| Title: | Increasing the accuracy of runoff and streamflow simulation in the Nzoia Basin, Western Kenya, through the incorporation of satellite-derived CHIRPS data |
| Authors: | Le, A.M. and N.G. Pricope |
| Year: | 2017 |
| Journal: | Water |
| Volume (Issue): | 9(2) |
| Pages: | |
| Article ID: | 114 |
| DOI: | 10.3390/w9020114 |
| URL (non-DOI journals): | |
| Model: | SWAT |
| Broad Application Category: | hydrologic only |
| Primary Application Category: | climate data effects |
| Secondary Application Category: | hydrologic assessment |
| Watershed Description: | >12,000 km^2 Nzoia River, which drains a portion of western Kenya and is located in the Lake Victoria drainage area. |
| Calibration Summary: | |
| Validation Summary: | |
| General Comments: | |
| Abstract: | Hydrologic models will be an increasingly important tool for water resource managers
as water availability dwindles and water security concerns become more pertinent in data-scarce
regions. Fortunately, newly available satellite remote sensing technology provides an opportunity
for improving the spatial resolution and quality of input data to hydrologic models in such regions.
In particular, the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) dataset
provides quasi-global high resolution precipitation information derived from a blend of in situ
and active and passive remote sensing data sources. We piloted the incorporation of the CHIRPS
dataset into the Soil and Water Assessment Tool (SWAT), a hydrologic model. Comparisons of results
between estimation of streamflow using in situ rainfall gauge station data, the Climate Forecast
System Reanalysis (CFSR) dataset, and the CHIRPS dataset in the data-scarce Nzoia Basin in western
Kenya over the temporal range 1990–2000 were reported. Simulated streamflow estimates were poor
with rainfall gauge station data but improved significantly with the CFSR and CHIRPS datasets.
However, the use of the CHIRPS dataset in comparison with the CFSR dataset provided an improved
statistical performance following model calibration with the exception of one streamflow gauge
station in higher elevation regions. Overall, the use of the CHIRPS dataset had the greatest linear
correlation, relative variability, and normalized bias despite overall average Nash-Sutcliffe Efficiency
(NSE) and R2 values. |
| Language: | English |
| Keywords: | hydrologic modeling; satellite precipitation; SWAT; CHIRPS; CFSR; Kenya |