Simulation of Rainfall Data by The GPM Satellite (Case Study at Sriwijaya University, Indralaya)

Abstract

The problem in obtaining rainfall data information is that the measurement results of rainfall from the measuring station are not recorded and areas are difficult to reach to measure rainfall directly. Lack of data availability and continuity of rainfall data is one of the obstacles in obtaining climatological information in South Sumatra. GPM satellites (Global Precipitation Measurement) need to be researched in order to overcome obstacles in obtaining rainfall measurement data in an area. This study aims to validate rainfall data from the GPM satellite and daily rainfall data from the measurement results of the Hellmen type automatic rain gauge located in the Hydraulics Laboratory of Sriwijaya University. Validation of rainfall data was carried out to determine the accuracy of the measurement results. Validation was carried out by the Root Mean Square Error Method and the Nash-Sutcliffe Method. The results of the validation showed a high correlation value for the average daily rainfall. The correlation coefficient value is 0,77, the RMSE value is 11,42 and the NSE value is 0,996. The results of the validation of these methods show a strong correlation between the measurement rainfall data in the field and the GPM satellite.

Utilization of GPM Satellite and PERSIANN Satellite Data for Estimated Monthly Rainfall in South Sumatera

“…Monthly rainfall data is validated by calculating the bias parameter [2], [16]. Data validation is carried out to prove whether a process or method can produce consistent results by predetermined specifications [6]. Data validation before and after calibration will be carried out using three statistical parameters, namely correlation coefficient (r), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE).…”

“…This will decrease the data accuracy variable because rainfall is strongly influenced by space and time. One of the areas experiencing this problem is South Sumatra, where in some areas, it is difficult to obtain sufficient and sustainable rainfall data [6].…”

“…While checking the accuracy of the model is done by calculating the Nash-Sutcliffe efficiency coefficient [6] The satellite data sources used are PERSIANN and GPM IMERG V06. GPM is the successor of the first precipitation measurement in collaboration with NASA and JAXA, namely TRMM (Tropical Rainfall Measuring Mission).…”

“…Research on monthly rainfall data with the GPM satellite and PERSIANN satellite in the South Sumatra district has not been carried out much. Based on a literature study, research in South Sumatra was conducted in Indralaya, using calibrated daily rainfall data from the short-duration GPM satellite for three months [6]. In this study, the rainfall data is long enough for three years (2019 -2021) in 9 districts in South Sumatra.…”

The Evaluation of GPM IMERG v.06 Rainfall Product over the Lau Simeme Watershed in Indonesia

“…In Indonesia, [13], [14], [15], [16], [17], [18], [19], and [20] have also conducted the same study. Especially for the island of Sumatra, [21], [22], [23], and [24] showed that GPM IMERG is one of the possible rainfall satellite data that can be used in imitating the ground station data.…”