Abstract
The paper examines the quality of satellite-based precipitation estimates for the lower Mahanadi River basin (eastern India). The considered data sets known as 3B42 and 3B42-RT (version 7/7A) are routinely produced by the tropical rainfall measuring mission (TRMM) from passive microwave and infrared recordings. While the 3B42-RT data are disseminated in real time, the gauge-adjusted 3B42 data set is published with a delay of some months. The quality of the two products was assessed in a two-step procedure. First, the correspondence between the remotely sensed precipitation rates and rain gauge data was evaluated at the sub-basin scale. Second, the quality of the rainfall estimates was assessed by analysing their performance in the context of rainfall-runoff simulation. At sub-basin level (4000 to 16 000 km2) the satellite-based areal precipitation estimates were found to be moderately correlated with the gauge-based counterparts (R2 of 0.64-0.74 for 3B42 and 0.59-0.72 for 3B42-RT). Significant discrepancies between TRMM data and ground observations were identified at high-intensity levels. The rainfall depth derived from rain gauge data is often not reflected by the TRMM estimates (hit rate < 0.6 for ground-based intensities > 80 mm day-1). At the same time, the remotely sensed rainfall rates frequently exceed the gauge-based equivalents (false alarm ratios of 0.2-0.6). In addition, the real-time product 3B42-RT was found to suffer from a spatially consistent negative bias. Since the regionalisation of rain gauge data is potentially associated with a number of errors, the above results are subject to uncertainty. Hence, a validation against independent information, such as stream flow, was essential. In this case study, the outcome of rainfall-runoff simulation experiments was consistent with the above-mentioned findings. The best fit between observed and simulated stream flow was obtained if rain gauge data were used as model input (Nash-Sutcliffe index of 0.76-0.88 at gauges not affected by reservoir operation). This compares to the values of 0.71-0.78 for the gauge-adjusted TRMM 3B42 data and 0.65-0.77 for the 3B42-RT real-time data. Whether the 3B42-RT data are useful in the context of operational runoff prediction in spite of the identified problems remains a question for further research. © Author(s) 2014.
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CITATION STYLE
Kneis, D., Chatterjee, C., & Singh, R. (2014). Evaluation of TRMM rainfall estimates over a large Indian river basin (Mahanadi). Hydrology and Earth System Sciences, 18(7), 2493–2502. https://doi.org/10.5194/hess-18-2493-2014
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