Browsing by Author "Mutuga, K. J."

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    Publication
    Use of downscaled tropical rainfall measuring mission data for meteorological drought monitoring: case study of Narumoru catchment
    (International Journal of Advances in Engineering & Technology, 2014) Mutuga, K. J.; Nyadawa, Maurice O.; Home, P. G.
    Remotely sensed satellite rainfall data has gained popularity in the recent past, been especially attractive to ungauged catchments or poorly gauged catchments. Tropical Rainfall Measuring Mission (TRMM) data is considered to be most accurate of the satellite derived rainfall data and with the best spatial resolution at 250 x 250 grid. For purposes of hydrological modelling in small catchments, this data is usually downscaled to 1km x 1km grid to bring it closer to point measurement rain gauge data. This study evaluates whether downscaling of TRMM improves its meteorological drought monitoring capacity. TRMM was downscaled from the original 250 x 250 resolution (Approximately 28km x28km) to 1km x 1km resolution based on the relationship between Normalised Difference Vegetation Index (NDVI) and precipitation. Standardized Precipitation Index (SPI) was computed at 3, 6, 9, 12, and 24-month aggregation periods using the downscaled TRMM data (TRMM1km), TRMM at original resolution (TRMM28km) and observed rain gauge data. Analysis of Variance (ANOVA), t-test and data visualization methods were used to determine the similarity of the SPIs from the three datasets. Similarly, correlation analysis was done to determine dependency and modelling capability of the datasets. TRMM1km derived SPI was found to have lower correlation with the (correlation coefficients ranging from 0.34 to 0.42 for the different aggregation periods) rain gauge derived SPI as compared to TRMM28km derived SPI which had correlation coefficients ranging from 0.57 to 0.66. From analysis of variance, there was no significant difference between the SPI computed from TRMM and from that computed from rain gauge data. Additionally, SPI visualization indicated similar drought patterns were identified by both TRMM and rain gauge computed SPIs. Therefore, it was concluded that TRMM data, whether downscaled or at original resolution are useful for meteorological drought monitoring in Narumoro catchment