A COMPLEX NETWORK ANALYSIS OF THE GANGA RIVER BASIN

Abstract

A complex network is a relatively young, multidisciplinary field to unravel the spatiotemporal interaction in natural processes. Though network theory has become a fundamental paradigm in many areas, the applications in the hydrology field are still at an emerging stage. Therefore, the present study investigates the different aspects of precipitation networks in the Ganga river basin by employing complex network-based measures. In the first part of the thesis, the satellite-based precipitation products (TRMM) were evaluated with ground-based IMD gridded data. We employ complex network-based measures to investigate the influence of similarity measure, correlation threshold on the spatial connections and attempts to rank the influential grid points in the Ganga River Basin (GRB), India. We employ degree, clustering coefficient, average path length to examine the connections and weighted degree betweenness to rank the influential grid points. By generating the classical random network of as same numbers of links and size as that of the precipitation network at every threshold, we assess the significance of the precipitation network's small-world network characteristics. Our results reveal that the choice of correlation method does not significantly affect the network measures and reconfirm that the thresholds greatly influence network construction and network properties. The CC and degree's spatial distribution indicated an inverse relationship independent of similarity measures and correlation thresholds. Again, we analysed the architecture of precipitation networks and found that the network has a small-world network behaviour.