Spatial and temporal rainfall variability in mountainous areas: A case study from the south Ecuadorian Andes

Abstract

Particularly in mountain environments, rainfall can be extremely variable in space and time. For many hydrological applications such as modelling, extrapolation of point rainfall measurements is necessary. Decisions about the techniques used for extrapolation, as well as the adequacy of the conclusions drawn from the final results, depend heavily on the magnitude and the nature of the uncertainty involved. In this paper, we examine rainfall data from 14 rain gauges in the western mountain range of the Ecuadorian Andes. The rain gauges are located in the western part of the rio Paute basin. This area, between 3500 and 4100 m asl, consists of mountainous grasslands, locally called páramo, and acts as major water source for the interAndean valley. Spatial and temporal rainfall patterns were studied. A clear intraday pattern can be distinguished. Seasonal variation, on the other hand, is low, with a difference of about 100 mm between the dryest and the wettest month on an average of about 100 mm month À1 , and only 20% dry days throughout the year. Rain gauges at a mutual distance of less than 4000 m are strongly correlated, with a Pearson correlation coefficient higher than 0.8. However, even within this perimeter, spatial variability in average rainfall is very high. Significant correlations were found between average daily rainfall and geographical location, as well as the topographical parameters slope, aspect, topography. Spatial interpolation with thiessen gives good results. Kriging gives better results than thiessen, and the accuracy of both methods improves when external trends are incorporated.

Regionalization as a learning process

“…[34] The absence of a dry season [Buytaert et al, 2006b], and the marked drop of soil hydraulic conductivity in nonsaturated conditions result in continuously wet soils (>60 vol% [Buytaert et al, 2005]). Field research has shown that also in dry periods a saturated soil layer exists above the bedrock, even on steep slopes [Buytaert et al, 2005].…”

Spatio‐temporal rainfall variability in the Amazon basin countries (Brazil, Peru, Bolivia, Colombia, and Ecuador)

“…Nevertheless the need to consider comprehensive data set is important in the Andean regions. Rainfall tends to decrease with altitude, but the windward or leeward exposure of the stations to the dominant moist wind makes it difficult to find a simple relationship between rainfall and altitude (Johnson, 1976;Roche et al, 1990;Guyot, 1993;Pulwarty et al, 1998;Buytaert et al, 2006;Ronchail and Gallaire, 2006;Laraque et al, 2007). On the contrary, in Brazil, the spatiotemporal rainfall variability has been more widely studied and published than in the Andean countries.…”

A spatial regression analysis of the influence of topography on monthly rainfall in East Africa

“…Increasing precipitation is expected to occur with increasing elevation (Spreen, 1947;Arora et al, 2006). Since steeper slopes provide stronger orographic lifting, increasing slope or standard deviation is expected to be associated with higher rainfall (locally, at least; Buytaert et al, 2006). It is anticipated that the spatial scale at which these processes occur will vary month to month due to different synoptic forcings, wind patterns, and other seasonal variations (e.g.…”