%0 Journal Article
%T Using SWAT Model and Field Data to Determine Potential of NASA-POWER Data for Modelling Rainfall-Runoff in Incalaue River Basin
%A Ezrah Natumanya
%A Natasha Ribeiro
%A Majaliwa Jackson Gilbert Mwanjalolo
%A Franziska Steinbruch
%J Computational Water, Energy, and Environmental Engineering
%P 65-83
%@ 2168-1570
%D 2022
%I Scientific Research Publishing
%R 10.4236/cweee.2022.112004
%X Incalaue is a tributary of Lugenda<span><span style=\"font-family:;\" \"=\"\"> </span></span><span style=\"font-family:Verdana;\"><span style=\"font-family:Verdana;\">River 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 กม 30 m downloaded from USGS (</span></span><span style=\"font-family:Verdana;\"><span style=\"font-family:Verdana;\">the </span></span><span style=\"font-family:Verdana;\"><span style=\"font-family:Verdana;\">United States Geological Survey) website; clipped
river basin FAO digital soil and land use/cover maps; and field</span></span><span style=\"font-family:Verdana;\"><span style=\"font-family:Verdana;\">-</span></span><span style=\"font-family:Verdana;\"><span style=\"font-family:Verdana;\">collected data were used. SWAT (Soil and Water
Assessment Tool) model was used to assess rainfall </span></span><span style=\"font-family:Verdana;\"><span style=\"font-family:Verdana;\">-</span></span><span><span style=\"font-family:;\" \"=\"\"><span style=\"font-family:Verdana;\">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. </span><span style=\"font-family:Verdana;\">SWAT model showed a good
rainfall-runoff relationship usin</span><span style=\"font-family:Verdana;\">g NASA-POWER data for the area (R</span><sup><span style=\"font-family:Verdana;\">2</span></sup><span style=\"font-family:Verdana;\"> = 0.7749) for the studied period (2019-2021). There was an equally strong
rainfall-runoff relationship for gauged data (R</span><sup><span style=\"font-family:Verdana;\">2</span></sup><span style=\"font-family:Verdana;\"> = 0.8131). There
were
%K Modelling
%K Rainfall-Runoff
%K Satellite Data
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=116163