers their current erosion risk. The present soil erosion risk map serves on the one hand to identify and prioritise the high-erosion risk areas, and on the other hand to promote awareness amongst farmers and authorities. It was published on the internet and will be made available to the authorities in digital form. It is intended as a tool for simplifying and standardising enforcement of the legal framework for soil erosion prevention in Switzerland. The work therefore provides a successful example of cooperation between science, policy and practice.
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Off-site effects of soil erosion are becoming increasingly important, particularly the pollution of surface waters. In order to develop environmentally efficient and cost effective mitigation options it is essential to identify areas that bear both a high erosion risk and high connectivity to surface waters. This paper introduces a simple risk assessment tool that allows the delineation of potential critical source areas (CSA) of sediment input into surface waters concerning the agricultural areas of Switzerland. The basis are the erosion risk map with a 2 m resolution (ERM2) and the drainage network, which is extended by drained roads, farm tracks, and slope depressions. The probability of hydrological and sedimentological connectivity is assessed by combining soil erosion risk and extended drainage network with flow distance calculation. A GIS-environment with multiple-flow accumulation algorithms is used for routing runoff generation and flow pathways. The result is a high resolution connectivity map of the agricultural area of Switzerland (888,050 ha). Fifty-five percent of the computed agricultural area is potentially connected with surface waters, 45% is not connected. Surprisingly, the larger part of 34% (62% of the connected area) is indirectly connected with surface waters through drained roads, and only 21% are directly connected. The reason is the topographic complexity and patchiness of the landscape due to a dense road and drainage network. A total of 24% of the connected area and 13% of the computed agricultural area, respectively, are rated with a high connectivity probability. On these CSA an adapted land use is recommended, supported by vegetated buffer strips preventing sediment load. Even areas that are far away from open water bodies can be indirectly connected and need to be included in planning of mitigation measures. Thus, the connectivity map presented is an important decision-making tool for policy-makers and extension services. The map is published on the web and thus available for application.
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The geography of Scotland, with a highly undulating hinterland, long and indented coastline, together with a large number of islands, means that much social and economic activity is largely located at the coast. The importance of the coast is further highlighted by the large number of ecosystem services derived from the coast. The threat posed by climate change, particularly current and future sea level rise, is of considerable concern and the associated coastal erosion and coastal flooding has the potential to have a substantial effect on the socioeconomic activity of the whole country. Currently, the knowledge base of coastal erosion is poor, which serves to hinder the current and future management of the coast. This research reported here aimed to establish four key aspects of coastal erosion within Scotland: the physical susceptibility of the coast to erosion; the assets exposed to coastal erosion; the vulnerability of communities to coastal erosion; and the coastal erosion risk to those communities. Coastal erosion susceptibility was modelled here within a GIS, using data for ground elevation, rockhead elevation, wave exposure and proximity to the open coast. Combining these data produced the Underlying Physical Susceptibility Model (UPSM), in the form of a 50 m2 raster of national coverage. The Coastal Erosion Susceptibility Model (CESM) was produced with the addition of sediment supply and coastal defence data, which then moderates the outputs of the UPSM. Asset data for dwellings, key assets, transport infrastructure, historic assets, and natural assets were used along with the UPSM and CESM to assess their degree of exposure to coastal erosion. A Coastal Erosion Vulnerability Model (CEVM) was produced using Experian Mosaic Scotland (a geodemographic classification which identifies 44 different social groups within Scotland) to classify populations based upon 11 vulnerability variables. Dwellings were assigned a CESM and CEVM score in order to establish their coastal erosion risk. This research demonstrated that the issue of coastal erosion will impact on a relatively low number of properties compared to those impacted by flooding (both coastal and fluvial) as many dwellings are already protected by coastal defences. There is therefore, a considerable future liability, and great pressure for coastal defences to be maintained and upgraded in their current form. The use of the CEVM is a novel inclusion within a coastal erosion assessment for Scotland. Use of the CEVM established that coastal erosion risk is not distributed equally amongst the Scottish coastal population and highlighted that risk can be reduced by either reducing exposure or reducing vulnerability. Thus far in Scotland, reducing exposure has been the primary management approach, which has a number of implications with regards social justice. This research identified the existing data gaps that should be addressed by future research in order to further improve coastal management in Scotland. Future research should focus on assessing historical coastal change rates on a national scale, improve modelling of national scale wave exposure, enhance the information held about current coastal defences and, determine the direct and indirect economic cost associated with the loss of different asset types. It is also necessary to clarify the social justice implications of using adaptation approaches to manage coastal erosion as well as establishing a method to communicate the susceptibility, exposure, vulnerability and risk aspects whilst minimising the potential negative impacts (e.g. property blight) of releasing such information.
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The objective of this work was to evaluate the seasonal variation of soil cover and rainfall erosivity, and their influences on the revised universal soil loss equation (Rusle), in order to estimate watershed soil losses in a temporal scale. Twenty-two TM Landsat 5 images from 1986 to 2009 were used to estimate soil use and management factor (C factor). A corresponding rainfall erosivity factor (R factor) was considered for each image, and the other factors were obtained using the standard Rusle method. Estimated soil losses were grouped into classes and ranged from 0.13 Mg ha-1 on May 24, 2009 (dry season) to 62.0 Mg ha-1 on March 11, 2007 (rainy season). In these dates, maximum losses in the watershed were 2.2 and 781.5 Mg ha-1 , respectively. Mean annual soil loss in the watershed was 109.5 Mg ha-1 , but the central area, with a loss of nearly 300.0 Mg ha-1 , was characterized as a site of high water-erosion risk. The use of C factor obtained from remote sensing data, associated to corresponding R factor, was fundamental to evaluate the soil erosion estimated by the Rusle in different seasons, unlike of other studies which keep these factors constant throughout time.
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This work aimed to study the space behavior of the water erosion in a red-yellow latosol. Then a study was developed in an area with colinon coffee cultivation in an Experimental Farm of Bananal do Norte of INCAPER in Cachoeiro de Itapemirim - ES. Soil samples were obtained from 0,0 to 0,20 m depth in an irregular grid with 109 samples. The analyzed variables were granulometric fractions, erodibility (K), natural erosion potential (PNE), soil loss (A) and erosion risk (RE). All the variables showed space dependency with moderate index of space dependency and similar standard of space distribution. The soil loss is related with the space distribution of the granulometric fractions.
Resumo:
Within the scope of a comprehensive assessment of the degree of soil erosion in Switzerland, common methods have been used in the past including test plot measurements, artificial rainfall simulation, and erosion modelling. In addition, mapping guidelines for all visible erosion features have been developed since the 1970s and are being successfully applied in many research and soil conservation projects. Erosion damage has been continuously mapped over a period of 9 years in a test region in the central Bernese plateau. In 2005, two additional study areas were added. The present paper assesses the data gathered and provides a comparison of the three study areas within a period of one year (from October 2005 to October 2006), focusing on the on-site impacts of soil erosion. During this period, about 11 erosive rainfall events occurred. Average soil loss rates mapped at each study site amounted to 0.7 t ha-1, 1.2 t ha-1 and 2.3 t ha-1, respectively. About one fourth of the total arable land showed visible erosion damage. Maximum soil losses of about 70 t ha-1 occurred on individual farm plots. Average soil erosion patterns are widely used to underline the severity of an erosion problem (e.g. impacts on water bodies). But since severe rainfall events, wheel tracks, headlands, and other “singularities” often cause high erosion rates, analysis of extreme erosion patterns such as maximum values led to a more differentiated understanding and appropriate conclusions for planning and design of soil protection measures. The study contains an assessment of soil erosion in Switzerland, emphasizing questions about extent, frequency and severity. At the same time, the effects of different types of land management are investigated in the field, aiming at the development of meaningful impact indicators of (un-)sustainable agriculture/soil erosion risk as well as the validation of erosion models. The results illustrate that conservation agriculture including no-till, strip tillage and in-mulch seeding plays an essential role in reducing soil loss as compared to conventional tillage.
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At many locations in Myanmar, ongoing changes in land use have negative environmental impacts and threaten natural ecosystems at local, regional and national scales. In particular, the watershed area of Inle Lake in eastern Myanmar is strongly affected by the environmental effects of deforestation and soil erosion caused by agricultural intensification and expansion of agricultural land, which are exacerbated by the increasing population pressure and the growing number of tourists. This thesis, therefore, focuses on land use changes in traditional farming systems and their effects on socio-economic and biophysical factors to improve our understanding of sustainable natural resource management of this wetland ecosystem. The main objectives of this research were to: (1) assess the noticeable land transformations in space and time, (2) identify the typical farming systems as well as the divergent livelihood strategies, and finally, (3) estimate soil erosion risk in the different agro-ecological zones surrounding the Inle Lake watershed area. GIS and remote sensing techniques allowed to identify the dynamic land use and land cover changes (LUCC) during the past 40 years based on historical Corona images (1968) and Landsat images (1989, 2000 and 2009). In this study, 12 land cover classes were identified and a supervised classification was used for the Landsat datasets, whereas a visual interpretation approach was conducted for the Corona images. Within the past 40 years, the main landscape transformation processes were deforestation (- 49%), urbanization (+ 203%), agricultural expansion (+ 34%) with a notably increase of floating gardens (+ 390%), land abandonment (+ 167%), and marshlands losses in wetland area (- 83%) and water bodies (- 16%). The main driving forces of LUCC appeared to be high population growth, urbanization and settlements, a lack of sustainable land use and environmental management policies, wide-spread rural poverty, an open market economy and changes in market prices and access. To identify the diverse livelihood strategies in the Inle Lake watershed area and the diversity of income generating activities, household surveys were conducted (total: 301 households) using a stratified random sampling design in three different agro-ecological zones: floating gardens (FG), lowland cultivation (LL) and upland cultivation (UP). A cluster and discriminant analysis revealed that livelihood strategies and socio-economic situations of local communities differed significantly in the different zones. For all three zones, different livelihood strategies were identified which differed mainly in the amount of on-farm and off-farm income, and the level of income diversification. The gross margin for each household from agricultural production in the floating garden, lowland and upland cultivation was US$ 2108, 892 and 619 ha-1 respectively. Among the typical farming systems in these zones, tomato (Lycopersicon esculentum L.) plantation in the floating gardens yielded the highest net benefits, but caused negative environmental impacts given the overuse of inorganic fertilizers and pesticides. The Revised Universal Soil Loss Equation (RUSLE) and spatial analysis within GIS were applied to estimate soil erosion risk in the different agricultural zones and for the main cropping systems of the study region. The results revealed that the average soil losses in year 1989, 2000 and 2009 amounted to 20, 10 and 26 t ha-1, respectively and barren land along the steep slopes had the highest soil erosion risk with 85% of the total soil losses in the study area. Yearly fluctuations were mainly caused by changes in the amount of annual precipitation and the dynamics of LUCC such as deforestation and agriculture extension with inappropriate land use and unsustainable cropping systems. Among the typical cropping systems, upland rainfed rice (Oryza sativa L.) cultivation had the highest rate of soil erosion (20 t ha-1yr-1) followed by sebesten (Cordia dichotoma) and turmeric (Curcuma longa) plantation in the UP zone. This study indicated that the hotspot region of soil erosion risk were upland mountain areas, especially in the western part of the Inle lake. Soil conservation practices are thus urgently needed to control soil erosion and lake sedimentation and to conserve the wetland ecosystem. Most farmers have not yet implemented soil conservation measures to reduce soil erosion impacts such as land degradation, sedimentation and water pollution in Inle Lake, which is partly due to the low economic development and poverty in the region. Key challenges of agriculture in the hilly landscapes can be summarized as follows: fostering the sustainable land use of farming systems for the maintenance of ecosystem services and functions while improving the social and economic well-being of the population, integrated natural resources management policies and increasing the diversification of income opportunities to reduce pressure on forest and natural resources.
Resumo:
Soil erosion data in El Salvador Republic are scarce and there is no rainfall erosivity map for this region. Considering that rainfall erosivity is an important guide for planning soil erosion control practices, a spatial assessment of indices for characterizing the erosive force of rainfall in El Salvador Republic was carried out. Using pluviometric records from 25 weather stations, we applied two methods: erosivity index equation and the Fournier index. In all study area, the rainiest period is from May to November. Annual values of erosivity index ranged from 7,196 to 17,856 MJ mm ha(-1) h(-1) year(-1) and the Fournier index ranged from 52.9 to 110.0 mm. The erosivity map showed that the study area can be broadly divided into three major erosion risk zones, and the Fournier index map was divided into four zones. Both methods revealed that the erosive force is severe in all study area and presented significant spatial correlation with each other. The erosive force in the country is concentrated mainly from May to November.
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O objetivo deste trabalho foi estudar a influência das superfícies geomórficas na variação espacial da perda de solo por erosão na região de Pereira Barreto, São Paulo (SP). Os solos foram amostrados nos pontos de cruzamento de uma malha, georreferenciados, com intervalos de 350m, na profundidade de 0,0-0,2m, totalizando 67 pontos. Foram feitas determinações da composição granulométrica e do conteúdo de matéria orgânica. Foram avaliados os fatores de erosão locais, tais como erosividade (R), erodibilidade (K), fator topográfico (LS), uso e manejo (C), práticas conservacionistas (P), potencial natural de erosão (PNE), perda de solo com e sem práticas conservacionistas (A e *A), tolerância de perda de solo (T) e risco de erosão (RE). As variáveis A, PNE e RE apresentaram forte correlação espacial com o fator topográfico (LS), indicando a forte relação do relevo sobre os fatores de erosão. As perdas de solo (A e *A) apresentaram comportamento coerente com a conceituação de superfícies geomórficas, evidenciando as relações de dependência do processo erosivo do solo aos ambientes geomórficos.
Resumo:
Visando a avaliar a variabilidade espacial de fatores de erosão em Latossolo Vermelho eutroférrico, foram obtidas amostras do solo em intervalos regulares de 50 m, em forma de grid, totalizando 206 pontos de amostragem. Foram coletadas amostras nas profundidades de 0,0-0,2 m para a determinação da composição granulométrica e do conteúdo de matéria orgânica. Os fatores de erosão locais, como erosividade (R), erodibilidade (K), relevo (LS), perda de solo (A), potencial natural de erosão (PNE), risco de erosão (RE) e expectativa de erosão (EE), foram avaliados. A variabilidade do solo medida pelo coeficiente de variação registrou-se média para K, alta para o RE e EE e muito alta para A, LS e PNE. As variáveis estudadas apresentaram estrutura de dependência espacial com grau moderado para as variáveis K, A, PNE e RE, e forte para o LS e EE. Mapas obtidos por krigagem foram apresentados para descrição dos padrões de distribuição dos fatores de erosão na paisagem.
Resumo:
As formas do relevo podem ser indicadores da variação dos atributos do solo, pois essa variabilidade é causada por pequenas alterações do declive que afetam os processos pedogenéticos bem como o transporte e o armazenamento de água no perfil do solo. O trabalho foi desenvolvido em Catanduva (SP), com o objetivo de caracterizar a variabilidade espacial de atributos do solo e fatores de erosão em diferentes pedoformas sob cultivo de cana-de-açúcar. de acordo com o modelo de Troeh classificou-se as formas do relevo em duas pedoformas, côncava e convexa. Com a utilização de um DGPS levantaram-se as cotas altimétricas, estabelecendo-se uma malha, com intervalos regulares de 50 m, com 270 pontos na pedoforma côncava e 353 pontos na pedoforma convexa, perfazendo um total de 623 pontos, coletados na profundidade de 0,0 - 0,2 m em uma área de 200 ha. em cada ponto da malha foram determinados os atributos químicos do solo, granulometria, espessura do solo e fatores de erosão locais, tais como erosividade (R), erodibilidade (K), fator topográfico (LS), uso e manejo (C), práticas conservacionistas (P), potencial natural de erosão (PNE), perda de solo (A) e risco de erosão (RE). Os dados foram avaliados primeiramente por uma análise estatística exploratória, calculando-se a média, mediana, variância, coeficiente de variação, coeficiente de assimetria, coeficiente de curtose e teste de normalidade. Posteriormente, a dependência espacial foi verificada por meio da técnica de geoestatística utilizando-se semivariogramas. As maiores perdas de solo, risco de erosão e potencial natural de erosão e menor espessura do solo ocorreram na pedoforma convexa, indicando forte dependência espacial com a forma do relevo. A pedoforma côncava proporcionou maior variabilidade espacial, demonstrando que a forma do relevo condiciona padrões diferenciados de variabilidade. A magnitude da variabilidade dos atributos do solo é mais influenciada pela forma do relevo que pela erosão. A espessura do horizonte A+E integrado com a forma do relevo é um indicador de processos erosivos para classe de Argissolos.
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The objective of this work was to identify the spatial variability of the natural erosion potential, soil loss and erosion risk in two intensely cultivated areas, in order to assess the erosion occurrence patterns. The soil of the area located at Monte Alto, São Paulo state, was classified as Paleudalf (PVA) with moderately slope, with different managements. The soil of the area located at Jaboticabal, São Paulo state, was classified as Haplortox(LV) with gentle slope and cultivated with sugarcane. A irregular grid was imposed on the experimental areas. Soil samples were obtained from 0-0.2 m depth at each grid point: 88 samples in Monte Alto area (1465 ha) and 128 samples at Jaboticabal area (2597 ha). In order to obtain the values of the studied variables USLE was applied at each grid point. Descriptive statistics were calculated, and geoestatistical analyses were performed for defining semivariograms. Kriging techniques to develop map showing spatial patterns in variability of selected soil attributes were used. All variables showed spatial dependence. The PVA soil showed higher erosion risk due to the slope and atual management compared to the soil LV.
Resumo:
Accelerated soil erosion is, at present, one of the most widespread environmental problems in the world. Geographic Information Systems (GIS) have become an essential tool in soil erosion studies and consequently in the development of appropriate soil conservation strategies. The objective of this paper was to assess the degree of soil erosion associated with land cover dynamics through GIS analysis and to validate the modeling with indicators of soil erosion. Universal Soil Loss Equation (USLE) model, GIS technology and ground-truth dataset (erosion indicators) were employed to elaborate the soil loss maps for four dates at Sorocaba Municipality (SP, Brazil). It was verified that, although the predicted soil loss rate is normally small along the study area, such rate is significantly greater than the soil formation rate. This shows a non-sustainable situation of soil and land cover management. Unplanned urban expansion seems be the main driving force that acts in increasing the erosion risk/occurrence along the study area.
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The objective of this work was to verify the application of cluster analysis to evaluate soil erosion risk for different soil classes, soil slopes and soil managements. The study was conducted in a 33 ha section of a large field located in Carmo do Rio Claro County, MG, Brazil. The field had been managed in a corn/bean rotation under conventional tillage and under coffee plantation for seven years, both under sprinkle irrigation. Soil samples were obtained at every 10 m at 0.20 m depth along a transect of 1050 m. Soil erosion risk (A), natural potential erosion (PN), and erosion expectation (EE) were determined and submitted to a cluster and principal component analysis. The application of clustering analysis showed high correlation between the clusters and soil types. With clustering analysis plus principal components analysis, it was possible to identify groups of high and low soil erosion expectation, showing that the areas with higher soil erosion expectation are correlated to the soil class, soil slope and soil management. Among the studied variables, the natural potential erosion (PN) showed to be the most important factor to identify different soil erosion groups. The cluster analysis showed that 98% of the variables were classified within each group, and that they should be managed differently due to the soil erosive potential of each group,.