Modeling impacts of climate change on meteorological droughts during cropping seasons and groundwater sustainability

Abstract

Rising temperature and changing rainfall patterns due to global warming would change the frequency and severity of meteorological droughts. This change in climate would impact on several sectors particularly agricultural and water resources. Groundwater, protected from surface hydrological extremes is considered a reliable source to supplement water deficit during droughts and therefore, considered a valuable resource for climate change adaptation across the world. However, prolonged droughts may also affect groundwater resources and hence, it is critical to understand how droughts and groundwater resources will be affected by climate change in order to aid reliable planning of adaptation. The major objective of the present study is to model the impacts of climate change on meteorological droughts during crop growing seasons and groundwater sustainability using general circulation model (GCM) projections. Nigeria, one of the most vulnerable countries of the world to climate change was considered as the case study area. Considering scarcity of data, gauge based gridded rainfall data of global precipitation climatology centre (GPCC) and temperature data of climate research unit (CRU) for the period 1901-2010 and groundwater storage anomaly data of gravity recovery and climate experiment (GRACE) for the period 2002-2016 were used. The temporal variations in droughts estimated using standardized precipitation evapotranspiration index (SPEI) and their interrelations with rainfall and temperature trends were assessed using a 50-year moving window with a 10-year time step. The concept of reliability-resiliency-vulnerability (RRV) was used for the assessment of groundwater sustainability. Novel entropy based methods were used for selection of GCMs to reduce uncertainties in climate change projections. The performance of four state-of-the-art bias correction approaches was compared for selecting the best method for reliable downscaling of climate. Random Forest (RF) and Support Vector Machine (SVM) were used for the projection of groundwater storage anomaly due to climate change. Results revealed increase in drought severity for all the cropping seasons of Nigeria. Temperature was found to be the dominating factor for defining droughts in semi-arid regions in the north while rainfall influence dominates in the monsoon and tropical savanna zones in the south. Four GCMs namely MRI-CGCM3, HadGEM2-ES, CSIRO-Mk3-6-0 and CESM1-CAM5 were found to be the most suitable for the projection of rainfall and temperature in Nigeria. Future projection of rainfall and temperature using ensemble model for the period 2010 – 2100 revealed increase in annual maximum temperature in the range of 0 – 5.1oC and changes in rainfall between 0 and 27.5% in rainy season. Maximum temperature was projected to increase more (3.5-5.1oC) in the northwest and least (2.0-2.5oC) in the south, while rainfall was projected to decrease up to 7.5% in the central and southern parts and increase up to 27.5% in north east. The study showed increase in droughts severity, frequency and affected area due to rises in temperature and changes in precipitation. Groundwater storage was projected to decline up to -12 m during rainy periods at some parts. Spatial assessment of changes in groundwater storage for future shows the northeast, southeast and south-south parts of Nigeria would mostly experience decrease in groundwater storage. Groundwater sustainability will be low in these areas and some other parts of the country for the future.