Rain Station Network Analysis in the Sampean Watershed: Comparison of Variations in Data Aggregation
Abstract
The lack of rainfall-runoff accuracy is important for some applications. The choice of data aggregation that affects the estimation results is important at the level of accuracy. Some commonly used aggregations are daily, ten days, and monthly rainfall. This study aimed to compare the results of the estimation of the effect of data aggregation and to analyze the density of the rain gauge network in the Sampean watershed. The evaluation of the rain station network is carried out through the Kagan calculation. Rainfall data are from the rainfall data records for 20 years at 33 rain gauge stations. Measurement of the performance of aggregation variations using the relationship between the correlation value of rainfall with the distance between station locations. Station network positioning is assessed from alignment errors and interpolation errors. The results showed differences in the correlation and estimation values in the variation of data aggregation.The greater interval can increase the effectiveness of deployment with minimum error. Based on Kagan's analysis, there is an uneven distribution of gauge stations in the Sampean watershed eventhough the average and interpolation error in the monthly rainfall is less than 5%. It is this inequality that causes gauge stations to be inefficient.
Keywords : Rain gauge network; correlation; Kagan; data aggregation
Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember
This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
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Adhikary, S. K., Yilmaz, A. G., & Muttil, N. (2014). Optimal design of rain gauge network in the Middle Yarra River catchment, Australia. Hydrological Processes, 29(11), 2582–2599. https://doi.org/10.1002/hyp.10389.
Arifianto, Y. D. (2019) Mitigasi Bencana Banjir Daerah Aliran Sungai (DAS) Sampean Berbasis Pemberdayaan Masyarakat, Di Wilayah Bondowoso Dan Situbondo, Provinsi Jawa Timur. INFRASTRUKTUR, 5(1).
Bakhtiari, B., Kermani, M. N., & Bordbar, M. H. (2021). Rain Gauge Station Network Design for Hormozgan Province in Iran. Journal of Environmental Science, 18(8). https://doi.org/10.22059/jdesert.2013.36274.
Bárdossy, A., & Das, T. (2008). Influence of rainfall observation network on model calibration and application. Hydrology and Earth System Sciences, 12(1), 77–89. https://doi.org/10.5194/hess-12-77-2008.
Cheng, T., & Adepeju, M. (2014). Modifiable Temporal Unit Problem (MTUP) and Its Effect on Space-Time Cluster Detection. PLoS ONE, 9(6), e100465. https://doi.org/10.1371/journal.pone.0100465.
Errington, A., Einbeck, J., Cumming, J., & Rössler, U. (2021). The effect of data aggregation on dispersion. Int. J. Biostat. https://doi.org/https://doi.org/10.1515/ijb-2020-0079.
Erwanto, Z., Ulfiyati, Y., & Hadiyati, S. (2016). Evaluasi Database Sumber Daya Air Menggunakan Metode Kagan Pada Sungai-Sungai Besar Kabupaten Banyuwangi Dengan Sistem Informasi Geografis. Logic: Jurnal Rancang Bangun dan Teknologi, 16(3), 140.
Falconi, T. M. A., Estrella, B., Sempértegui, F., & Naumova, E. N. (2020). Effects of data aggregation on time series analysis of seasonal infections. International journal of environmental research and public health, 17(16), 5887.
Fattoruso, G., Longobardi, A., Pizzuti, A., Molinara, M., Marocco, C., De Vito, S., ... & Di Francia, G. (2017). Evaluation and design of a rain gauge network using a statistical optimization method in a severe hydro-geological hazard prone area. In AIP Conference Proceedings (Vol. 1836, No. 1, p. 020055). AIP Publishing LLC. https://doi.org/10.1063/1.4981995.
Kagan R.L. (1972). Planning the spatial distribution of hydrometeorological stations to meet an error criterion. In: Casebook on Hydrological Network Design Practice, III-1.2. WMO Publication No. 324.
Kagan, R. L. (1967). Some problems of interpreting precipitation gauge data. Leningrad, Glav. Geof, Obs., T. vyp 208,,64-75.
Mair, A., & Fares, A. (2011). Comparison of Rainfall Interpolation Methods in a Mountainous Region of a Tropical Island. Journal of Hydrologic Engineering, 16(4), 371–383. https://doi.org/10.1061/(asce)he.1943-5584.0000330.
Morsy, M., Taghizadeh-Mehrjardi, R., Michaelides, S., Scholten, T., Dietrich, P., & Schmidt, K. (2021). Optimization of Rain Gauge Networks for Arid Regions Based on Remote Sensing Data. Remote Sensing, 13(21), 4243. https://doi.org/10.3390/rs13214243.
Nandiasa, J. E., & Amatullah, F. (2020). Analysis of Placement Pattern and Number of Rain Stations Based on The Equation of Kagan Rodda in Ciliwung Watershed. ADRI International Journal of Engineering and Natural Science, 5(2), 27-33.
Nandiasa, J. E., & Purwaning, M. (2021). Analysis of The Placement Pattern and The Needs of The Rain Station With Kagan - Rodda Methode on Das Progo Yogyakarta. Journal of World Conference, 3(2), 204–211.
Nazaripour, H., & Mansouri Daneshvar, M. R. (2017). Rain gauge network evaluation and optimal design using spatial correlation approach in arid and semi-arid regions of Iran. Theoretical and Applied Climatology, 129(3), 1255-1261. https://doi.org/10.1007/s00704-016-1853-3.
Ndiritu, J. G., & Mkhize, N. (2017). Effect of monthly areal rainfall uncertainty on streamflow simulation. Physics and Chemistry of the Earth, 100(October), 51–61. https://doi.org/10.1016/j.pce.2016.10.005
Prawati, E., & Dermawan, V. (2018). Analisa Penyebaran Stasiun Hujan Terhadap Debit Banjir Rancangan Pada DAS Kedunglarangan (Kabupaten Pasuruan Jawa Timur). Seminar Nasional Sains dan Teknologi, 24, 1–11.
Rafiei Emam, A., Kappas, M., Fassnacht, S., & Linh, N. H. K. (2018). Uncertainty analysis of hydrological modeling in a tropical area using different algorithms. Frontiers of Earth Science, 12(4), 661–671. https://doi.org/10.1007/s11707-018-0695-y.
Razmkhah, H., AkhoundAli, A. M., Radmanesh, F., & Saghafian, B. (2016). Evaluation of rainfall spatial correlation effect on rainfall-runoff modeling uncertainty, considering 2-copula. Arabian Journal of Geosciences, 9(4). https://doi.org/10.1007/s12517-016-2392-z.
Renaldhy, R., Yasa, I. W., & Setiawan, E. (2021). Evaluasi Rasionalisasi Stasiun Hujan Metode Kagan Rodda dengan Mempertimbangkan Kriteria Penentuan Lokasi Pembangunan Stasiun Hujan. Jurnal Teknik Pengairan: Journal of Water Resources Engineering, 12(1), 49-60. https://doi.org/10.21776/ub.pengairan.2021.012.01.05
Rodda, J. C. (2011). Guide to Hydrological Practices. Hydrological Sciences Journal, 56(1), 196–197. https://doi.org/10.1080/02626667.2011.546602.
Siegmund, J., Peitek, N., Apel, S., & Siegmund, N. (2020). Mastering Variation in Human Studies: The Role of Aggregation. ACM Transactions on Software Engineering and Methodology (TOSEM), 30(1), 1-40.
Tekleyohannes, M., Grum, B., Abebe, N., & Abebe, B. A. (2021). Optimization of rain gauge network using multi-criteria decision analysis and entropy approaches: case of Tekeze River basin, northwestern Ethiopia. Theoretical and Applied Climatology, 145(1), 159-174. https://doi.org/10.1007/s00704-021-03604-1.
Wang, K., Gong, Y., Peng, Y., Hu, C., & Chen, N. (2020). An improved fusion crossover genetic algorithm for a time-weighted maximal covering location problem for sensor siting under satellite-borne monitoring. Computers and Geosciences, 104406. https://doi.org/10.1016/j.cageo.2020.104406.
Wu, H., Chen, Y., Chen, X., Liu, M., Gao, L., & Deng, H. (2020). A New Approach for Optimizing Rain Gauge Networks: A Case Study in the Jinjiang Basin. Water, 12(8), 2252. https://doi.org/10.3390/w12082252 .
Xu, H., Xu, C.-Y., Sælthun, N. R., Xu, Y., Zhou, B., & Chen, H. (2015). Entropy theory based multi-criteria resampling of rain gauge networks for hydrological modelling – A case study of humid area in southern China. Journal of Hydrology, 525, 138–151. https://doi.org/10.1016/j.jhydrol.2015.03.034.
Published
2022-04-27
How to Cite
HIDAYAH, Entin; HALIK, Gusfan; TRILITA, Minarni Nur.
Rain Station Network Analysis in the Sampean Watershed: Comparison of Variations in Data Aggregation.
Geosfera Indonesia, [S.l.], v. 7, n. 1, p. 96-108, apr. 2022.
ISSN 2614-8528.
Available at: <https://jurnal.unej.ac.id/index.php/GEOSI/article/view/29160>. Date accessed: 20 apr. 2024.
doi: https://doi.org/10.19184/geosi.v7i1.29160.
Section
Original Research Articles
