Rainfall Distribution Trend Analysis of the Philippine National Capital Region (2013-2016)

Miguel Bobadilla, Ryan Eugenio, Maria Pulido

2019

Abstract

The Philippine archipelago is a tropical country that experiences only two major seasons annually: wet (June-November) and dry (December-May). Due to these conditions, the country is bound to experience significant amounts of rainfall, followed by drought. Hence, studying long-term rainfall trends is highly beneficial for the country’s livelihood and safety. In this work, we studied the rainfall distribution in the National Capital Region covering the period of 2013 to 2016, and analysed the data using the Mann-Kendall Test and the Bootstrap procedure. Using a monthly scale, we found a negative trend, signifying a decrease in rainfall amount over the four years of data. Interestingly, we found a positive trend using a yearly scale, showing an increase of rainfall overall. Therefore it is quite risky to generalize a certain region's rainfall condition just by looking at it annually, but must consider as well its seasonal and monthly phenomena for a more detailed analysis. We note also that the area being studied was considerably large and the rainfall data varied with the location of the weather station where it was obtained. This work demonstrates the potential of using Big Data and the Internet of Things to measure and predict weather trends using various sensors and processors.

Paper Citation

in Harvard Style

Bobadilla M., Eugenio R. and Pulido M. (2019). Rainfall Distribution Trend Analysis of the Philippine National Capital Region (2013-2016).In Proceedings of the 4th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS, ISBN 978-989-758-369-8, pages 370-375. DOI: 10.5220/0007750303700375

in Bibtex Style

@conference{iotbds19,
author={Miguel Bobadilla and Ryan Eugenio and Maria Pulido},
title={Rainfall Distribution Trend Analysis of the Philippine National Capital Region (2013-2016)},
booktitle={Proceedings of the 4th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,},
year={2019},
pages={370-375},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007750303700375},
isbn={978-989-758-369-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,
TI - Rainfall Distribution Trend Analysis of the Philippine National Capital Region (2013-2016)
SN - 978-989-758-369-8
AU - Bobadilla M.
AU - Eugenio R.
AU - Pulido M.
PY - 2019
SP - 370
EP - 375
DO - 10.5220/0007750303700375