Abstract

This study projects water availability and sustainability in Nigeria due to climate change. This study used Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage data (TWS), Global Precipitation Climatology Center (GPCC) precipitation data and Climate Research Unit (CRU) temperature data. Four general circulation models (GCMs) of the Coupled Model Intercomparison Project 5 were downscaled using the best of four downscaling methods. Two machine learning (ML) models, RF and SVM, were developed to simulate GRACE TWS data for the period 2002–2016 and were then used for the projection of spatiotemporal changes in TWS. The projected TWS data were used to assess the spatiotemporal changes in water availability and sustainability based on the reliability–resiliency–vulnerability (RRV) concept. This study revealed that linear scaling was the best for downscaling over Nigeria. RF had better performance than SVM in modeling TWS for the study area. This study also revealed there would be decreases in water storage during the wet season (June–September) and increases in the dry season (January–May). Decreases in projected water availability were in the range of 0–12 mm for the periods 2010–2039, 2040–2069, and 2070–2099 under RCP2.6 and in the range of 0–17 mm under RCP8.5 during the wet season. Spatially, annual changes in water storage are expected to increase in the northern part and decrease in the south, particularly in the country’s southeast. Groundwater sustainability was higher during the period 2070–2099 under all RCPs compared to the other periods and this can be attributed to the expected increases in rainfall during this period.

Highlights

  • Water is not uniformly distributed across the globe as there is variability in its natural occurrence, and it can be affected by direct and indirect human actions [1,2]

  • Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage data (TWS) anomaly and gridded climate data were used in the development of a water storage simulation model

  • The projected model ensemble (MME) mean for rainfall and temperature of selected general circulation models (GCMs) were used for simulating the water storage for representative concentration pathways (RCPs) 2.6, 4.5, 6.0, and 8.5

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Summary

Introduction

Water is not uniformly distributed across the globe as there is variability in its natural occurrence, and it can be affected by direct and indirect human actions [1,2]. Climate changes have further aggravated water availability due to decreases in rainfall [4,5,6,7] and generally increasing temperature [8,9,10]. These have led to shrinkages of lakes and other surface water bodies in some parts of the globe. Lake Chad in the Sahelian zone of west-central Africa has been reported to have shrunk from 1339.018 km in 1987 to 130.686 km in 2005 [12]

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