scholarly journals Soil erosion vulnerability in the verde river basin, southern minas gerais

2014 ◽  
Vol 38 (3) ◽  
pp. 262-269 ◽  
Author(s):  
Vinícius Augusto de Oliveira ◽  
Carlos Rogério de Mello ◽  
Matheus Fonseca Durães ◽  
Antônio Marciano da Silva
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Minas Gerais ◽  
Annual Rainfall ◽  
Southeastern Brazil ◽  
Rainfall Erosivity ◽  
Verde River ◽  
Gis Environment ◽  
Elevation Model ◽  
Very High

Soil erosion is one of the most significant environmental degradation processes. Mapping and assessment of soil erosion vulnerability is an important tool for planning and management of the natural resources. The objective of the present study was to apply the Revised Universal Soil Loss Equation (RUSLE) using GIS tools to the Verde River Basin (VRB), southern Minas Gerais, in order to assess soil erosion vulnerability. A annual rainfall erosivity map was derived from the geographical model adjusted for Southeastern Brazil, calculating an annual value for each pixel. The maps of soil erodibility (K), topographic factor (LS), and use and management of soils (C) were developed from soils and their uses map and the digital elevation model (DEM) developed for the basin. In a GIS environment, the layers of the factors were combined to create the soil erosion vulnerability map according to RUSLE. The results showed that, in general, the soils of the VRB present a very high vulnerability to water erosion, with 58.68% of soil losses classified as "High" and "Extremely High" classes. In the headwater region of VRB, the predominant classes were "Very High" and "Extremely High" where there is predominance of Cambisols associated with extensive pastures. Furthermore, the integration of RUSLE/GIS showed an efficient tool for spatial characterization of soil erosion vulnerability in this important basin of the Minas Gerais state.

scholarly journals RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection in Fincha Catchment, Abay River Basin, Ethiopia.

2021 ◽  
Author(s):  
Habtamu Tamiru ◽  
Meseret Wagari
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Soil Loss ◽  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
Landsat 8 ◽  
Land Resources ◽  
Rusle Model ◽  
Factor C ◽  
Significant Factors

Abstract Background: The quantity of soil loss as a result of soil erosion is dramatically increasing in catchment where land resources management is very weak. The annual dramatic increment of the depletion of very important soil nutrients exposes the residents of this catchment to high expenses of money to use artificial fertilizers to increase the yield. This paper was conducted in Fincha Catchment where the soil is highly vulnerable to erosion, however, where such studies are not undertaken. This study uses Fincha catchment in Abay river basin as the study area to quantify the annual soil loss, where such studies are not undertaken, by implementing Revised Universal Soil Loss Equation (RUSLE) model developed in ArcGIS version 10.4. Results: Digital Elevation Model (12.5 x 12.5), LANDSAT 8 of Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), Annual Rainfall of 10 stations (2010-2019) and soil maps of the catchment were used as input parameters to generate the significant factors. Rainfall erosivity factor (R), soil erodibility factor (K), cover and management factor (C), slope length and steepness factor (LS) and support practice factor (P) were used as soil loss quantification significant factors. It was found that the quantified average annual soil loss ranges from 0.0 to 76.5 t ha-1 yr-1 was obtained in the catchment. The area coverage of soil erosion severity with 55%, 35% and 10% as low to moderate, high and very high respectively were identified. Conclusion: Finally, it was concluded that having information about the spatial variability of soil loss severity map generated in the RUSLE model has a paramount role to alert land resources managers and all stakeholders in controlling the effects via the implementation of both structural and non-structural mitigations. The results of the RUSLE model can also be further considered along with the catchment for practical soil loss quantification that can help for protection practices.

The Relationship of Debris Flow Hazards and Rainfall Erosivity in the Bailong River Basin of Southern Gansu Province, China

2014 ◽  
Vol 1073-1076 ◽  
pp. 1614-1619
Author(s):  
Peng Zhang ◽  
He Ping Shu ◽  
Jin Zhu Ma ◽  
Gang Wang ◽  
Li Ming Tian
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Debris Flows ◽  
Temporal Distribution ◽  
Gansu Province ◽  
Annual Precipitation ◽  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
Erosive Rainfall ◽  
Bailong River Basin

Rainfall is one of the main factors that drive soil erosion, leading to environmental problems such as increased frequency and severity of debris flows, and ecosystem damage. Rainfall erosivity represents the potential of rainfall to cause soil erosion, and is determined by a combination of rainfall intensity. The spatial and temporal distribution of rainfall erosivity was analyzed to get its relationship with the debris flows in the Bailong River Basin in China's Gansu Province. The mean annual amount of erosive rainfall accounts for 36.0-47.1% of annual precipitation. The annual mean rainfall erosivity amounts to 798.8 MJ mm ha-1 h-1 yr-1 in the Bailong River Basin. A positive correlation between annual precipitation and annual rainfall erosivity was demonstrated at all 18 rainfall stations. However, further research is required to reveal the key factors that explain soil erosion and debris flows.

scholarly journals RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection: A Case of Fincha Catchment, Ethiopia

2021 ◽  
Vol 14 ◽  
pp. 117862212110462
Author(s):  
Meseret Wagari ◽  
Habtamu Tamiru
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Physical Factors ◽  
Rainfall Erosivity ◽  
Rusle Model ◽  
Raster Calculator ◽  
Gis Environment ◽  
Elevation Model ◽  
The Individual ◽  
P Factor

In this study, Revised Universal Soil Loss Equation (RUSLE) model and Geographic Information System (GIS) platforms were successfully applied to quantify the annual soil loss for the protection of soil erosion in Fincha catchment, Ethiopia. The key physical factors such as rainfall erosivity ( R-factor), soil erodibility ( K-factor), topographic condition (LS-factor), cover management ( C-factor), and support practice ( P-factor) were prepared in GIS environment from rainfall, soil, Digital Elevation Model (DEM), Land use/Land cover (LULC) respectively. The RUSLE equation was used in raster calculator of ArcGIS spatial tool analyst. The individual map of the derived factors was multiplied in the raster calculator and an average annual soil loss ranges from 0.0 to 76.5 t ha−1 yr−1 was estimated. The estimated annual soil loss was categorized based on the qualitative and quantitative classifications as Very Low (0–15 t ha−1 yr−1), Low (15–45 t ha−1 yr−1), Moderate (45–75 t ha−1 yr−1), and High (>75 t ha−1 yr−1). It was found from the generated soil erosion severity map that about 45% of the catchment area was vulnerable to the erosion with an annual soil loss of (>75 t ha−1 yr−1), and this demonstrates that the erosion reduction actions are immediately required to ensure the sustainable soil resources in the study area. The soil erosion severity map generated based on RUSLE model and GIS platforms have a paramount role to alert all stakeholders in controlling the effects of the erosion. The results of the RUSLE model can also be further considered along with the catchment for practical soil loss protection practices.

scholarly journals Quantifying the water soil erosion hazard using RUSLE, GIS, and RS approach: A case study of Al-Qshish River Basin, Lattakia, Syria.

2021 ◽  
Author(s):  
Hazem Ghassan Abdo
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Environmental Sustainability ◽  
Soil Loss ◽  
Coastal Region ◽  
Spatial Average ◽  
Basic Step ◽  
Erosion Hazard ◽  
Gis Environment ◽  
Very High

Abstract Soil erosion is one of the most prominent geomorphological hazards threatening environmental sustainability in the coastal region of western Syria. The current war conditions in Syria has led to a lack of field data and measurements related to assessing soil erosion. Mapping the spatial distribution of potential soil erosion is a basic step in implementing soil preservation procedures mainly in the river catchments. The present paper aims to conduct a comprehensive assessment of soil erosion severity using revised universal soil loss equation (RUSLE) and remote sensing (RS) data in geographic information system (GIS) environment across the whole Al-Qshish river basin. Quantitatively, the annual rate of soil erosion in the study basin was 81.13 t ha− 1 year − 1 with a spatial average reaching 55.18 t ha− 1 year − 1. Spatially, the soil erosion hazard map was produced with classification into five susceptible-zones: very low (40.99%), low (40.49%), moderate (8.90%), high (5.41%) and very high (4.21%). The current study presented a reliable assessment of soil loss rates and classification of erosion-susceptible areas within the study basin. These outputs can be relied upon to create measures for maintaining areas with high and very high soil erosion susceptibility under the current war conditions.

scholarly journals Soil erosion assessment of a Himalayan river basin using TRMM data

2015 ◽  
Vol 366 ◽  
pp. 200-200 ◽  
Author(s):  
A. Pandey ◽  
S. K. Mishra ◽  
A. K. Gautam ◽  
D. Kumar
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Soil Loss ◽  
Daily Rainfall ◽  
Point Of View ◽  
Rainfall Erosivity ◽  
Severe Erosion ◽  
Basin Area ◽  
Very High ◽  
Himalayan River

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

scholarly journals Compartimentação dos elementos do relevo da bacia hidrográfica do arroio Pantanoso – Canguçu/RS, através da proposta dos geomorphons

2020 ◽  
Vol 13 (2) ◽  
pp. 713
Author(s):  
Danilo Da Silva Dutra ◽  
André Ricardo Furlan ◽  
Luís Eduardo De Souza Robaina
Keyword(s):  
Digital Elevation Model ◽  
River Basin ◽  
Spatial Resolution ◽  
Advantages And Disadvantages ◽  
Digital Elevation ◽  
Relief Elements ◽  
Gis Environment ◽  
Elevation Model

O relevo é a base onde todas as populações vivem e desenvolvem suas atividades, derivando dessa relação vantagens e desvantagens, daí a importância de conhecê-lo através do estudo de suas diferentes formas e elementos. Nesse contexto insere-se a importância de metodologias para o seu estudo, sendo que atualmente vivencia-se a expressividade de dados disponíveis para aplicação de geoprocessamento. A partir das geotecnologias pode-se empreender diversas análises sobre o relevo, destacando-se nesse contexto, a proposta dos geomorphons a qual foi aplicada na bacia hidrográfica do arroio Pantanoso. O objetivo da pesquisa é a identificação e análise dos elementos do relevo definido por geomorphons, quais sejam: 1) Planos, 2) Picos, 3) Cristas, 4) Ressaltos, 5) Crista secundária, 6) Encostas, 7) Escavado, 8) Base de encosta, 9) Vales e 10) Fosso. A determinação dos geomorphons foi a partir do processamento em ambiente SIG do Modelo Digital de Elevação (MDE) do Shuttle Radar Topograph Mission (SRTM) com resolução espacial 3 arcsec (90 metros), “L” Lookup (distância em metros) definiu-se como de 20 pixels (1800 metros) e o “T” Theresholdt (nivelamento em graus) definiu-se em 2º. Para visualização do comportamento dos elementos do relevo na área de estudo realizaram-se trabalhos de campo, o que contribuiu para evidenciar a padronização desses elementos. Os quatro elementos geomorphons mais representativos são encostas, vales, cristas e planos. Subdivision of relief elements through the proposal of geomorphons: river basin of arroio Pantanoso - Canguçu/RS A B S T R A C TRelief is the basis where all populations live and develop their activities, deriving from this relation advantages and disadvantages, hence the importance of knowing it through the study of its different forms and elements. In this context, the importance of methodologies for its study is inserted and geoprocessing application for data available for is currently experienced. From the geotechnologies one can undertake several analyzes on the relief, highlighting in this context, the proposal of the geomorphons which was applied in Pantanoso stream basin. The objective of the research is to identify and analyze the elements of the relief defined by geomorphons, namely: 1) Flats, 2) Peaks, 3) Ridges, 4) Shoulders, 5) Spurs, 6)Slopes, 7) Hollows, 8) Footslope, 9) Valley and 10) Pits. The determination of the geomorphons was based on the GIS environment of the Shuttle Radar Topograph Mission (SRTM) Digital Elevation Model (DEM) with spatial resolution 3 arcsec (90 meters), "L" Lookup (distance in meters) was defined as of 20 pixels (1800 meters) and the "T" Theresholdt (leveling in degrees) was defined in 2º. In order to visualize the behavior of the relief elements in the study area, fieldwork was carried out, which contributed to the standardization of these elements. The four most representative geomorphons, which are: Slopes, Valleys, Ridges and Flat.Keywords: SIG, Geomorphons; Canguçu/RS; relief

scholarly journals Reconstruction of Seasonal Net Erosion in a Mediterranean Landscape (Alento River Basin, Southern Italy) over the Past Five Decades

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2306 ◽  
Author(s):  
Nazzareno Diodato ◽  
Gianni Bellocchi
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Rainfall Erosivity ◽  
Monthly Basis ◽  
Antecedent Soil Moisture ◽  
Rainfall Events ◽  
Sediment Yields ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
Basic Scale

In the low Mediterranean basin, late spring and autumn rainfall events have the potential to increase discharge and transport substantial amounts of sediment soil (that is, the net soil erosion from a watershed). For the Alento River Basin (ARB), located in the low Tyrrhenian coast of Italy, we estimated changes of net erosion as dependent on the seasonality of antecedent soil moisture and its control on rainfall-runoff and erosivity. Based on rainfall and runoff erosivity sub-models, we developed a simplified model to evaluate basin-wide sediment yields on a monthly basis by upscaling point rainfall input. For the period 1951–2018, the reconstruction of a time series of monthly net erosion data indicated a decreasing trend of the sediment yield after 1991. Revegetation and land abandonment that occurred in the last decades can explain such a decrease of net erosion, which occurred even when rainfall erosivity increased. This response, obtained at the basic scale, does not exclude that rapidly developing mesoscale convective systems, typically responsible for the heaviest and most destructive rainfall events in the ARB, can affect small catchments, which are the most vulnerable systems to storm-driven flash floods and soil erosion hazards during soil tilling in spring and at beginning of autumn.

Assessment of surface runoff depth changes in Sǎrǎţel River basin, Romania using GIS techniques

2014 ◽  
Vol 6 (3) ◽  
Author(s):  
Costache Romulus ◽  
Fontanine Iulia ◽  
Corodescu Ema
Keyword(s):  
River Basin ◽  
Surface Runoff ◽  
Land Use Changes ◽  
Curve Number ◽  
Annual Rainfall ◽  
Average Annual Rainfall ◽  
Runoff Depth ◽  
Gis Environment ◽  
Quantitative Changes ◽  
Scs Cn

AbstractSǎrǎţel River basin, which is located in Curvature Subcarpahian area, has been facing an obvious increase in frequency of hydrological risk phenomena, associated with torrential events, during the last years. This trend is highly related to the increase in frequency of the extreme climatic phenomena and to the land use changes. The present study is aimed to highlight the spatial and quantitative changes occurred in surface runoff depth in Sǎrǎţel catchment, between 1990–2006. This purpose was reached by estimating the surface runoff depth assignable to the average annual rainfall, by means of SCS-CN method, which was integrated into the GIS environment through the ArcCN-Runoff extension, for ArcGIS 10.1. In order to compute the surface runoff depth, by CN method, the land cover and the hydrological soil classes were introduced as vector (polygon data), while the curve number and the average annual rainfall were introduced as tables. After spatially modeling the surface runoff depth for the two years, the 1990 raster dataset was subtracted from the 2006 raster dataset, in order to highlight the changes in surface runoff depth.

scholarly journals Características de um Rio Cárstico na Bacia do São Francisco (Characteristics of a Cárstico River in the São Francisco Basin)

2017 ◽  
Vol 10 (5) ◽  
pp. 1576
Author(s):  
José Henrique Izidoro Apezteguia Martinez
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
River Basin ◽  
High Sensitivity ◽  
Minas Gerais ◽  
Annual Rainfall ◽  
Flow Temperature ◽  
Temperature Conductivity ◽  
Western State ◽  
The Mean

Este trabalho teve como objeto de estudo o Córrego do Barreado localizado na mesorregião do oeste do estado de Minas Gerais, que tem sua bacia contida na região da bacia do Alto São Francisco sobre relevo cárstico. A Bacia do São Francisco abastece 14,2 milhões de habitantes em 6 estados, sendo assim importante o conhecimento de suas características limnológicas. Para se avaliar as águas do Córrego do Barreado foi efetuado um monitoramento hidrológico mensal de um ano, entre outubro de 2014 e setembro de 2015, os parâmetros avaliados foram: precipitação, vazão, temperatura, condutividade, oxigênio dissolvido, pH, turbidez, nitrito, nitrato, ortofosfato e amônia. O acumulado de chuva anual entre outubro de 2014 e setembro de 2015 foi 1464,8 mm, as médias de cada parâmetro para todo o Córrego do Barreado foram respectivamente: oxigênio dissolvido (OD) – 2,83 mg/l, pH – 7,25, turbidez – 53,6, nitrito – 0,03 mg/l de NO2, nitrato – 0,14 mg/l de NO3, ortofosfato – 0,05 mg/l de P, amônia – 0,16 mg/l NH3. Conclui se que a combinação da impropriedade da qualidade das águas, ocupação do solo e alta sensibilidade dos aquíferos cársticos amplificam efeitos poluidores no Córrego do Barreado, que alteram suas características com efeito percebido principalmente nos valores de oxigênio dissolvido.Palavras-chave: água, relevo cárstico, monitoramento hidrológico, usos da água.A B S T R A C TThis study object was the Córrego do Barreado located in the mesoregion of the western state of Minas Gerais, which has its basin inserted in the region of the Upper São Francisco basin on karst relief. The São Francisco River Basin supplies 14.2 million inhabitants in 6 states, so it is important to know its limnological characteristics. The following parameters were evaluated: rainfall, flow, temperature, conductivity, dissolved oxygen, pH, turbidity, nitrite, precipitation, precipitation, nitrate, orthophosphate and ammonia. The annual rainfall accumulated between October 2014 and September 2015 was 1464.8 mm, the mean of each parameter for the entire Barreado Stream were: OD - 2.83 mg / l, pH - 7.25, turbidity - 53.6, nitrite – 0.03 mg/l de NO2, nitrate - 0.14 mg/l de NO3, orthophosphate - 0.05 mg/l de P, ammonia - 0.16 0,16 mg/l NH3. It is concluded that the combination of water quality improperness, soil occupation and high sensitivity of the karstic aquifers amplify polluting effects in the Barreado Stream, which alter their characteristics with a perceived effect mainly on the values of dissolved oxygen.Keywords: water, carstic relief, hidrologic monitoring, warer uses. 

Sign in / Sign up

Export Citation Format

Share Document