A Cluster-Based Data Assimilation Approach to Generate New Daily Gridded Time Series Precipitation Data in the Himalayan River Basins

Recent studies show variations in precipitation-gridded data set accuracy with changing geographical parameters. Ensemble precipitation products, combining diverse data sets, offer global-scale effectiveness, but applying them to regional studies, particularly in small to medium-sized sub-basins, presents challenges in addressing precipitation dependence on specific geographical conditions. Here, we present a newly developed Clusters Based-Minimum Error approach to assimilate different open-source gridded precipitation data sets for forming an accurate precipitation product over small to medium-sized hilly terrain basins, with limited precipitation gauges. This methodology generates the New Gridded Precipitation Data Set (NGPD) from 1991 to 2022 for the Upper Ganga Basin in the western Himalaya, covering approximately 22,292 km². The study utilizes nine open-source gridded precipitation data sets and 11 observed precipitation gauges, NGPD is evaluated through station-wise, grid-wise, and elevation-wise analyses using statistical parameters, quantile-quantile plots, daily coefficient of determination, Rainfall Anomaly Index, and seasonality/precipitation pattern analyses. Results demonstrate the superior performance of NGPD compared to other gridded precipitation sources across various evaluation metrics. Nash-Sutcliffe Efficiency (NSE), Coefficient of determination (R²), and Root mean squared error (RMSE) range from 0.67 to 0.90, 0.73–0.93, and 4.4–10.69 mm/day, respectively, w.r.t 11 observed precipitation gauges. NGPD outperforms the widely used IMD data set in India, exhibiting a monthly scale improvement of 18.47% and 17.7% in average NSE and R² values, respectively. Additionally, the methodology is also successfully applied to the Tamor Basin in Nepal, proving its reliability for various Himalayan regions. This approach reliably creates accurate gridded precipitation data sets for hilly sub-basins, especially in Himalayan regions with limited station data.