Projected Rainfall Trends and Variability in the Mrica Catchment under the SSP5-8.5 Scenario

Abstract

This study analyzes changes in rainfall, inflow discharge, and electricity production at PLTA Mrica using historical data (1985–2014) from CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) and six global climate models (GCMs) under CMIP6 (Coupled Model Intercomparison Project Phase 6). Future projections are based on the SSP5-8.5 (Shared Socioeconomic Pathway 5 – fossil-fueled development) scenario to represent a worst-case pathway, enabling assessment of maximum potential climate impacts on hydropower reliability [2] scenario for the period 2021–2100. A delta-based statistical downscaling method is applied to produce high-resolution rainfall projections. This method is deterministic in nature; it applies a fixed anomaly (delta) between future and historical climatologies onto observed datasets, without simulating transient atmospheric processes as done in prognostic models. It is computationally efficient and widely used for impact studies where capturing long-term mean changes is prioritized over day-to-day weather variability [2][3]. The results indicate an increase in rainfall during the wet season and a significant decline during the dry season, particularly from January to March, with projected rises of up to +2.5 mm/day, or approximately +30–40%, compared to the historical baseline. Conversely, the dry season (June–September) is projected to experience a decline of up to 1.5 mm/day, equivalent to a reduction of 25–40%, depending on the month and future time slice. Historical data indicate that monthly rainfall of at least 100–120 mm is generally required to sustain sufficient reservoir inflow for optimal electricity generation at PLTA Mrica, especially during the dry season. Variability in rainfall, particularly prolonged dry spells or delayed wet season onset, can lead to inflow shortages, reducing turbine operation hours and ultimately affecting annual energy output. This study highlights the importance of using climate data such as projected rainfall thresholds and variability to guide reservoir operations, optimize electricity production, and reduce risks during dry periods. Integrating such information supports more adaptive and resilient hydropower planning under future climate uncertainty.