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Quantitative Precipitation Estimation (QPE) Rainfall from Meteorology Radar over Chi Basin

期刊

HYDROLOGY
卷 9, 期 10, 页码 -

出版社

MDPI
DOI: 10.3390/hydrology9100178

关键词

rainfall estimation; Quantitative Precipitation Estimation (QPE); radar; bias correction; Kriging

资金

  1. National Research Council of Thailand [106/2563]

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This study used meteorological radar data to quantify precipitation in the Chi Basin of northeast Thailand, and calibrated and corrected the data using rain gauge station measurements. The results showed that using meteorological radar for precipitation estimation is accurate and particularly useful in areas without rain gauge stations.
This study of the Quantitative Estimation Precipitation (QEP) of rainfall, detected by two Meteorology Radars over Chi Basin, North-east Thailand, used data from the Thai Meteorological Department (TMD). The rainfall data from 129 rain gauge stations in the Chi Basin area, covering a period of two years, was also used. The study methodology consists of: firstly, deriving the QPE between radar and rainfall based on meteorological observations using the Marshall Palmer Stratiform, the Summer Deep Convection, and Regression Model and calibrating with rain gauge station data; secondly, Bias Correction using statistical method; thirdly, determining spatial variation using three methods, namely Kriging, Inverse Distance Weight (IDW), and the Minimum Curvature Method. The results of the study demonstrated the accuracy of estimating precipitation using meteorological radar. Estimated precipitation compared against an equivalent of 2 years of rain station measurement had a probability of detection (POD) of 0.927, where a value of 1 indicated perfect agreement, demonstrating the effectiveness of the method used to calibrate the radar data. The bias correction method gave high accuracy compared with measured rainfall. Furthermore, of the spatial estimation of rainfall methods, the Kriging methodology showed the best fit between estimation of rainfall distribution and measured rainfall distribution. Therefore, the results of this study showed that the rainfall estimation, using data from a meteorology radar, has good accuracy and can be useful, especially in areas where it is not possible to install and operate rainfall measurement stations, such as in heavily forested areas and/or in steep terrain. Additionally, good accuracy rainfall data derived from radar data can be integrated with other data used for water management and natural disasters for applications to reduce economic losses, as well as losses of life and property.

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