Improving Spatial Rainfall Estimates at Mt. Merapi Area Using Radar-Rain Gauge Conditional Merging

Hambali, Roby; Legono, Djoko; Jayadi, Rachmad; Oishi, Satoru

doi:10.20965/jdr.2019.p0069

Cited by 5 publications

(2 citation statements)

References 20 publications

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“…It can perform better accuracy than previous radar generations, such as the Sand C-band conventional radar. It is also more sensitive and can detect smaller particles due to smaller wavelength (Hambali, et al, 2019).…”

Section: Prambanan Templementioning

confidence: 99%

Snake Line Performance Applying Single Pixel X-Band MP Radar Data (Case of Mt. Merapi Area, Indonesia)

Hairani

Rahardjo

Legono

et al. 2019

Journal of the Civil Engineering Forum

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The short-duration-rainfall monitoring techniques have become important recently due to the high demand for disaster risk mitigation. Such techniques produce important information on the rainfall intensity during heavy rainfall in the form of snake line. At the same time, use of X-Band Multi-Parameter Radar (XMP Radar) in rainfall monitoring has increased significantly because of its capacity to cover wide area. An assessment on the snake line performance that was developed based on XMP Radar and ground rainfall monitoring instrument (i.e. Automatic Rainfall Recorder or ARR) has been applied to Mt. Merapi area, Java, Indonesia. Selected rainfall data of November-December 2018 were examined. The assessment used a single pixel of radar data at the location of the ARR. The result shows that rainfall data obtained from XMP Radar are lower than those from ARR. The computed snake line obtained from XMP Radar differs from that from ARR data. The XMP Radar underestimates the warning level by about two level out of four.

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Section: Prambanan Templementioning

confidence: 99%

Snake Line Performance Applying Single Pixel X-Band MP Radar Data (Case of Mt. Merapi Area, Indonesia)

Hairani

Rahardjo

Legono

et al. 2019

Journal of the Civil Engineering Forum

Self Cite

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“…This radar rainfall station was still under study. Several studies have used radar rainfall data, such as in [2][3][4][5]. However, the researchers and the other users have not utilized the 3D features of the recorded radar rainfall data extensively.…”

Section: Introductionmentioning

confidence: 99%

Estimating Additional Flood Warning Time Using Raindrops Intensity Data Captured by X-Band Mp Radar

Rahardjo¹,

Syahmi²,

Legono³

2021

GEOMATE

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The current monitoring system of flood warnings on Mt. Merapi slope, Yogyakarta, Indonesia relies on rainfall gages and visual observation. Most flood events occurred with a fast-moving front resulting in a very short available warning time. An X-Band Multi-Parameter Radar installed at the southwest slope of Mt. Merapi measures raindrop intensity high above the ground and provides rainfall information earlier. This paper presents the effort to estimate the additional warning time available by extracting binary radar data, transforming it into 3D grid data, and visualize it into meaningful charts. This study compared the IDW and NN interpolation methods and verified the grid resolution and the limiting distance, r, of the IDW method for obtaining optimal performance. This study also conducted a qualitative review on the sequences of horizontal contour images and the comparison of horizontal and vertical grid resolutions. The estimation of time lag of peak raindrop intensity of different elevations was evaluated qualitatively by overlaying time-series data at four elevations and quantitatively by conducting a cross-correlation analysis of pairs of time series data of +3000 m and +1300 m elevations with horizontal offset for considering wind drift. The result shows that the optimal value of r is 400 m, and the optimal grid resolution is 100x100x100 m. It found that the approximate additional warning time was 6 minutes. The conclusion is that the developed interpolation method is reliable for raindrop analysis. The cross-correlation analysis gives a conservative estimate of the additional warning time.

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Sensitivity analysis of using unreliable rain gauge stations for evaluating the accuracy of radar rainfall estimates

Hambali

Legono

Jayadi

2020

IOP Conf. Ser.: Earth Environ. Sci.

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Providing reliable rainfall information through the integration of all possible data sources such as rain gauge and radar can make a valuable contribution to the development of the lahar flow warning system. However, the reliability of radar rainfall (R) data still needs to be evaluated based on ground rainfall (G) given the estimated value of radar rainfall depth is not so precise compared to ground rainfall. The selection of which ground rainfall data can be used as an evaluation reference is based on the assessment of the variance analysis. Through the Scheffe test, the unreliable rain gauge stations can be known. The use of unreliable rain gauge stations for evaluating the accuracy of radar rainfall estimates affecting the parameter values of radar rainfall and ground rainfall conformity. This paper discusses sensitivity analysis of using unreliable rain gauge stations for evaluating the accuracy of radar rainfall estimates. Based on the Scheffe test, several scenarios are set to assess the change of conformity parameter values. The conformity between radar rainfall and ground rainfall are evaluated by using Log (G/R), FSE, and RMSE index. A number of 10-minute rainfall intensity data during 2016-2018 from 21 automatic rain gauge and X-band MP radar stations in the Merapi volcano region are used in the analysis. The result show that the less unreliable rain gauge stations used to assess the radar rainfall accuracy, the better the conformity parameter values.

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Improving Spatial Rainfall Estimates at Mt. Merapi Area Using Radar-Rain Gauge Conditional Merging

Cited by 5 publications

References 20 publications

Snake Line Performance Applying Single Pixel X-Band MP Radar Data (Case of Mt. Merapi Area, Indonesia)

Snake Line Performance Applying Single Pixel X-Band MP Radar Data (Case of Mt. Merapi Area, Indonesia)

Estimating Additional Flood Warning Time Using Raindrops Intensity Data Captured by X-Band Mp Radar

Sensitivity analysis of using unreliable rain gauge stations for evaluating the accuracy of radar rainfall estimates

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