عنوان مقاله [English]
نویسندگان [English]چکیده [English]
Rainfall is one of the most important natural sources of water used by mankind for
agricultural and industrial applications. Because of the difficulty of rainfall monitoring,
which has high spatial and temporal variability, our knowledge of both the its synoptic
and climatological distribution over most of the country is not well known.
Climatological investigations in Iran lack adequate meteorological observations to
understand and interpret diverse climatic features. In the country as a whole, the
ground observation network is not dense enough to provide the detailed information
required, especially in rugged regions. Combined with this is the problem of poor
accessibility to the mountainous regions, which has resulted in the areal distribution of
rainfall being poorly known. In addition, the data collected by the existing
meteorological stations, with a few exceptions, are mostly discontinuous, nonhomogenous
and short period observations. Such limited data sets, make it difficult to
both accurately delimit different climatic regimes across the country and identify
significant departures from normal conditions, whereas many climatological
applications and investigations should ideally be based on the data collected at given
points over long periods and should have a good spatial and temporal coverage.
Perhaps the most urgent problem facing rainfall measurement at the present time is
data collection - one of the most costly areas in meteorology and hydrology.
In this paper, the central aim is to investigate the potential of Geographical
Information System for monitoring Fars province’s rainfall with special reference to
Kriging and IDW (Inverse Distance Weighting), to describe pre-processing
approaches, including relative calibration, and to examine various techniques for both
Analyses of the GIS techniques provided very useful information on both the
spatial and temporal distributions of rainfall over regional space, although data
collected by Kriging technique showed more accurate than IDW technique. In order to
explore the appropriate method, the accuracy of the obtained results from different
methods using RMS was examined. The results showed that among different used
kriging methods, the circular and exponential ordinary had lowest error.