Technical NoteNetwork theory and spatial rainfall connections: An interpretation

- Network theory is applied for studying spatial rainfall connections.
- Connections are examined using clustering coefficient, a measure of local density.
- The role of correlation thresholds in clustering coefficient analysis is investigated.
- Clustering coefficients are interpreted in terms of topographic and rainfall characteristics.

SummaryAdequate knowledge of spatial connections in rainfall is important for reliable modeling of catchment processes and water management. This study applies the ideas of network theory to examine and interpret the spatial connections in rainfall in Australian conditions. As case studies, monthly rainfall data across a network of raingages from two vastly different areas are studied: (1) Western Australia - data over a period of 67 years (1937-2003) from 57 raingages; and (2) Sydney catchment - data over a period of 114 years (1890-2003) from 47 monitoring stations. The spatial rainfall connections in the two networks are examined using clustering coefficient (CC), a popular network connectivity measure. The clustering coefficient measures the local density and quantifies the network's tendency to cluster. Different values of rainfall correlation threshold (CT) are used to measure the strength of connections in rainfall between different stations and, hence, to calculate CC. The clustering coefficient values are interpreted in terms of topographic factors (latitude, longitude, and elevation) and rainfall properties (mean, standard deviation, and coefficient of variation).