Abstract:
Worldwide agriculture is sensitive to short-term changes in weather and to seasonal,
annual and longer-term variations in climate. The variations in the meteorological
parameters have overriding influence on the agricultural systems. It is widely believed
that developing countries such as India will be impacted more severely than developed
countries, where, about 56% of the net cultivated area is rain-fed that largely depends
on monsoon rainfall. Thus accurate estimation of rainfall is crucial for crop yield
assessment, water resource management and flood and drought monitoring for the
area. But, traditional precipitation records are thought to be rarely complete, to
analyze these limitations a comparison between rain gauge observations and satellite based estimates such as the Tropical Rainfall Measuring Mission (TRMM) is carried
out in this paper. Different statistical tools like coefficient of determination, Mean
Bias Error, Root Mean Square Error and NRMSE are used to have validation of
TRMM data with rain gauge data. TRMM data found overestimated to the rain gauge
data with 58.17 % of error, capturing 60.6 % of variability in spatial distribution with
traditional rain gauges. It is concluded from the analysis that there is some
dissimilarity in the spatial distribution between the two which may due to lack of
ground rain gauge stations at some remote areas or diversified topography of the
district area. Hence, it may be useful in estimating rainfall particularly in regions
where no gauge observations available and therefore such measurements are useful for
many water related applications.
