Next Article in Journal
Water Leakage and Nitrate Leaching Characteristics in the Winter Wheat–Summer Maize Rotation System in the North China Plain under Different Irrigation and Fertilization Management Practices
Previous Article in Journal
Recent Advances in the Use of Chemical Markers for Tracing Wastewater Contamination in Aquatic Environment: A Review
Previous Article in Special Issue
Integrating Local Scale Drainage Measures in Meso Scale Catchment Modelling
Article Menu
Issue 2 (February) cover image

Export Article

Open AccessArticle
Water 2017, 9(2), 145; doi:10.3390/w9020145

Developing Intensity–Duration–Frequency (IDF) Curves under Climate Change Uncertainty: The Case of Bangkok, Thailand

1
UNESCO-IHE, Institute for Water Education, Westvest 7, AX Delft 2611, The Netherlands
2
School of Engineering and Technology, Asian Institute of Technology, P.O. Box 4 Klong Luang, Pathumthani 12120, Thailand
3
College of Engineering, Mathematics and Physics, University of Exeter, Exeter EX4 4QF, UK
4
School of Civil Engineering, University of Belgrade, Bulevar kralja Aleksandra 73, Beograd 11000, Serbia
*
Author to whom correspondence should be addressed.
Academic Editor: Athanasios Loukas
Received: 8 December 2016 / Revised: 10 February 2017 / Accepted: 15 February 2017 / Published: 22 February 2017
(This article belongs to the Special Issue Hydroinformatics and Urban Water Systems)
View Full-Text   |   Download PDF [2400 KB, uploaded 23 February 2017]   |  

Abstract

The magnitude and frequency of hydrological events are expected to increase in coming years due to climate change in megacities of Asia. Intensity–Duration–Frequency (IDF) curves represent essential means to study effects on the performance of drainage systems. Therefore, the need for updating IDF curves comes from the necessity to gain better understanding of climate change effects. The present paper explores an approach based on spatial downscaling-temporal disaggregation method (DDM) to develop future IDFs using stochastic weather generator, Long Ashton Research Station Weather Generator (LARS-WG) and the rainfall disaggregation tool, Hyetos. The work was carried out for the case of Bangkok, Thailand. The application of LARS-WG to project extreme rainfalls showed promising results and nine global climate models (GCMs) were used to estimate changes in IDF characteristics for future time periods of 2011–2030 and 2046–2065 under climate change scenarios. The IDFs derived from this approach were corrected using higher order equation to mitigate biases. IDFs from all GCMs showed increasing intensities in the future for all return periods. The work presented demonstrates the potential of this approach in projecting future climate scenarios for urban catchment where long term hourly rainfall data are not readily available. View Full-Text
Keywords: climate change; climate modelling; Intensity–Duration–Frequency; rainfall disaggregation; urban drainage climate change; climate modelling; Intensity–Duration–Frequency; rainfall disaggregation; urban drainage
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Shrestha, A.; Babel, M.S.; Weesakul, S.; Vojinovic, Z. Developing Intensity–Duration–Frequency (IDF) Curves under Climate Change Uncertainty: The Case of Bangkok, Thailand. Water 2017, 9, 145.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Water EISSN 2073-4441 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top