Incalaue is a tributary of LugendaRiver in NSR (Niassa Special Reserve) in
North-Eastern Mozambique. NSR is a data-poor remote area and there is a need
for rainfall-runoff data to inform decisions on water resources management, and
scientific methods are needed for this wide expanse of land. This study
assessed the potential of a combination of NASA-POWER (National Aeronautics and
Space Administration and Prediction of Worldwide Energy Resources) remotely
sensed rainfall data and FAO (Food and Agriculture Organization of the United
Nations) soil and land use/cover data for modelling rainfall-runoff in Incalaue
river basin. DEM (Digital Elevation Model) of 1:250,000 scale and a grid resolution
of 30 m × 30 m downloaded from USGS (the United States Geological Survey) website; clipped
river basin FAO digital soil and land use/cover maps; and field-collected data were used. SWAT (Soil and Water
Assessment Tool) model was used to assess rainfall -runoff data generated using the NASA-POWER dataset
and gauged rainfall and river flow data collected during fieldwork. FAO soil
and land use/cover datasets which are globally available and widely used in the
region were used for comparison with soil data collected during fieldwork.
Field collected data showed that soil in the area is predominantly sandy loam
and only sand content and bulk density were uniformly distributed across the
soil samples. SWAT model showed a good
rainfall-runoff relationship using NASA-POWER data for the area (R2 = 0.7749) for the studied period (2019-2021). There was an equally strong
rainfall-runoff relationship for gauged data (R2 = 0.8131). There
were
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