Integrated Streamflow Forecasting System: A Step Towards Smart Flood Management

Authors

  • Irfan Ardiansah Universitas Padjadjaran
  • Alfonsus Mario Agung Universitas Padjadjaran
  • Chay Asdak Universitas Padjadjaran
  • Nurpilihan Bafdal Universitas Padjadjaran
  • Roni Kastaman Universitas Padjadjaran
  • Selly Harnesa Putri Universitas Padjadjaran
  • Desy Nurliasari Suparno Universitas Padjadjaran

DOI:

https://doi.org/10.31449/inf.v47i9.4890

Abstract

This study aims to create an online monthly streamflow forecast system that will assist users in managing water resources and avoiding floods. We integrated a regression model into the system, utilizing historical rainfall and streamflow selective information from multiple monitoring stations in the Upper Cimanuk sub-basin. Users can access the online system to input and view rainfall and streamflow data and enumerate monthly streamflow rate projections. To verify the system's forecast accuracy, we compared it with manual calculations employing the velocity-area method and field observations. The system provides reasonably accurate forecasts, as indicated by the system's high coefficient of determination (R2) value of 0.91. However, discrepancies between forecasted and measured values suggest that we still can improve the accuracy of the system by incorporating additional variables and more comprehensive data. Future enhancements may include the incorporation of precipitation intensity, duration, basin shape, and basin size, as well as additional validation using a broader array of field data. The developed monthly streamflow forecasting system is a valuable tool for analyzing and forecasting streamflow rates, providing a basis for making informed decisions in water resource management and flood disaster mitigation.

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Published

2023-11-29

How to Cite

Ardiansah, I., Agung, A. M., Asdak, C., Bafdal, N., Kastaman, R., Putri, S. H., & Suparno, D. N. (2023). Integrated Streamflow Forecasting System: A Step Towards Smart Flood Management. Informatica, 47(9). https://doi.org/10.31449/inf.v47i9.4890

Issue

Vol. 47 No. 9 (2023): Online-only issue

Section

Online-only

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