Quantifying the Impacts of Climate and Land Cover Changes on the Hydrological Regime of a Complex Dam Catchment Area

Muhammad Umer Masood, Saif Haider, Muhammad Rashid, Mohammed Suleman Aldlemy (), Chaitanya B. Pande (), Bojan Đurin, Raad Z. Homod, Fahad Alshehri and Ismail Elkhrachy
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Muhammad Umer Masood: Geological Engineering Department, Montana Technological University, Butte, MT 59701, USA
Saif Haider: Centre of Excellence in Water Resources Engineering, University of Engineering and Technology, Lahore 54890, Pakistan
Muhammad Rashid: Centre of Excellence in Water Resources Engineering, University of Engineering and Technology, Lahore 54890, Pakistan
Mohammed Suleman Aldlemy: Department of Mechanical Engineering, Collage of Mechanical Engineering Technology, Benghazi 16063, Libya
Chaitanya B. Pande: Abdullah Alrushaid Chair for Earth Science Remote Sensing Research, Geology and Geophysics Department, College of Science, King Saud University, Riyadh 11451, Saudi Arabia
Bojan Đurin: Department of Civil Engineering, University North, 48000 Koprivnica, Croatia
Raad Z. Homod: Department of Oil and Gas Engineering, Basrah University for Oil and Gas, Basra 61004, Iraq
Fahad Alshehri: Abdullah Alrushaid Chair for Earth Science Remote Sensing Research, Geology and Geophysics Department, College of Science, King Saud University, Riyadh 11451, Saudi Arabia
Ismail Elkhrachy: Civil Engineering Department, College of Engineering, Najran University, King Abdulaziz Road, Najran 66454, Saudi Arabia

Sustainability, 2023, vol. 15, issue 21, 1-28

Abstract: In this study, hydrological modeling at the watershed level is used to assess the impacts of climate and land use changes on the catchment area of the Khanpur Dam, which is an important water source for Rawalpindi and Islamabad. The hydrological impact of past and anticipated precipitation in the Khanpur Dam watershed was forecast by using a HEC-HMS model. After calibration, the framework was employed to analyze the effects of changes in land cover and climate on the hydrological regime. The model used information from three climatic gauge stations (Murree, Islamabad Zero Point, and Khanpur Dam) to split the Khanpur Dam catchment area into five sub-basins that encompass the entire watershed region, each with distinctive characteristics. The model was evaluated and checked for 2016–2018 and 2019–2020, and it produced an excellent match with the actual and anticipated flows. After statistical downscaling with the CMhyd model, the most effective performing GCM (MPI-ESM1-2-HR) among the four GCMs was chosen and used to forecast projections of temperature and precipitation within two shared socioeconomic pathways (SSP2 and SSP5). The predictions and anticipated changes in land cover were incorporated into the calibrated HEC-HMS model to evaluate the potential impact of climate change and land cover change at the Khanpur Dam. The starting point era (1990–2015) and the projected period (2016–2100), which encompassed the basis in the present century, were analyzed annually. The results indicated a spike in precipitation for the two SSPs, which was predicted to boost inflows all year. Until the end of the twenty-first century, SSP2 predicted a 21 percent rise in precipitation in the Khanpur Dam catchment area, while SSP5 predicted a 28% rise in precipitation. Increased flows were found to be projected in the future. It was found that the calibrated model could also be used effectively for upcoming studies on hydrological effects on inflows of the Khanpur Dam basin.

Keywords: land cover alteration; Khanpur Dam; climate change; GCMs; statistical downscaling; CA Markov; HEC-HMS (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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