Soil Erosion Susceptibility Prediction in Railway Corridors Using RUSLE, Soil Degradation Index and the New Normalized Difference Railway Erosivity Index (NDReLI)

This study presents a remote sensing-based index for the prediction of soil erosion susceptibility within railway corridors. The empirically derived index, Normalized Difference Railway Erosivity Index (NDReLI), is based on the Landsat-8 SWIR spectral reflectances and takes into account the bare soil and vegetation reflectances especially in semi-arid environments. For the case study of the Botswana Railway Corridor (BRC), the NDReLI results are compared with the RUSLE and the Soil Degradation Index (SDI). The RUSLE model showed that within the BRC, the mean annual soil loss index was at 0.139 ton ha−1 year−1, and only about 1% of the corridor area is susceptible to high (1.423–3.053 ton ha−1 year−1) and very high (3.053–5.854 ton ha−1 year−1) soil loss, while SDI estimated 19.4% of the railway corridor as vulnerable to soil degradation. NDReLI results based on SWIR1 (1.57–1.65 μm) predicted the most vulnerable areas, with a very high erosivity index (0.36–0.95), while SWIR2 (2.11–2.29 μm) predicted the same regions at a high erosivity index (0.13–0.36). From empirical validation using previous soil erosion events within the BRC, the proposed NDReLI performed better that the RUSLE and SDI models in the prediction of the spatial locations and extents of susceptibility to soil erosion within the BRC.

Database of rainfall erosivity factor for 141 locations in Brazil.

Soil erosion is a serious agricultural and environmental problem considered as a threat to sustainable development around the world. Rainfall is the primary cause of soil erosion, what leads the knowledge of its potential to cause soil erosion (rainfall erosivity – R-factor) to be a valuable tool for the design of land conservation best practices. As Brazil has a lack of information about rainfall erosivity, the present paper has determined the R-factor of 141 pluviographic stations distributed over Brazilian territory. Initially, erosive rainfalls were identified, and then the EI30 erosivity index was used to obtain the rainfall erosivity values. Regression models for the estimation of rainfall erosivity using daily rainfall data were established based on the correlation between the monthly average values of erosivity and the modified Fournier index. Results showed that the annual rainfall erosivity in the Brazilian stations analyzed ranged from 368.7 to 16,850.6 MJ mm ha-1 h-1 year-1. The results presented help to expand information about the spatial distribution of rainfall erosivity in Brazil, contributing to better conservation planning of land use.

Application of Angot precipitation index in the assessment of rainfall erosivity: Vojvodina Region case study (North Serbia)

The paper aims to provide an overview of the most important parameters (the occurrence, frequency and magnitude) in Vojvodina Region (North Serbia). Monthly and annual mean precipitation values in the period 1946–2014, for the 12 selected meteorological stations were used. Relevant parameters (precipitation amounts, Angot precipitation index) were used as indicators of rainfall erosivity. Rainfall erosivity index was calculated and classified throughout precipitation susceptibility classes liable of triggering soil erosion. Precipitation trends were obtained and analysed by three different statistical approaches. Results indicate that various susceptibility classes are identified within the observed period, with a higher presence of very severe rainfall erosion in June and July. This study could have implications for mitigation strategies oriented towards reduction of soil erosion by water.

ASSESSMENT AND MAPPING OF RAINFALL EROSIVITY INDEX (R) FOR MAJHA REGION, PUNJAB IS A STATE IN NORTHERN, INDIA

Purpose: This study gives a critical assessment of the rainfall erosivity factor (R) for selected sites in the Majha region, representing different locations use of mean monthly rainfall data. Methodology: By applying empirical methods, the rainfall intensity for all the locations were obtained and was further determined at three different intervals of 30-minutes, 45-minutes and 60-minutes, respectively. The rainfall erosivity factor (R) was calculated by the revised universal soil loss equation (RUSLE). Main Findings: Using RUSLE, the rainfall erosivity factor (R) for each of the locations was measured as follows; EI = 3878.49 (MJmmha-1hr-1), EI = 4013.71 (MJmmha-1hr-1), EI = 4302.24 (MJmmha-1hr-1) for Majha region of Amritsar, Tarntaran and Pathankot respectively. A close observation of the data obtained revealed that as rainfall intensity increased with the duration, the rainfall erosivity index reduced or decreased. Implications of study: Nevertheless, it is expected that if proper cover crop and management practices are applied despite the region, the study area falls within, rainfall erosivity can be cushioned, thus reducing further erosion tendencies and enhancing food production chances from productive lands within the area. The novelty of study: The rainfall erosivity factor (R) was calculated by the revised universal soil loss equation (RUSLE).

Susceptibility to erosion risks in soils dedicated to the pineapple cultivation in the state of Valle del Cauca, Colombia

In Colombia almost half of the soils are prone to erosion, where Valle del Cauca is one of the most affected departments with respect to its severity. In order to identify the susceptibility to erosion risks in terms of the rainfall erosivity and the incidence of the topographic factor in the main pineapple producing municipalities of the department, a study was carried out that contemplated the historical climatological information of more than 50 years, for which all available weather stations in the area were selected. The erosivity index (R–EI30), the modified Fournier index (MFI), and the topographic factor (LS) were estimated. The results indicate that the average MFI values ranged between (91.31 and 582.79) which correspond to the moderate, high and very high categories, the results of R-EI30 presented moderate, high, very high and extremely severe values (5076.91 MJ.mm.ha-1 - 22718.83 MJ.mm.ha-1), while the highest values of the topographic factor (with slopes up to 81°) coincide with the upper part of the river basin Dagua, predominantly in the municipality of Dagua. These values indicate that the soils in the area are susceptible to erosion risks depending on the rainfall erosivity and the topographic factor at a moderate, high and very high level, which can generate significant soil losses, and therefore they should be considered when establishing a pineapple crop.

A Rainfall Erosivity database for Brazil from MSWEP rainfall dataset

<p>In erosion studies the behavior of rainfall is primordial, since rain is responsible for the first stage of the erosion process: the detachment of soil particles. The erosive potential of rainfall, erosivity, is considered in the universal soil loss equations (R)USLE family through the parameter R, or R factor. This factor is calculated from the rainfall erosivity index, which is the product of kinetic energy of the rain by the maximum intensity of the rain of 30 minutes of duration. As sub-hour rainfall data is not always available, there are in the literature a series of equations obtained from regression, which use monthly and annual rainfall and present a good estimate of erosivity for your study site. In Brazil, in addition to limitations regarding the temporal resolution of rainfall data, there are also spatial limitations. Monitoring stations are concentrated mostly in urbanized areas, usually near the coast. The other regions, such as agricultural and forest areas, are poorly monitored, and these areas are of great interest for monitoring erosion, not only because they are periodically exposed soil areas, but also because of the high rainfall rates that humid forests like Amazon have. MSWEP is a rainfall database that combines observed, satellite and reanalysis data. It has global coverage, temporal resolution of 3 hours, spatial 0.1º and data from 1979 to 2016. Databases like this have great potential to be used in areas such as Brazil, due to its spatial and temporal resolution. In this context, considering the relevance that the soil loss equations still present today, this work developed a rainfall erosivity database entitled REDB-BR (Rainfall Erosivity Database for Brazil). It provides the R factor in a 0.1º resolution grid, developed with 37 years of rainfall data from the MSWEP dataset. The R factor was calculated trough 73 erosivity index regression equations, which mostly uses the Modified Fournier Index (MFI), a relation between monthly precipitation and annual precipitation. Thiessen polygons were used in order to spatialize and define the areas of each equation. Over the Brazilian territory, the R factor ranges from 1.200 to 20.000 MJ mm ha-1 h-1 year-1, with the higher values in the North region, and the lowest values in the Northeast. The spatial patterns of erosivity are very similar to the climatic zones of Brazil. The R factor map takes advantage of MSWEP dataset and presents a spatial resolution very detailed to a country with continental scale such as Brazil. The database includes the equations shapefile and table, Thiessen Polygons shapefile and the R factor map in raster format, which allows more possibilities of application. The database can be accessed at <https://zenodo.org/record/4428308#.X_hxsOhKiUk>. We identified sudden changes in behavior between the delimited areas, which suggests a need for more regression equations in order to better represent the behavior of the erosivity in the Brazilian territory.</p>

Precipitation Patterns and Rainfall Erosivity Return Period Under Savanna Conditions in Formosa, Goiás, Brazil

Losses of soil and nutrients affect a large part of agricultural areas in tropical regions, regardless of the level of technology adopted. This study evaluated the physical attributes and erosivity indices associated with rainfall patterns and return periods in the region of Formosa, State of Goiás, Brazil. Using series of pluviographic (2002-2008) and pluviometric (1975-1998) data from a station located at municipality of Formosa, the erosive potential (EI30 and KE>25), rainfall patterns (advanced, intermediate and delayed) and the erosivity associated with the rainfall return periods were determined. The average annual rainfall of the region was 1,391.6 mm with 87.4% of the rains concentrated in October to March. The average annual values of EI30 and KE>25 corresponded to 8,041.6 MJ mm ha-1 h-1 year-1 and 125.7 MJ ha-1 year-1, respectively. The months of the year did not differ based on rainfall pattern. The advanced hydrological pattern had the highest frequency of occurrence, followed by the delayed and intermediate patterns. The highest EI30 and KE>25 indices for individual rainfall seasons occurred under the intermediate and the advanced patterns in February and under the intermediate pattern in October for the index KE>25. The average annual erosivity index (R factor of USLE) (8041.6 MJ mm ha-1 h-1 year-1) is expected to occur at least once every 1.89 years, corresponding to a probability of occurrence of 52.84%. The average annual values of EI30 estimated for the return periods of 2, 5, 10, 25, 50 and 100 years were 8,230, 10,225, 10,889, 11,222, 11,421 and 11,488 MJ mm ha-1 h-1 year-1, respectively.

Estimation of Erosion with Geographic Information Systems (GIS) in the TAHURA RADEN SOERJO Fire Areas

The Ledug Block is one of the areas in TAHURA R Soerjo which is experiencing fire. The fire causes the existing land cover to change or decrease, with the reduced land cover, the land will be easily exposed to surface runoff. This study aims to calculate the erosion rate in the TAHURA R Soerjo Ledug Block using the USLE equation, visual presentation of erosion using the Goegraphic Information System (GIS). This research was conducted in December 2018 in the rehabilitation area of Tahura R Soerjo Priug Ledug Block, Pasuruan. The method used is the Geographic Information System (GIS) whose data is sourced from calculations with the USLE method. The results of the study are the rain erosivity index (R) obtained from the month rainfall in 2018. The soil at the study site in each SUL is dusty clay. The vegetation in the research location in each SUL is in the form of bushes and added to SUL 3 there are several trees. The average erosion rate is 0.034 tons / ha / year. Erosion hazard classes that occur at the research location are included in class I (very mild). Enriching the land cover by planting trees with tree stands needs to be done so that the land is tightly closed and better withstand surface runoff.

Spatial and temporal rainfall variability and erosivity: Case of the Issen watershed, SW-Morocco

The Issen basin is a dry area affected by climate variability and desertification. It is located in high spot of Moroccan flora biodiversity that includes argan tree ecosystem as a part of the Western High Atlas (WHA). The objective of this work is to assess rainfall variability and erosivity as determining factors of soil erosion and vegetation cover degradation. The results reveal an arid to superior semi-arid climate where annual rainfall range from 200 mm in the centre of the Argana corridor, to 500 mm in the snow-covered northern foothills. The analysis of the 37 years of rainfall data indicate a coefficient of variation Cvis about67%. The erosivity index presents a high variability range from 34 to more than 81 MJ.mm/ha.h.yr in the wettest areas, indicating considerable soil erosion. In addition, the basin suffering from severe periods of drought due to the occurrence of the continuous decrease of the accumulated precipitation. Eventually, the rainfall variability and erosivity can affect ecosystem function and services (ecosystem degradation, water availability, etc).

Avaliação do padrão hidroclimático e da erosividade no Sertão de Pernambuco

A erosão hídrica é um dos grandes problemas que atingem regiões com potenciais agrícolas e áreas com propensão para deslizamento de terras. A chuva é considerada o fator climático que exerce maior influência no processo erosivo, especialmente nos trópicos por causa da sua distribuição temporal, espacial, características físicas e duração. Este trabalho teve como objetivo determinar o padrão hidrológico e o índice de erosividade no sertão Pernambucano, visando contribuir com informações estratégicas para gestão agrícola e ambiental na região. Foram utilizados dados pluviométricos horários de 2000 a 2017 localizados no município de Petrolina, disponibilizados pela (APAC). A partir dos dados da precipitação, utilizou-se o aplicativo Climap 3.0 para avaliar os eventos extremos de precipitação e o padrão hidrológico, bem como determinou-se por meio de equações o índice de erosividade para a região. No período analisado os maiores valores da precipitação ocorreram entre os meses de janeiro e abril e identificou-se 8 anos consecutivos de seca na região. Os resultados apontam que houve tendências significativas nas séries de dados, a erosividade foi considerada fraca a moderada em sua maioria, e o padrão hidrológico mais frequente foi o padrão intermediário, resultando uma alta suscetibilidade dos solos da região em sofrer erosão hídrica.Evaluation of hydroclimatic pattern and erosivity Sertão of Pernambuco A B S T R A C T Water erosion is one of major problems affecting regions with agricultural potential and landslide-prone areas. Rain is considered the climatic factor that exerts greatest influence on erosive process, especially in tropics because its temporal, spatial distribution, physical characteristics and duration. This work purpose to determine hydrological pattern and erosivity index in Pernambucano Sertão, to contribute with strategic information for agricultural and environmental management in region. Rainfall data from 2000 to 2017 located in city of Petrolina, provided by (APAC) were used. From the rainfall data, the Climap 3.0 was used to evaluate the extreme rainfall events and hydrological pattern, as well to determine through equations the erosivity index for region. During analyzed period the highest rainfall values occurred between January and April and 8 consecutive years of drought were identified in region. The results indicate that there were significant trends in data series, erosivity was considered weak to moderate mostly, and most frequent hydrological pattern was the intermediate pattern, resulting in high susceptibility of region's soils to water erosion.Keywords: climate variability, hydrological pattern, extreme indexes.