Global Rainfall Erosivity Database - GloREDa

At global scale, this is the first time ever that an erosivity database of such dimension is compiled. The Global Rainfall Erosivity Database, named hereafter as GloREDa, contains erosivity values estimated as R-factors (refer to the method section) from 3,625 stations distributed in 63 countries worldwide. This is the result of an extensive data collection of high temporal resolution rainfall data from the maximum possible number of countries in order to have a representative sample across different climatic and geographic gradients. GloREDa has three components, which are described in the methods section: a) the Rainfall Erosivity database at European Scale (REDES)14 b) 1,865 stations from 23 countries outside Europe and c) 85 stations collected from a literature review.

The number of GloREDa stations varied greatly among continents (Fig. 1). Europe had the largest contribution to the dataset, with 1,725 stations (48% of total), while South America had the lowest number of stations (141 stations or ~4% of total). Africa has very low density of GloREDa stations (5% of the total). In North America and the Caribbean, we collected erosivity values from 146 stations located in 6 countries (Unites States, Canada, Mexico, Cuba, Jamaica and Costa Rica). Finally, Asia and the Middle East were well represented in GloREDa, with 1,220 stations (34% of the total) distributed in 10 countries including the Siberian part of the Russian Federation (Fig. 1b). The geographic distribution within each continent also differed substantially. For instance, stations in Europe, Oceania and North America covered most of the territory, while those in Africa and South America were largely clustered. However, the stations are well distributed among different erosivity classes (Fig. 2b).

Figure 1 (a) Global distribution of rainfall erosivity stations (red dots) compiled in the Global Rainfall Erosivity Database (GloREDa); (b) Distribution of rainfall erosivity stations by continent. Maps generated with ESRI ArcGIS ver. 10.4 (http://www.esri.com). Full size image

Figure 2 (a) Global Rainfall Erosivity map (spatial resolution 30 arc-seconds). Erosivity classes correspond to quantiles. Map generated with ESRI ArcGIS ver. 10.4 (http://www.esri.com); (b) number and cumulative percentage of GloREDa stations grouped by erosivity; (c) mean erosivity by continent; (d) mean erosivity by climate zone. Full size image

Global erosivity map

The Gaussian Process Regression (GPR) model used to interpolate the erosivity (R-factor) point values to a map showed a good performance for the cross-validation dataset [R2 = 0.722, RMSE (Root Mean Square Error) = 1,629 MJ mm ha−1 h−1 yr−1]. The annual global erosivity map (Fig. 2) is presented at 30 arc-seconds (~1 km) spatial resolution and subdivided in 10 erosivity classes corresponding to the quantiles. The mean of the global R-factor map is 2,190 MJ mm ha−1 h−1 yr−1 with high variability as expressed by the standard deviation of 2,974 MJ mm ha−1 h−1 yr−1. The median (50th percentile) of the global erosivity map is 1,150 MJ mm ha−1 h−1 yr−1 while 20% of the erosivity values (20th percentile) are lower than 200 MJ mm ha−1 h−1 yr−1 and the highest 20% (80th percentile) are higher than 5,200 MJ mm ha−1 h−1 yr−1 (Fig. 2). According to the global erosivity map, the highest values are located in south-eastern Asia (Cambodia, Indonesia, Malaysia, the Philippines and Bangladesh), Central Africa (Congo and Cameroon), South America (Brazil, Colombia and Peru), Central America and the Caribbean. The lowest erosivity is mainly located in Siberia, the Middle East, Northern Africa, Canada and Northern Europe. The Polar Regions have been masked out in the global erosivity map.

We found that the spatial patterns of the highest erosivity values (Fig. 2) are coincident with the corresponding patterns of extreme rainfall events reported by Zipser et al.14. Zipser et al.14 defined intense storms based on the convective vertical velocity of rain. The authors compiled a 7-year period (1998–2004) database of intense storms and they generated global maps of extreme rainstorm events based on lightening flash, brightness, temperature and noise. According to their study the highest frequency of extreme rainfall events (similar to high annual erosivity values) occurs in the central part of Latin America, Gulf of Mexico, central and western Africa, Madagascar, south-eastern Asia (mainly Bangladesh, south China), Indonesia and North Australia.

Continental assessments

At the continental level, South America experiences the highest mean R-factor with 5,874 MJ mm ha−1 h−1 yr−1, followed by Africa (3,053 MJ mm ha−1 h−1 yr−1), Asia and the Middle East (1,487 MJ mm ha−1 h−1 yr−1). In Oceania, the mean R-factor was estimated at 1,675 MJ mm ha−1 h−1 yr−1(Fig. 2c).

Africa exhibits the highest erosivity estimates at the country level; Mauritius and Comoros have the highest worldwide mean annual erosivity values with an R-factor close to 20,000 MJ mm ha−1 h−1 yr−1. In Western Africa (Liberia, Sierra Leone and Equatorial Guinea), Central Africa (D.R of Congo, Republic of Congo and Cameroon) and Madagascar mean annual R-factor is higher than 7,000 MJ mm ha−1 h−1 yr−1. These patterns agree with those from other continental-scale assessments15, 16 which indicated highest erosivity values (>10,000 MJ mm ha−1 h−1 yr−1) along the Guinea coast of west and central Africa, the Congo basin and Madagascar. Ethiopia and South Africa have mean R-factor values close to 2,500 MJ mm ha−1 h−1 yr−1, but the spatial patterns are highly variable with the Ethiopian highlands having extremely high erosivity (>7,000 MJ mm ha−1 h−1 yr−1) while the lowlands have 3–4 times smaller values. The lowest mean R-factor, with values less than 115 MJ mm ha−1 h−1 yr−1, was estimated for Western Sahara, Libya and Egypt.

Within Asia, the Middle East has the lowest erosivity values, with a mean annual R-factor less than 220 MJ mm ha−1 h−1 yr−1 in Jordan, Saudi Arabia, Kuwait, Syria, Iran and Iraq (Fig. 2). China has a mean value of 1,600 MJ mm ha−1 h−1 yr−1, but exhibits high variability with zero erosivity in the arid north-west areas (Taklimakan desert), and extreme erosivity (>15,000) in the south-eastern coastal zones. Regional studies conducted by Zhu and Yu17 and Qin et al.18 show very similar spatial patters compared to our rainfall erosivity distribution in China. In Japan, the mean annual erosivity was estimated as 4,815 MJ mm ha−1 h−1 yr−1, a value close to the 5,130 MJ mm ha−1 h−1 yr−1 modelled by Shiono et al.19.

As expected the Siberian part of the Russian Federation and the former Union of Soviet Socialist Republics (Kazakhstan, Turkmenistan and Uzbekistan) have very low mean erosivity values (<250 MJ mm ha−1 h−1 yr−1) due their continental climate. On the contrary, Southeast Asia falls almost completely within the highest erosivity class (>7,400 MJ mm ha−1 h−1 yr−1), in agreement with national assessments for Peninsular Malaysia20. Their erosivity values, generated from pluviographic data range from 7,500 to 20,000 MJ mm ha−1 h−1 yr−1.

In South America, Chile has the lowest R-factor with a mean annual value 1,320 MJ mm ha−1 h−1 yr−1, followed by Argentina (2,232 MJ mm ha−1 h−1 yr−1). The rest of the South American countries have high mean erosivity values (>3,700 MJ mm ha−1 h−1 yr−1), with the highest ones in Brazil, Colombia and Ecuador (>7,000 MJ mm ha−1 h−1 yr−1). The erosivity gradient created by the Andes is clearly visible in the erosivity map. There were few national assessments on rainfall erosivity in south America21,22,23,24. Most of the data used for these studies have been used as input for GloREDa and their spatial patterns are in broad agreement to ours.

In North America and the Caribbean, the mean R-factor is 1,409 MJ mm ha−1 h−1 yr−1 with very low values in Canada and the Northern part of the United States, and extremely high values (>8,000 MJ mm ha−1 h−1 yr−1) along the Gulf of Mexico and the Caribbean countries. The erosivity map for the United States25 also shows high values along the Gulf of Mexico and southern Florida (>8,500 MJ mm ha−1 h−1 yr−1), while overall low values are observed in the Midwestern region (<690 MJ mm ha−1 h−1 yr−1).

In Australia, the mean R-factor is 1,535 MJ mm ha−1 h−1 yr−1 close to 1,767 MJ mm ha−1 h−1 yr−1 estimated by Teng et al.26 based on 11 years (2002–2012) satellite derived Tropical Rainfall Measuring Mission data. In terms of spatial patterns, Teng et al.26 also found maximum erosivity values along the northern and eastern coastal areas (>8,000 MJ mm ha−1 h−1 yr−1), which decreased towards the south-central region (<300 MJ mm ha−1 h−1 yr−1). In New Zealand, the high erosivity values (>4,000 MJ mm ha−1 h−1 yr−1) occur on the west coast of the South Island and decrease towards the east similar to the patterns observed by Klik et al.27 based on 35 weather stations.

The mean erosivity value for Europe was 488 MJ mm ha−1 h−1 yr−1, which is much lower than the one estimated by Panagos et al.28 for the European Union (722 MJ mm ha−1 h−1 yr−1). This is due to the inclusion of European Russia, Ukraine (422 MJ mm ha−1 h−1 yr−1) and Belarus (365 MJ mm ha−1 h−1 yr−1), all of which have low values compared to the other European countries.

Analysis by Climate zones

The global rainfall erosivity map was further analysed per climate zones. The updated world Kopper-Geiger climate classification29 is the most widely used and accepted climate map in the scientific community. As expected, tropical climate group showed the highest mean erosivity with 7,104 MJ mm ha−1 h−1 yr−1. Within this group the tropical rainforest (Af) and monsoon (Am) climatic types had the highest mean erosivity and the lowest variability (Fig. 3). Second highest mean erosivity (3,729.3 MJ mm ha−1 h−1 yr−1) occurs in the temperate climate group.

Figure 3 R-factor descriptive statistics per Kopper-Geiger climate type. Colour bars are the mean values per climate zone. Error bars represent the standard deviation. Percentages below each main climate category represent its proportion within the study area. Climate zones: Af (tropical rainforest), Am (tropical monsoon), Aw (tropical savannah), BWh (hot desert), BWk (cold desert), BSh (hot steppe), BSk (cold steppe), Csa (dry hot summer), Csb (dry warm summer), Cwa (subtropical dry winter), Cwb (dry winter and dry summer), Cfa (temperate without dry season and hot summer), Cfb (temperate without dry season and warm summer), Cfc (temperate without dry season and cold summer), DSa (cold and dry hot summer), Dsb (cold and dry warm summer), Dsc (cold and dry cold summer), Dwa (cold and dry winter, and hot summer), Dwb (cold and dry winter, and warm summer), Dwc (cold and dry winter, and cold summer), Dwd (cold and dry winter, and very cold winter), Dfa (cold without dry season and hot summer), Dfb (cold without dry season and warm summer), Dfc (cold without dry season and cold summer), Dfd (cold without dry season and very cold winter), E (polar). Full size image

The humid temperate, and temperate with dry winter climate type (Cfa, Cwa), mainly present in the southeastern United States, eastern Australia and southeast China, have mean erosivity values higher than 4,600 MJ mm ha−1 h−1 yr−1. The Mediterranean (Csa, Csb) and the Oceanic (Cfb) climate zones have mean erosivity values lower than 2,000 MJ mm ha−1 h−1 yr−1 (Fig. 3).

The arid climate group has a relatively low mean erosivity (842 MJ mm ha−1 h−1 yr−1) characterised by the highest spatial variability (e.g. the Cold desert (BWk) type). In this group, the hot desert (BWh) has the largest spatial share (13.9% of global area) with low mean erosivity values (537 MJ mm ha−1 h−1 yr−1). The cold desert climate (BWk), characteristic of northwest China and large areas of Kazakhstan, Turkmenistan, Uzbekistan, North Chile and Argentina, has a very low mean erosivity of 362 MJ mm ha−1 h−1 yr−1. The hot steppe climate (BSh), which is a transition from hot dessert to the tropical group (mainly in Africa and India), had medium mean erosivity of 2,371 MJ mm ha−1 h−1 yr−1.

The cold climate group had the lowest mean erosivity, with 493 MJ mm ha−1 h−1 yr−1 whereof the subarctic or boreal climate type (Dsc, Dwc, Dfc), covering major areas of Scandinavia, Siberia and Canada, had minimum mean erosivity values (<285 MJ mm ha−1 h−1 yr−1). By comparison, the climate zones immediately north of hot continental summers (Dfb, Dwb) that cover most of central and eastern Europe, European Russia and the northern United States, have much higher mean erosivity values (526 MJ mm ha−1 h−1 yr−1). The polar areas, mainly located in the Alps, Pyrenees and part of the Tibetan plateau, have a mean erosivity of approximately 990 MJ mm ha−1 h−1 yr−1.

The greatest uncertainty of the global erosivity map is likely related to transition areas between different climatic zones. The different climatic conditions, which result in high variability of rainfall amount, duration, magnitude and intensity, is the main reason for different spatial patterns of erosivity between climatic zones. The standard deviation shows the variability inside the climatic zone (Fig. 3). Moreover, the seasonal variation of climatic conditions play an important role in rainfall erosivity variability.