Precipitation Modeling of Gwadar Port Baluchistan for Environmental Sustainability using Multilinear Regression Analysis Technique

Erum  Aamir; Farah  Naz; Fasiha  Safdar

doi:10.51732/njssh.v8i2.142

Authors

Erum Aamir Corresponding Author, Institute of Environmental Sciences and Engineering, NUST, Islamabad, Pakistan
Farah Naz School of Social Sciences & Humanities, National University of Sciences and Technology (NUST), Islamabad
Fasiha Safdar Institute of Environmental Sciences and Engineering, NUST, Islamabad

DOI:

https://doi.org/10.51732/njssh.v8i2.142

Keywords:

Precipitation, Mann-Kendal, Multiple Linear Regression, Statistical Modeling, Trend, Variables, Sustainable Development Goals (SDGs)

Abstract

Precipitation is the main source of fresh water in the water cycle. Climate change, because of global warming and the consequent change in the water cycle, is a global security issue. It would significantly influence water and food security. Disasters such as floods and droughts would lead to an adverse effect on the economy, peace, and geo-political situation around the world. In the present study, the change in precipitation patterns at Gwadar port is quantified in the context of climate change since it is the crown jewel in the China-Pakistan Economic Corridor (CPEC), as well as a vital part of One Belt One Road (OBOR) project. A data set of 40 years (1979-2018) is analyzed utilizing Mann-Kendall (MK) technique for precipitation trend detection, and Multi-Linear Regression Analysis (MLR) to develop a model of the study area. The model presents the potential determinants causing the variability in the precipitation patterns of the selected region. The model developed accounts for 80.47% (51.16%) of precipitation variability. The model successfully passed all estimation tests. This research will help the policymakers in legislation. The research also addresses United Nations Sustainable Development Goals (SDG): SDG# 13 (Climate Action).