| dc.description.abstract | The lack of rainfall-runoff accuracy is important for some applications. The
choice of data aggregation that affects the estimation results is important at the
level of accuracy. Some commonly used aggregations are daily, ten days, and
monthly rainfall. This study aimed to compare the results of the estimation of the
effect of data aggregation and to analyze the density of the rain gauge network in
the Sampean watershed. The evaluation of the rain station network is carried out
through the Kagan calculation. Rainfall data are from the rainfall data records for
20 years at 33 rain gauge stations. Measurement of the performance of
aggregation variations using the relationship between the correlation value of
rainfall with the distance between station locations. Station network positioning is
assessed from alignment errors and interpolation errors. The results showed
differences in the correlation and estimation values in the variation of data
aggregation.The greater interval can increase the effectiveness of deployment
with minimum error. Based on Kagan's analysis, there is an uneven distribution
of gauge stations in the Sampean watershed eventhough the average and
interpolation error in the monthly rainfall is less than 5%. It is this inequality that
causes gauge stations to be inefficient. | en_US |
