Unlocking the mysteries of drought: integrating snowmelt dynamics into drought analysis at the Narayani River Basin, Nepal

Abstract Drought is among the most impactful natural hazards, undermining water security, agriculture, and livelihoods worldwide. Analysing droughts in large catchments presents several unique challenges, primarily related to the complexity of land surface characteristics and data availability limitations. Conducting drought analysis in the Narayani River Basin, which encompasses a vast area within the Himalayan region of Nepal, is extremely challenging but crucial for maintaining the river basin's social, economic, and environmental balance. In response, this study develops a new combined drought index (CDI), integrating satellite-based reanalysis parameters [i.e., Land Surface Temperature ( LST ), Snow Cover ( SC ), and Normalised Difference Vegetation Index ( NDVI )] with a meteorological parameter [i.e., Standardised Precipitation ( std_prec )]. The novel CDI was applied at the Narayani Basin to assess the droughts over the 2004–2013 period, and the results were independently evaluated using streamflow observations to validate the accuracy of the novel drought index. The principal component analysis (PCA) technique was used to determine the contribution of input parameters to the multivariate drought index. The PCA results show a strong positive correlation (0.78) between the CDI and standardised streamflow, indicating the effectiveness of the novel index in monitoring drought conditions. Accordingly, it can be concluded that surface water availability is interdependent on landscape characteristics, such as LST , SC , and NDVI , in addition to the effects of precipitation. Also, the novel CDI can identify the specific drought-affected areas in the Narayani River Basin, offering insights into its drought characteristics beyond traditional drought assessment techniques.