Rationalization of Hydrology Station Network Using Rainfall Ground and Satellite Data

The rainfall data used in the hydrology analysis is obtained from the precision of rainfall data measurement and the condition of the rain station. The higher density of rain station network, the data obtained will be more accurate, but it should be noted other aspects such as economic aspects. The best network is obtained by conducting a rationalization analysis to get the most effective number and location of rain station This research obtains rainfall data from satellite for analysis as a solution to the problem of data limitations while others only use ground data. The method of this research is the first, the existing rain station network is evaluated whether it comply with WMO (World Meteorological Organization) standards or not. Then regression analysis is carried out on ground and satellite rainfall and water discharge data to find out the correlation between them. Next, the rain station network is rationalized using Kagan Rodda interpolation method, which mean there are some changes in the number and location of the station. The location of the new rain station doesn’t have rainfall ground data, so it uses satellite rainfall data. The correlation analysis is then carried out on the new rain station network using satellite rainfall data. This network is then compared to the existing network. This research is located in Kemuning River Catchment Area, Madura Island, which has six rain stations with a correlation coefficient of rainfall to discharge is 0.50. The number of rain stations on the recommendation network has not changed because the existing conditions has fulfilled WMO Standard. Whereas the location of the Palengan Laok Rain Station was relocated according to the Kagan-Rodda net so that the correlation coeffiicient of rainfall to the discharge increased to 0.53. The use of satellite data can be used for the analysis of rationalization of the rain station network with suggestions for correction of satellite data