scholarly journals Crop-management factor calculation using weights of spatio-temporal distribution of rainfall erosivity

2018 ◽  
Vol 13 (No. 3) ◽  
pp. 150-160
Author(s):  
Brychta Jiří ◽  
Janeček Miloslav ◽  
Walmsley Alena

Inappropriate integration of USLE or RUSLE equations with GIS tools and Remote Sensing (RS) data caused many simplifications and distortions of their original principles. Many methods of C and R factor estimation were developed due to the lack of optimal data for calculations according to original methodology. This paper focuses on crop-management factor evaluation (C) weighted by fully distributed form of rainfall erosivity factor (R) distribution throughout the year. We used high resolution (1-min) data from 31 ombrographic stations (OS) in the Czech Republic (CR) for monthly R map creation. All steps of the relatively time-consuming C calculation were automated in GIS environment with an innovative procedure of R factor weight determination for each agro-technical phase by land parcel geographic location. Very high spatial and temporal variability of rainfall erosivity within each month and throughout the year can be observed from our results. This highlights the importance of C factor calculation using a correctly presented method with emphasis on the geographic location of given land parcels.

2017 ◽  
Vol 31 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Danang Sri Hadmoko ◽  
Franck Lavigne ◽  
Junun Sartohadi ◽  
Christopher Gomez ◽  
D Daryono

Java Island, the most populated island of Indonesia, is prone to landslide disasters. Their occurrence and impact have increased mainly as the result of natural factors, aggravated by human imprint. This paper is intended to analyse: (1) the spatio-temporal variation of landslides in Java during short term and long-term periods, and (2) their causative factors such as rainfall, topography, geology, earthquakes, and land-use. The evaluation spatially and temporally of historical landslides and consequences were based on the landslide database covering the period of 1981 – 2007 in the GIS environment. Database showed that landslides distributed unevenly between West Java (67 %), Central Java (29 %) and East Java (4 %). Slope failures were most abundant on the very intensively weathered zone of old volcanic materials on slope angles of 30O – 40O. Rainfall threshold analysis showed that shallow landslides and deep-seated landslides were triggered by rainfall events of 300 – 600 mm and > 600 mm respectively of antecedent rainfall during 30 consecutive days, and many cases showed that the landslides were not always initiated by intense rainfall during the landslide day. Human interference plays an important role in landslide occurrence through land conversion from natural forest to dryland agriculture which was the host of most of landslides in Java. These results and methods can be used as valuable information on the spatio-temporal characteristics of landslides in Java and their relationship with causative factors, thereby providing a sound basis for landslide investigation in more detail.


2009 ◽  
Vol 138 (8) ◽  
pp. 1105-1113 ◽  
Author(s):  
E. AFONSO ◽  
P. THULLIEZ ◽  
E. GILOT-FROMONT

SUMMARYThe aim of this study was to analyse the spatio-temporal dynamics of Toxoplasma gondii infection in long-term monitoring of domestic cats (8–15 years) in three populations living in rural France. Overall seroprevalence was 52·7% (modified agglutination test ⩾1:40). Incidence was 0·26–0·39 seroconversions/cat per year, and the estimated rate of soil contamination by T. gondii oocysts ranged between 31 and 3600 oocysts/m2 per year, depending on the population. Incidence risk in cats was related to mean precipitation, explaining both the spatial and temporal variability in risk: local conditions explained differences between the three study sites and incidence risk increased during rainy years. This study brings rare quantitative information on the level of contamination of the environment by T. gondii oocysts, and suggests that the spatio-temporal distribution of incidence risk in cats may reflect both the influence of rain on prey populations and infectivity of T. gondii oocysts.


Author(s):  
Luis Augusto Di Loreto Di Raimo ◽  
Ricardo Santos Silva Amorim ◽  
Eduardo Guimarães Couto ◽  
Rodolfo Luiz Bezerra Nóbrega ◽  
Gilmar Nunes Torres ◽  
...  

The impact of rainfall on surfaces lacking vegetal cover can dissociate soil particles, thereby initiating the erosion process. This is known as rainfall erosivity and is expressed by the R factor in the Universal Soil Loss Equation. Agricultural areas often show seasonally erosion susceptibility throughout the year due to oscillations of the soil exposure rate and the vegetation change. Considering that approximately 30 million ha of the Mato Grosso State in Brazil is used for agriculture, this study aimed to predict and map the spatial and temporal variability of its territory. We evaluated the monthly (EI30) and annual (R) erosivity for 158 rain gauge stations and spatialized the values of EI30 and R by the Kriging method. It was observed that R values ranked as very high in the north, and high and medium-high in the south of Mato Grosso state. The mean value is 8835 MJ mm ha-1 h-1 year-1, considered high. Ninety-one percent of the annual erosivity was concentrated in the period between October and April, corresponding to the rainy season. The highest R factor values were found in the macro-regions of the northwest, north, west and medium-north of Mato Grosso State.


Author(s):  
Bastian Saez ◽  
Jose Vargas Baecheler ◽  
Alfonso Gutierrez-Lopez

The Norte Grande of Chile (17°S-29°S) features arid regions, where rainfall is generally convective with high spatial and temporal variability, which is the cause of floods with large amounts of sediments due to water erosion. The most relevant factor in erosive processes in arid regions is erosivity, which can be quantified by the RUSLE R-factor, but precipitation data are required every 30 minutes, however, these records are limited. The ones that are available are not enough to characterize it spatially. Consequently, the objective of this study is to evaluate regression models of the annual erosivity using rainfall aggressiveness indices as an explanatory variable, with the aim of analyzing the spatial behavior of erosion. Correlations were made between the maximum intensity in 30 minutes (I30) to the maximum intensity in one hour (I60), which were useful for calculating the R-factor for stations with hourly data by applying a correction factor to I60 determined by the correlations. Four regression models were established for each of the six aggressiveness indices and a relationship was selected through validation, using stations with few years of continuous recording. The selected equation allowed generating 103 spatially distributed erositivy-values, which served to make a subsequent co-kriging, in order to make a spatial analysis of rainfall erosivity. Results showed that there are under-estimations of I30, however, they are considered acceptable due to the efficiency obtained (Nash-Sutcliffe = 0.787). The calculated R-factor data-points allowed selection of the best-fit potential equation, which uses the mean annual rainfall as a predictor


2021 ◽  
Vol 14 (3) ◽  
pp. 1220
Author(s):  
Maíra Iaê Savioli Rocha ◽  
Diego Tarley Ferreira Nascimento

Usualmente empregadas pelos povos tradicionais, as queimadas também têm sido utilizadas para o desmatamento de vegetação natural e incorporação de atividades agropecuárias. Diante desse contexto, tem-se como objetivo analisar a distribuição espaço-temporal dos focos de queimadas no bioma Cerrado no período de 1999 a 2018, verificando sua ocorrência entre os diferentes tipos de cobertura e uso do solo, no intuito de avaliar a hipótese de que a prática de queimadas esteja recorrentemente associada à desmatamentos e à implantação de atividades agropecuárias. Para tanto, foram compilados, organizados e processados em ambiente SIG, arquivos vetoriais de focos de queimadas, a partir do Banco de Dados de Queimadas (BDQ/INPE), e arquivos raster de mapeamentos de cobertura e uso do solo do Cerrado, elaborados e disponibilizados pelo Projeto MapBiomas, ambos dados referente ao bioma Cerrado e ao recorte temporal de 1999 a 2018. Em termos médios, verifica-se a ocorrência de 65.513 focos anuais de queimadas, porém, em alguns anos a quantidade de queimadas atinge o montante de 137.918 focos, como visto em 2007. Há uma concentração das queimadas no período seco, especialmente, no trimestre agosto-setembro-outubro, que responde por 72% das ocorrências anuais. A maior densidade de queimadas é percebida ao longo da fronteira agrícola na região do MATOPIBA e próxima ao Arco do Desmatamento, nos estados do Maranhão, Tocantins e de Mato Grosso, ao passo que evidencia-se a maior incidência das queimadas sobre determinadas classes de cobertura e uso do solo, sobretudo representadas por formações savânicas e campestres.  Space-temporal distribution of fires in the Cerrado biome (1999/2018) and their occurence according to different types of coverage and soil uses A B S T R A C TUsually employed by traditional communities, fires have also been used to deforest and incorporate agricultural activities. Given this context, the objective is to analyze the spatio-temporal distribution of the fires in the Cerrado biome, from 1999 to 2018, verifying their occurrence between the different types of cover and land use, in order to assess the hypotheses that the practice of fires is recurrently associated with deforestation and the implementation of agricultural activities. For this purpose, were compiled, organized and processed in a GIS environment, fires focus from the Burn Database of the National Institute for Space Research and mappings of cover and land use, elaborated and availabled by the MapBiomas Project, both data referring to the Cerrado biome and over the years 1999 to 2018. On average, there are 65,513 annual fires, but in some years the amount of burns reaches the amount of 137,918 – as seen in 2007. There is a concentration of fires in the dry period, mainly in the August-September-October, which accounts for 72% of annual fires. The highest density of fires occurs mainly along the agricultural frontier in the MATOPIBA region and close to the Arc of Deforestation, specifically in the states of Maranhão, Tocantins and Mato Grosso, while there is a greater incidence of fires on certain classes of coverage and land use, especially represented by savanna and grassland formation, which corroborates the hypothesis of the use of fires to convert vegetation cover into anthropic uses.Keywords: Fires, Cerrado, Cover and land use.


2013 ◽  
Vol 38 (7) ◽  
pp. 1286-1294 ◽  
Author(s):  
Zong-Xin LI ◽  
Yuan-Quan CHEN ◽  
Qing-Cheng WANG ◽  
Kai-Chang LIU ◽  
Wang-Sheng GAO ◽  
...  

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