Performance assessment of interpolation techniques for optimal areal rainfall–temperature estimation: the case of two contrasting river catchments, Akaki and Mille, in Ethiopia

Abstract

In the topographic complex catchments, landscape features have a significant impact on the spatial prediction of rainfall and temperature. In this study, performance assessments were made of various interpolation techniques for the prediction of the spatial distribution of rainfall and temperature in the Mille and Akaki River catchments, Ethiopia, through an improved approach on selecting the auxiliary variables as a covariate. Two geostatistical interpolation techniques, ordinary kriging (OK) and kriging with external drift (KED), and one deterministic interpolation technique, inverse distance weighting (IDW), were tested through a leave-one-out cross-validation (LOOCV) procedure. The results indicated that using the multivariate geostatistical interpolation technique (KED) with the auxiliary variables as a covariate outperformed the univariate geostatistical (OK) and deterministic (IDW) techniques for the spatial interpolation of sampled rainfall–temperature data in both contrasting catchments, Akaki and Mille, with the lowest estimation errors (e.g., for Mille annual mean rainfall: root mean square error=75.32, 77.34, 245.72, mean bias error=3.70, −33.18, −15.61, mean absolute error=67.99, 69.51, 192.64) using KED with the combination of elevation and easting as a covariate, IDW and OK, respectively. Thus, the study confirmed that the use of elevation and easting/northing coordinates as predictors in geostatistical interpolation techniques could significantly improve the spatial prediction of climatic variables.

Comparação de modelos geoestatísticos para estimativa de precipitação em Minas Gerais, Brasil, entre os anos hidrológicos de 2000 e 2021

“…Este modelo apresenta aplicabilidade quando não há significativa relação espacial entre as estações pluviométricas (Subyani, 2019). Houve um baixo desempenho deste modelo para Minas Gerais, mesmo existindo aplicabilidade deste nos climas semiárido (Oliveira et al, 2022) e amazônico (Millán-Vega et al, 2020), assim como no estado do Tocantins (Neto et al, 2020b) e do Mato Grasso (Cerón et al, 2021), e em outros países (Machiwal et al, 2020;Benavides-Bravo et al, 2021;Bati et al, 2022).…”