Infilling Monthly Rain Gauge Data Gaps with Satellite Estimates for ASAL of Kenya
Design and operation of water resources management systems in sub-Saharan Africa suffer from inadequate observation data. Long running uninterrupted time series of data are often not available for water resource planning. Incomplete datasets with missing gaps is a challenge for users of the data. Inadequate data compromise results of analyses leading to wrong inference and conclusions of scientific assessments and research. Infilling of missing sections of data is necessary prior to the practical use of hydrometeorological time series. This paper proposes the use of Tropical Rainfall Measuring Mission satellite data as a viable alternate source of infill for missing rain gauge records. The least square regression method, using satellite-based estimates of rainfall was tested to fill in the missing data for 153 data points at nine rain gauge stations in Machakos, Makueni and the Kitui region of Kenya. Results suggest that the satellite rainfall estimates can be used as an alternative data source for rainfall series where the missing data gaps are large. The infilled data series were used in the development of monitoring, forecasting and drought early warning for Arid and Semi-Arid Lands (ASAL) in Kenya.