TY - JOUR
T1 - Interpolation of daily raingauge data for hydrological modelling in data sparse regions using pattern information from satellite data
AU - Stisen, S.
AU - Tumbo, M.
N1 - Publisher Copyright:
© 2015 IAHS.
PY - 2015/11/2
Y1 - 2015/11/2
N2 - In order to cope with a severe reduction of the raingauge network in the Great Ruaha River basin over the past 30 years, an interpolation scheme using spatial patterns from satellite images as covariate has been evaluated. The regression-based interpolation attempts to combine the advantages of accurate rainfall amounts from raingauge records with the unique spatial pattern information obtained from satellite-based rainfall estimates. A spatial pattern analysis reveals that the simple interpolation of the sparse current raingauge network compares very poorly to the pattern originating from the much denser historic network. In contrast, the rainfall datasets that include patterns from satellite data show good correlation with the historic pattern. The evaluation based on hydrological modelling showed similar and good performance for all rainfall products, including raingauge records, whereas the purely satellite-based product performed poorly.
AB - In order to cope with a severe reduction of the raingauge network in the Great Ruaha River basin over the past 30 years, an interpolation scheme using spatial patterns from satellite images as covariate has been evaluated. The regression-based interpolation attempts to combine the advantages of accurate rainfall amounts from raingauge records with the unique spatial pattern information obtained from satellite-based rainfall estimates. A spatial pattern analysis reveals that the simple interpolation of the sparse current raingauge network compares very poorly to the pattern originating from the much denser historic network. In contrast, the rainfall datasets that include patterns from satellite data show good correlation with the historic pattern. The evaluation based on hydrological modelling showed similar and good performance for all rainfall products, including raingauge records, whereas the purely satellite-based product performed poorly.
KW - daily raingauge data
KW - hydrological modelling
KW - regression-based interpolation
KW - satellite rainfall estimates
KW - Tanzania
UR - http://www.scopus.com/inward/record.url?scp=84949529736&partnerID=8YFLogxK
U2 - 10.1080/02626667.2014.992789
DO - 10.1080/02626667.2014.992789
M3 - Article
SN - 0262-6667
VL - 60
SP - 1911
EP - 1926
JO - Hydrological Sciences Journal
JF - Hydrological Sciences Journal
IS - 11
ER -