Kajian Koefisien Koreksi Indeks Kekeringan Menggunakan Basis Data Satelit TRMM dan Hujan Lapangan
Analyzing drought requires a long period of rainfall data more than 30 years. Obtaining enough rainfall data, however, it is very difficult especially for areas outside of Java that have limited data. To solve this problem, the possibility of using Tropical Rainfall Measuring Mission (TRMM) satellit...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Institut Teknologi Bandung
2015-08-01
|
Series: | Jurnal Teknik Sipil |
Subjects: | |
Online Access: | http://journals.itb.ac.id/index.php/jts/article/view/2903/1487 |
id |
doaj-a3958701edac479bac5f86bd88e16222 |
---|---|
record_format |
Article |
spelling |
doaj-a3958701edac479bac5f86bd88e162222020-11-25T01:39:09ZengInstitut Teknologi BandungJurnal Teknik Sipil0853-29822549-26592015-08-0122213714610.5614/jts.2015.22.2.7Kajian Koefisien Koreksi Indeks Kekeringan Menggunakan Basis Data Satelit TRMM dan Hujan LapanganEdy Anto Soentoro 0Levina 1Wanny K Adidarma 2Fakultas Teknik Sipil dan Lingkungan - Institut Teknologi BandungProgram Studi Magister Pengelolaan Sumber Daya Air, Fakultas Teknik Sipil dan Lingkungan Institut Teknologi BandungPuslitbang Sumber Daya Air - Badan Litbang Kementerian Pekerjaan Umum Analyzing drought requires a long period of rainfall data more than 30 years. Obtaining enough rainfall data, however, it is very difficult especially for areas outside of Java that have limited data. To solve this problem, the possibility of using Tropical Rainfall Measuring Mission (TRMM) satellite rainfall data to substitute long-period of rainfall data is examined. For a case study, data from Pemali Comal river basin is used. This study is aimed to obtain the value of drought correction coefficient index based on the TRMM data, so that the data can be used as an alternative to analyze drought index / severity of drought in areas with limited rainfall data. Standardized Precipitation Index (SPI) method is used to analyze drought severity, and the correction factor is determined by Root Mean Square Error (RMSE) with 0.5 as a threshold. Then the RMSE is compared between RMSE SPI of long period of groundstation rainfall data (1951-2013) and the TRMM satellite data (2002-2013). The results is that the average RMSE SPI correction is <0.5 for all SPI time scales, while the average RMSE without correction, correction α-β (whole region and sub-region) were > 0.5. Thus, the TRMM data with SPI correction can be used in the analysis of the SPI drought at all the time scale. http://journals.itb.ac.id/index.php/jts/article/view/2903/1487DroughtDrought index correctionSPI |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Edy Anto Soentoro Levina Wanny K Adidarma |
spellingShingle |
Edy Anto Soentoro Levina Wanny K Adidarma Kajian Koefisien Koreksi Indeks Kekeringan Menggunakan Basis Data Satelit TRMM dan Hujan Lapangan Jurnal Teknik Sipil Drought Drought index correction SPI |
author_facet |
Edy Anto Soentoro Levina Wanny K Adidarma |
author_sort |
Edy Anto Soentoro |
title |
Kajian Koefisien Koreksi Indeks Kekeringan Menggunakan Basis Data Satelit TRMM dan Hujan Lapangan |
title_short |
Kajian Koefisien Koreksi Indeks Kekeringan Menggunakan Basis Data Satelit TRMM dan Hujan Lapangan |
title_full |
Kajian Koefisien Koreksi Indeks Kekeringan Menggunakan Basis Data Satelit TRMM dan Hujan Lapangan |
title_fullStr |
Kajian Koefisien Koreksi Indeks Kekeringan Menggunakan Basis Data Satelit TRMM dan Hujan Lapangan |
title_full_unstemmed |
Kajian Koefisien Koreksi Indeks Kekeringan Menggunakan Basis Data Satelit TRMM dan Hujan Lapangan |
title_sort |
kajian koefisien koreksi indeks kekeringan menggunakan basis data satelit trmm dan hujan lapangan |
publisher |
Institut Teknologi Bandung |
series |
Jurnal Teknik Sipil |
issn |
0853-2982 2549-2659 |
publishDate |
2015-08-01 |
description |
Analyzing drought requires a long period of rainfall data more than 30 years. Obtaining enough rainfall data, however, it is very difficult especially for areas outside of Java that have limited data. To solve this problem, the possibility of using Tropical Rainfall Measuring Mission (TRMM) satellite rainfall data to substitute long-period of rainfall data is examined. For a case study, data from Pemali Comal river basin is used. This study is aimed to obtain the value of drought correction coefficient index based on the TRMM data, so that the data can be used as an alternative to analyze drought index / severity of drought in areas with limited rainfall data. Standardized Precipitation Index (SPI) method is used to analyze drought severity, and the correction factor is determined by Root Mean Square Error (RMSE) with 0.5 as a threshold. Then the RMSE is compared between RMSE SPI of long period of groundstation rainfall data (1951-2013) and the TRMM satellite data (2002-2013). The results is that the average RMSE SPI correction is <0.5 for all SPI time scales, while the average RMSE without correction, correction α-β (whole region and sub-region) were > 0.5. Thus, the TRMM data with SPI correction can be used in the analysis of the SPI drought at all the time scale.
|
topic |
Drought Drought index correction SPI |
url |
http://journals.itb.ac.id/index.php/jts/article/view/2903/1487 |
work_keys_str_mv |
AT edyantosoentoro kajiankoefisienkoreksiindekskekeringanmenggunakanbasisdatasatelittrmmdanhujanlapangan AT levina kajiankoefisienkoreksiindekskekeringanmenggunakanbasisdatasatelittrmmdanhujanlapangan AT wannykadidarma kajiankoefisienkoreksiindekskekeringanmenggunakanbasisdatasatelittrmmdanhujanlapangan |
_version_ |
1725050265298534400 |