Open AccessSpatial and temporal estimation of the erosivity factor R based on daily rainfall data for the department of Atlántico, Colombia
Author(s) -
Boris Ávila,
Humberto Ávila
Publication year - 2015
Publication title -
ingeniería e investigación/ingeniería e investigación
Language(s) - English
Resource type - Journals
eISSN - 2248-8723
pISSN - 0120-5609
DOI - 10.15446/ing.investig.v35n2.47773
Subject(s) - storm , orographic lift , rain gauge , environmental science , soil loss , universal soil loss equation , precipitation , hydrology (agriculture) , erosion , spatial distribution , meteorology , climatology , geography , remote sensing , geology , geomorphology , geotechnical engineering
Soil erosion caused by rain is the detachment and movement of soil particles caused by the impact of raindrops on the surface. Erosivity factor R is a measure of the rain erosive power used for estimating the erosion rate with the RUSLE method (Revised Universal Soil Loss Equation). Estimating R factor requires rainfall intensity records of storms greater than 12.5 mm or greater than 6 mm but longer than 15 min. However, most of the Colombian rainfall stations have daily rainfall records with which it is not possible to estimate the intensity of each storm and, therefore, makes it difficult to estimate the R factor for a specific area. In this paper a methodology for estimating the erosivity factor R for the department of Atlántico, Colombia from daily records of 16 IDEAM stations is presented. The spatial distribution of the erosivity factor R in the department and its temporal distribution throughout the year are also shown. The results showed a minimum erosivity factor R of 6,894 MJ∙mm∙Ha -1 ∙Hr -1 ∙yr -1 and a maximum of 10,925 MJ∙mm∙Ha -1 ∙Hr -1 ∙yr -1 . The average erosivity factor R for the department of Atlántico was 8,697 MJ∙mm∙Ha -1 ∙Hr -1 ∙yr -1 . This methodology might be used for estimating the erosion factor R in different Colombian regions where high-resolution precipitation data is limited, but seasonal and orographic conditions should be considered for selecting the rain gages and the area of study.