Application of TRMM in the Hydrological Analysis of Upper Bengawan Solo River Basin
Theo Senjaya(1*), Doddi Yudianto(2), Xie Yuebo(3), Wanny K. Adidarma(4)
(1) Department of Civil Engineering, Parahyangan Catholic University, INDONESIA
(2) Department of Civil Engineering, Parahyangan Catholic University, INDONESIA
(3) Departement of Hydrology and Water Resources, Hohai University, CHINA
(4) Department of Civil Engineering, Parahyangan Catholic University, INDONESIA
(*) Corresponding Author
Abstract
Rainfall is a major water resource with a significant role in terms of growth, environment concerns, and sustainability. Several human activities demand adequate water supply for drinking, agriculture, domestic, and commercial consumption. The accuracy of any hydrologic study depends heavily on the availability of good-quality precipitation estimates. Most countries are unable to provide sufficient climatic data, including rainfall and observed discharge statistics. This scarcity is a huge obstacle in conducting thorough hydrologic studies over a certain period. For instance, Indonesia, as an archipelagic country, has long been faced with data availability problems. For this reason, Tropical Rainfall Measuring Mission (TRMM), which was developed by NASA, became an alternative solution to rainfall data limitations. However, to be applied in hydrologic investigations, TRMM data require proper estimation and adjustment. The aim of this study was to evaluate the quality of TRMM rainfall data and its application in determining design flood and water availability. Dividing the data into several groups based on its magnitude and multiplying each unit with a correction coefficient are parts of the modification process. Subsequently, objective functions, including false alarm ratio (FAR), probability of detection (POD), and root mean square error (RMSE) were also applied. Rainfall-runoff modeling and design storm analysis at Delingan dam were used to study the TRMM correction performance. Based on the analysis, corrected TRMM showed considerable findings compared to ground station data. Model calibration and verification using corrected TRMM data provide satisfactory model parameters compared to ground station derivatives. The results also disclosed a closer fit of the corrected TRMM to catchment response translated from derived rainfall-runoff model parameters to ground station compared to control. Furthermore, design storm calculated from corrected TRMM reflects an improvement compared to uncorrected TRMM data.
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As-Syakur, A.R., Tanaka, T., Prasetia, R., Swardika, I.K. and Kasa, I.W., 2011. Comparison of TRMM multisatellite precipitation analysis (TMPA) products and daily-monthly gauge data over Bali. International Journal of Remote Sensing, 32(24), pp.8969–8982.
Beaufort, A., Gibier, F. and Palany, P., 2019. Assessment and correction of three satellite rainfall estimate products for improving flood prevention in French Guiana. International Journal of Remote Sensing, 40(1), pp.171–196.
Booij, M.J., 2005. Impact of climate change on river flooding assessed with different spatial model resolutions. Journal of Hydrology, 303(1–4), pp.176–198.
Chai, T. and Draxler, R.R., 2014. Root mean square error (RMSE) or mean absolute error (MAE)? -Arguments against avoiding RMSE in the literature. Geoscientific Model Development, 7(3), pp.1247–1250.
Hardika, M.R., 2017. Hydro-Economic based Model of Damage and Loss Analysis of Winongo River Flood. Journal of the Civil Engineering Forum, 3(2), p.371.
Immerzeel, W.W., Droogers, P., de Jong, S.M. and Bierkens, M.F.P., 2009. Large-scale monitoring of snow cover and runoff simulation in Himalayan river basins using remote sensing. Remote Sensing of Environment, 113(1), pp.40–49.
Kidd, C. and Huffman, G., 2011. Global precipitation measurement. Meteorological Applications, 18(3), pp.334–353.
Mamenun, Pawitan, H. and Sophaheluwakan, A., 2014. Validasi dan koreksi data satelit TRMM pada tiga pola hujan di Indonesia (Validation and correction of TRMM satellite data on three rainfall patterns in Indonesia). Jurnal Meteorologi dan Geofisika, 15(1), pp.13–23.
Rozante, J.R., Moreira, D.S., de Goncalves, L.G.G. and Vila, D.A., 2010. Combining TRMM and surface observations of precipitation: Technique and validation over South America. Weather and Forecasting, 25(3), pp.885–894.
Tang, Q., Gao, H., Lu, H. and Lettenmaier, D.P., 2009. Remote sensing: Hydrology. Progress in Physical Geography, 33(4), pp.490–509.
Willy, W., Riyanto, B.A., Yudianto, D. and Wicaksono, A., 2020. Application of TRMM Data to the Analysis of Water Availability and Flood Discharge in Duriangkang Dam. Journal of the Civil Engineering Forum, 6(1), p.79.
Zhang, X. and Lindström, G., 1997. Development of an automatic calibration scheme for the HBV hydrological model. Hydrological Processes, 11(12), pp.1671–1682.
DOI: https://doi.org/10.22146/jcef.57125
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