The study focused on fitting non-stationary rainfall Intensity-Duration-Frequency (IDF) curves based on the General Extreme Value (GEV) distribution function to establish climate change existence in Benin City. The intensity levels were calculated, with the aid of the open-access R-studio software. Four linear behavioural parameter models considered for incorporating time as a covariate had the second model selected for producing the least corrected Akaike Information Criteria (AICC). The AICC varied from 370.30 to 125.20 for 15 and 1440 minutes, respectively, used in the calibration of the GEV equation. The computed non-stationary intensities produced higher values above those of stationary models, showing that the later IDF models undervalued extreme events. Differences of +15.24% (18.22 mm/hr), +9.4% (7.37 mm/hr), and +12.64% (12.78 mm/hr), for a 2, 10, and 50-year return periods, respectively, are serious underestimation from a stationary IDF model. Having extreme value differences could further aggravate the flood risk more than the design provision for the drainage facilities. The test statistic result confirmed a significant difference at a 95% confidence level between the non-stationary and stationary IDF curves, showing evidence of climatic change influenced by location as the time-variant parameter. The use of shorter-duration storms is advised for design purposes because they produce higher intensities and percentage differences in the extreme values, increasing the flood risk and infrastructural failures to induce climatic change in the study area.
| Published in | Hydrology (Volume 11, Issue 4) |
| DOI | 10.11648/j.hyd.20231104.13 |
| Page(s) | 85-93 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Rainfall, Time Series Data, Trend, Non-Stationary, Stationary, Curve Fitting
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APA Style
G. Sam, M., L. Nwaogazie, I., Ikebude, C. (2023). General Extreme Value Fitted Rainfall Non-Stationary Intensity-Duration-Frequency (NS-IDF) Modelling for Establishing Climate Change in Benin City. Hydrology, 11(4), 85-93. https://doi.org/10.11648/j.hyd.20231104.13
ACS Style
G. Sam, M.; L. Nwaogazie, I.; Ikebude, C. General Extreme Value Fitted Rainfall Non-Stationary Intensity-Duration-Frequency (NS-IDF) Modelling for Establishing Climate Change in Benin City. Hydrology. 2023, 11(4), 85-93. doi: 10.11648/j.hyd.20231104.13
AMA Style
G. Sam M, L. Nwaogazie I, Ikebude C. General Extreme Value Fitted Rainfall Non-Stationary Intensity-Duration-Frequency (NS-IDF) Modelling for Establishing Climate Change in Benin City. Hydrology. 2023;11(4):85-93. doi: 10.11648/j.hyd.20231104.13
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Download@article{10.11648/j.hyd.20231104.13,
author = {Masi G. Sam and Ify L. Nwaogazie and Chiedozie Ikebude},
title = {General Extreme Value Fitted Rainfall Non-Stationary Intensity-Duration-Frequency (NS-IDF) Modelling for Establishing Climate Change in Benin City},
journal = {Hydrology},
volume = {11},
number = {4},
pages = {85-93},
doi = {10.11648/j.hyd.20231104.13},
url = {https://doi.org/10.11648/j.hyd.20231104.13},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.hyd.20231104.13},
abstract = {The study focused on fitting non-stationary rainfall Intensity-Duration-Frequency (IDF) curves based on the General Extreme Value (GEV) distribution function to establish climate change existence in Benin City. The intensity levels were calculated, with the aid of the open-access R-studio software. Four linear behavioural parameter models considered for incorporating time as a covariate had the second model selected for producing the least corrected Akaike Information Criteria (AICC). The AICC varied from 370.30 to 125.20 for 15 and 1440 minutes, respectively, used in the calibration of the GEV equation. The computed non-stationary intensities produced higher values above those of stationary models, showing that the later IDF models undervalued extreme events. Differences of +15.24% (18.22 mm/hr), +9.4% (7.37 mm/hr), and +12.64% (12.78 mm/hr), for a 2, 10, and 50-year return periods, respectively, are serious underestimation from a stationary IDF model. Having extreme value differences could further aggravate the flood risk more than the design provision for the drainage facilities. The test statistic result confirmed a significant difference at a 95% confidence level between the non-stationary and stationary IDF curves, showing evidence of climatic change influenced by location as the time-variant parameter. The use of shorter-duration storms is advised for design purposes because they produce higher intensities and percentage differences in the extreme values, increasing the flood risk and infrastructural failures to induce climatic change in the study area.
},
year = {2023}
}
TY - JOUR T1 - General Extreme Value Fitted Rainfall Non-Stationary Intensity-Duration-Frequency (NS-IDF) Modelling for Establishing Climate Change in Benin City AU - Masi G. Sam AU - Ify L. Nwaogazie AU - Chiedozie Ikebude Y1 - 2023/11/17 PY - 2023 N1 - https://doi.org/10.11648/j.hyd.20231104.13 DO - 10.11648/j.hyd.20231104.13 T2 - Hydrology JF - Hydrology JO - Hydrology SP - 85 EP - 93 PB - Science Publishing Group SN - 2330-7617 UR - https://doi.org/10.11648/j.hyd.20231104.13 AB - The study focused on fitting non-stationary rainfall Intensity-Duration-Frequency (IDF) curves based on the General Extreme Value (GEV) distribution function to establish climate change existence in Benin City. The intensity levels were calculated, with the aid of the open-access R-studio software. Four linear behavioural parameter models considered for incorporating time as a covariate had the second model selected for producing the least corrected Akaike Information Criteria (AICC). The AICC varied from 370.30 to 125.20 for 15 and 1440 minutes, respectively, used in the calibration of the GEV equation. The computed non-stationary intensities produced higher values above those of stationary models, showing that the later IDF models undervalued extreme events. Differences of +15.24% (18.22 mm/hr), +9.4% (7.37 mm/hr), and +12.64% (12.78 mm/hr), for a 2, 10, and 50-year return periods, respectively, are serious underestimation from a stationary IDF model. Having extreme value differences could further aggravate the flood risk more than the design provision for the drainage facilities. The test statistic result confirmed a significant difference at a 95% confidence level between the non-stationary and stationary IDF curves, showing evidence of climatic change influenced by location as the time-variant parameter. The use of shorter-duration storms is advised for design purposes because they produce higher intensities and percentage differences in the extreme values, increasing the flood risk and infrastructural failures to induce climatic change in the study area. VL - 11 IS - 4 ER -
Department of Civil and Environmental Engineering, University of Port Harcourt, Port Harcourt, Nigeria
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