Modeling the potential impacts of climate change on surface and groundwater resources in the Niger Delta part of Nigeria

  • Ibrahim Hassan

Student thesis: Doctoral Thesis


Climate change impact studies are challenging in developing countries due to the paucity of climatological datasets resulting from insufficient monitoring stations, and constraint in human and computational resources. The Niger Delta region is one of the most vulnerable and densely populated regions in Nigeria, which presents special challenges for water resource policy and management due to climate change and anthropogenic activities, especially with an increase in water demands. Flooding events are recorded annually in settlements along River Niger and its tributaries, inundating many towns, displacing people from their homes and polluting the surface and groundwater resources. As the surface and groundwater resources are two interconnected components of one single resource, any negative impacts on one will inevitably affect the quantity or quality of the other component. The increase in intense stress on the groundwater from shallow coastal plain sand aquifers as the significant source of water resources for domestic, industrial and agricultural purposes in the area. This study, therefore, presents a novel approach for climate change impact assessment on surface and groundwater resources in developing countries.;The first stage of this study assessed the performance of three widely used daily gridded precipitation (prcp), maximum and minimum temperature (Tmax and Tmin) datasets from the Climatic Research Unit (CRU), Princeton University Global Meteorological Forcing (PGF) and Climate Forecast System Reanalysis (CFSR) datasets available over the Niger Delta part of Nigeria against the observed station datasets to select the best datasets that can serve as a possible replacement to the observed datasets. Symmetrical uncertainty (SU) filter was employed together with the selected hydro-climatological datasets to assess the performance of 26 Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation model (GCM)outputs. The selection was made according to their capability to simulate observed daily precipitation (prcp), maximum and minimum temperature (Tmax and Tmin) over the historical period 1980-2005 (Baseline periods) in the Niger Delta region. The selected GCMs were used for climate change predictions and impacts assessment over the period 2020s (2010-2039), 2050s (2040-2069) and 2080s (2070-2099), under Representative Concentration Pathway (RCP) 4.5 and 8.5. Standardized precipitation index (SPI) of 1-month and 12-month time steps were used for extreme event assessment. SWAT (Soil and Water Assessment Tool) model was used to analyse the effects of climate change on the hydrologic processes of the Niger River Basin (NRB)in Nigeria. The hydrostratigraphy of the Niger Delta shallow coastal aquifers was characterised coupled with the simulated aquifer recharge and evapotranspiration deduced from Global Climate Model (GCM) simulations under two Representative concentration pathways (RCP4.5 and RCP8.5) to develop a transient groundwater flow model to investigate the potential impacts of climate change and increased groundwater abstraction on the coastal plain sand aquifer over the periods 2010 to 2099.;Results of the hydro-climatological study revealed that the CRU datasets performed better in most of the statistical assessments conducted. The symmetrical uncertainty filter revealed the four top-ranked GCMs, namely ACCESS1.3, MIROCESM, MIROC-ESM-CHM, and NorESM1-M as the best set of GCMs to form an ensemble for the Spatio-temporal climate projection over the study area. The selected GCM ensemble predicted an increase in the mean annual precipitation in the range of 0.26% to 3.57% under RCP4.5, and 0.7% to 4.94% under RCP 8.5 by the end of the century as compared to the base period. The study also revealed an increase in maximum temperature in the
Date of Award8 Jul 2020
Original languageEnglish
Awarding Institution
  • University Of Strathclyde
SupervisorRobert Kalin (Supervisor) & Chris White (Supervisor)

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