The diploma thesis is focused on the evaluation of vulnerability of land to water erosion in the sub-basin of the river Bystřice with the hydrological order number 4-15-01-0402-0-00. The work contains research dealing with soil erosion and erosion protection. Part of the thesis describes the basin of interest on the basis of a site survey and available literature. The principle of erosion risk evaluation is calculation of the universal USLE Wischmeier-Smith equation factors and the determination of the average long-term loss of soil caused by water erosion. Partial analyzes are performed using GIS tools and LS converter 1.0 and Usle2D programs. Appropriate anti-erosion measures are proposed if necessary. The measures are based on the results of the evaluation corresponding to the conditions and possibilities of the area of interest. Part of the thesis contains mapping documentation created by the ArcGIS program.

Poor harvesting practices can accelerate soil erosion and decrease water quality and site productivity. Forestry Best Management Practices (BMPs) were developed to protect water quality, primarily by minimizing erosion during and after timber harvests. Although properly employed BMPs mitigate against the immediate potential for soil loss, little information exists regarding their long-term effectiveness. Since 1993, the Virginia Department of Forestry (VDOF) has conducted random water quality audits on forest harvesting operations. The VDOF will recommend remedial BMPs immediately if there is an active water quality law violation, and these recommendations are usually obviously clear to all parties. However, the potential for water degradation is more controversial and debates can arise over these recommendations. The VDOF, as in most states, does not have the resources to make visits to post harvest sites over time. Therefore, it is imperative that the BMPs employed at the closeout of the timber harvest be sufficient to ensure erosion control until the site has recovered, yet, BMP evaluations should represent real or potential problems. This study was undertaken to provide a quantitative analysis of erosion rates over time on VDOF random audited harvest sites and to identify key factors of erosion rates for log decks, skid trails, access roads, harvest areas, and stream crossings within each of Virginia's physiographic regions. A secondary objective was to provide a greater level of decision support for VDOF field staff, through the identified key factors which would indicate potential problem areas of erosion and water quality degradation particularly from logging activities and temporary roads. To better understand the primary causes of erosion over time the Dissmeyer and Foster Universal Soil Loss Equation (USLE) was used to establish quantitative erosion rates which officials can use to focus BMP recommendations. Such a decision support system for field staff, based on quantifiable erosion estimates, provides a proactive targeted prevention assessment prior to the development of actual water pollution problems. Analyses of logged tracts throughout Virginia revealed that estimated erosion rates were not statistically significant between physiographic provinces as well as VDOF audit classifications. Timber access roads were the greatest source of erosion in the Piedmont and Mountains, while harvested areas were the largest identified erosion area in the Coastal Plain, based upon the disturbance categories ratio to the total tract area. Estimated erosion rate trends over time indicated that the majority of disturbance categories were essentially recovered between eight to ten years after harvest. Further, disturbance categories in the Coastal Plain recovered faster than the other province. Erosion rates could not be explained by the year since harvest, since numerous variables interact to cause erosion. Overall predicted erosion rates and VDOF audit classifications of problems did not have consistent agreement. This indicates the need for additional calibration of VDOF ratings and perhaps the establishment of more quantifiable BMP inspection criteria. / Master of Science

The aim of the work is to find out the application of intercrops and their influence in crop rotation in the cadastral area of Krašovice u Čížové. The first part of the thesis deals with erosion, anti-erosion measures and intercrops. In the second part there is a calculation of erosion shear on given cadastral area. The erosion of soil on the soil blocks is calculated using the Wischmeier-Smith equation (USLE). The wash is then further compared, using crop rotation and crop rotation with the application of intercrops.

The construction of Baku-Tbilisi-Ceyhan (BTC) Oil and South Caucasus Gas (SCP) pipelines was completed in 2005. The Azerbaijan section of BTC Oil and SCP Gas pipelines is 442 km long and 44 m wide corridor named as the Right-of-Way. BTC and SCP pipelines are aligned parallel to each other within the same 44m corridor. The construction process of the pipelines significantly disturbed vegetation and soil cover along Right-of-Way of pipelines. The revegetation and erosion control measures were conducted after the completion of construction to restore the disturbed footprints of construction activities. The general goals of the present studies, dedicated to the environmental monitoring of revegetation and planning of erosion control measures were: to evaluate the status of the revegetation in 2007 since the completion of the construction activities in 2005, to determine the climate and ground factors controlling the vegetation regrowth and to predict erosion-prone areas along Right-of-Way of pipelines. Regression and root mean square error analysis between the Normalized Difference Vegetation Index (NDVI) of IKONOS images acquired in 2007 and in-situ estimations of vegetation cover percentage revealed R2 equal to 0.80 and RMSE equal to 6% which were optimal for the normalization of NDVI to vegetation cover. The total area of restored vegetation cover between 2005 and 2007 was 8.9 million sq. m. An area of 10.7 million sq. m. of ground vegetation needed restoration in order to comply with the environmental acceptance criteria. Based on the Global Spatial Regression Model, precipitation, land surface temperature and evapotranspiration were determined as the main climate factors controlling NDVI of grasslands along Right-of-Way of pipelines. In case of croplands, precipitation, evapotranspiration and annual minimum temperature were determined as the main factors controlling NDVI of croplands. The regression models predicting NDVI for grasslands and croplands were also formulated. The Geographically Weighted Regression analyses in comparison with the global regression models results clearly revealed that the relationship between NDVI of grasslands and croplands and the predictor variables was spatially non-stationary along the corridor of pipelines. Even though the observed R2 value between elevation and NDVI of grasslands was low (R2= 0.14), the accumulation of the largest NDVI patterns was observed higher than 150m elevation. This revealed that elevation has non-direct control of NDVI of grasslands through its control of precipitation and temperature along the grasslands of Right-of-Way. The spatial distribution percentage of NDVI classes within slope aspect categories was decreasing in the southern directions of slope faces. Land surface temperature was decreasing with elevation but no particular patterns of land surface temperature in the relationship with NDVI accumulation within the aspect categories were observed. Aspect categories have non-direct control of NDVI and there are some other factors apart from land surface temperature which require further investigations. Precipitation was determined to be controlling the formation of topsoil depth and the topsoil obviously controls the VC growth of grasslands as one of the main ground factors. The regression analysis between NDVI of grasslands and croplands with groundwater depth showed very low correlation. But the clustered patterns of vegetation cover were observed in the relationship with groundwater depth and soil moisture for both grasslands and croplands. The modeling of groundwater depth relative to soil moisture and MODIS NDVI of grasslands determined that the threshold of groundwater depth for vegetation growth is in the range of 1-5 m. MODIS NDVI and soil moisture did not reveal a significant correlation. Soil moisture revealed R2 equal to 0.34 with elevation, R2 equal to 0.23 with evapotranspiration, R2 equal to 0.57 with groundwater depth and R2 equal to 0.02 with precipitation. This allowed to suspect that precipitation is not the main factor controlling soil moisture whereas elevation, evapotranspiration and groundwater depth have non-direct control of soil moisture. Therefore, soil moisture has also non-direct control of vegetation cover growth along the corridor of pipelines. The variations of soil moisture in the 1-3 m soil depth range may have the threshold of depth controlling vegetation cover regrowth and this requires more detailed soil moisture data for further investigations. The reliability of the Global Spatial Regression Model and Geographically Weighted Regression predictions is limited by the MODIS images spatial resolution equal to 250 m and spectral characteristics. The Morgan-Morgan-Finney (MMF) and Universal Soil Loss Equation (USLE) predictions revealed non-similarity in the spatial distribution of soil loss rates along Right-of-Way. MMF model revealed more clustered patterns of predicted critical erosion classes with soil loss more than 10 ton/ha/year in particular ranges of pipelines rather than Universal Soil Loss Equation model with the widespread spatial distribution. Paired-Samples T-Test with p-value less than 0.05 and Bivariate correlation with the Pearson\'s correlation coefficient equal to 0.23 showed that the predictions of these two models were significantly different. Verification of USLE- and MMF- predicted erosion classes against in-situ 316 collected erosion occurrences collected in the period of 2005-2012 revealed that USLE performed better than MMF model along pipeline by identifying of 192 erosion occurrences out of 316, whereas MMF identified 117 erosion sites. USLE revealed higher ratio of frequencies of erosion occurrences within the critical erosion classes (Soil Loss > 10 t/ha), what also showed higher reliability of soil loss predictions by USLE. The validation of quantitative soil loss predictions using the measurements from 48 field erosion plots revealed higher R2 equal to 0.67 by USLE model than by MMF. This proved that USLE-predicted soil loss rates were more reliable than MMF not only in terms of spatial distributions of critical erosion classes but also in the quantitative terms of soil loss rates. The total number of erosion-prone pipeline segments with the identified erosion occurrences was 316 out of 38376. The number of erosion-prone pipeline segments realistically predicted by USLE model e.g. soil loss more than 10 t/ha was 97 whereas MMF predicted only 70 erosion-prone pipeline segments. The regression analysis between 354 USLE and MMF erosion-prone segments revealed R2 equal to 0.36 what means that the predictions by USLE and MMF erosion models are significantly different on the level of pipeline segments. The average coefficients of variation of predicted soil loss rates by USLE and MMF models and the number of accurately predicted erosion occurrences within the geomorphometric elements of terrain, vegetation cover and landuse categories were larger in the USLE model. This supported the hypothesis that larger spatial variations of erosion prediction models can contribute to the better soil loss prediction performance and reliability of erosion prediction models. This also supported the hypothesis that better understanding of spatial variations within geomorphometric elements of terrain, land-use and vegetation cover percentage classes can support in the selection of the appropriate erosion models with better performance in the particular areas of pipelines. Qualitative multi-criteria assessment for the determination of erosion-prone areas revealed stronger relations with the USLE predictions rather than with MMF. Multi-criteria assessment identified 35 of erosion occurrences but revealed more reliable predictions on the level of terrain units. Predicted erosion-prone areas by USLE revealed higher correlation coefficient with erosion occurrences than MMF model within terrain units what proved higher reliability of the USLE predictions and its stronger relation with the multi-criteria assessment.

Submitted by Cláudia Bueno (claudiamoura18@gmail.com) on 2016-06-02T17:44:33Z No. of bitstreams: 2 Dissertação - Thiago Henrique Arbués Botelho - 2015.pdf: 8613837 bytes, checksum: 09a30216ecc0fd5f4e488e8223e6a47c (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2016-06-03T12:39:43Z (GMT) No. of bitstreams: 2 Dissertação - Thiago Henrique Arbués Botelho - 2015.pdf: 8613837 bytes, checksum: 09a30216ecc0fd5f4e488e8223e6a47c (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2016-06-03T12:39:43Z (GMT). No. of bitstreams: 2 Dissertação - Thiago Henrique Arbués Botelho - 2015.pdf: 8613837 bytes, checksum: 09a30216ecc0fd5f4e488e8223e6a47c (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2015-02-26 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / The monitoring of soil loss by erosion is a source of information relevant to land management, forecasting impacts and conservation recommendations. In this sense, the objective of this study was to apply computer simulation methodology of soil erosion using the Universal Soil Loss Equation (USLE) and sources of information available to characterize, quantify and analyze soil losses in the Samambaia River watershed (BHRS). This basin was chosen as the study unit, due to the availability of spatial data in different scales (1: 250,000 and 1: 10,000). A Geographic Information System (GIS) was used in handling, sorting and updating of data of interest as well as to build the Digital Elevation Model (DEM) and the spatial database of USLE factors in two different scales. To quantitatively analyze the results calculated the Natural Potential Erosion (PNE) and the current erosion (Ea) that considers the influence of coverage, Land Use and Occupancy (UCS), also used for qualitative studies of soil losses. The study area was divided into three sub-basins. The mapping of the UCS showed that agricultural areas represent about 70% of land cover in the sub-basin of Samambaia River and Arrasta-burro Stream. The results indicated that more than 80% of the area of these two sub-basins has a weak PNE. Have the sub-basin of Moreira Stream had the highest percentage of natural vegetation and forestry classes, as well as the lowest percentage of bare soil class, in relation to other sub-basins. However, had the highest average value of current erosion (71.10 Mg ha-1 yr-1), which is probably due to the PNE ranging from moderate to very strong in more than 40% of the area. Most of the basin soil has medium erodibility. For Cambisols and Petric Plinthosols of BHRS, the average soil loss is at least twice higher than the average level of tolerance. The LS factor has more influence in the PNE, especially when the relief was wavy, followed by the K factor, when the relief was flat. Use the database scale 1: 10,000 affected area of the watershed caused increases in slope and rise of strong corrugated relief classes, mountainous and rugged, yet showed higher coefficients of variation for all the factors of USLE. The results show greater difference between the wavy relief classes in both applied scales. In most maps produced by means of databases on different scales there is distinction of the results, especially for the slope maps, PNE and Ea generated for the watershed of the Samambaia. The analysis of soil losses in the areas of central pivot showed higher average and median values when using the scale 1: 250,000. It is important that managers and farmers are aware of the risks and provide mitigation measures. An interesting solution is to expand the use of lower impact to soil management systems, to promote its wider coverage, such as forestry, especially in the areas susceptible to erosion. / O monitoramento das perdas de solo por erosão é fonte de informação relevante para a gestão do território, previsão de impactos e recomendações conservacionistas. Nesse sentido, o objetivo deste estudo foi aplicar metodologia de simulação computacional da erosão hídrica do solo utilizando a Equação Universal de Perda de Solo (USLE) e fontes de informação disponíveis para caracterizar, quantificar e analisar as perdas de solo na bacia hidrográfica do Rio Samambaia (BHRS). Essa bacia hidrográfica foi escolhida como unidade de estudo, em razão da disponibilidade de dados espaciais em escalas distintas (1:250.000 e 1:10.000). Um Sistema de Informação Geográfica (SIG) foi utilizado na manipulação, classificação e atualização dos dados de interesse, bem como para construir o Modelo Digital de Elevação (MDE) e a base de dados espaciais dos fatores da USLE nas duas escalas distintas. Para analisar quantitativamente os resultados calculou-se o Potencial Natural à Erosão (PNE) e a Erosão atual (Ea) que considera a influência da Cobertura, Uso e Ocupação do Solo (UCS), também usado para estudos qualitativos das perdas de solo. A área de estudo foi dividida em três sub-bacias hidrográficas. O mapeamento do UCS demonstrou que as áreas agrícolas representam aproximadamente 70% da cobertura do solo na sub-bacia do Rio Samambaia e do Córrego Arrasta-burro. Os resultados obtidos indicaram que mais de 80% da área dessas duas sub-bacias possui um PNE fraco. Já a sub-bacia do Ribeirão Moreira apresentou o maior percentual das classes vegetação natural e silvicultura, bem como o menor percentual da classe solo exposto, em relação às outras sub-bacias. Contudo, obteve o maior valor médio de erosão atual (71,10 Mg ha-1 ano-1), o que se deve provavelmente em razão do PNE que variou de moderado a muito forte em mais de 40% da área. A maioria dos solos da bacia apresenta média erodibilidade. Para os Cambissolos e Petroplintossolos (Plintossolos Pétricos) da BHRS, a perda média de solo está no mínimo duas vezes acima do limite médio de tolerância. O fator LS tem maior influência no PNE, principalmente quando o relevo foi ondulado, seguido pelo fator K, quando o relevo foi plano. O uso da base de dados na escala 1:10.000 afetou a área da microbacia, provocou aumento de declividade e surgimento das classes de relevo forte ondulado, montanhoso e escarpado, ainda apresentou maiores coeficientes de variação para todos os fatores da USLE. Os resultados comprovam maior diferença entre as classes de relevo ondulado nas duas escalas aplicadas. Na maioria dos mapas produzidos por meio das bases de dados em diferentes escalas existe distinção dos resultados, principalmente para os mapas de declividade, PNE e Ea gerados para a microbacia do Rio Samambaia. A análise das perdas de solo nas áreas de pivô central demonstrou aumento dos valores de média e mediana ao se utilizar a escala 1:250.000. É importante que os gestores e produtores rurais tomem consciência sobre os riscos e estabeleçam medidas mitigadoras. Uma solução interessante é ampliar a utilização de sistemas de manejo menos impactantes ao solo, que promovam sua maior cobertura, tais como a silvicultura, especialmente nas áreas mais suscetíveis à erosão.

The subject of the diploma thesis was the evaluation of erosion and drainage conditions in the cadastral area of Čejkovice in the Morava basin and the subsequent proposal of protective measures. The erosion analysis and the subsequent design of the protective measures were carried out in four variants depending on the increasing R factor. In conclusion, the scope of individual protective measures for each variant was evaluated.

The construction of Baku-Tbilisi-Ceyhan (BTC) Oil and South Caucasus Gas (SCP) pipelines was completed in 2005. The Azerbaijan section of BTC Oil and SCP Gas pipelines is 442 km long and 44 m wide corridor named as the Right-of-Way. BTC and SCP pipelines are aligned parallel to each other within the same 44m corridor. The construction process of the pipelines significantly disturbed vegetation and soil cover along Right-of-Way of pipelines. The revegetation and erosion control measures were conducted after the completion of construction to restore the disturbed footprints of construction activities. The general goals of the present studies, dedicated to the environmental monitoring of revegetation and planning of erosion control measures were: to evaluate the status of the revegetation in 2007 since the completion of the construction activities in 2005, to determine the climate and ground factors controlling the vegetation regrowth and to predict erosion-prone areas along Right-of-Way of pipelines. Regression and root mean square error analysis between the Normalized Difference Vegetation Index (NDVI) of IKONOS images acquired in 2007 and in-situ estimations of vegetation cover percentage revealed R2 equal to 0.80 and RMSE equal to 6% which were optimal for the normalization of NDVI to vegetation cover. The total area of restored vegetation cover between 2005 and 2007 was 8.9 million sq. m. An area of 10.7 million sq. m. of ground vegetation needed restoration in order to comply with the environmental acceptance criteria. Based on the Global Spatial Regression Model, precipitation, land surface temperature and evapotranspiration were determined as the main climate factors controlling NDVI of grasslands along Right-of-Way of pipelines. In case of croplands, precipitation, evapotranspiration and annual minimum temperature were determined as the main factors controlling NDVI of croplands. The regression models predicting NDVI for grasslands and croplands were also formulated. The Geographically Weighted Regression analyses in comparison with the global regression models results clearly revealed that the relationship between NDVI of grasslands and croplands and the predictor variables was spatially non-stationary along the corridor of pipelines. Even though the observed R2 value between elevation and NDVI of grasslands was low (R2= 0.14), the accumulation of the largest NDVI patterns was observed higher than 150m elevation. This revealed that elevation has non-direct control of NDVI of grasslands through its control of precipitation and temperature along the grasslands of Right-of-Way. The spatial distribution percentage of NDVI classes within slope aspect categories was decreasing in the southern directions of slope faces. Land surface temperature was decreasing with elevation but no particular patterns of land surface temperature in the relationship with NDVI accumulation within the aspect categories were observed. Aspect categories have non-direct control of NDVI and there are some other factors apart from land surface temperature which require further investigations. Precipitation was determined to be controlling the formation of topsoil depth and the topsoil obviously controls the VC growth of grasslands as one of the main ground factors. The regression analysis between NDVI of grasslands and croplands with groundwater depth showed very low correlation. But the clustered patterns of vegetation cover were observed in the relationship with groundwater depth and soil moisture for both grasslands and croplands. The modeling of groundwater depth relative to soil moisture and MODIS NDVI of grasslands determined that the threshold of groundwater depth for vegetation growth is in the range of 1-5 m. MODIS NDVI and soil moisture did not reveal a significant correlation. Soil moisture revealed R2 equal to 0.34 with elevation, R2 equal to 0.23 with evapotranspiration, R2 equal to 0.57 with groundwater depth and R2 equal to 0.02 with precipitation. This allowed to suspect that precipitation is not the main factor controlling soil moisture whereas elevation, evapotranspiration and groundwater depth have non-direct control of soil moisture. Therefore, soil moisture has also non-direct control of vegetation cover growth along the corridor of pipelines. The variations of soil moisture in the 1-3 m soil depth range may have the threshold of depth controlling vegetation cover regrowth and this requires more detailed soil moisture data for further investigations. The reliability of the Global Spatial Regression Model and Geographically Weighted Regression predictions is limited by the MODIS images spatial resolution equal to 250 m and spectral characteristics. The Morgan-Morgan-Finney (MMF) and Universal Soil Loss Equation (USLE) predictions revealed non-similarity in the spatial distribution of soil loss rates along Right-of-Way. MMF model revealed more clustered patterns of predicted critical erosion classes with soil loss more than 10 ton/ha/year in particular ranges of pipelines rather than Universal Soil Loss Equation model with the widespread spatial distribution. Paired-Samples T-Test with p-value less than 0.05 and Bivariate correlation with the Pearson\'s correlation coefficient equal to 0.23 showed that the predictions of these two models were significantly different. Verification of USLE- and MMF- predicted erosion classes against in-situ 316 collected erosion occurrences collected in the period of 2005-2012 revealed that USLE performed better than MMF model along pipeline by identifying of 192 erosion occurrences out of 316, whereas MMF identified 117 erosion sites. USLE revealed higher ratio of frequencies of erosion occurrences within the critical erosion classes (Soil Loss > 10 t/ha), what also showed higher reliability of soil loss predictions by USLE. The validation of quantitative soil loss predictions using the measurements from 48 field erosion plots revealed higher R2 equal to 0.67 by USLE model than by MMF. This proved that USLE-predicted soil loss rates were more reliable than MMF not only in terms of spatial distributions of critical erosion classes but also in the quantitative terms of soil loss rates. The total number of erosion-prone pipeline segments with the identified erosion occurrences was 316 out of 38376. The number of erosion-prone pipeline segments realistically predicted by USLE model e.g. soil loss more than 10 t/ha was 97 whereas MMF predicted only 70 erosion-prone pipeline segments. The regression analysis between 354 USLE and MMF erosion-prone segments revealed R2 equal to 0.36 what means that the predictions by USLE and MMF erosion models are significantly different on the level of pipeline segments. The average coefficients of variation of predicted soil loss rates by USLE and MMF models and the number of accurately predicted erosion occurrences within the geomorphometric elements of terrain, vegetation cover and landuse categories were larger in the USLE model. This supported the hypothesis that larger spatial variations of erosion prediction models can contribute to the better soil loss prediction performance and reliability of erosion prediction models. This also supported the hypothesis that better understanding of spatial variations within geomorphometric elements of terrain, land-use and vegetation cover percentage classes can support in the selection of the appropriate erosion models with better performance in the particular areas of pipelines. Qualitative multi-criteria assessment for the determination of erosion-prone areas revealed stronger relations with the USLE predictions rather than with MMF. Multi-criteria assessment identified 35 of erosion occurrences but revealed more reliable predictions on the level of terrain units. Predicted erosion-prone areas by USLE revealed higher correlation coefficient with erosion occurrences than MMF model within terrain units what proved higher reliability of the USLE predictions and its stronger relation with the multi-criteria assessment.

Submitted by Jorge Silva (jorgelmsilva@ufrrj.br) on 2017-04-25T20:29:14Z No. of bitstreams: 1 2012 - Eliete Nazar? Eduardo.pdf: 947644 bytes, checksum: d85c318ce9c161ce157d42e89ed6c4af (MD5) / Made available in DSpace on 2017-04-25T20:29:14Z (GMT). No. of bitstreams: 1 2012 - Eliete Nazar? Eduardo.pdf: 947644 bytes, checksum: d85c318ce9c161ce157d42e89ed6c4af (MD5) Previous issue date: 2012-02-27 / FAPERJ / The purpose of this study was to determine the soil erodibility (K) and soil cover and management factor (C) under natural and simulated rainfall in an Udult soil in Serop?dica, Rio de Janeiro State, Brazil. In the study with natural rainfall, the soil losses (SL) were evaluated from measurements in Wischmeier standard-plots in the period of 2006 to 2011, with their respective erosivity index (EI30). The soil erodibility values were calculated from the ratio of soil loss and the annual rainfall erosivity (Ka) and total period (Kt), considering the angular coefficient generated from the linear regression analysis between those parameters (Kci and Kct). For the determination of C factor under natural rainfall, it was evaluated the treatments maize in contour lines (MN) and maize in slope lines (MMA) during three years of cultivation. In the study with simulated rainfall, soil losses were evaluated during the period of September to December 2011, under the same treatments (MN and MMA). The soils erodibility under natural rainfall for 5 years of study is 0.0090 Mg ha h ha-1 MJ-1 mm-1. For the simulated rain, this value is 0.00021 Mg ha h ha-1 MJ-1 mm-1; under natural rainfall, the average values of C factor calculated are 0.0070 and 0.0132 Mg ha Mg-1 ha-1, respectively, for maize grown in contour and slope line, and 0.0932 and 0.1298 Mg ha Mg-1 ha-1 under simulated rainfall. In both studies, the C factor showed higher values in the beginning of the study period, decreasing with the evolution of culture. The higher C factor values obtained in the study with simulated rainfall are associated with higher erosivity index resulting from the characteristics adopted in the use of simulator rainfall. / O objetivo desse trabalho foi determinar a erodibilidade do solo (K) e o fator manejo e cobertura do solo (C), sob chuva natural e simulada, em um ARGISSOLO VERMELHO-AMARELO em Serop?dica (RJ), informa??es necess?rias para o planejamento do uso da terra e conserva??o do solo e da ?gua. No estudo com chuva natural foram avaliadas as perdas de solo (PS) ocorridas em parcelas padr?o de Wischmeier, no per?odo de 2006 a 2011, com seus respectivos ?ndices de erosividades (EI30). As erodibilidades do solo foram calculadas pelo quociente entre a perda de solo e a erosividade das chuvas anuais (Ka) e total no per?odo (Kt), considerando o coeficiente angular gerado na an?lise de regress?o linear entre esses mesmos par?metros (Kci e Kct). Para a determina??o do fator C, sob chuva natural foram avaliados os tratamentos de milho em n?vel (MN) e de milho morro a baixo (MMA) em tr?s anos de cultivo. No estudo com chuva simulada, as perdas de solo foram avaliadas no per?odo de setembro a dezembro de 2011, sob os mesmos tratamentos (MN e MMA). A erodibilidade do solo estudado sob chuva natural, para 5 anos de estudo ? de 0,0090 Mg ha h ha-1 MJ-1 mm-1. Para a chuva simulada, esse valor ? de 0,00021 Mg ha h ha-1 MJ-1 mm-1; sob chuva natural, os valores m?dios do fator C calculados s?o de 0,0070 e 0,0132 Mg ha Mg-1 ha-1, respectivamente, para a cultura do milho cultivado em n?vel e morro abaixo, e de 0,0932 e 0,1298 Mg ha Mg-1 ha-1 sob chuva simulada. Em ambos os estudos, o fator C apresentou maiores valores no in?cio do per?odo avaliado, decrescendo com a evolu??o da cultura. Os elevados valores do fator C obtidos no estudo com chuva simulada est?o associados ao elevado ?ndice de erosividade resultante das caracter?sticas adotadas no uso do simulador de chuva.

The thesis is focused on the system erosion and the flood control measures in the cadastral territory of Smetanova Lhota. For the calculation of the erosion threat was used universal soil loss equation (USLE) and runoff characteristics are calculated using the runoff CN - curves. The proposal has the influence of several factors. It's rainfall, vegetation cover, soil characteristics, morphology and other. Several calculations were carried out using the program ERCN.

The aim of this work is to determine the effect of the application of catch crops in crop rotation in the cadastral territory Vrábče in Czech Budweis. Erosion washing away from the land is calculated using the USLE, also compared washing off using conventional crop rotation and intercropping with the application process. Analyze here the influence of intercropping to increase anti-erosion effect of vegetation cover. The resulting values of erosion are transported using erosion of crop rotations with intercropping significantly reduced.