Hodson Makurira
University of Zimbabwe
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Hodson Makurira.
Hydrology and Earth System Sciences Discussions | 2017
Webster Gumindoga; T.H.M. Rientjes; Alemseged Tamiru Haile; Hodson Makurira; Paolo Reggiani
Satellite rainfall estimates (SREs) are prone to bias as they are indirect derivatives of the visible, infrared, and/or microwave cloud properties, and hence SREs need correction. We evaluate the influence of elevation and distance from large-scale open water bodies on bias for Climate Prediction Center-MORPHing (CMORPH) rainfall estimates in the Zambezi basin. The effectiveness of five linear/non-linear and time–space-variant/-invariant bias-correction schemes was evaluated for daily rainfall estimates and climatic seasonality. The schemes used are spatio-temporal bias (STB), elevation zone bias (EZ), power transform (PT), distribution transformation (DT), and quantile mapping based on an empirical distribution (QME). We used daily time series (1998–2013) from 60 gauge stations and CMORPH SREs for the Zambezi basin. To evaluate the effectiveness of the bias-correction schemes spatial and temporal crossvalidation was applied based on eight stations and on the 1998–1999 CMORPH time series, respectively. For correction, STB and EZ schemes proved to be more effective in removing bias. STB improved the correlation coefficient and Nash–Sutcliffe efficiency by 50 % and 53 %, respectively, and reduced the root mean squared difference and relative bias by 25 % and 33 %, respectively. Paired t tests showed that there is no significant difference (p<0.05) in the daily means of CMORPH against gauge rainfall after bias correction. ANOVA post hoc tests revealed that the STB and EZ bias-correction schemes are preferable. Bias is highest for very light rainfall (<2.5 mm d−1), for which most effective bias reduction is shown, in particular for the wet season. Similar findings are shown through quantile–quantile (q– q) plots. The spatial cross-validation approach revealed that most bias-correction schemes removed bias by >28 %. The temporal cross-validation approach showed effectiveness of the bias-correction schemes. Taylor diagrams show that station elevation has an influence on CMORPH performance. Effects of distance>10 km from large-scale open water bodies are minimal, whereas effects at shorter distances are indicated but are not conclusive for a lack of rain gauges. Findings of this study show the importance of applying bias correction to SREs.
Physics and Chemistry of The Earth | 2009
Hodson Makurira; Hubert H. G. Savenije; Stefan Uhlenbrook; Johan Rockström; Aidan Senzanje
Agricultural Water Management | 2011
Elin Enfors; Jennie Barron; Hodson Makurira; Johan Rockström; Siza D. Tumbo
Physics and Chemistry of The Earth | 2007
Hodson Makurira; Marloes Mul; N.F. Vyagusa; Stefan Uhlenbrook; Hubert H. G. Savenije
Archive | 2006
Yogesh Bhatt; Deborah A. Bossio; Elin Enfors; Line J. Gordon; Victor Kongo; Job Rotich Kosgei; Hodson Makurira; Kenneth Masuki; Marloes Mul; Siza D. Tumbo
Physics and Chemistry of The Earth | 2012
C.T. Tsiko; Hodson Makurira; A. M. J. Gerrits; Hubert H. G. Savenije
Physics and Chemistry of The Earth | 2007
Dominic Mazvimavi; E. Madamombe; Hodson Makurira
Physics and Chemistry of The Earth | 2007
Hodson Makurira; Hubert H. G. Savenije; Stefan Uhlenbrook; Johan Rockström; A. Senzanje
Agricultural Water Management | 2011
M.L. Mul; J.S. Kemerink; N.F. Vyagusa; M.G. Mshana; P. van der Zaag; Hodson Makurira
Hydrology and Earth System Sciences | 2009
Hodson Makurira; Hubert H. G. Savenije; Stefan Uhlenbrook