Streamflow extreme value analysis using correlation of streamflow data with TRMM derivatives at Bone Watershed Gorontalo, Indonesia

5th International Symposium on LAPAN-IPB Satellite for Food Security and Environmental Monitoring 2018

生态环境科学

Prakoso, W.G.^1 ; Murtilaksono, K.^2 ; Tarigan, S.D.^2 ; Purwanto, Y.J.^3

Graduate School Bogor Agricultural University, Gedung Sekolah Pascasarjana IPB, Kampus IPB Darmaga, Jl. Raya Darmaga, Bogor, Jawa Barat

16680, Indonesia^1

Watershed Management, Departement of Soil Science and Land Resources, Jl. Meranti Kampus IPB Darmaga, Bogor

16680, Indonesia^2

Department of Civil and Environmental Engineering, Gedung FATETA, Jl. Lingkar Akademik, Jawa Barat

16680, Indonesia^3

关键词: Continuous modelling;    Daily rainfall;    Extreme value analysis;    Rainfall intensity;    Rainfall runoff;    Simulated discharges;    Spatial resolution;    Value estimation;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/284/1/012015/pdf
DOI  :  10.1088/1755-1315/284/1/012015

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Most recent studies that have attempted to use rainfall dataset for continuous modelling of rainfall-runoff have found that, without detailed local calibration against traditional rain-gauge measurements, the TRMM data is simply not accurate enough for that purpose. This is partly a result of the coarse spatial resolution of the dataset, with each grid cell being 0.25° x 0.25°, and partly to do with the inherent difficulty in remotely sensing rainfall intensity. For this study, however, it was decided to derive a more general rainfall parameter, the total amount of rainfall calculated to have fallen on each of the delineated catchments, processed as a mean annual total, (in m3), and to see how closely that was correlated with the streamflow data. Considering that most of the streamflow data available is from 2007 - 2010, TRMM V6 3B42 3 hourly data covering this four year period were used. Given the lack of long-term data both discharge and rainfall, at Bone Watershed, Gorontalo Province, Indonesia), the limitations of an Extreme Value Analysis using such a short data set must be stressed from the outset. Most data sets available comprise approximately 3 - 4 years of data, which are insufficient to provide reliable predictions of discharge events with large return periods. A satisfactory hidrological correlation could be achieved using catchments weighted time series of TRMM daily rainfall data after scaling, with streamflow data from Bone River (Alale and Tulabolo) to obtain a time series of simulated discharge. Realatively reliable extrema value estimation on the design flood parameter were produced with resasonable several limitation.