STREAMFLOW VARIABILITY AND ITS LINKAGE TO ENSO EVENTS IN THE KARNALI RIVER BASIN OF NEPAL

Abstract

This research explores into the complex interplay between streamflow variability and the ENSO phenomenon within the Karnali River basin, aiming to unravel the complexities of streamflow dynamics. Through a comprehensive analysis of long-term seasonal streamflow patterns, annual streamflow, and annual extreme flow events, coupled with statistical techniques including simple and cross-correlation, Mann-Kendall test, this study uncovers relationships between ENSO phases and streamflow. This study explores the results of the cross-correlation analysis, which further elucidates the relationship between monthly Nino 3.4 and SOI anomalies and monthly streamflow. The findings reveal consistently positive coefficients across various lags, suggesting 6-7 months of potential delayed effects of ENSO on streamflow patterns within the basin. Furthermore, the Mann-Kendall trend analysis conducted on streamflow and ENSO indicators indicates non-significant trends in monthly and annual streamflow across three out of four gauging stations within the basin. However, the Jamu station at Bheri River exhibited a negative trend during the winter months and a rising trend during the summer monsoon period, suggesting seasonal variability in the influence of ENSO on streamflow. Annual and seasonal streamflow analysis for the period 1962-2020 for four key hydrological stations explains contrasting impacts of El Nino and La Nina phases, with El Nino periods associated with decreased streamflow and La Nina periods leading to increased flow, particularly during the monsoon season. Moreover, examination of extreme flow events highlights the potential influence of ENSO on the occurrence of floods and droughts, with El Nino phases exhibiting a higher occurrence of extreme flow events below the mean extreme of the study period. These insights underline the need for adaptive water resource management strategies that account for hydro-climatic variability and the potential impacts of ENSO on hydrological patterns. By integrating advanced statistical techniques, hydrological modelling, remote sensing applications, and this research provides a holistic understanding of hydrological variability within the Karnali River Basin and offers valuable insights for sustainable water resource management in the face of changing climatic conditions.