@article{bonillaRainfallErosivityCentral2011,
  title = {Rainfall Erosivity in {{Central Chile}}},
  author = {Bonilla, Carlos A. and Vidal, Karim L.},
  date = {2011-11-15},
  journaltitle = {Journal of Hydrology},
  volume = {410},
  pages = {126--133},
  issn = {0022-1694},
  doi = {10.1016/j.jhydrol.2011.09.022},
  url = {https://doi.org/10.1016/j.jhydrol.2011.09.022},
  urldate = {2019-11-13},
  abstract = {[Highlights]
[::] We built the first rainfall erosivity map for most of the cultivated land in Chile. 
[::] Erosivities varied as a result of the rainfall depths, elevation and latitude. 
[::] We established a relation between the calculated erosivities and annual rainfall. 
[::] This relation offers a means of estimating erosivity when time or data is limiting.

[Abstract]
One of the most widely used indicators of potential water erosion risk is the rainfall-runoff erosivity factor (R) of the Revised Universal Soil Loss Equation (RUSLE). R is traditionally determined by calculating a long-term average of the annual sum of the product of a storm’s kinetic energy (E) and its maximum 30-min intensity (I30), known as the EI30. The original method used to calculate EI30 requires pluviograph records for at most 30-min time intervals. Such high resolution data is difficult to obtain in many parts of the world, and processing it is laborious and time-consuming. In Chile, even though there is a well-distributed rain gauge network, there is no systematic characterization of the territory in terms of rainfall erosivity. This study presents a rainfall erosivity map for most of the cultivated land in the country. R values were calculated by the prescribed method for 16 stations with continuous graphical record rain gauges in Central Chile. The stations were distributed along 800km (north–south), and spanned a precipitation gradient of 140–2200mmyr−1. More than 270years of data were used, and 5400 storms were analyzed. Additionally, 241 spatially distributed R values were generated by using an empirical procedure based on annual rainfall. Point estimates generated by both methods were interpolated by using kriging to create a map of rainfall erosivity for Central Chile. The results show that the empirical procedure used in this study predicted the annual rainfall erosivity well (model efficiency=0.88). Also, an increment in the rainfall erosivities was found as a result of the rainfall depths, a regional feature determined by elevation and increasing with latitude from north to south. R values in the study area range from 90MJmmha−1h−1yr−1 in the north up to 7375MJmmha−1h−1yr−1 in the southern area, at the foothills of the Andes Mountains. Although the map and the estimates could be improved in the future by generating additional data points, the erosivity map should prove to be a good tool for land-use planners in Chile and other areas with similar rainfall characteristics.},
  keywords = {~INRMM-MiD:z-IUTWW8QJ,chile,empirical-equation,erosivity,soil-erosion,soil-resources},
  langid = {english},
  number = {1-2}
}

{"_id":"nhJrMRz3ASctxcNJu","bibbaseid":"bonilla-vidal-rainfallerosivityincentralchile","authorIDs":[],"author_short":["Bonilla, C. A.","Vidal, K. L."],"bibdata":{"bibtype":"article","type":"article","title":"Rainfall Erosivity in Central Chile","author":[{"propositions":[],"lastnames":["Bonilla"],"firstnames":["Carlos","A."],"suffixes":[]},{"propositions":[],"lastnames":["Vidal"],"firstnames":["Karim","L."],"suffixes":[]}],"date":"2011-11-15","journaltitle":"Journal of Hydrology","volume":"410","pages":"126–133","issn":"0022-1694","doi":"10.1016/j.jhydrol.2011.09.022","url":"https://doi.org/10.1016/j.jhydrol.2011.09.022","urldate":"2019-11-13","abstract":"[Highlights] [::] We built the first rainfall erosivity map for most of the cultivated land in Chile. [::] Erosivities varied as a result of the rainfall depths, elevation and latitude. [::] We established a relation between the calculated erosivities and annual rainfall. [::] This relation offers a means of estimating erosivity when time or data is limiting. [Abstract] One of the most widely used indicators of potential water erosion risk is the rainfall-runoff erosivity factor (R) of the Revised Universal Soil Loss Equation (RUSLE). R is traditionally determined by calculating a long-term average of the annual sum of the product of a storm’s kinetic energy (E) and its maximum 30-min intensity (I30), known as the EI30. The original method used to calculate EI30 requires pluviograph records for at most 30-min time intervals. Such high resolution data is difficult to obtain in many parts of the world, and processing it is laborious and time-consuming. In Chile, even though there is a well-distributed rain gauge network, there is no systematic characterization of the territory in terms of rainfall erosivity. This study presents a rainfall erosivity map for most of the cultivated land in the country. R values were calculated by the prescribed method for 16 stations with continuous graphical record rain gauges in Central Chile. The stations were distributed along 800km (north–south), and spanned a precipitation gradient of 140–2200mmyr−1. More than 270years of data were used, and 5400 storms were analyzed. Additionally, 241 spatially distributed R values were generated by using an empirical procedure based on annual rainfall. Point estimates generated by both methods were interpolated by using kriging to create a map of rainfall erosivity for Central Chile. The results show that the empirical procedure used in this study predicted the annual rainfall erosivity well (model efficiency=0.88). Also, an increment in the rainfall erosivities was found as a result of the rainfall depths, a regional feature determined by elevation and increasing with latitude from north to south. R values in the study area range from 90MJmmha−1h−1yr−1 in the north up to 7375MJmmha−1h−1yr−1 in the southern area, at the foothills of the Andes Mountains. Although the map and the estimates could be improved in the future by generating additional data points, the erosivity map should prove to be a good tool for land-use planners in Chile and other areas with similar rainfall characteristics.","keywords":"~INRMM-MiD:z-IUTWW8QJ,chile,empirical-equation,erosivity,soil-erosion,soil-resources","langid":"english","number":"1-2","bibtex":"@article{bonillaRainfallErosivityCentral2011,\n title = {Rainfall Erosivity in {{Central Chile}}},\n author = {Bonilla, Carlos A. and Vidal, Karim L.},\n date = {2011-11-15},\n journaltitle = {Journal of Hydrology},\n volume = {410},\n pages = {126--133},\n issn = {0022-1694},\n doi = {10.1016/j.jhydrol.2011.09.022},\n url = {https://doi.org/10.1016/j.jhydrol.2011.09.022},\n urldate = {2019-11-13},\n abstract = {[Highlights]\n[::] We built the first rainfall erosivity map for most of the cultivated land in Chile. \n[::] Erosivities varied as a result of the rainfall depths, elevation and latitude. \n[::] We established a relation between the calculated erosivities and annual rainfall. \n[::] This relation offers a means of estimating erosivity when time or data is limiting.\n\n[Abstract]\nOne of the most widely used indicators of potential water erosion risk is the rainfall-runoff erosivity factor (R) of the Revised Universal Soil Loss Equation (RUSLE). R is traditionally determined by calculating a long-term average of the annual sum of the product of a storm’s kinetic energy (E) and its maximum 30-min intensity (I30), known as the EI30. The original method used to calculate EI30 requires pluviograph records for at most 30-min time intervals. Such high resolution data is difficult to obtain in many parts of the world, and processing it is laborious and time-consuming. In Chile, even though there is a well-distributed rain gauge network, there is no systematic characterization of the territory in terms of rainfall erosivity. This study presents a rainfall erosivity map for most of the cultivated land in the country. R values were calculated by the prescribed method for 16 stations with continuous graphical record rain gauges in Central Chile. The stations were distributed along 800km (north–south), and spanned a precipitation gradient of 140–2200mmyr−1. More than 270years of data were used, and 5400 storms were analyzed. Additionally, 241 spatially distributed R values were generated by using an empirical procedure based on annual rainfall. Point estimates generated by both methods were interpolated by using kriging to create a map of rainfall erosivity for Central Chile. The results show that the empirical procedure used in this study predicted the annual rainfall erosivity well (model efficiency=0.88). Also, an increment in the rainfall erosivities was found as a result of the rainfall depths, a regional feature determined by elevation and increasing with latitude from north to south. R values in the study area range from 90MJmmha−1h−1yr−1 in the north up to 7375MJmmha−1h−1yr−1 in the southern area, at the foothills of the Andes Mountains. Although the map and the estimates could be improved in the future by generating additional data points, the erosivity map should prove to be a good tool for land-use planners in Chile and other areas with similar rainfall characteristics.},\n keywords = {~INRMM-MiD:z-IUTWW8QJ,chile,empirical-equation,erosivity,soil-erosion,soil-resources},\n langid = {english},\n number = {1-2}\n}\n\n","author_short":["Bonilla, C. A.","Vidal, K. 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