Disentangling spatiotemporal characteristics of six different unregulated streamflow stations in India

With the increasing stress on water resources for a developing country like India, it is very much pertinent to study how the water resources are varying with time and investigate the dominant streamflow patterns for carrying effective planning and management activities. In this study, we attempt to investigate the spatiotemporal characterization of streamflow of six unregulated catchments in India and also quantify the impact of precipitation changes and four climate indices, namely, Niño 3.4, IOD, PDO and NAO on streamflow. Initial analysis of streamflow and precipitation was carried out using Mann Kendall and step change detection methods. Temporal variability of streamflow and its association with precipitation and climate indices was unraveled using continuous wavelet transform and Wavelet coherence respectively. Cross-wavelet transform was also used to capture the coherent relationships and phase relationships between streamflow and climate indices. The results of the study reveal an in-phase relationship between precipitation and streamflow. The analysis also considers that streamflow is mostly affected by Niño 3.4 and PDO indices. Based on the results of this work, better understanding of interrelationship between the streamflow and precipitation was well captured using Wavelet coherence when compared to Cross wavelet. It was observed that almost all basins had showed the effect of changes in precipitation on streamflow. Based on these observations, it is clear that WTC can be used for understanding interrelationship between variable when compared to XWT and gives better insights regarding the interrelationship