Author(s): Khoirunnisaa Ronaa Fairuuz; Shakti Rahadiansyah; Nabilla Aranda Shinta S; Muhamad Anif Ainul Murtaqi

Linked Author(s):

Keywords: GCM; Ensemble; Serayu-Bogowonto river basin; CRU; Downscaling

Abstract: Rainfall data is underlying data of hydrological and hydraulics analysis in the planning stage of water infrastructure construction. The uncertainty of rainfall prediction from hydrological analysis results forms a new pattern for the necessity of an approach for climate change prediction. Rainfall data is also data that is frequently used in water resources management in decision-making and disaster control such as flooding, erosion, change in stream-flow patterns, drought, etc. The response to global warming is in line with the increasing intensity of rainfall, which will be shown through visualization and curves of climate impact and mathematical models to determine specific climate influence coefficients. Global Climate Models (GCM) and Single Model Initial Condition Large Ensemble (SMILE) are methods used to make specific climate predictions by calculating the ensemble average values at the correlation level of the trend relationship between dry seasons and subsequent dry seasons, and rainy seasons with subsequent rainy seasons. GCM is a model used to test a correlation, which in this study is the correlation between each season in tropical climates. The SMILE method is the most suitable method for hydrological modeling that uses a projection range and event distribution approach. The derivation from that method is Parameter Regression Independent Slope Method (PRISM), Ensemble models using this downscaling approach are packaged in a model called CMIP5, this model was developed to reduce the bias of climate uncertainty prediction errors that usually occur at a scale of 70-500 km. The recording of hydrological data, which in this study is rainfall. The SMILE method can produce an approach to the value of climate extremes that may occur in a certain period. The combination of GCM and SMILE is expected to show how extreme the influence of climate change is in a particular river basin. The research is conducted in the Serayu Bogowonto River Basin, under the authority of the Serayu Opak River Basin Agency of the Ministry of Public Works and Public Housing. The prediction of climate change is a response to the real threat to infrastructure and water resources, directly impacting the extremes of climate change. The key hazard, which is a controlled variable, is rainfall data, also influenced by La Nina and El Nino factors that have shown more frequent trends over the past 40 years. The rainfall trend over a minimum of 20 years in a river basin area is one of the independent parameters for conducting multiple regression analysis to determine each season's correlation.

DOI: https://doi.org/10.64697/HIC2024_P591

Year: 2024