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Spatio-Temporal Variation in Rainfall Erosivity over Jordan Using Annual and Seasonal Precipitation  [PDF]
Y. Farhan, S. Alnawaiseh
Natural Resources (NR) , 2018, DOI: 10.4236/nr.2018.96016
Abstract:
The objective of this research is to estimate the annual and seasonal rainfall erosivity over Jordan based on three different regression models. Readily available annual and seasonal precipitation data with long records (40 - 53 years) pertaining to 40 weather stations were utilized to estimate rainfall erosivity. The spatial distribution of rainfall erosivity over Jordan is controlled largely by morphological (relief) and climatic factors. The lowest R-values (28 MJ mm.ha-1.h-1.yr-1) are found in the arid zone, where the average annual rainfall is below 100 mm, whereas the highest R-values are found in the northern highlands (505 MJ mm.ha-1.h-1.yr-1) where the average annual rainfall approaches 650 mm. The correlation between annual and seasonal precipitation (mm) and annual erosivity exhibits a very strong relationship (R varies from 0.964 to 1.0, and all correlations are significant at 0.01 level [2-tailed test]). Moderate positive correlations were achieved
Rainfall Erosivity in Southeastern Nigeria
MN Ezemonye, CN Emeribe
Ethiopian Journal of Environmental Studies and Management , 2012,
Abstract: In developing land management plans to minimize erosion problem, it is imperative to provide quantitative information on aggressiveness of storms for identifying areas in the landscape which are sensitive to disturbances. The study established that rainfall erosivity (R) indices over Southeastern Nigeria range from very low to very high erosivity. Periods of very low erosivity coincided with the dry season months in the region while the very high R coincided with the rainy season peak periods (June-September). Calabar Owerri and Port-Harcourt recorded the highest erosive storms/ more months of very high erosivity index. The deterministic relationship between kinetic energy of rains and erosivity pattern observed for the different stations showed that erosive rains contribute significantly to detachment of soil materials in the study area. The need for proper land use management and maintenance of surface vegetal covers cannot be overemphasized with increased weather variability. Monitoring of hydrologic regime and climate –related factors in the region as well as defining areas most vulnerable to erosion would help in erosion disaster management.
Mapping rainfall erosivity at a regional scale: a comparison of interpolation methods in the Ebro Basin (NE Spain)  [PDF]
M. Angulo-Martínez,M. López-Vicente,S. M. Vicente-Serrano,S. Beguería
Hydrology and Earth System Sciences Discussions , 2009,
Abstract: Rainfall erosivity is a major causal factor of soil erosion, and it is included in many prediction models. Maps of rainfall erosivity indices are required for assessing soil erosion at the regional scale. In this study a comparison is made between several techniques for mapping the rainfall erosivity indices: i) the RUSLE R factor and ii) the average EI30 index of the erosive events over the Ebro basin (NE Spain). A spatially dense precipitation data base with a high temporal resolution (15 min) has been used. Global, local and geostatistical interpolation techniques were employed to produce maps of the rainfall erosivity indices, as well as mixed methods (regression plus local interpolation). To determine the reliability of the maps several goodness-of-fit and error statistics were computed, using a cross-validation scheme. All methods represented correctly the spatial patterns of both erosivity indices, but the mixed approaches tended to be better overall considering the validation statistics. Additionally, they allowed identifying statistically significant relationships between rainfall erosivity and other geographical variables, as elevation and distance to the water bodies. All models had a relatively high uncertainty, caused by the high variability of rainfall erosivity indices both in time and space, what stresses the importance of using the longest data series available with a good spatial coverage.
Mapping rainfall erosivity at a regional scale: a comparison of interpolation methods in the Ebro Basin (NE Spain)
M. Angulo-Martínez, M. López-Vicente, S. M. Vicente-Serrano,S. Beguería
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2009,
Abstract: Rainfall erosivity is a major causal factor of soil erosion, and it is included in many prediction models. Maps of rainfall erosivity indices are required for assessing soil erosion at the regional scale. In this study a comparison is made between several techniques for mapping the rainfall erosivity indices: i) the RUSLE R factor and ii) the average EI30 index of the erosive events over the Ebro basin (NE Spain). A spatially dense precipitation data base with a high temporal resolution (15 min) was used. Global, local and geostatistical interpolation techniques were employed to produce maps of the rainfall erosivity indices, as well as mixed methods. To determine the reliability of the maps several goodness-of-fit and error statistics were computed, using a cross-validation scheme, as well as the uncertainty of the predictions, modeled by Gaussian geostatistical simulation. All methods were able to capture the general spatial pattern of both erosivity indices. The semivariogram analysis revealed that spatial autocorrelation only affected at distances of ~15 km around the observatories. Therefore, local interpolation techniques tended to be better overall considering the validation statistics. All models showed high uncertainty, caused by the high variability of rainfall erosivity indices both in time and space, what stresses the importance of having long data series with a dense spatial coverage.
Spatial and temporal variability of rainfall erosivity factor for Switzerland
K. Meusburger, A. Steel, P. Panagos, L. Montanarella,C. Alewell
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2012,
Abstract: Rainfall erosivity, considering rainfall amount and intensity, is an important parameter for soil erosion risk assessment under future land use and climate change. Despite its importance, rainfall erosivity is usually implemented in models with a low spatial and temporal resolution. The purpose of this study is to assess the temporal- and spatial distribution of rainfall erosivity in form of the (Revised) Universal Soil Loss Equation R-factor for Switzerland. Time series of 22 yr for rainfall (10 min resolution) and temperature (1 h resolution) data were analysed for 71 automatic gauging stations distributed throughout Switzerland. Regression-kriging was used to interpolate the rainfall erosivity values of single stations and to generate a map for Switzerland. Latitude, longitude, average annual precipitation, biogeographic units (Jura, Midland, etc.), aspect and elevation were used as covariates, of which average annual precipitation, elevation and the biographic unit (Western Central Alps) were significant (p<0.01) predictors. The mean value of long-term rainfall erosivity is 1330 MJ mm ha 1 h 1 yr 1 with a range of lowest values of 124 MJ mm ha 1 h 1 yr 1 at an elevated station in Grisons to highest values of 5611 MJ mm ha 1 h 1 yr 1 in Ticino. All stations have highest erosivity values from July to August and lowest values in the winter months. Swiss-wide the month May to October show significantly increasing trends of rainfall erosivity for the observed period (p<0.005). Only in February a significantly decreasing trend of rainfall erosivity is found (p<0.01). The increasing trends of rainfall erosivity in May, September and October when vegetation cover is scarce are likely to enhance soil erosion risk for certain agricultural crops and alpine grasslands in Switzerland.
Spatial and temporal variability of rainfall erosivity factor for Switzerland
K. Meusburger,A. Steel,P. Panagos,L. Montanarella
Hydrology and Earth System Sciences Discussions , 2011, DOI: 10.5194/hessd-8-8291-2011
Abstract: Rainfall erosivity, considering rainfall amount and intensity, is an important parameter for soil erosion risk assessment under future land use and climate change. Despite its importance, rainfall erosivity is usually implemented in models with a low spatial and temporal resolution. The purpose of this study is to assess the temporal- and spatial distribution of rainfall erosivity (R-factor) in Switzerland. Time series of 22 yr for rainfall (10 min resolution) and temperature (1 h resolution) data were analysed for 71 automatic gauging stations distributed throughout Switzerland. Multiple regression was used to interpolate the erosivity values of single stations and to generate a map for Switzerland. Latitude, longitude, average annual precipitation, biogeographic units (Jura, Midland, etc.), aspect and elevation were used as covariates, of which average annual precipitation, elevation and the biographic unit (Western Alps) were significant predictors. The mean value of long-term rainfall erosivity is 1323 MJ mm ha 1 h 1 yr 1 with a range of lowest values of 124 MJ mm ha 1 h 1 yr 1 at an elevated station in Grisons to highest values of 5611 MJ mm ha 1 h 1 yr 1 in Ticino. All stations have highest erosivity values from July to August and lowest values in the winter month. Swiss-wide the month May to October show significantly increasing trends of erosivity (p<0.005). Only in February a significantly decreasing trend of rainfall erosivity is found (p<0.01). The increasing trends of erosivity in May, September and October when vegetation cover is susceptible are likely to enhance soil erosion risk for certain agricultural crops and alpine grasslands in Switzerland.
A comparative study of rainfall erosivity for eastern and western Slovenia
Andrej Ceglar, Zalika repin ek, Vesna Zupanc, Lu ka Kajfe -Bogataj
Acta agriculturae Slovenica , 2008, DOI: 10.2478/v10014-008-0013-6
Abstract: Climate in Slovenia has changed notably over the past century. As regional temperatures have risen, a more vigorous hydrologic cycle ensued; in many places the intensity of rainstorms has become greater. The seasonal distributions of rainfall has changed with significant implications for patterns of vegetation growth and hence for soil erosion. Due to predicted climate change increased frequency of extreme precipitation events can be expected during the time when soil is without plant cover and exposed to the erosive forces. In addition to ample daily and several day precipitation events, water erosion occurs with heavy rainfalls that last from couple of minutes to several hours. Overview of rainfall intensity index and rainfall erosivity, calculated with adapted USLE (universal soil loss equation) method, is given for three meteorological stations in Slovenia for period 1991-2006. Analyzed locations are situated on different climate areas with noticeable different rainfall regime at western (Bilje at Nova Gorica, Rate e) and eastern (Murska Sobota) part of Slovenia.
Estimation of local rainfall erosivity using artificial neural network
Teodorico Alves Sobrinho,Caroline Alvarenga Pertussatti,Lais Cristina Soares Rebucci,Paulo Tarso Sanches de Oliveira
Ambiente e água : An Interdisciplinary Journal of Applied Science , 2011,
Abstract: The information retrieval of local values of rainfall erosivity is essential for soil loss estimation with the Universal Soil Loss Equation (USLE), and thus is very useful in soil and water conservation planning. In this manner, the objective of this study was to develop an Artificial Neural Network (ANN) with the capacity of estimating, with satisfactory accuracy, the rainfall erosivity in any location of the Mato Grosso do Sul state. We used data from rain erosivity, latitude, longitude, altitude of pluviometric and pluviographic stations located in the state to train and test an ANN. After training with various network configurations, we selected the best performance and higher coefficient of determination calculated on the basis of data erosivity of the sample test and the values estimated by ANN. In evaluating the results, the confidence and the agreement indices were used in addition to the coefficient of determination. It was found that it is possible to estimate the rainfall erosivity for any location in the state of Mato Grosso do Sul, in a reliable way, using only data of geographical coordinates and altitude.
Rainfall erosivity and rainfall return period in the experimental watershed of Aracruz, in the coastal plain of Espirito Santo, Brazil
Martins, Sérgio Gualberto;Avanzi, Junior Cesar;Silva, Marx Leandro Naves;Curi, Nilton;Norton, Lloyd Darrell;Fonseca, Sebasti?o;
Revista Brasileira de Ciência do Solo , 2010, DOI: 10.1590/S0100-06832010000300042
Abstract: knowledge on the factors influencing water erosion is fundamental for the choice of the best land use practices. rainfall, expressed by rainfall erosivity, is one of the most important factors of water erosion. the objective of this study was to determine rainfall erosivity and the return period of rainfall in the coastal plains region, near aracruz, a town in the state of espírito santo, brazil, based on available data. rainfall erosivity was calculated based on historic rainfall data, collected from january 1998 to july 2004 at 5 min intervals, by automatic weather stations of the aracruz cellulose s.a company. a linear regression with individual rainfall and erosivity data was fit to obtain an equation that allowed data extrapolation to calculate individual erosivity for a 30-year period. based on this data the annual average rainfall erosivity in aracruz was 8,536 mj mm ha-1 h-1 yr -1. of the total annual rainfall erosivity 85 % was observed in the most critical period october to march. annual erosive rains accounted for 38 % of the events causing erosion, although the runoff volume represented 88 % of the total. the annual average rainfall erosivity return period was estimated to be 3.4 years.
Rainfall Erosivity in Urban Zone of Chongqing Municipality
重庆市主城区降雨侵蚀力特征分析

MIAO Chi-yuan,XU Xia,WEI Xin,ZENG Xian-qin,
缪驰远
,徐霞,魏欣,曾宪勤

资源科学 , 2007,
Abstract: Rainfall erosivity is an important factor for predicting soil loss quantitatively. The paper studied on rainfall erosivity (R) and its characteristics in the Shapingba area of Chongqing city, based on the rainfall data from 1954 to 2001. The method for calculating rainfall erosivity factor (R) is based on the RUSLE(revised universal soil loss equation). Results show that the values of single rainfall erosivity change greatly; the contribution rate caused by several maximum rainfall erosivity is significant for total rainfall erosivity; the maximum value of single rainfall erosivity is 2.36% of the total value of rainfallerosivity among 48 years; the monthly rainfall erosivity mainly concentrated from May to September; the rainfall erosivity of this period is 91.13% of annual rainfall erosivity; the values of rainfall erosivity per year change greatly too. the paper used two indicators to describe the change of annual rainfall erosivity: the coefficient of changed trend r and the coefficient of variation Cv. By calculation, the coefficient of changed trend r is 0.061, the coefficient of variation Cv is 0.65. So the whole trend of the yearly erosivity value among 48 years is balanced. The single rainfall and single rainfallerosivity, the monthly rainfall and monthly rainfall erosivity are in exponential function relation, but the yearly rainfall and yearly rainfall erosivity is in index relation, the determinate coefficient R2 is 0.9687, 0.8921 and 0.4822 respectively. The paper, under the insufficient rainfall information simplify the calculation process and make use of the rainfall data and results in research area through correlated analysis to conclude two kinds of the simple arithmetic about rainfall erosivity finally, according to the results of determinate coefficient R2 and mean absolute percentage error (MAPE). For using the daily and the monthly rainfall to calculate the annual rainfall erosivity, the determinate coefficient R2 is 0.9181 and 0.8300 respectively, the calculated MAPE is 8.35% and 22.28%, which are obviously better than the others simple means.
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