Development of intensity–duration–frequency curves for Herat, Afghanistan: enhancing flood risk management and implications for infrastructure and safety

Ziaul Haq Doost (), Shakhawat Chowdhury (), Ahmed M. Al‑Areeq (), Ibrahim Tabash (), Guled Hassan (), Habibullah Rahnaward () and Abdul Raqib Qaderi ()
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Ziaul Haq Doost: King Fahd University of Petroleum and Minerals
Shakhawat Chowdhury: King Fahd University of Petroleum and Minerals
Ahmed M. Al‑Areeq: King Fahd University of Petroleum and Minerals
Ibrahim Tabash: King Fahd University of Petroleum and Minerals
Guled Hassan: King Fahd University of Petroleum and Minerals
Habibullah Rahnaward: King Fahd University of Petroleum and Minerals
Abdul Raqib Qaderi: Kathmandu University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2024, vol. 120, issue 14, No 16, 12933-12965

Abstract: Abstract Herat Province of Afghanistan has been suffering from flood damages due to inadequate infrastructure and the impacts of civil wars. There is a critical need for advanced infrastructure, particularly in communication and flood protection while these infrastructures require appropriate understanding of rainfall patterns and their recurrence intervals. This study develops the Intensity Duration Frequency (IDF) curves in this province for the 1st time through employing the rainfall data of 42 years (1982–2023). In this study, the Exponential, Gumbel, Log Pearson Type III (LP3), Weibull, Generalized Extreme Value (GEV), and Halphen Inverse B statistical distribution models were applied. The GEV model showed the highest posterior probabilities given the data P(Mi|x) = 32.17, indicating a superior fit compared to other models. This is reinforced by its relatively low Bayesian Information Criterion = 323.22 and Akaike Information Criterion = 318.01, suggesting that it provided a robust and efficient representation of the data. In contrast, the models with fewer parameters, such as the Exponential, Gumbel, and Weibull distributions, showed significantly lower P(Mi|x) values (0–10.86), indicating the weaker fits. The GEV model effectively predicted rainfall intensities for various return periods (2, 5, 10, 20, 50, and 100 years). This study established the depth–duration relationships enabling the estimation of hourly and sub-hourly rainfall from annual daily maximum. These outcomes enhance water resource management and aid in the development of resilient infrastructure, thereby supporting sustainable development in the region.

Keywords: Herat province; Intensity duration frequency curve; Resilient infrastructure; Depth–duration relationships; Annual daily maximum rainfall; Flood protection; Water resources management (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11069-024-06730-x

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