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12 results for “rainfall erosivity”
Daily rainfall series and rainfall erosivity in Mexico for three climatic normals (1968-1997, 1978-2007, and 1988-2017)
As in many countries around the world, there are some issues in the Mexican rainfall series, such as missing values, short measurement periods, and series homogeneity (breaks due to station relocation and measurement mistakes), which further compound the challenge of using climate data. Furthermore, it is necessary to develop a complete and helpful rainfall series database by following an imputing and homogenization process of the rainfall series. This research has compiled and systematized a national dataset with daily rainfall and rainfall erosivity for three climatic normals CN (1968-1997, 1978-2007, and 1988-2017). We have used the "climatol" package to fill the data. After, we calculated daily rainfall erosivity using a power law model. As a result, we obtained 1370, 1679, and 1683 rainfall series for the CNs 1968-1997, 1978-2007, and 1988-2017, respectively. The median values of the rainfall erosivity for the three CNs were 3245, 3070, and 3327 MJ mm/ ha h yr, respectively. We are making this database available for public consultation for researchers and students, technical assistants, decision-makers, and others interested in environmental studies in Mexico.
REDB-BR: Rainfall Erosivity Database for Brazil
<p>This is REDB-BR, the Rainfall Erosivity Database for Brazil from the MSWEP rainfall dataset.</p> <p>It provides the R factor from the Universal Soil Loss Equation (USLE) in a 0.1º resolution grid, developed with 37 years of rainfall data from the MSWEP dataset.</p> <p>The R factor was calculated trough 73 erosivity index regression equations, which mostly uses a relation between monthly precipitation and annual precipitation, the Modified Fournier Index (MFI), and represents a good approximation to locals with no sub-hourly data for long periods. </p> <p>The main product of REDB-BR is the R factor map, available also as a .tif raster. The database also includes the equations shapefile, Thiessen Polygons shapefile and the equations table. </p>
GloRESatE - Global Rainfall Erosivity from Reanalysis and Satellite Estimates
<p>Rainfall erosivity measures the impact of rainfall kinetic energy and intensity or its potential to cause soil erosion. The sparsely available gauge rainfall dataset limits reliable rainfall erosivity assessment globally. GloRESatE is a state-of-the-art global rainfall erosivity dataset with a high spatial resolution of 0.1° × 0.1°. It integrates satellite data (CMORPH, IMERG Final Run), reanalysis data (ERA5-Land), and observations from 6,170 gauge stations worldwide. Created using advanced Gaussian Process Regression, this dataset provides accurate and reliable rainfall erosivity information. It serves as a vital resource for hydrological research, aiding studies in soil erosion, water resource management, and climate change impact assessments on a global scale.</p> <p> </p> <p>Das, S., Jain, M.K., Gupta, V., McGehee, R.P., Yin, S., de Mello, C.R., Azari, M., Borrelli, P. and Panagos, P., 2024. GloRESatE: A dataset for global rainfall erosivity derived from multi-source data. <em>Scientific Data</em>, <strong>11</strong>:926. https://doi.org/10.1038/s41597-024-03756-5</p>
Annual rainfall erosivity in Greece
<p>Estimated mean annual erosivity values over Greece in (Mj.mm/ha/h/y) using precipitation records that suffered from a significant volume of missing values. As an intermediate step the creation of monthly precipitation and erosivity density models was utilized.</p>
Past, present and future rainfall erosivity in Northwestern Europe
<p>Past, present and future rainfall erosivity in Northwestern Europe calculated from convection-permitting climate simulations in CNRM-AROME (Lucas-Picher et al., 2023; <a href="https://doi.org/10.1007/s00382-022-06637-y">https://doi.org/10.1007/s00382-022-06637-y</a>) using emission scenario RCP 8.5. A description of the methodology is given in the article "Past, present and future rainfall erosivity in central Europe based on convection-permitting climate simulations" by Magdalena Uber et al. (2024) in Hydrology and Earth System Sciences (<a href="https://doi.org/10.5194/hess-28-87-2024">https://doi.org/10.5194/hess-28-87-2024</a>). Please see the README-file for further information.</p> <p>This work was funded by the German Federal Ministry for Digital and Transport in the framework of the DAS-Basisdienst.</p>
Past, present and future rainfall erosivity in Central Europe
<p>Past, present and future rainfall erosivity in central Europe calculated from convection-permitting climate simulations in COSMO-CLM using emission scenario RCP 8.5. A description of the dataset and methodology is given in the article "Past, present and future rainfall erosivity in central Europe based on convection-permitting climate simulations" by Magdalena Uber et al. (2024) in Hydrology and Earth System Sciences (https://doi.org/10.5194/hess-28-87-2024).</p> <p>This work was funded by the German Federal Ministry for Digital and Transport Network of Experts.</p> <p> </p> <p> </p>
Global Rainfall Erosivity database (GloREDa)
<p>Table with the data of annual rainfall erosivity and auxiliary information for 3,939 stations.</p> <p>Table with the data of monthly erosivity.</p> <p>Shape file with all the stations and their erosivity values.</p> <p>12 Raster (GeoTIFF) with global monthly erosivity at 1km x 1km resolution</p> <p>Relevant publication to cite for those datasets:</p> <p>Panagos, P., Hengl, T., Wheeler, I., Marcinkowski, P., Rukeza, M.B., Yu, B., Yang, J.E., Miao, C., Chattopadhyay, N., Sadeghi, S.H. and Levi, Y., et al. 2023. <a href="https://www.sciencedirect.com/science/article/pii/S2352340923005826">Global Rainfall Erosivity database (GloREDa) and monthly R-factor data at 1km spatial resolution</a>. <em>Data in Brief</em>, <strong>50</strong>, Art.no.109482. DOI: 10.1016/j.dib.2023.109482</p>
Long-term effectiveness of sustainable land management practices to control runoff, soil erosion, and nutrient loss and the role of rainfall intensity in Mediterranean rainfed agroecosystems
<p>This data set corresponds to the open-access article "Long-term effectiveness of sustainable land management practices to control runoff, soil erosion, and nutrient loss and the role of rainfall intensity in Mediterranean rainfed agroecosystems" published in CATENA. (<a href="https://doi.org/10.1016/j.catena.2019.104352">https://doi.org/10.1016/j.catena.2019.104352</a>), funded by he European Commission Horizon 2020 project Diverfarming [grant agreement 728003]. </p>
Effects of Grass Cover on the Overland Soil Erosion Mechanism under Simulated Rainfall
<p><span>Grass cover has a complex influence on overland soil erosion. This study quantified the impact of grass cover on overland soil erosion using a dimensionless water flow path index. It systematically analyzed the response mechanism among overland soil erosion, slope gradient, rainfall intensity, and hydrodynamic parameters, aiming to identify the optimal hydrodynamic parameters capable of characterizing overland soil erosion. A predictive model for soil erosion was constructed based on general dimensionless water flow intensity parameters, comprehensively evaluating the mechanism of soil erosion on grass-covered overland under simulated rainfall conditions. The results indicate that the model constructed using dimensionless parameters exhibits strong adaptability and can be effectively validated in other experiments.</span></p>
Indian Rainfall Erosivity Dataset (IRED)
<p>Soil erosion induced by water has been identified as one of the major environmental problems worldwide. The erosive force of rainfall, also known as rainfall erosivity (R-factor), is the potential of rain to cause soil degradation and one of the factors in the widely adopted RUSLE (Revised Universal Soil Loss Equation) empirical soil erosion estimation model. About 68.4% of total eroded soil in India is eroded due to erosion by water, and rainfall erosivity is one of the major factors. The past assessments of rainfall erosivity in India were however largely based on rain-gauge recordings and surveys which hinders its understanding and estimation over large areas. Growing availability of gridded precipitation datasets presents an unprecedented opportunity to study long-term rainfall erosivity over varied terrains and address some of the limitations of point data-based studies. IRED (Indian Rainfall Erosivity Dataset) is the first such national-scale assessment of rainfall erosivity over India using gridded precipitation datasets, which will be helpful for agricultural experts, watershed managers, agronomists, and soil-conservational experts in order to understand and mitigate rainfall-induced erosion. In this dataset, long term yearly average R-factor, Fourier Index (FI), and Modified Fourier Index (MFI) maps have been included with a distributional analysis over IMD (India Metrological Department) defined regions, states and districts of India.</p>
Annual rainfall erosivity projected differences in Greece
<p>This dataset contains the raster files of the differences between projected and historical mean average values of R in Greece from the paper: </p> <p>Vantas, K.; Sidiropoulos, E.; Loukas, A. Estimating Current and Future Rainfall Erosivity in Greece Using Regional Climate Models and Spatial Quantile Regression Forests. Water 2020, 12, 687, DOI: <a href="https://doi.org/10.3390/w12030687">https://doi.org/10.3390/w12030687</a></p> <p> </p>
Mitigating Rainfall Induced Soil Erosion through Bio-approach: From Laboratory Test to Field Trail
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