Journal of Water Engineering and Management

( International Peer-reviewed Journal )

Climate Change and Hydrological Risk Assessment: Probable Maximum Precipitation Analysis in the Sindh Basin

Shringar Mishra1, Vinod Kumar Tripathi*1, R.K. Jaiswal2, Samikshya Panda1, Deepak Kumar1

1Department of Farm Engineering, I.Ag.Scs, BHU, Varanasi 221005

2Scientist F, National Institute of Hydrology, Bhopal

*Corresponding Author E-mail: vktripathi@bhu.ac.in

 

Received on: May 5, 2023

Revised on: August 10 2023

Accepted on: August 21, 2023

 

ABSTRACT

The Probable Maximum Precipitation (PMP) is the theoretical maximum precipitation that could occur over a given area during a specified period and is commonly used in designs of hydraulic structures such as dams, spillways, weirs, barrages levees etc. Climate change affects the PMP, as warming temperatures can increase the moisture-holding capacity of the atmosphere and alter precipitation patterns. Hershfield method was applied to estimate the PMP of daily maximum rainfall data over 32 years (1991-2022) in the Sindh basin. This paper investigates the possible spatio-temporal change in PMP over the Sindh basin under changing climate. To capture this change in PMP, 1-day, 2-day and 3-day PMP maps are developed for the entire Sindh basin for four time periods, spanning over 110 years from past to future – one historical period, viz. (1991– 2022) and three future periods, viz. near-future (2025–2050), future (2051–2075) and far-future (2076–2100), following four possible climate change scenarios (SSP1-2.6, SSP2-4.5, SSP3- 7.0 and SSP5- 8.5). These PMP maps, especially the historical and its future projections will serve as a piece of important information for the design engineers and hydro-meteorologists for revised planning and designing various major water-energy infrastructures in the context of climate change. The performance evaluation of thirteen climatic models was done with reference to observed IMD data using three performance indices (NSE, PBIAS, R2) for mean annual precipitation from 1991 to 2014. The comparison between different scenarios also revealed that precipitation value is decreasing in case of 1-day PMP variation for all scenarios in the near future, future and far future. SSP1-2.6 scenario shows a maximum decrease in precipitation in the case of 1-day and 2-day PMP variation for all three futures. The historical and future PMP maps were created using IMD-observed daily precipitation data.  In this study, a distinct decreasing trend in PMP for all the periods in future in most of the region was found.

Keywords: Probable maximum precipitation, Climate change, GCM climate model, SSP scenario, Hershfield method, Inverse Distance weighting

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